Science and Soccer

Now in a fully revised and updated fourth edition, Science and Soccer is still the most
comprehensive and accessible introduction to the science behind the world’s most pop-
ular sport. Offering important guidance on how science translates into practice, the
book examines every key facet of the sport, with a particular focus on the development
of expert players. The topics covered include:

• anatomy, physiology, psychology; sociology and biomechanics;

• principles of training;
• nutrition;
• physical and mental preparation;
• injury;
• ­decision-​­making and skill acquisition;
• coaching and coach education;
• performance analysis;
• talent identification and youth development.

Science and Soccer: Developing Elite Performers is a unique resource for students and
academics working in sports science. It is essential reading for all professional support
staff working in the game, including coaches at all levels, physiotherapists, condition-
ing specialists, performance analysts, club doctors and sports psychologists.

A. Mark Williams, PhD is a Professor and Senior Research Scientist at The Institute
for Human & Machine Cognition (IHMC) in Florida, USA.

Paul R. Ford, PhD is a Senior Lecturer in the School of Sport, Exercise and Applied
Sciences at St Mary’s University, UK.

Barry Drust, PhD is an Applied Exercise Physiologist and an Industrial Professorial

Fellow in the School of Sport, Exercise and Rehabilitation Sciences at the University
of Birmingham, UK.
Science and Soccer
Developing Elite Performers

Fourth Edition

Edited by A. Mark Williams,

Paul R. Ford, and Barry Drust
Cover image: Stanislaw Pytel
Fourth edition published 2023
by Routledge
605 Third Avenue, New York, NY 10158
and by Routledge
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Routledge is an imprint of the Taylor & Francis Group, an informa business
© 2023 selection and editorial matter, A. Mark Williams, Paul R. Ford, and
Barry Drust; individual chapters, the contributors
The right of A. Mark Williams, Paul R. Ford, and Barry Drust to be identified
as the authors of the editorial material, and of the authors for their individual
chapters, has been asserted in accordance with sections 77 and 78 of the
Copyright, Designs and Patents Act 1988.
All rights reserved. No part of this book may be reprinted or reproduced or
utilised in any form or by any electronic, mechanical, or other means, now
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publishers.
Trademark notice: Product or corporate names may be trademarks or registered
trademarks, and are used only for identification and explanation without intent
to infringe.
First edition published by Willan 2008
Third edition published by Routledge 2013

ISBN: ­978-­​­­0 -­​­­367-­​­­70895-​­5 (­hbk)

ISBN: ­978-1-032-46030-7 (­pbk)
ISBN: ­978-­​­­1-­​­­0 03-­​­­14841-​­8 (­ebk)

DOI: 10.4324/­9781003148418
Typeset in Times
by codeMantra
Contents

Preface viii
List of figures xiii
List of tables xvii
List of contributors xx

SECTION A
Biological Sciences 1

1 Physical preparation 3
T. S T RU DW IC K

2 Resistance training 15
C ONA L L M U RTAGH , DAV I D RY DI NG S A N D BA R RY DRUS T

3 Aerobic and anaerobic training 34

L I A M A N DE R S ON A N D BA R RY DRUS T

4 Soccer in the heat: Performance and mitigation 52

CA ROL I N E S U N DE R L A N D, S TAC E Y C OW E , A N D R AC H E L M A L C OL M

5 Nutrition for match play and training 67

JA M E S P. MORT ON , L I A M A N DE R S ON , H A N NA H SH E R I DA N
A N D G R A E M E L . C L O SE

6 Recovery strategies 90
WA R R E N G R E G S ON , G R E G ORY DU P ON T, ­A BD - ​­E L BA S SE T A BA I DI A A N D
ROBI N T HOR PE

SECTION B
Social and Behavioural Sciences 109

7 Psychological characteristics of players 111

GE I R JOR DE T A N D T Y N K E T OE R I NG
vi Contents
8 Anticipation and ­decision-​­making 124
A . M A R K W I L L I A M S , JO S PE H L . T HOM A S , GE I R JOR DE T,
A N D PAU L R . FOR D

9 Skill acquisition: Player pathways and effective practice 141

PAU L R . FOR D A N D A . M A R K W I L L I A M S

10 Sociological influences on the identification and development of players 155

M AT T H E W J. R E E V E S A N D SI MON J. ROBE RT S

11 Player wellbeing and career transitions 168

CA ROL I NA LU N D QV I S T A N D DAV I D P. S C H A RY

12 Developing (­adaptive) coaching expertise 183

C H R I S T OPH E R J. C USH ION A N D A N NA S T OD T E R

SECTION C
Sports Medicine and Biomechanics 197

13 Injury epidemiology, monitoring, and prevention 199

I A N BE A SL E Y

14 Infectious diseases 223

MON ICA DUA RT E M U ÑOZ A N D T I M M E Y E R

15 Biomechanical assessments 238

M A R K A . ROBI N S ON , K AT H E R I N E A . J. DA N I E L S , A N D
JO S VA N R E N T E RGH E M

SECTION D
Analysing and Monitoring Performances 251

16 Analysis of physical performance in ­match-​­play 253

C H R I S T OPH E R CA R L I NG A N D NAOM I DAT S ON

17 Technical and tactical match analysis 273

A L L I S TA I R P. M c ROBE RT, JAV I E R ­F E R NÁ N DE Z -​­NAVA R RO, A N D L AU R A SE T H

18 Monitoring training 292

BA R RY DRUS T A N D L AU R A B OW E N

19 Utilising training and match load data 309

PAT R IC K WA R D A N D BA R RY DRUS T
 Contents vii
SECTION E
Talent Identification, Growth, and Development 327

20 Growth and maturation 329

SE A N P. C U M M I NG , M E GA N H I L L , DAV I D JOH N S ON , JA M E S PA R R ,
JA N W I L L E M T EU N N I SE N , A N D ROBE RT M. M A L I NA

21 Talented or developmentally advanced? How player evaluation can be improved 346

S T E PH E N C OBL E Y, C H R I S T OW L S ON , SH AU N A BB O T T,
M IC H A E L ROM A N N A N D R IC L OV E L L

22 Talent identification and talent promotion 363

A R N E GÜ L L IC H A N D PAU L L A R K I N

23 Modern approaches to scouting and recruitment 382

DAV I D PIG G O T T A N D B OB M U I R

SECTION F
Some Key Organizational Roles at Clubs 395

24 Working as a director of sports science or h­ igh-​­performance director 397

T ON Y S T RU DW IC K

25 Working as a sporting director 414

DA N I E L PA R N E L L , R E BE C CA CA PL E HOR N , K E V I N T H E LW E L L ,
T ON Y A S GH A R A N D M A R K BAT E Y

Index 429
Preface

Science and Soccer (4th Edition)

Developing Elite Performers

This fully revised fourth edition of Science and Soccer includes 25 chapters grouped
into two parts and six different sections. The chapters are written by some of the lead-
ing authorities globally in their respective fields, particularly regarding the focus on
soccer. In recruiting authors, we made concerted efforts to try and include both ac-
ademics and practitioners in efforts to better translate research into practice. While
acknowledging that there remains far less research on women and special popula-
tion groups in soccer, we tasked authors with integrating this information into each
chapter where possible. The book testifies to the increasing role played by scientists in
supporting the work undertaken by practitioners and coaches in soccer, particularly
in the professional environment.
The book is not intended as an encyclopaedia of science and soccer, and we ac-
knowledge that some important topics are not covered in the book, such as, for
example, child development and safeguarding, and the role of soccer in promoting
health and physical activity in non-elite populations. These are all important topics,
but space is limited, and the focus in this book is strongly geared towards the more
elite end of the soccer pyramid. Moreover, the book is not intended as an exhaustive
course text per se, but rather may be seen as a reference source that provides back-
ground reading for students on sports science related degree programs and research
academics, as well as for practitioners and coaches, particularly those working at the
elite level.
The first part of the book is somewhat mono-disciplinary in scope. Three sections
are presented which focus respectively on the role played by the biological sciences,
the social and behavioural sciences, and sports medicine and biomechanics in enhanc-
ing scientific understanding of soccer. The second part of the book is more multi-­
disciplinary in nature focusing on three separate themed areas. The three themed
areas are analysing and monitoring performance, talent identification, growth, and
development, and finally, an overview of some of the key organisational roles per-
formed by sports science and medicine practitioners in professional clubs. The overall
aim of the book is to highlight the varied and significant role played by science in en-
hancing player performance in soccer.
In the opening section, we consider the role played by the biological sciences in
the training and preparation of players for competition. First, Strudwick highlights
the importance of how players should warm-up prior to match play and training. The
 Preface ix
chapter presents a scientific approach to designing effective warm-up routines for
training and competition. He provides insights into training methods and regimens
relevant to real working practices in elite professional soccer. In the second chapter,
Murtagh, Rydings, and Drust consider the importance of resistance training in soc-
cer. They answer questions related to the why, when, and what of resistance training
at the elite level. A model is presented to guide resistance training in elite soccer and
some of the practicalities in implementing such an approach are discussed. In similar
vein, Anderson and Drust consider the importance of aerobic and anaerobic training
to high-level performance in soccer. The authors highlight the relative importance of
both energy systems and present some practical examples as to how components of
fitness may be developed in training. Next, Sunderland, Cowe, and Marshal highlight
how performance in soccer is influenced in warm climates. They discuss some of the
mechanisms involved when adapting to playing and training in the heat and present
several mitigation strategies that can be used to minimise any adverse effects on per-
formance. Morton and colleagues outline the nutritional requirements associated with
performing at the highest level. They present guidelines for the consumption of carbo-
hydrates, protein, fluids, micronutrients, and nutritional supplements and how these
should fluctuate relative to training and match-play demands. They consider practical
considerations in implementing good nutritional practices in the professional game
and discuss the importance of recovery after match-play. Finally, Gregson and col-
leagues highlight the physiological and psychological mechanisms involved in recov-
ery and review the evidence supporting various methods proposed to facilitate the
process. These methods include, amongst others, the use of stretching, massage, cryo-
therapy, compression garments, and hot-water immersion.
In Section 2, we explore how the social and behavioural sciences have advanced un-
derstanding of the factors underpinning successful performance in soccer. First, Jor-
det and Toering highlight how certain psychological characteristics are associated with
superior performance and enhanced player development and present examples of how
these factors may be evaluated in youth and adult players. The authors provide a com-
pelling argument for greater interaction between coaches and scientists in exploring
the psychological characteristic that underpin elite player development and how psy-
chological skills may be developed through targeted interventions. ­Williams, Thomas,
Jordet and Ford then discuss the importance of anticipation and decision-making in
soccer. They review published work that has identified the skills that underpinning
superior game intelligence. They highlight how these skills may be measured and sug-
gest interventions that can be used to enhance the acquisition of ‘game intelligence’.
Notably, they highlight the importance of coaching and instruction and the poten-
tial of using virtual reality and other forms of technology to increase opportunities
for practice. Next, Ford and Williams explore some key concepts underlying skill ac-
quisition in soccer. They identify the typical developmental history profiles of elite
players, highlighting the pre-eminence of an early-engagement pathway, and review
video-based, time-use analysis of coaching sessions to identify the types of practice
activities that may be most beneficial. The authors close by briefly highlighting re-
cent conceptual developments in the field of skill acquisition and how these could be
integrated into the coaching curriculum. Reeves and Roberts focus more so on the
sociological factors that impact on talent development. They highlight the important
roles played by families, including siblings, and the importance of coach-athlete re-
lationships in player development. Moreover, they review research that has explored
x Preface
the importance of culture and socio-economic background, highlighting significant
changes in the landscape of professional soccer over recent decades. Lundqvist and
Schary explore what has hitherto been an under-researched topic in soccer, that is,
mental health and wellbeing. The authors highlight different interventions that may be
used to reduce the risks associated with mental health and increase wellbeing. Nota-
bly, they touch on the challenges involved when players transition from a professional
career into retirement and how players can be supported through this process. Finally,
to close the section, Cushion and Stodter consider the crucial role played by coaches in
player development. The authors differentiate between routine and adaptive expertise
and discuss the importance of formal and informal learning in coach education. They
highlight shortcomings with existing methods of coach education and present several
suggestions as to how the process could be improved to develop more adaptive experts.
In Section 3, chapters focus on sports medicine and the role of biomechanics in
soccer. First, Beasley reviews the most common types of injuries in soccer. He out-
lines how these injuries occur, how they are diagnosed, and the types of treatments
that are typically undertaken. Moreover, he contrasts the types of injuries that occur
in the men’s and women’s’ game, and highlights increasing awareness of the impact
of concussion on player health. Next, Muñoz and Meyer consider what impact in-
fectious diseases such as COVID-19 may have on health and performance in soccer.
They discuss the frequency, diagnosis, and treatment of infectious diseases and what
precautions may be taken to prevent infection. Guidelines are provided for returning
to training and match-play post infection. Robinson, Daniels, and Vanrenterghem
close this section by considering how biomechanical assessments may be used in a
professional soccer setting. The authors argue that the role of biomechanics in soccer
has shifted focus over time away from technique analysis and more towards providing
measures that support medical and rehabilitation monitoring. They highlight the in-
creased availability of portable and low-cost biomechanical assessments and discuss
how such measures can help in injury prevention and performance enhancement.
In Section 4, our first themed area, we explore several topics related to analysing and
monitoring player performance. First, Carling and Datson review the research carried
out on motion analysis in soccer. They highlight the physical demands of match-play
and how this differs across player position. Also, they consider how motion analysis
data may be used to monitor player workloads across periods in a match and how
such data may be used to develop player-specific training programmes as well as to
identify risks of injury. Next, McRobert, Fernández-Navarro, and Seth highlight the
key role played by technology in enhancing our tactical and technical understanding
of the game. They illustrate how performance analysis has become a crucial weapon
in the coach’s armoury. The authors review how performance analysis is used to shape
modern approaches to the game and helps coaches develop key performance indica-
tors to evaluate team and individual development. Drust and Bowen then review the
methods available for measuring and monitoring training load in elite players. They
highlight the importance of using valid measures and some of the practical difficulties
associated with monitoring, as well as the importance of building effective lines of
communication with coaches and players. Next, Ward and Drust discuss how data
gathered through the player monitoring process can be used to guide the implemen-
tation of relevant training interventions. The authors present a framework that may
be used to facilitate better efforts at identifying and answering relevant applied ques-
tions. While the framework is presented in the context of addressing questions around
 Preface xi
training workload, the approach is translatable as a working framework that may be
used across discipline areas. The authors highlight different approaches when analys-
ing and presenting data to coaches.
In Section 5, the theme is talent identification, growth, and development in soccer.
In the opening chapter, Cumming and colleagues explore the key factors underpinning
growth and maturation and how these factors can impact negatively the talent and
identification process. The authors highlight how maturity status impacts on training
and risk of injury and suggest several approaches that may be used to monitor and
mediate the potential risks associated with overtraining and burnout in youth players.
Cobley and colleagues then review the extant literature focusing on the relative age
effect in soccer. That is, the tendency of scouts and coaches to select players advanced
in chronological age relative to the selection year. They highlight the extent of the
problem and suggest some strategies that may be employed to alleviate the systematic
bias that exists in soccer, including the role of bio-banding. Next, Güllich and Larkin
present a comprehensive and critical review of existing research focusing on talent
identification. They highlight the generally low predictive utility of talent identifica-
tion programmes and argue that more resources should be devoted to promoting the
development of talent rather than on trying to identify markers of ‘potential’ that may
have limited value. The authors highlight the negative factors associated with early
talent identification programmes and suggest alternative emphases for practitioners.
Finally, Pigott and Muir discuss the tole of talent scouts in professional soccer, with
a particular emphasis on the international game. The authors highlight the paucity of
research examining the thought processes and observational skills used in scouting
and outline how they worked with a national association to develop a more systematic
and structured scouting process.
In the final section, we consider some of key the organisational roles at clubs. First,
Strudwick highlights the many roles and responsibilities that may be held when work-
ing as a Director of Sports Science both at club and international level. He outlines the
different in structures employed by clubs as well as the varying nature and emphases
of the role. Finally, Parnell and colleagues consider the role of Sporting Directors at
professional clubs. The role is comparatively new, yet many clubs at the highest eche-
lons of the sport are now embracing this management structure. The authors highlight
the potential responsibilities of the Sporting Director and discuss some of the chal-
lenges faced in the role. A couple of case studies are used to provide examples of how
such a role has already worked successfully in professional clubs in Europe.
Our intention in pulling this book together was to highlight the significant progress
made in our scientific understanding of soccer over the last decade, notably since the
last edition of this book was published in 2012. The number of scientists undertaking
research on soccer and working as practitioners in professional clubs or within na-
tional associations has mushroomed. By way of example, when the Premier League
launched in 1993, there were barely a handful of sports scientists working in the club
setting in England, whereas these days many of the elite clubs have sports science and
medicine units that are larger than the average university department in this field. The
same pattern of growth in the field is exhibited globally, albeit with some variance
depending on the financial resources available to clubs and national associations. Our
now long-passed former colleague, Professor Thomas Reilly, who had the vision to
edit the first edition of this book, and co-edited the second edition with the current
book’s lead editor, could never have envisaged the extent to which his dream became
xii Preface
a reality for those that have followed. Yet, while celebrating scientific progress, we
acknowledge that soccer at the highest level remains an art form that expresses human
creativity, skill, and imagination in its greatest form. In editing this book, we have at-
tempted to illustrate how the art of soccer can be informed and enhanced by science,
and in this regard, we hope it inspires future generations of scientists to continue to
explore the limits of performance in soccer. However, scientists working in isolation
cannot create solutions to real-world problems, and in many instances are not always
aware of the questions of interest. What remains crucial is the need for continuous
interaction and dialogue between scientists, practitioners, and coaches in efforts to
ensure that soccer as a sport continues to impact positively on society across the globe.

A. Mark Williams, Ph.D.

Florida Institute of Human and Machine Cognition

Paul R. Ford, Ph.D

St Mary’s University, London

Barry Drust, Ph.D.

University of Birmingham
Figures

2.1 The ability to produce, apply, and tolerate power/­powerful actions is

considered paramount to successful soccer performance at the elite
playing level 16
2.2 The table displays the cost associated with resistance training
exercises in each specific category 18
2.3 The repeated bout effect is a key concept to inform the detailed
prescription process 20
2.4 An illustration of the processes utilised when prescribing resistance
training interventions for the elite soccer players 22
2.5 ­Real-​­world prescription process for player 1 in different match
play formats 28
2.6 ­Real-​­world prescription process for player 2 in different match
play formats 29
2.7 ­Real-​­world prescription process for player 3 in different
match play formats 29
3.1 An overview of energy system training guidelines, physiological
adaptations, and performance changes for soccer players 38
3.2 Some typical training drills for the aerobic energy system 40
3.3 Some typical training drills for the anaerobic energy system 42
4.1 The total distance covered in a simulated soccer match in control
(­18oC) and hot (­30oC) environmental conditions (­control vs hot:
P < 0.05). Redrawn from Aldous et al. (­2015) 53
4.2 The sprint distance covered in a simulated soccer match in control
(­18oC) and hot (­30oC) environmental conditions (­control vs hot:
P < 0.05). Redrawn from Aldous et al. (­2015) 54
4.3 The h ­ igh-​­speed running distance completed during a soccer match
in control (­21oC) and hot (­43oC) environmental conditions (­control
vs hot: P < 0.05). Redrawn from Mohr et al. (­2012) 54
4.4 The baseline level response times for visual search. (­Data are mean
± SD. Pre: prior to the match simulation, HT: half time and FT: full
time. Main effect of trial, P < 0.01 and trial*time interaction,
P < 0.01.) Redrawn from Malcolm (­2018) 56
4.5 The proportion correct on the baseline level of the visual search test. 56
5.1 The energy expenditure of elite soccer players, as assessed using the
doubly labelled water method 68
xiv Figures
5.2 (­A) Resting metabolic rate (­RMR), (­B) ­fat-​­free mass, (­C) fat mass,
and (­D) percent body fat between in adolescent male soccer players
(­­U12–​­U23 age groups; n = 99) from an English Premier League academy 79
6.1a and 6.1b Recovery of knee flexor isometric force, counter movement
jump height (­1a) and ratings of subjective muscle soreness
and creatine kinase concentrations (­1b) throughout the ­72-​­h
period following m­ atch-​­play. Redrawn from Silva et al. (­2018) 92
6.2 An example of an active recovery strategy 95
6.3 An example of a foam rolling exercise 97
6.4 ­Cold-​­water immersion 99
6.5 Compression garments 100
7.1 The number of peer review articles from a search with keywords
“­psychology” and “­soccer”, registered in bibliographic database
SPORT Discus between 2001 and 2020 112
7.2 The 1­ 1-​­model. Behavioural outcomes that are important to
successfully transition from youth academy to professional first
team. Adapted from Jordet, 2016 118
8.1 A scan (­fi lmed from the position of the ball), where a player’s face is
temporarily directed away from the ball. Photo credit: Karl Marius
Aksum and Lars Brotangen 126
8.2 Some images from eye tracking goggles worn by a central midfielder
in an 11 vs. 11 match, with the small circle indicating the player’s
foveal gaze location in a scan (­scan starting at 1, ending at 5).
Photo credit: Karl Marius Aksum and Geir Jordet 127
8.3 The p ­ enalty-​­taker as presented in a ­temporal-​­occlusion condition
where information is available up to ­foot-​­ball contact (­left side)
and a spatial occlusion condition where only the hips are presented
(­r ight side) (­from Causer & Williams, 2015) 128
9.1 Hours per week in soccer practice and play across the development
of (­a) 14 national team and (­b) 15 Bundesliga players in Germany 143
9.2 The continuum of representativeness for common practice activities
with the ball in soccer 146
10.1 Parents’ experiences of the youth soccer academy parenting journey. 157
Source: Adapted from Newport et al. (­2020)
11.1 An overview of mental health as an umbrella term for both w ­ ell-​
b­ eing and illbeing 170
11.2 Classifications of interventions based on their overall target and
­r isk-​­factors (­based on Barry, 2001; Jacobsson & Timka, 2015) 172
11.3 Overview of essential factors for players’ ­well-​­being 177
13.1 Hamstring injury 201
13.2 Meniscal tear 205
13.3 Meniscal cyst 205
13.4 Degenerative change after meniscectomy 206
13.5 ACL rupture coronal 206
13.6 ACL rupture sagittal 207
13.7 Ankle injury 209
13.8 Wobble board 209
13.9 Patellar tendinopathy 211
 Figures xv
13.10 Patellar tendinopathy with Doppler © 2022 Christoph Spang,
Lorenzo Masci and Håkan Alfredson https://­w ww.mdpi.com/­­1648-​
­9144/­58/­5/­601/­htm 211
13.11 Jones fracture 213
13.12 Pocket Concussion recognition tool-5 217
14.1 The risk of URTI is lower with moderate levels of physical activity
when compared to more sedentary people. The risk of URTI
increases progressively with higher levels of physical activity.
Adapted from Nieman, 1994 227
15.1 The processing stages of a raw EMG signal 243
15.2 An isokinetic dynamometer set up for right knee testing 244
15.3 (­Left) Visualisation of the joint moment, angle, and angular velocity
profiles for a ­concentric-​­concentric ­Quadriceps-​­Hamstrings
protocol with the isokinetic phase highlighted. (­Right) Calculation
of a ­10-​­point moving average joint ­moment-​­angle profile for the
multiple trials 246
16.1 Physical match performance in professional male and female soccer
players (­adapted from Bradley et al., 2013; Datson et al., 2017) 255
16.2 A summary of the numerous factors influencing soccer ­match-​­play
running performance 260
16.3 ­High-​­intensity ­match-​­r unning performance in elite youth soccer
players according to age group (­data adapted from Saward et al., 2016) 263
17.1 The coaching process (­adapted from Maslovat & Franks, 2008) 275
17.2 The five moments of play (­Hewitt, 2016) 277
17.3 Soccer teams styles of play. Attacking styles of play: (­A) factors 1
and 6, (­B) factors 3 and 4. Defensive styles of play: (­C) factors 2 and 5 282
18.1 A schematic representation of the role on monitoring training in
supporting the training process 293
18.2 Some theoretical and practical considerations in monitoring training 295
18.3 A female player’s physical “­profile” compared to the squad average 301
18.4 An example ­well-​­being report illustrating colour coding and marks
to help inform player readiness 303
18.5 A graphical representation of the progressive increase of a player’s
chronic ­h igh-​­speed running (­training load metric) over the course of
8 weeks 304
19.1 The Problem, Plan, Data, Analysis, and Conclusion (­PPDAC) cycle 311
19.2 The normal distribution represented as a density plot and a box plot 318
19.3 Some examples of common data visualization approaches 322
19.4 Visualizing analysis of weekly change scores (­A) for an entire
team, (­B) for a single individual from ­week-­​­­to-​­week, or (­C) for an
individual player for each week relative to baseline 323
19.5 An example of a run chart for a professional soccer player 324
19.6 (­A) Astronomical point above or below the three SD control limits
(­B) Two out of three points above or below the two SD control
limits. (­C) Six or more points on the same side of the centre line.
(­D) Six or more points all going in the same direction 325
20.1 The Percentages of Male Academy Players by Maturation Status
Across Competitive Age Groups. Adapted from Johnson et al., 2017 334
xvi Figures
20.2a and 20.2b Heat maps showing the combined effects of growth
rate and POAH on estimated (­A) injury likelihood and
(­B) injury burden 338
20.3 Use of percentage of predicted adult stature to determine location in
adolescent growth curve in young athletes 338
21.1a and b The relationship between chronological and relative age with
(­a) the agility (­­T-​­test) and (­b) with the ­multi-​­stage fitness
test (­­20-​­m MFST) in UK soccer academy players (­N = 969;
Towlson et al., 2018) 349
21.2a and b The relationship between maturity status (­YPHV) with
(­a) the agility (­­T-​­test) and (­b) with the ­multi-​­stage fitness test
(­­20-​­m MFST) in UK soccer academy players (­N = 969;
Towlson et al., 2018) 350
22.1 Proportions of members of youth soccer academies and ­under-​­age
national teams persisting in the programme through subsequent age
categories (­g rey lines) and proportions of senior first Bundesliga/­
Premier League players involved in youth academies and of
senior national team players involved in ­under-​­age national teams
through previous age categories (­black lines). Aggregated data from
Anderson & Miller, 2011; Güllich, 2014, 2019; Grossmann & Lames,
2015; Hornig et al., 2016; and Schroepf & Lames, 2017 375
23.1 A ­three-​­phase approach to talent reporter CPD 387
23.2 The new talent reporter framework 388
23.3 An example of performance problems by position (­c entral defender) 389
24.1 Example organisational model associated with the operation of a
modern elite soccer team 405
24.2 A typical sports science performance management model 406
24.3 Model showing a potential periodisation strategy for player and
team preparation for a international soccer team 411
25.1 A football management structure where the Sporting Director
reports to a CEO 415
25.2 A football management structure where the Sporting Director, Head
Coach, and CEO report to the Governance Board/­Chair/­Owner 416
25.3 A simplified football management structure where the Sporting
Director would take responsibility for player recruitment 417
Tables

1.1 The rational for ­warming-​­up prior to ­match-​­play 5

1.2 Some examples of m ­ ovement-​­based stretching exercises 6
1.3 An example of an elite ­soccer-​­specific ­warm-​­up 8
1.4 A typical squad ­warm-​­up/­activation circuit 10
1.5 A hamstring strengthening programme following injury performed
twice a week as part of a ­pre-​­training routine 12
1.6 An adductor strengthening programme following groin injury
performed twice a week as part of a p ­ re-​­training routine 12
1.7 A quadriceps muscle group strengthening programme following a
quadriceps injury performed twice a week as part of p ­ re-​­training routine 12
1.8 A calf strengthening programme following calf injury performed
twice a week as part of a ­pre-​­training routine 12
2.1 The relationship between factors affecting fixture schedule demands
and the opportunity for resistance training exposures in soccer
players in starts and squad players 26
3.1 Physical testing results of n ­ on-​­elite and elite soccer players 36
5.1 An overview of CHO recommendations for soccer match
play and training 69
5.2 A suggested practical model of the “­fuel for the work required”
CHO periodisation paradigm as applied to professional soccer
players during a ­one-­​­­game-­​­­p er-​­week schedule with match day on
Saturday. Representative loads are taken from Anderson et al. (­2015) 73
5.3 An overview of specific vitamin and minerals that have been
highlighted as a potential cause for concern for soccer players
(­Collins et al., 2021), including their physiological function,
recommended nutrient intake (­RNI), typical food sources, and
potential supplement strategy if required 82
5.4 An overview of supplements that may be ergogenic to ­soccer-​­specific
physical performance 83
8.1 The average hours per year in three soccer activities for soccer
players aged 18 years in the six years prior to the ­p erceptual-​
c­ ognitive test (­Williams et al., 2012) 132
9.1 The main soccer activities in which players participate. Nb. The
main intentions of a small set of individual players within the
activity might differ compared to the main intention 142
xviii Tables
9.2 Some examples of manipulations to the rules of ­small-​­sided games
(­e.g., 3 vs. 3) that may reduce the difficulty of the sport for learners 148
9.3 Some examples of manipulations to the rules of ­small-​­sided games
(­e.g., 4 vs. 4) so that players practice specific ­p erceptual-​­motor skills
more frequently than normal 150
11.1 A summary of various subdimensions of hedonic and eudaimonic
perspectives on ­well-​­being (­based on Diener, 2009; Keyes,
1998; Ryff, 2014) 171
13.1 The POLICE/­PRICE guidelines to initial/­­first-​­aid treatment 202
13.2 Summary of information on ­CRT-​­5 form 216
14.1 Prevention of v­ ector-​­borne infectious diseases (­­Tickborne
Encephalitis, 2022; Yellow Fever, 2022) 225
14.2 Preventive measures 226
14.3 CDC recommendations for athletes for prevention of spread of
MRSA (­MRSA, 2019) 227
14.4 Infectious diseases to consider in traveling athletes 229
15.1 A schematic overview of commonly used jump evaluation approaches 239
16.1 Influence of playing position on match physical activity profile in
elite female soccer players (­data adapted from Datson et al., 2017, 2019) 257
16.2 Total distance covered (­m) by soccer players during first and second
halves of competitive ­match-​­play 258
16.3 Mean recovery duration between sprints using individualised speed
thresholds and frequency of recovery periods according to the time
elapsed between consecutive sprints, collectively and in relation to
positional role in German Bundesliga players (­data adapted from
Schimpchen, et al., 2016) 262
18.1 Potential approaches for training load monitoring including
outcome measures 298
19.1 Some examples of different forms of validity that a sport scientist
might encounter in the applied environment (­Thomas, Nelson,
Silverman, 2015) 313
19.2 Example of calculating typical error measurement and minimal
difference for a ­test-​­retest trial 314
19.3 An example of transforming raw scores into percentile rank, ­z-​­score,
and ­t-​­scores 349
21.1 Modelled differences in physiological performance indices
according to relative age between two hypothetical youth male
soccer players at the entry point to the talent development process
(­i.e., under 10 ­age-​­g roup) 349
21.2 Modelled differences in physical qualities according to biological
maturity between two ­elite-​­youth male soccer players within the
same chronological age (­14.­3-​­years old; i.e., under 15 ­age-​­group) 351
21.3 Agility test performance according to ‘­­top-​­five ranked’, ‘­relatively
youngest’, and ‘­lowest maturation status’ youth academy football
players (­under 13 years). Relative age and maturity status corrective
adjustment procedures determined adjusted performance scores and
ranks based on the relatively oldest (*) and most mature male player
(†), respectively 355
 Tables xix
21.4 ­Multi-​­stage fitness test performance according to ‘­­top-​­five’ ranked’,
‘­relatively youngest’, and ‘­lowest maturation status’ youth academy
football players (­under 13 years). Relative age and maturity status
corrective adjustment procedures determined adjusted performance
scores and ranks based on the relatively oldest (*) and most mature
male player (†), respectively 356
22.1 The effect sizes for studies investigating predictive effects of
potential talent indicators of youth soccer players on their later
playing performance 367
22.2 An overview of predictive effects of potential talent indicators of
youth soccer players on their later playing performance (­references
reported in ­Table 22.1) 368
22.3 Some impediments to reliable talent identification in youth soccer
(­following Güllich & Cobley, 2017) 369
22.4 The effects (­Cohen’s d) of the age of selection for a talent promotion
programme on later junior and adult playing performance 373
22.5 The annual player turnover in TPPs and the proportion of identical
players in a squad after 3 and 5 years 374
23.1 An example short report (­for a YDP player) [team names redacted] 391
23.2 Extracts of reports of the same player (­U21 #9) under the old and
new systems 392
24.1 Some of the key responsibilities of a ­High-​­Performance Director 399
24.2 ­High-​­performance status of elite players 401
24.3 Some key challenges at an international level of competition 409
25.1 Some challenges facing the Sporting Director in practice and the
skills and competencies required to address them 424
Contributors

Shaun Abbott is at The University of Sydney, Australia.

­Abd-​­Elbasset Abaidia is at University of Sfax, Tunisia.
Liam Anderson is at Crewe Alexandra Football Club, UK.
Tony Asghar is at Dundee United Football Club, UK.
Mark Batey is at Manchester Metropolitan University, UK.
Ian Beasley is at Queen Mary University of London, UK.
Laura Bowen is at Southampton Football Club, UK.
Rebecca Caplehorn is at Tottenham Hotspur Football Club, UK.
Christopher Carling is at French Football Federation; and French Institute of Sport,
France.
Graeme L. Close is at Liverpool John Moores University, UK.
Stephen Cobley is at The University of Sydney, Australia.
Stacey Cowe is at Nottingham Trent University, UK.
Sean P. Cumming is at University of Bath, UK.
Christopher J. Cushion is at Loughborough University, UK.
Katherine A. J. Daniels is at Manchester Metropolitan University, UK.
Naomi Datson is at University of Chichester, UK.
Barry Drust is at University of Birmingham, UK.
Monica Duarte Muñoz is at Saarland University, Germany.
Gregory Dupont is at Liverpool John Moores University, UK.
Javier ­Fernández-​­Navarro is at Liverpool John Moores University, UK.
Paul R. Ford is at St Mary’s University, UK.
Warren Gregson is at Manchester Metropolitan University, UK.
Arne Güllich is at Technical University of Kaiserslautern, Germany.
 Contributors xxi
Megan Hill is at Southampton Football Club; University of Bath; and Leeds Beckett
University, UK.
David Johnson is at AFC Bournemouth; and University of Bath, UK.
Geir Jordet is at Norwegian School of Sport Sciences, Norway.
Paul Larkin is at Victoria University, Australia.
Ric Lovell is at Western Sydney University, Australia.
Carolina Lundqvist is at Linköping University, Sweden.
Robert M. Malina is at University of Texas, USA.
Allistair P. McRobert is at Liverpool John Moores University, UK.
Tim Meyer is at Saarland University, Germany.
Rachel Malcolm is at Nottingham Trent University, UK.
James P. Morton is at Liverpool John Moores University, UK.
Bob Muir is at Leeds Beckett University, UK.
Conall Murtagh is at Liverpool Football Club, UK.
Daniel Parnell is at University of Liverpool, UK.
James Parr is at Manchester United Football Club, UK.
David Piggott is at Leeds Beckett University, UK.
Matthew J. Reeves is at University of Central Lancashire, UK.
Simon J. Roberts is at Liverpool John Moores University, UK.
Mark A. Robinson is at Liverpool John Moores University, UK.
Michael Romann is at Swiss Federal Institute of Sport Magglingen, Switzerland.
David Rydings is at Liverpool Football Club, UK.
David P. Schary is at Winthrop University, USA.
Laura Seth is at The Football Association, UK.
Hannah Sheridan – ​­Tottenham Hotspur Football Club, UK.
Anna Stodter – Leeds
​­ Beckett University, UK
Tony Strudwick – Arsenal
​­ Football Club, UK
Caroline Sunderland – ​­Nottingham Trent University, UK
Jan Willem Teunnisen – ​­Bruges University, Belgium.
Jospeh L. Thomas is at Real Salt Lake, USA.
Chris Towlson is at University of Hull, UK.
Kevin Thelwell is at Everton FC, UK.
xxii Contributors
Robin Thorpe is at Liverpool John Moores University, UK.
Tynke Toering is at Hanze University of Applied Sciences, The Netherlands.
Jos Vanrenterghem is at KU Leuven, Belgium.
Patrick Ward is at Seattle Seahawks, USA.
A. Mark Williams is at The Institute for Human & Machine Cognition, Florida, USA.
Section A

Biological Sciences
1 Physical preparation
T. Strudwick

Introduction
The key objective of this chapter is to provide a comprehensive account of the pa-
rameters that impact upon the physical preparation of elite players. This chapter will
help coaches and practitioners use current scientific information in designing effective
activation and ­warm-​­up routines for training and competition.
In the first section, a brief theoretical background about the importance of effective
­match-​­day routines will be given. The second section is mostly focused on applying
the principles of activation and w ­ arm-​­up strategies, with a special insight into training
methods and regimens relevant to real working practices in professional soccer.

Preparation
The physiological demands on the modern soccer player are more variable and com-
plex than in many individual sports and are dependent on many factors such as po-
sitional role, style of employed by the team, and the level of the opposition. It’s clear
that contemporary players are required to not only produce actions, but also to repeat
them throughout the duration of competition while maintaining a low fatigue index.
Soccer consists of ­h igh-​­intensity movements that include sprints, jumps, intermittent
movement direction, and speed changes with many acceleration and deceleration ac-
tions. These kinds of activities require appropriate preparation to enable athletes to
show their full physical potential from the very beginning of a competition (­Pagaduan
et al., 2012).
At the elite level of play, there has been a shift towards systematic methods of prepar-
ing players for ­match-​­play. While the formal ‘­­warm-​­up’ has not always been a tradition
within the soccer community, current day players have been exposed to a more robust
and scientific approach prior to competitive m ­ atch-​­play and ­h igh-​­intensity training
sessions. Moreover, it is now widely accepted that w ­ arming-​­up prior to exercise is vital
for the attainment of optimum performance.
A ­warm-​­up refers to the execution of physical exercise prior to the main activity
in training or competition (­Hedrick, 1992). Coaches and conditioning practitioners
routinely use ­warm-​­up routines to facilitate the increase in body temperature, the
acceleration of metabolism, and elevated oxygen uptake kinetics. Independently of
the increase in muscle temperature, a w ­ arm-​­up can potentially increase performance
by ‘­­pre-​­conditioning’ the muscle (­Racinais et al., 2017). This phenomenon called

DOI: 10.4324/9781003148418-2
4 T. Strudwick
­post-​­activation potentiation (­PAP) is generally obtained by performing a maximal or
near maximal contraction and has been suggested to have additional benefits relative
to a traditional ­warm-​­up to improve performance in explosive activities (­Güllich &
Schmidtbleicher, 1996; Tillin & Bishop, 2009).
Recently, a new concept of PAP has been proposed to be more ­in-​­line with the
timeline of peak voluntary performance enhancement (­Silva et al., 2020). Thus, ­post-​
a­ ctivation performance enhancement (­PAPE) occurs when a ­h igh-​­intensity voluntary
conditioning contraction leads to enhancement of subsequent involuntary muscular
performance without confirmatory evidence of classical PAP (­­ Cuenca-​­Fernandez
et al., 2017). The PAPE effect can be explained with the increase of muscle tempera-
ture, fibre water content, and activation, but inhibited by residual fatigue and motor
pattern interference (­Blazevich & Babault, 2019). Therefore, the PAPE effectiveness
depends on the balance between potentiation and fatigue, and this should be taken
into consideration when designing ­warm-​­up routines (­Silva et al., 2020).
The application of ­evidence-​­based preparation strategies has a ­self-​­evident role in
improving elite performance. In general, individuals and teams that adopt a strategic
approach have been rewarded with success by gaining an advantage over competitors.
However, it has taken some time for the accumulation of ­scientific-​­based knowledge
to be translated into a form usable by practitioners. McGowan et al. (­2015) provided
­research-​­based support for the physiological and neural responses to passive and ac-
tive ­warm-​­up strategies.
Passive ­warm-​­up strategies are those techniques used to increase body temperature
without depleting energy substrate stores. Active w ­ arm-​­up strategies, on the contrary,
induce greater metabolic changes, leading to increased preparedness for a subsequent
exercise task. According to McGowan and colleagues (­2015), the following key points
pertaining to the use of a w­ arm-​­up are supported in the literature.

• Passive and active w­ arm-​­ups markedly influence subsequent exercise performance

via increase in adenosine triphosphate turnover, muscle ­cross-​­bridge cycling, and
oxygen uptake kinetics, which enhance muscular function.
• An active ­warm-​­up, consisting of a brief (<15 min) aerobic portion and completion
of four to five activation sprints/­­race-​­pace efforts, PAP exercises, or ­small-​­sided
games, elicits improvements in performance.
• Passive heat maintenance techniques can preserve the beneficial temperature ef-
fects induced via active ­warm-​­up during lengthy transition phases.

It is important that the ­warm-​­up is well planned. The routine needs to be specific and
objective, taking into consideration the player’s potential and rate of development. It
is apparent that there are many components that need to be incorporated into the rou-
tine. These include a full range of activities such as individual and team preparation,
match rehearsal, activation modalities, and injury prevention strategies, in addition
to the more obvious ­warming-​­up. The design of the routine should be based on indi-
vidual training philosophy and specificity to match performance per se. The need to
isolate match performance components and to control workload intensity is achieved
by a series of activities conducted within the period.
All ­warm-​­up routines should incorporate elements of muscular activation and
warming up to facilitate the appropriate recruitment of muscle fibres associated with
the correct sequencing and timing of s­occer-​­specific activities. Speed preparation
 Physical preparation 5
should follow with adequate recovery time between repetitions and sets to allow con-
tinual energy resynthesis. Subsequent stimulation of the aerobic systems should then
be performed via specific drills with the ball involving changes of speed, direction, and
specific movement patterns typical of those performed during match play. Exercises
such as ­small-​­sided games (­SSG) and shooting are often employed by coaches in the
­warm-​­up routine. These exercises can potentially boost performance through priming
neural pathways and increased neuromuscular activation while maintaining a link to
technical and tactical principles (­Silva et al., 2020).

Match day routines

In addition to the physiological rationale for w ­ arming-​­up prior to m
­ atch-​­play, some of
the main reasons for ­warm-​­up activities are listed in T ­ able 1.1. First, the term w ­ arm-​
u
­ p signifies that the objective is to raise body temperature so that subsequent perfor-
mance potential is enhanced. As muscles utilize energy during contraction, less than
a ¼ of the energy goes towards producing mechanical work, leaving the remainder
to generate heat within the muscle cells. Muscular performance is improved as tem-
perature rises, but only up to a point. An increase in body temperature of one degree
[Celsius] is sufficient to maximize the ergogenic effect on the active muscles (­Reilly &
Waterhouse, 2005). Clearly, the most effective means of generating the necessary inter-
nal heat is via different modes of movement and running.
When designing a w ­ arm-​­up routine, coaches should take into consideration sev-
eral factors, such as duration, volume, intensity, and the sequencing of the selected
exercises (­Silva et al., 2020). In contemporary elite soccer, the ­warm-​­up is frequently
performed over an extended period (>20 min), which may promote fatigue and in-
hibit performance enhancement. While a shorter w ­ arm-​­up appears to have similar
benefits as a longer w ­ arm-​­up (­Mujika et al., 2012), some players report the need for
longer ­warm-​­up periods to feel psychologically prepared for competition (­Yanci et al.,
2019). It may well be that future p ­ re-​­match routines will involve an educational shift to
shorter duration and hence less physiologically taxing routines, while at the same time
satisfying ­h igh-​­intensity stimulation and psychological readiness.
Regardless of exercise sequence, the ­warm-​­up should progress in intensity, preparing
for the specific tasks of the sport, and finishing with tasks of maximum intensity (­Silva
et al., 2018). The specific skill tasks should be related to game situations to promote
transfer to match actions. Within the framework, coaches may design shooting and
tactical combinations to replicate positional attacking patterns. Where appropriate,

­Table 1.1 The rational for ­warming-​­up prior to ­match-​­play

Elevate body temperature Increase range of motion

Increase muscle temperature Familiarize with environment
Reduce muscle tightness Potentiate neuromuscular system
Decrease risk of injury
Activate neuromuscular system
Match rehearsal
Increase arousal levels
Rehearse game skills
6 T. Strudwick
skill tasks with opposition should be included to replicate the competitive demands of
­match-​­play. To maximize preparation effectiveness, it makes sense to include w ­ arm-​
u ­ p exercises that combine physical demands with a technical and tactical purpose,
­in-​­line with the context of the upcoming competitive match (­Silva et al., 2020).
Historically, the w
­ arm-​­up routine consisted of a jog around the pitch, static, and
dynamic flexibility exercises, and speed, agility, and quickness activities. In this re-
spect, the mode of activity is important. Stretching the main muscles used during the
subsequent performance via eccentric contractions results in a transient increase in
flexibility. This enhanced range of motion improves the capability of the muscle to
yield under the anticipated strain. The stretching activity is generally promoted as a
way of improving flexibility and preventing injuries. Dynamic and static stretching are
the two major types of stretching interventions. Dynamic stretching involves the exe-
cution of a muscle group to a full range of motion without the help of an external force.
On the contrary, static stretching uses the assistance of an external force to achieve the
full range of motion of a muscle group (­Pagaduan et al., 2012).
Stretching the main thigh muscles is especially important prior to evening matches
and in cold winter conditions. Particular attention should be directed toward the ham-
strings and hip adductor muscles. Tightness in these muscle groups is often prevalent
in elite soccer players and is associated with an increased predisposition to injury.
­Table 1.2 provides a selection of m
­ ovement-​­based stretching that can form the basis on
which to progress to a more dynamic exercise selection.
Flexibility exercises form an essential component of the w ­ arm-​­up, although the
method of exercises designed to increased range of motion may vary due to individual
philosophy. Although contemporary scientific research supports dynamic stretching
routines over traditional methods like static stretching, some practitioners are still
reluctant to totally discontinue traditional methods. Dynamic flexibility refers to the
ability to move part or parts of the body quickly. Intuitively, including exercises de-
signed to move the body quickly should form an integral component of p ­ re-​­match
routines.
Previously, researchers have reported that static stretching leads to reduced knee
extensor power and jump performance compared to dynamic stretching (­Costa et al.,
2010; Hough et al., 2009; Yamaguchi & Ishii, 2005; Cornwell et al., 2002). However,

­Table 1.2 Some examples of ­movement-​­based stretching exercises

Forward high knee march Maintain tall posture. Bring thigh up and flex knee maximally.
Forward lunge walking Keep hand on hips. Lunge far forward to get a stretch. Stand up
and bring the opposite hip up to 90º before lunging again.
­Jack-​­k nife walk ­P ush-​­up position. Walk the feet towards your hands (­keep legs
straight). Maintain flat heels and flat hands. Walk the hands
forward. Repeat.
Lateral lunge Step out to right and squat by sitting back and down on right leg.
Keep left leg straight.
Backward lunge with a Step back with right leg into a lunge. Arch back while twisting
twist torso over left leg and reaching right hand to sky.
Drop lunge Turn hips to left and reach back with left foot until it is about 0.75 m
to the outside of right foot, left toes pointing to right heel.
Rotate hips so facing forward and square. Drop into full squat.
Inverted hamstring Balance on right foot and bend at waist.
 Physical preparation 7
when static stretching is incorporated with other dynamic activities (­e.g., jogging),
similar jump performance with dynamic stretching and dynamic activities is observed
(­Vetter, 2007; Chaouachi et al., 2010). Other authors have reported deleterious ef-
fects of static stretching on sprint performance despite being combined with dynamic
stretching or an aerobic ­warm-​­up (­Sim et al., 2009; Winchester et al., 2008; Fletcher &
Annes, 2007).
While it is not suggested that static stretching should be eliminated from ­pre-​­match
routines, the scientific community supports the concept of a more dynamic approach
to w­ arm-​­up regimens. These dynamic routines emphasize progressive, ­whole-​­body,
continuous movement and are typically performed in running drills that include for-
ward, lateral, and changes of direction. Some examples of dynamic w ­ arm-​­up exercises
include lunges, squats, hops, jumps, high knees, high kicks, and leg swings. Moreover,
these routines have the potential to bolster the execution of ­match-​­play activities that
involve jumping or rapid body movement.
New scientific methods for exercise preparation also point to the role of the ­warm-​
u­ p in injury prevention (­FIFA 11+). Injury prevention strategies are most effective
when the w ­ arm-​­up activities are specific to the sport. This principle implies that the
­warm-​­up routines include unorthodox modes of running, sprinting, turning, and
jumping as well as intense muscular bursts such as accelerations and decelerations.
All these efforts exacerbate the physiological strain imposed on players and contrib-
ute to high physical workloads during subsequent competition, so caution should be
made to ensure the ­warm-​­up routine is neither too exhaustive or prolonged. There is a
balance to be struck between the arousal and activation benefits on the one hand and
the induction of fatigue on the other. Most elite teams have a total preparation time of
around 30 min taking into consideration climatic conditions. Moreover, in cold winter
conditions, more focus should be placed on elevating body temperature in the form of
­r unning-​­based exercises compared to warm climatic conditions.
The intensity and duration of the w ­ arm-​­up should be reduced when the weather is
hot. In contrast to the beneficial effects of ­warming-​­up, the development of ­whole-​
b
­ ody hyperthermia impairs neuromuscular function, with alterations occurring at
both the central and peripheral level (­Racinais et al., 2017). The goal of the ­warm-​
u
­ p in hot climates is to optimize physiological readiness through the activation of
predominant energy systems and movement patterns, without producing unnecessary
metabolic heat that may become more p ­ erformance-​­limiting toward the end of the
competition (­­González-​­Alonso et al., 2008).
There are specific effects of the ­warm-​­up on the neuromuscular system. Among
the more obvious consequences are the likely psychological benefits of m ­ atch-​­play re-
hearsal, such as passing and shooting skills. There are also the PAP effects of stimu-
lating the nervous system by means of brief, highly intense muscular efforts prior to
competition (­Tillin & Bishop, 2009). However, the effect is thought to decay after only
a few minutes (­Wilson et al., 2013).
A final consideration is the timing of the w ­ arm-​­up so that its benefits are not negated
prior to the start of the game. Muscle and body temperature will remain elevated for
some minutes after exercise is finished. It would therefore be prudent to terminate
the ­warm-​­up 10 min prior to the start of competition to facilitate a short recovery
and allow for psychological preparations. This information is also relevant for the
management of substitutes, as these players must be ready to enter the field of play at
any given moment. It is therefore advisable to instruct substitutes to w ­ arm-​­up every
8 T. Strudwick
­Table 1.3 An example of an elite ­soccer-​­specific ­warm-​­up

­KO – ​­40 min Leave dressing room

­KO – ​­38 min Individual preparation
­KO – ​­35 min Start of dynamic movements/­stretching
­KO – ​­29 min 4 v 4 + 2 (­work 60 s: rest 30 s × 2)
­KO – ​­26 min Attacking shape
­KO – ​­21 min Finishing 90 s each side
­KO – ​­17 min Individual/­corners/­free kicks
­KO – ​­12 min Sprints
­KO – ​­10 min ­Re-​­enter dressing room
­KO – ​­2 min Leave dressing room

Active ­warm-​­up induces greater metabolic changes, leading to increased

preparedness for a subsequent exercise task.

20 min throughout ­match-​­play for approximately ­5 –​­10 min. The half time interval
also provides an excellent opportunity to raise body temperature and increase match
readiness. Once again, climate plays an important role in the management of substi-
tutes, where cold winter conditions necessitate the need to extend working periods and
ensure muscle temperature is optimal. An example of a typical elite s­occer-​­specific
­warm-​­up prior to elite participation is provided in ­Table 1.3.
Over the past decade, it has become common for elite teams to conduct a ­re-­​­­warm-​
­up to protect against physiological changes and reductions in exercise performance
due to a passive recovery during the ­half-​­time period (­Yanaoka et al., 2021). Previously,
researchers reported that intermittent ­team-​­sport players perform a lower amount of
­h igh-​­intensity running during the first 15 min of the second half compared to the first
half (­Mohr et al., 2005). This finding is surprising given the fact that players have a
passive recovery during the h ­ alf-​­time period. Lack of preparation and/­or activation
for the second half may be a reason for the reduced amount of high intensity, as players
­warm-​­up before matches, but not during h ­ alf-​­time (­Silva et al., 2018). It is, therefore
prudent for coaches to administer a ­re-​­warm up before the onset of the second half to
maximize performance after half time. This would include m ­ atch-​­specific movements
as well as h ­ igh-​­intensity explosive actions.

Training routines
In recent years, match analysis data have clearly demonstrated that the game includes
more explosive events than ever before (­Bradley et al., 2009). These increased demands
mean that players require the strength, power, and speed to perform actions repeat-
edly, such as kicking, accelerating, maximal velocity sprinting, decelerating, changing
direction, tackling, and jumping. At all competitive levels, these h ­ igh-​­powered actions
can prove to be the difference between winning and losing. Therefore, it is prudent for
practitioners to utilize player preparation time and/­or the w
­ arm-​­up/­activation routines
for ­multi-​­lateral physical development and injury prevention.
­Modern-​­day elite players should undergo valid and reliable assessment or test-
ing protocols to ascertain their movement competency, strength, and power perfor-
mance status. ­Player-​­specific programmes can then be prescribed and delivered via
preparation/­activation routines to improve many aspects of movement competency or
athleticism, strength, and power where a player has a particular weakness or deficit.
 Physical preparation 9
Increasing a player’s movement competency in key movements such as squatting, lung-
ing (­in multiple planes), hip hinging, bracing, and rotating is a component of many
contemporary training w ­ arm-​­up regimens and can assist in the important goals of
reducing injury incurrence and increasing physical performance. Moreover, players
who are sufficiently competent in specific movement patterns can then be trained to
express force maximally or explosively.
In the preparation of elite soccer players, practitioners have a responsibility to im-
plement a comprehensive and planned training programme that allows for ­g ym-​­based
injury prevention strategies. The player must be trained in such a way that the body
will be prepared for optimum response to the physical demands of training and compe-
tition. Strength training has been increasingly employed in the holistic management of
contemporary soccer players and has become more evident in the training day ­warm-​
u
­ p and activation routines. In simple terms, strength training involves increasing the
ability of the athlete to apply force. The ultimate objectives of strength training are to
develop the capacity to reproduce forceful bursts of energy and withstand the forces
of physical impact, landing, and deceleration. Following specific screening protocols
for local muscles, as well as joints and lower back/­p elvis, preventative ­g ym-​­based pro-
grammes in the form of core stability, balance, proprioception, muscular strength,
and power should be implemented to address the increasing issues of muscle strains in
contemporary elite soccer.
Training that prepares the muscle and muscle cells for the trauma and damage
caused by repeated h ­ igh-​­force generation has become an area of increased attention
in the training of elite soccer players. Friden and Leiber (­1992) suggest that eccentric
activity, given the relatively small amount required to induce muscle damage and ad-
aptation, may have a valuable role to play in a training regime. It follows that eccentric
training in the form of g­ ym-​­based activation/­preventative exercises may be an effec-
tive way to promote resistance to muscular damage. Therefore, a training programme
should include periodic and systematic exposure to activities involving the generation
of large muscle forces to stimulate changes in the cytoskeletal system. Clearly, for this
type of adaptation to be transferable to soccer, one must ensure that the h ­ igh-​­force
activities fully exploit the muscles and motor units, the range of motion, and the con-
traction velocity typical of movements performed.
While there are many components that need to be incorporated into ­g ym-​­based
activation/­injury prevention programmes, the following areas may be included in the
physical preparation programme of elite players.

1 Mobilization/­ activation
2 Core stability and rotational strength
3 Power exercises
4 Eccentric exercises
5 Reactive exercises
6 Balance/­proprioception
7 Strength exercises
8 Stretching

A recommended w ­ arm-​­up/­activation circuit conducted prior to training twice a week

is provided in ­Table 1.4. Players may work for 5 min in each group and then move to
the next group. Exercise selection, sets, reps, and resistance will depend upon the age
10 T. Strudwick
­Table 1.4 A typical squad ­warm-​­up/­activation circuit

Area Rationale Sample exercises

Activity 1 Glut activation/­ Strengthen the gluts, Glut ­m ini-​­band walks,

movement groins & hamstrings with med ball squat, lunge, lateral
mechanics functional movements squat, single leg RDL.
using light or no
resistance. The inability
to activate gluteal group
is associated with injuries
such as lower back pain,
hamstring strain and
anterior knee pain.
Activity 2 Torso Stability/­ To improve the players’ Torso stability: Front &
Strengthening ability to transfer force side plank exercises and
from the ground to variations, Posterior stability
the extremities, while exercises.
preventing uncontrolled Torso Strengthening: (­a)
movements of spine/­p elvis. ­A nti-​­extension exercises;
movements of arm and leg
with limited movement of
torso, (­b) Rotational and
­anti-​­rotational exercises;
producing and resisting
against rotary force.
Activity 3 Proprioception/­ To improve the ability of the Bilateral landings in place,
landing body to land and stabilize bilateral landings with
mechanics correctly yet provide a movement, unilateral
foundation from which to landings in place, unilateral
progress to more explosive landings with movement.
plyometric movements. A intensity can be increased by
recurrence of inadequate increasing height/ resistance/­
landings may lead to surface instability.
ankle, knee, and hip joint
injury.
Activity 4 Hip mobility The ability to maintain Hurdle overs (­Hip flexion/­
strength through a range extension), hurdle adduction/­
of motion is important for abduction (­b ent/­straight
soccer players to prevent leg), resisted leg swings
injury and to provide (­­front–​­back, ­side–​­side),
a platform to produce hurdle unders, slideboard
power. adduction.

and experience of the player and stage of season. An outline of this strategy, with the
rationale for exercise selection, is also provided in T
­ able 1.4.
More recently, the FIFA 11+ has gained popularity as a strategy to develop the
physical capacities of players and assist in injury prevention. The FIFA 11+ injury pre-
vention programme was developed by an international group of experts based on their
practical experience with various injury prevention programmes for amateur players
aged 14 or older (­Bizzini & Junge, 2016). It is a complete ­warm-​­up package that is rec-
ommended to replace the typical ­warm-​­up before training for amateur teams (­Bizzini
et al., 2013).
 Physical preparation 11
The FIFA 11+ has three parts.

• Part 1: Running exercises at a slow speed combined with active stretching and
controlled partner contacts.
• Part 2: Six sets of exercises focusing on core and leg strength, balance, and plyo-
metrics, and agility, each with three levels of increasing difficulty.
• Part 3: Running exercises at moderate to high speed combined with planting and
cutting movements.

The key point of the programme is to use the correct technique during all the exer-
cises. Players must pay full attention to correct posture and good body control, in-
cluding straight leg alignment, ­k nee-­​­­over-​­toe position, and soft landings (­Bizzini &
Junge, 2016).
A study of more than 1,500 youth female players reported that performing the FIFA
11+ regularly reduced training injuries by 37% compared with performing a standard
­warm-​­up (­Soligard et al., 2008). More recently, a large randomized controlled study in
male soccer players (­NCAA Divisions I and II) found fewer training and match inju-
ries in teams practicing the FIFA 11+ as a w ­ arm-​­up routine (­Silvers et al., 2015). Other
authors have found improvements in static and dynamic balance and thigh muscle
strength in male soccer and futsal players after they performed the FIFA 11+ pro-
gramme (­Brito et al., 2010; Daneshjoo et al., 2012; Reis et al., 2013).
­Re-​­injuries constitute 12% of all soccer injuries and cause longer absences than
other injuries (­Ekstrand et al., 2011). Although no definitive evidence suggests that
strengthening previously injured areas alone prevents reinjury, it has recently been
demonstrated that increasing eccentric hamstring strength is associated with re-
duced risk of future hamstring injury in a cohort of previously injured Australian
soccer player (­Opar et al., 2015). Therefore, it makes sense for strength and condi-
tioning practitioners to develop a supportive programme for soccer players to allow
for opportunities within the ­pre-​­training day routine when they return to training,
and, thereafter, to work on key areas of development. This area will depend on each
player’s injury history and nature. For some previous serious injury history, the player
may continue this area of development throughout his/her career. All routines should
consist of ­concentric–​­eccentric and isometric contractions working across the ­force-​
v­ elocity continuum. Some examples of development protocols for a player who is fully
rehabilitated from hamstring, adductor, quadriceps, and calf muscle group strains are
presented in ­Tables 1.­5 –​­1.8, respectively.

Future directions and conclusions

Traditionally, ­warm-​­up routines were developed largely on a ­trial-­​­­and-​­error basis, uti-
lizing coach and athlete experiences rather than scientific evidence. However, over the
past decade or so, new research has emerged, providing greater insight into how and
why ­warm-​­up influences subsequent performance. In future, match preparation rou-
tines will continue to develop to maximize performance from the onset of competitive
­match-​­play.
While there is a lack of research pertaining to the mental areas of p ­ re-​­match rou-
tines, the next decade will explore how physical and psychological techniques will
run in parallel as part of the same preparation strategy. The role of the performance
12 T. Strudwick
­Table 1.5 A hamstring strengthening programme following injury performed twice
a week as part of a ­pre-​­training routine

Exercise Sets Sample exercises

Nordic hamstring lowers 2 or 3 ­4 –​­6

­Single-​­leg RDL (­resisted) 2 or 3 6 On injured leg
Slide board hamstring curl 2 or 3 ­8 –​­10
­Single-​­leg hamstring bridge 2 or 3 6 On injured leg
­Single-​­leg speed hop 2 or 3 5 × 2 Each leg

A n adductor strengthening programme following groin injury performed

­Table 1.6 
twice a week as part of a p
­ re-​­training routine

Exercise Sets Sample exercises

­Single-​­leg squat 2 or 3 5 Each leg

Hip adduction 2 or 3 6 Each leg
Eccentric slide board adduction 2 or 3 6 Each leg
Kossacks 2 or 3 ­8 –​­10
Side plank with leg movements 2 or 3 ­6 –​­8 With injured leg

Table 1.7 A
 quadriceps muscle group strengthening programme following a
quadriceps injury performed twice a week as part of pre-training routine

Exercise Sets Sample exercises

­Single-​­leg squat 2 or 3 5 Each leg

Rear raised lunge 2 or 3 6 Each leg
Lateral speed skater hop & hold 2 or 3 ­8 –​­10 Each leg
­Single-​­leg speed hop 2 or 3 5 × 2 On injured leg
­Single-​­leg ­90-​­degree ISO hold 2 or 3 30 secs On injured leg

A calf strengthening programme following calf injury performed twice a

­Table 1.8 
week as part of a ­pre-​­training routine

Exercise Sets Sample exercises

Eccentric calf lower 2 or 3 ­6 –​­8 On injured leg

Calf raise 2 or 3 ­8 –​­10
Low box hold and freeze 2 or 3 ­8 –​­10
Bouncing calf raise 2 or 3 ­6 –​­8 Each leg
­Single-​­leg speed hop 2 or 3 5 × 2 On injured leg

psychologist will become more influential, employing techniques such as managing

emotions, performance focus, and technical/­tactical imaging. Thus, the focus may
shift from not only preparing the muscular system, but also the mind to facilitate
winning performance.
Now more than ever, the significance of the ­warm-​­up ­pre-​­match and after ­half-​­time
has been identified. The volume, intensity, and sequencing of activities will be further
 Physical preparation 13
explored when designing w ­ arm-​­up routines. In addition, practitioners will search for
solutions to create the appropriate balance between potentiation and fatigue, and
the future of the ­warm-​­up may look at quality vs quantity in attempts to maximize
performance.

References
Bizzini, M., & Junge, A. (­2016). Injury frequency and prevention. In Tony Strudwick (­Ed.),
Soccer Sci, p­p. ­337–​­364. Australia: Human Kinetics.
Bizzini, M., Junge, A., & Dvorak, J. (­2013). Implementation of the FIFA 11+ football warm up
program: how to approach and convince the Football associations to invest in prevention. Br
J Sports Med, 47, ­803–​­806.
Blazevich, A. J., & Babault, N. (­2019). ­Post-​­activation potentiation versus ­post-​­activation per-
formance enhancement in humans: Historical perspective, underlying mechanisms, and cur-
rent issues. Front Physiol, 10, 1359.
Bradley, P. S., Sheldon, W., Wooster, B., Olsen, P., Boanas, P., & Krustrup, P. (­2009). High
intensity running in English FA premier league soccer matches. J Sports Sci, 27, ­159–​­168.
Brito, J., Figueredo, P., Fernandes, L., & Seabra, A. (­2010). Isokinetic strength effects of FIFA’s
“­The 11+” injury prevention training programme. Isokin Exe Sci, 18(­4), ­211–​­215.
Chaouachi, A., Castagna, C., Chtara, M., Brughelli, M., Turki, O., Galy, O., Chamari, K., &
Behm, D. G. (­2010). Effect of ­warm-​­ups involving static or dynamic stretching on agility,
sprinting, and jumping performance in trained individuals. J Strength Cond Res, 24, ­2001–​­2011.
Cornwell, A., Nelson, A., & Sidaway, B. (­2002). Acute effects of stretching on the neuromechan-
ical properties of the triceps surae muscle complex. Eur J Appl Physiol, 86, ­428–​­434.
Costa, P. B., Ryan, E. D., Herda, T. J., Walter, A. A., Hoge, K. M., & Cramer, J. T. (­2010). Acute
effects of passive stretching on the electromechanical delay and evoked twitch properties.
Eur J Appl Physiol, 108, ­301–​­310.
­Cuenca-​­Fernandez, F., Smith, I. C., Jordan, M. J., MacIntosh, B. R., ­Lopez-​­Contreras, G.,
Arellano, R. (­2017). ­Non-​­localized post activation performance enhancement (­PAPE) effects
in trained athletes: a pilot study. Appl Physiol Nutr Metab, 42, ­1122–​­1125.
Daneshjoo, A., Mokhtar, A. H., Rahnama, N., & Yusof, A. (­2012). The effects of comprehensive
­warm-​­up programs on proprioception, static and dynamic balance on male soccer players.
PLoS ONE, 7(­12), e51568.
Ekstrand, J., Haggluned., & Walden., (­2011). Epidemiology of muscle injuries in professional
football (­soccer). Am J Sports Med, 39(­6), ­1226–​­1232.
Fletcher, I. M., & Annes, R. (­2007). The acute effects of combined static and dynamic stretch
protocols on ­fi fty-​­meter sprint performance in ­track-­​­­and-​­field athletes. J Strength Cond Res,
21, ­784–​­787.
Friden, J., & Leiber, R. L. (­1992). Structural and mechanical basis of ­exercise-​­induced muscle
injury. Med Sci Sports Exe, 24, ­521–​­530.
­González-​­Alonso, J., Crandall, C. G., & Johnson, J. M. (­2008). The cardiovascular challenge of
exercising in the heat. J Physiol, 586, ­45–​­53.
Güllich, A., & Schmidtbleicher, D. (­1996). ­MVC-​­induced ­short-​­term potentiation of explosive
force. New Studies Athletics, 11, ­67–​­81.
Hedrick, A. (­1992). Physiological responses to ­warm -​­up. J Strength Cond Res, 14, ­25–​­27.
Hough, P. A., Ross, E. Z., & Howatson, G. (­2009). Effects of dynamic and static stretching on
vertical jump performance and electromyographic activity. J Strength Cond Res, 23, ­507–​­512.
McGowan, C. J., Pyne, D. B., Thompson, K. G., & Rattray, B. (­2015). ­Warm-​­up strategies for
sport and exercise: Mechanisms and applications. Sports Med, 45(­11), 1523-46.
Mohr, M., Krustrup, P., & Bangsbo, J. (­2005). Fatigue in soccer: A brief review. J Sports Sci, 23,
­593–​­599.
14 T. Strudwick
Mujika, I., de Txabarri, R. G., ­Maldonado-​­Martin, S., & Pyne, D. B. (­2012). ­Warm-​­up inten-
sity and duration’s effect on traditional rowing t­ime-​­trial. Int J Sports Physiol Perform, 7,
­186–​­188.
Opar, D. A., Williams, M. D., Timmins, R. G., Hickey, J., Duhig, S. J., & Shield, A. J. (­2015).
Eccentric hamstring strength and hamstring injury risk in Australian footballers. Med Sci
Sports Exe, 47(­4), ­857–​­865.
Pagaduan, J. C., Pojskic, H., Uzicanin, E., & Babajic, F. (­2012). Effect of various w ­ arm-​­up pro-
tocols on jump performance in college football players. J Human Kin, 35(­1), ­127–​­132.
Racinais, S., Cocking, S., & Periard, J. D. (­2017). Sports and environmental temperature: From
­warming-​­up to heating up. Temperature, 4(­3), ­227–​­257.
Reilly, T., & Waterhouse, J. (­2005). Sport, Exercise and Environmental Physiology. Edinburgh:
Elsevier.
Reis, I., Rebelo, A., Krustrup, P., & Brito, J. (­2013). Performance enhancement effects of feder-
ation internationale de football association’s “­The 11+” injury prevention training program
in youth futsal players. Clin J Sport Med, ­23, 318–20.
Silva, L. M., Neiva, H. P., Marques, M. C., Izquierdo, M., & Marinho, D. A. (­2018). Effects of
­warm-​­up, ­post-­​­­warm-​­up, and ­re-­​­­warm-​­up strategies on explosive efforts in team sports: A
systematic review. Sports Med, 48, ­2285–​­2299.
Silva, N., Travassos, B., Goncalves, B., Brito, J., & Abade, E. (­2020). ­Pre-​­match ­warm-​­up dy-
namics and workload in elite futsal. Front Psych, 11, 584602.
Silvers, H., Mandelbaum, B., Adeniji, O., & Insler, S. (­2015). Efficacy of the FIFA 11+ injury
prevention program in the collegiate male soccer player. Am J Sports Med, 43(­11), ­2628–​­2637.
Sim, A.Y., Dawson, B.T., Guelfi, K.J., & Wallman, K.E. (­2009). Effects of Static Stretching in
­Warm-​­Up on Repeated Sprint Performance. J Strength Cond Res, 23(­7), ­2155–​­2162.
Soligard, T., Myklebust, G., & Steffen, K. (­2008). Comprehensive ­warm-​­up programme to
prevent injuries in young female footballers: Cluster randomised controlled trial. BMJ, 337,
a2469.
Tillin, N. A., & Bishop, D. (­2009). Factors modulating ­post-​­activation potentiation and its ef-
fect on performance of subsequent explosive activities. Sports Med, 39, ­147–​­166.
Vetter, R. E. (­2007). Effects of six w ­ arm-​­up protocols on sprint and jump performance. J
Strength Cond Res, 21, ­819–​­823.
Wilson, J. M., Duncan, N. M., Marin, P. J., Brown, L. E., Loenneke, J. P., & Wilson, S. M.
(­2013). ­Meta-​­analysis of postactivation potentiation and power: effects of conditioning ac-
tivity, volume, gender, rest periods, and training status. J. Strength Cond Res, 27, ­854–​­859.
Winchester, J. B., Nelson, A. G., Landin, D., Young, M. A., & Schexnayder, I. C. (­2008). Static
stretching impairs sprint performance in collegiate track and field athletes. J Strength Cond
Res, 22, ­13–​­19.
Yamaguchi, T., & Ishii, K. (­2005). Effects of static stretching for 30 seconds and dynamic
stretching on leg extension power. J Strength Condit Res, 19, ­677–​­683.
Yanaoka, T., Iwata, R., Yoshimura, A., & Hirose, N. (­2021). A ­1-​­minute ­re-​­warm up at ­h igh-​
­intensity improves sprint performance during the lough borough intermittent shuttle test.
Front Physiol, 11, 616158.
Yanci, J., Iturri, J., Castillo, D., Pardeiro, M., & Nakamura, F. Y. (­2019). Influence of ­warm-​­up
duration on perceived exertion and subsequent physical performance of soccer players. Biol
Sport, 36, ­125–​­131.
2 Resistance training
Conall Murtagh, David Rydings and Barry Drust

Introduction
Soccer players will always be judged by what they do on the pitch and not in the gym.
More specifically, the perceived success of any individual player is determined by his/­
her accomplishments during competitive match play. When we investigate the detail of
soccer match play from a physical perspective, explosive actions are performed nearly
once every minute (­81 ± 18 maximal actions during a ­90-​­min game) (­Murtagh et al.,
2019), and 83% of goals are preceded by at least one powerful action (­Faude et al.,
2012). The ability to produce maximal power, apply this power during complex motor
tasks and repeatedly tolerate the performance of such explosive actions throughout a
match(­es), may therefore be considered paramount to successful performance at the
elite level. Optimising such capabilities could therefore improve the chances of the
player having a successful career.
Researchers have documented that a variation of specific resistance training (­defined
as any training modality that requires a muscle contraction against an external load)
methods can enhance the ability to produce (­Loturco et al., 2016), apply (­Mendiguchia
et al., 2020), and tolerate (­Petersen, Thorborg, Nielsen, ­Budtz-​­Jørgensen, & Hölmich,
2011) force during powerful soccer actions. When rationalised in this context (­specific
definitions of this training model are displayed in ­Figure 2.1), it seems logical that re-
sistance training should play a role in the physical development of an elite soccer player.
However, resistance training comes at a cost to the player and can initially cause acute
neural fatigue, metabolic fatigue, and/­or ­m icro-​­damage in the ­muscle-​­tendon unit, all
of which are specific to the chosen training modality (­Draganidis et al., 2013). As soc-
cer is a unique sport which often requires elite players to operate for up to 49 weeks per
season, with weekly ­m icro-​­cycles that can often contain two to three games per week
alongside continued training, recovery becomes extremely important. Further intense
training (­such as resistance training) during these periods has the potential to blunt
the recovery process and lead to ­non-​­functional ­over-​­reaching, ­sub-​­optimal perfor-
mance, injury, or illness (­Doeven, Brink, Kosse, & Lemmink, 2018). Similarly, intense
training during taper periods leading into matches may cause fatigue and compromise
match performance levels. While resistance training may help soccer players achieve
more successful careers, the prescription should complement and not compete with
the pitch/­match training loads.
It is imperative when prescribing resistance training, those practitioners have an
insight into the individual player’s training ­load-​­recovery profile and consider several
other factors, such as the upcoming game schedule. The practitioner should rationalise

DOI: 10.4324/9781003148418-3
16 Conall Murtagh et al.
their programming by being specific about what they are trying to achieve (­i.e., our
model suggests identifying which of the following areas they are trying to improve: the
production, application, and/­or tolerance of/­to powerful ­soccer-​­specific actions), and
therefore, which physiological adaptations are being targeted. The goal of the prac-
titioner must be to optimise the balance between providing the appropriate training
stimulus to enhance or maintain a physical capacity, but not impede recovery, thus re-
ducing injury risk while maximising physical performance levels in competitive games.
In the current chapter, we present a novel systematic process for the prescription
of resistance training for the soccer player. We aim to answer three questions: Why
resistance training may be important in the training of soccer players? What are the
most optimal prescription models, and what are the challenges to their implementa-
tion? How may we navigate the challenges to implement this process in the real world?

Why? The production, application, and tolerance model

Model rationale
The ability to produce (­i.e., during strength and jump assessments, ­Murtagh, Nulty
et al., 2018; Murtagh et al., 2017) and apply (­i.e., during more specific actions such as
sprinting, ­Haugen, Tønnessen, & Seiler, 2013; Murtagh, Brownlee et al., 2018) force/­
power may determine elite soccer playing status and provide an advantage during
decisive moments of competitive games. Furthermore, the capacity to tolerate a high
volume of explosive actions over 90 min, often twice per week, is an important charac-
teristic for the elite player. Subsequently, it appears the ability to produce, apply, and
tolerate power/­powerful actions is imperative for the elite soccer performer; hence, we
have developed a novel ­soccer-​­specific resistance training model based on this concept
(­­Figure 2.1).

­Figure 2.1 The ability to produce, apply, and tolerate power/­powerful actions is consid-
ered paramount to successful soccer performance at the elite playing level.
 Resistance training 17
Production
Given that the ability to produce force is a determinant of sporting performance
(­Cometti, Maffiuletti, Pousson, Chatard, & Maffulli, 2001; Murtagh et al., 2017), it
is important to understand how to develop this attribute in applied practice. A key
factor underpinning the capacity to produce force is the development of muscular
strength. The most effective (­­non-​­pharmacological) means by which to enhance mus-
cular strength is a resistance training exercise. Numerous researchers have shown that
when the ability to produce force is increased via resistance training, there is an asso-
ciated performance improvement in key actions such as accelerating, sprinting, and
jumping (­Channell & Barfield, 2008). This improvement supports the notion that the
ability to produce large forces underpins performance and provides an indication that
resistance training may provide a potent stimulus to enhance such task performance.
Resistance training results in the radial growth of skeletal muscle and the promo-
tion of neural adaptations that result in enhanced force output. The application of
different resistance training exercise, and any associated loading patterns, will impose
diverse physiological stresses on an athlete’s neuromuscular system. These stresses
will, in turn, influence both the resultant adaptive signal and the accumulated level
of fatigue (­K illen, Gabbett, & Jenkins, 2010). Typically, a resistance training exer-
cise programme aimed at maximising muscle strength (­or the ability to produce force)
in athletes would involve performing traditional compound resistance training exer-
cises (­e.g., back squat), training at intensities of 85% of 1 repetition maximum (­1RM)
or greater, performing resistance exercise at least 2 days per week, and completing a
mean training volume of 8 sets per muscle group (­Peterson, Rhea, & Alvar, 2004).
Although resistance exercise is an effective strategy to increase skeletal muscle strength
(­or the ability to produce force), it is important to recognise that resistance exercise training
imparts acute skeletal muscle damage and neuromuscular fatigue. This damage and fatigue
results in a transient decrement in force production and an increase in p ­ ro-​­inflammatory
signalling molecules. While this may not be of consequence for the average exerciser, in
elite soccer, managing the recovery from resistance exercise is critical. The literature would
agree with anecdotal evidence that performing the resistance training necessary to en-
hance force production (­utilising loads >85% 1 RM) can take over 48 h to recover from
(­Draganidis et al., 2013). If the practitioner wants to maximise training opportunities to
improve production but wants to minimise the cost to the player, they often must think
a little more outside of the box. We suggest where traditional methods are inappropriate
alternative options could be to prescribe concentric only or an isometric exercise. We have
categorised the cost of different types of production exercises in F ­ igure 2.2 and elaborated
on how such information can be applied in the considerations “­cost” section.

Application
Soccer players at the elite level are required to produce high levels of force/­power
during complex motor tasks such as accelerating, sprinting, changing direction, and
attempting to maintain or gain possession of the ball while exerting physical force
against an opponent (­Bloomfield, Polman, & O’Donoghue, 2007). An athlete’s move-
ment strategy for a specific action can determine the speed of execution and, if ­sub-​
o
­ ptimal, can cause the biomechanical overload of specific tissues, thus elevating injury
risk (­K ing et al., 2018; Mendiguchia, ­Castano-​­Zambudio et al., 2021). To apply force
18 Conall Murtagh et al.

­Figure 2.2 The table displays the cost associated with resistance training exercises in each
specific category.

efficiently in any complex movement, we should aim to minimise energy leakage, re-
duce the risk of tissue overload and subsequent injury via the improved alignment
and coordination of specific movements. It, therefore, seems that resistance training
should be considered in a player’s training schedule.
Researchers using bony palpation methods observed that 92.5% of soccer players
are suffering from multiple innominate malalignments (­Elumalai, Declaro, Sanyal,
Bareng, & Mohammad, 2015). Such imbalances around the pelvis can potentially lead to
­sub-​­optimal biomechanics with compensatory patterns causing asymmetrically greater
workload, stress, and strain in specific muscles/­tendons. Although there is limited evi-
dence to document that optimal biomechanics exist for many dynamic s­ occer-​­specific
actions, specific movement dysfunctions have previously been associated with elevated
injury risk. For example, excessive pelvic and trunk motion during the swing phase of
­high-​­speed running is associated with soccer players who sustained a first hamstring
injury. More specifically, hamstring injury has been associated with significantly greater
anterior pelvic tilting and thoracic ­side-​­bending during acceleration (­Daly, McCarthy
Persson, Twycross‐Lewis, Woledge, & Morrissey, 2016; Schuermans, Van Tiggelen,
Palmans, Danneels, & Witvrouw, 2017). The current body of literature (­although lim-
ited with small sample sizes) suggests that team sport athletes who appear to be more
vulnerable to hamstring injury suffer from lacking proximal control and insufficient
dissociative capacity within the l­umbo-­​­­pelvic-​­hip complex, which may be further exac-
erbated by the repetitive nature of soccer actions. There is, therefore, sufficient evidence
to suggest that ­sub-​­optimal force application increases injury risk in soccer players.
Recently, researchers have documented that application training modalities can be
effective at improving biomechanics and improving performance in such actions. A
 Resistance training 19
specific intervention programme, including a focus on application training, was shown
to be effective in reducing anterior pelvic tilt kinematics during gait (­Mendiguchia,
Gonzalez De la Flor et al., 2021). Moreover, similar interventions have resulted in
faster sprint performance while continuing to alter the biomechanics towards a more
efficient movement strategy which is thought to reduce the risk of hamstring injury
(­Mendiguchia, C ­ astano-​­Zambudio et al., 2021) and athletic groin pain (­K ing et al.,
2018). Heavy sled sprint training has previously been shown to improve acceleration,
and sprint performance, via the improved ability to orientate horizontal force applied
to the ground during acceleration (­Morin et al., 2017), thus implying that there were
positive biomechanical alterations. Furthermore, when sprint “­application” training
(­oriented around improving sprint mechanics) was performed (­in addition to soccer
training) in elite players, not only were there improvements in sprint mechanics (­g reater
maximal horizontal force and ratio of force) and sprint performance but also in meas-
ures of muscle architecture of the hamstring muscles (­i.e., increased fascicle length).
Considering it has been shown in previous case studies that the ability to produce hori-
zontal force during acceleration can change prior to a hamstring injury (­Mendiguchia
et al., 2016), and that shorter biceps femoris fascicle lengths increase hamstring injury
risk (­Timmins et al., 2016), the inclusion of specific “­application” training oriented
around acceleration and sprint actions could provide a stimulus to improve perfor-
mance and reduce injury risk in elite soccer players (­Mendiguchia et al., 2020). There
is, therefore, sufficient evidence to show that application training can lead to improve-
ments in explosive soccer performance and, by reducing dysfunctional movement and
energy leakage during ­soccer-​­specific tasks, lowering the risk of overuse injuries.
For application training to be effective at improving movement, it is extremely im-
portant that the exercise prescribed requires the player to operate at similar joint angles
and/­or velocities to the specific movement(­s) on the soccer pitch. We have categorised
application training into three types according to the speed and resistance/­external
load (­see ­Figure 2.2). As ­inter-​­muscular coordination is the primary physiological adap-
tation, application training in its most complex format would be considered as neurally
demanding but low/­moderate cost from a structural perspective. While there is not much
literature investigating the cost associated with specific application training, ballistic
resistance training (­i.e., jump squat and lunges at 50% 1 RM), which may be classified as
application training if performed in a specific context, did not show any prolonged sup-
pression of performance (­countermovement jump, 10 m and 20 m sprint) or perceptual
recovery parameters (­delayed onset muscle soreness, total quality recovery, Brazilian
mood scale scores) 24 h p ­ ost-​­training. Such information supports anecdotal evidence
suggesting that light/­moderate load, ­high-​­speed resistance training doesn’t impede on
any performance or perceptual recovery parameters 24 h ­post-​­training (­Goulart et al.,
2020). Therefore, when performed with the optimal volume (­depending on pitch loads,
player training status), application training can be prescribed most days within the mi-
crocycle, even close to games. Regular exposure to such stimuli increases the chances of
making a positive impact on the player’s movement profile.

Tolerance
While applying force more efficiently is thought to reduce the risk of overuse injury,
the ability of the ­muscle-​­tendon unit to tolerate a high volume of repetitive forceful
actions performed at high speeds may decrease the risk of significant microtrauma
20 Conall Murtagh et al.

­Figure 2.3 The repeated bout effect is a key concept to inform the detailed prescription
process.

and subsequent tissue failure. Soccer actions often require the muscle to operate
eccentrically at long muscle lengths and fast contraction velocities. Such contrac-
tions are associated with the highest levels of muscle damage (­Barreto, de Lima,
Greco, & Denadai, 2019). Researchers have documented that there is a prolonged
impairment of ­lower-​­limb strength for as long as 60 (­Draganidis et al., 2015) and
72 h (­Trecroci et al., 2020) ­p ost-​­soccer game. Further eccentric activities at long
muscle lengths (­such as s­ occer-​­specific explosive actions) during such periods could
increase risk of tissue overload and injury. However, if recovery and regeneration
are optimal, a certain amount of muscle damage is a positive stimulus for ­muscle-​
t­endon unit restructuring, hypertrophy, and strength gains (­Roig et al., 2009).
Known as the repeated bout effect (­s ee ­Figure 2.3), the cell remodelling and adap-
tation that occurs after such eccentric exercise allows the tissue to become more
resilient to damage when performing similar movements in the future, hence, im-
proving tissue tolerance.
It has been well documented that specific resistance training interventions with an
eccentric focus can improve the tissue’s ability to tolerate eccentric actions at long
muscle lengths. Researchers have shown that eccentric overload resistance training
in different formats leads to structural (­i.e., increased fascicle length (­Presland et al.,
2018), lateral force transmission (­Erskine et al., 2011), physiological c­ ross-​­sectional
area (­Erskine, Fletcher, & Folland, 2014), tendon compliance at the muscle end of the
tendon (­Baar, 2017)) and neural ((­i.e., overcoming neural regulatory mechanism that
limits the recruitment and/­or discharge rate of motor units exists during maximal vol-
untary eccentric muscle contraction (­Aagaard et al., 2000; Duclay et al., 2008); muscle
activation at longer muscle lengths (­Hegyi et al., 2019)) adaptation that makes the tis-
sue less likely to tear or ­m icro-​­tear when put under the stress and strain associated with
elite soccer training and more specifically, m ­ atch-​­play. A number of prospective stud-
ies report that eccentric strength training performed at long muscle lengths reduces
the risk of hamstring injury in soccer players (­Askling, Tengvar, & Thorstensson, 2013;
 Resistance training 21
Petersen et al., 2011). It is therefore thought that training to improve tissue tolerance at
the neural and structural level in elite soccer players should have an eccentric compo-
nent and can be maximised when ensuring the muscle operates at long muscle lengths
and at a variety of contraction speeds.
From the r­ eal-​­world perspective, it must be considered that to gain such desirable
adaptations, eccentric strength training modalities come at high physiological cost to
the player (­fast eccentric exercise induces greater muscle damage compared to slow ec-
centric exercise (­Barreto et al., 2019)) and can initiate a cascade of catabolic processes
within the ­neuro-​­muscular system that lead to elevated muscle soreness and reduc-
tions in power/­speed outputs. Moreover, structural adaptation, such as increased fas-
cicle length, has been shown to return to baseline after 2 weeks of detraining (­Presland
et al., 2018), meaning such a stimulus needs to be applied frequently i­n-​­season. It is
challenging to regularly include traditional eccentric strength training in elite soccer,
especially at clubs who experience congested fixture schedules. However, it has been
documented that various other training protocols associated with lower cost, such
as ­m icro-​­dosing of two reps of maximal eccentric contractions (­Nosaka et al., 2001),
light, eccentric exercises (­6 × 5 reps at 10% MVC) (­Lavender & Nosaka, 2008), and
maximal isometric contractions (­g reater protection when performed at long muscle
lengths (­Lima & Denadai, 2015)), all offer a protective “­tolerance” effect to subsequent
exercise. More specifically, the body of literature suggests that maximal isometric
contractions at long muscle lengths in small doses (­i.e., ­2–​­10 maximal isometric con-
tractions) performed ­2–​­4 days prior to fast or slow eccentric exercise protocols can sig-
nificantly attenuate ­exercise-​­induced muscle damage symptoms (­Barreto et al., 2019)
and therefore acutely improve the tolerance of the ­muscle-​­tendon unit. Such training
modes can also be classed as moderate/­low cost tolerance training (­see ­Figure 2.2) and
could be useful for the soccer practitioner aiming to maximise training opportunities
in close proximity to competitive matches.
With injury rates continuing to increase in elite soccer (­Ekstrand, Waldén, & Häg-
glund, 2016) and fixtures regularly scheduled when the player’s recovery markers
(­such as hamstring strength) haven’t returned to baseline (­Trecroci et al., 2020), it
seems that many elite players would benefit from tolerance training with a view that
prevention is the best form of cure. However, such training generally comes at a high
cost, and the implementation needs to be strategically planned into the elite player’s
programme; especially if specific circumstances don’t allow this stimulus to be per-
formed regularly.

What? The most optimal resistance training prescription

Production, application, and tolerance resistance training interventions could benefit
the elite player by improving their chances of staying healthy and achieving more suc-
cessful match play performance. However, the implementation of such interventions
can be challenging in soccer and is often a point of contention amongst player support
staff. We present a novel systematic approach for the prescription of resistance train-
ing in elite soccer players that can be applied in clubs at various playing levels, who
employ different weekly training periodisation structures and engage in contrasting
fixture schedules. The process involves three key stages before the detail of the resist-
ance training session is finally prescribed and monitored accordingly (­­Figure 2.4).
22 Conall Murtagh et al.

SPEED
Based on the detailed needs analysis –
what type of resistance training would
POWER
MOVEMENT benefit the player:

IDENTIFY
TISSUE
TOLERANCE
QUALITY
STRENGTH
PRODUCTION
ENDURANCE
APPLICATION

Training Load-Recovery Balance

QUANTIFY
Balance Quantify the adaptative state for the various
physiological sub-systems and
musculoskeletal tissue. Ensure the resistance
training prescription induces +ve adaptation
within the time frames identified in the
considerations process.

MONITOR
Monitor how the
player responded to
the intervention and
reflect on this detail Game schedule: When is the next game?
to inform How long is there for +ve adaptation and
subsequent micro- supercompensation to occur?
cycle periodization
strategies.

Is the player a non-starter?

When did the player last perform match
specific eccentric actions at long muscle
lengths?

UNDULATING VS 4-DAY-LEAD
CONSIDER

Soccer training micro-cycle

periodization: Is there a taper day within
the training week or is the player
required to perform high intensity actions
AU

at long muscle lengths on the pitch

every day of the lead into the game?

M T W T F S M T W T F S

Exercise cost:
Considering the above criteria, which
resistance training exercises are
associated with a cost that will still ensure
+ve adaptation and supercompensation
before the next match.

Travelling arrangements / equipment:

What equipment is available to perform
the session? Do we have to utilize the
“travelling toolbox” to attempt to get
the desirable adaptations in the limited
time available?

PRESCRIBE

­Figure 2.4 An illustration of the processes utilised when prescribing resistance training
interventions for the elite soccer players.

­Identify – ​­How can resistance training help this player?

The most important element of player programming is to perform a detailed needs
analysis of the player and sport. An example of a needs analysis that could be used
for the elite soccer player is detailed in F
­ igure 2.4. The need analysis is a constant
process that should be performed regularly to determine effectiveness of the pro-
gramme and indicate of any adjustments/­changes that should be prescribed. From a
 Resistance training 23
resistance training perspective, the outcome of the needs analysis is to ascertain which
of the resistance training goals the player should prioritise at that moment and time
(­production, application, and/­or tolerance).

­Q uantify – What
​­ is the player’s current training ­load-​­recovery balance?
When planning resistance training interventions, the practitioner should always con-
sider the individual player’s training ­load-​­recovery balance. Such analyses provide an
indication or estimation of the adaptative state the player is in for the various physio-
logical ­sub-​­systems and musculoskeletal tissue. This information (­although it is always
an informed estimation regardless of the most recent technology available), should
guide the practitioner not only to which specific training methods the player should
perform to gain a positive adaptive response, but which training stimuli may further
stress a s­ ub-​­system or tissue that is already broken down and weakened leading to a
­mal-​­adaptive response. The practitioner should attempt to quantify every individual
player’s training stimulus and, considering specific ­load-​­adaptation pathway time-
frames, the subsequent response. Such an insight is crucial when prescribing the detail
of resistance training intervention.

Quantifying the stimulus?

When a soccer player engages in any form of physical training stimulus, internal bio-
chemical stresses simultaneous to internal mechanical stresses to the various muscu-
loskeletal tissues utilised during the activity. Based on the specificity of the training
stimulus and the time course of any subsequent physical stimuli (­further stress), the
physiological s­ ub-​­systems and tissues adapt. The authors believe that the most opti-
mal way of quantifying the stimulus (­or training load) of the training l­oad-​­recovery
balance is to use a theoretical framework in which physiological and biomechanical
­load-​­adaptation pathways are considered separately. Practitioners need to be very
aware that ­load-​­adaptation pathways have different response rates, which has con-
sequences for the planning of resistance training interventions (­Vanrenterghem et al.,
2017). Soccer match play, training, and resistance training all induce biochemical and
biomechanical stress and initiate a cascade of specific physiological and structural/­
functional adaptative processes, respectively. If specific time frames are respected
before the next stimulus, positive adaptation occurs, known as supercompensation.
Biomechanical adaptations have a longer response rate and adaptation time frame
compared to physiological adaptations.
While quantifying the biochemical and biomechanical stress on physiological ­sub-​
s­ ystems and musculoskeletal tissue from resistance training and prescribed ­pitch-​­based
running sessions is relatively straight forward, quantifying the complex, unorthodox
explosive actions performed during pitch based team training and match play provide
more of a challenge for the practitioner. It is clear we still cannot accurately quantify
the actual “­stress” the players’ body is exposed to during training or match play. Esti-
mating the adaptative state is also made difficult by the fact that players will respond
to the same loading stimuli in different ways, which has recently been supported by
research showing that muscle damage is related to genetic profile (­Baumert, 2019).
Moreover, adaptation rates are highly dependent on the player’s training status. When
estimating biomechanical adaptation rates relative to the player’s training status, the
24 Conall Murtagh et al.
repeated bout effect is an important concept for the practitioner to understand. While
it is important to consider the physiological adaptation profile when prescribing any
training intervention for the player, as the biomechanical load and subsequent adapta-
tion profile provide an insight into the structural and functional status of each specific
skeletal tissue, it is extremely important that this is considered when prescribing the
specificity of resistance training.

Quantifying the response?

The response to training load can be measured by several commercially available well-
ness devices which measure player sleep profiles and heart rate variability, providing
an insight into to the general recovery state of a player. Moreover, subjective ques-
tionnaires can be used to provide an insight into levels of fatigue or muscle soreness.
If possible, the fitness team should be liaising closely with the medical department,
who can assess a player to provide further insight into whether any tissue is still in a
state of adaptation. Assessments of range of motion, single joint isometric strength
at long muscle lengths or d ­ irection-​­specific power assessments can also provide the
practitioner with valuable information regarding the adaptation profile of joints or
­muscle-​­tendon complexes. Once the practitioner has quantified the training stimulus,
the subsequent response, and considered the player’s training status (­w ith reference
to the repeated bout effect) and natural ability to tolerate eccentric exercise (­Newton
et al., 2008), they have should have a good insight into which tissues are underloaded,
and if any tissue is overloaded. This information is crucial to the detailed prescription
process.

The training ­load-​­recovery balance after match play

Competitive matches typically represents the highest physiological and biomechani-
cal stress on the player’s body. It is crucial that the practitioner respects the recovery
time frames ­post-​­match when prescribing resistance training interventions. Several re-
searchers have investigated the recovery kinetics of muscle force production after a
soccer match, with some studies demonstrating lower limb strength levels remained
impaired up to ­12–​­24 h from a match (­Krustrup et al., 2011), with complete recov-
ery reached from 36 to 48 h. However, these studies only measured knee extensor
(­quadriceps) function when it is well known that the knee flexors (­hamstrings) are the
most frequently injured muscle in elite soccer. Other studies, which included assessment
of knee flexor strength, showed a more prolonged impairment of l­ower-​­limb strength
until 60 (­Draganidis et al., 2015) and 72 h (­Trecroci et al., 2020). This would suggest
that whilst the tissue responsible for producing peak force in knee extension activities
may be adapted and ready for another stimuli (­i.e., knee extensor dominant resistance
training exposure) 48 h ­post-​­game, the knee flexors (­hamstrings) may not be fully re-
covery until 6­ 0–​­72 h p
­ ost-​­game. Engaging in hamstring dominant eccentric activities
at long muscle lengths, such as ­resistance-​­specific training or maximal ­soccer-​­specific
explosive actions in a training or game format, during this time frame p ­ ost-​­game, could
increase the risk of injury and compromise the safety and w ­ ell-​­being of players.
From an individual player perspective, the magnitude of the decline in knee flexor
strength and countermovement jump performance may be affected by the total num-
ber of explosive actions (­Nedelec et al., 2014). Such observations are supported by
 Resistance training 25
anecdotal evidence from practitioners, which suggests that when a player achieves
statistically greater physical outputs compared to their average, physiological and per-
ceptual recovery markers are compromised, and it takes longer to return to baseline
­post-​­game. The quantification analyses of the training l­oad-​­recovery balance are ex-
tremely important if the practitioner is to effectively maximise training windows for
the individual player, especially during congested fixture periods.

The ­non-​­starter
It is well known amongst practitioners that a recent good rhythm of games may provide
protection to the skeletal muscle from strength attenuation and enhance recovery fol-
lowing a game. However, even the highest level of team training lacks the competitive-
ness and intensity of matches. When the player hasn’t been exposed to a game recently
(­i.e., a ­non-​­starter), it is imperative that specific ­g ym-​­based interventions initiate adap-
tations which offer a protective effect for when the player engages in their next bout of
maximal eccentric activity (­which in soccer players is generally a competitive game).
Physiological adaptations in untrained individuals who start playing soccer (­Jakobsen
et al., 2012) and anecdotal evidence suggests that performing multiple maximal explo-
sive actions in a match format improves the tolerance of specific tissue. Anecdotally,
the player will always perform more extreme actions at longer muscle lengths during
competitive games, possibly due to the competition component and other factors such
as pressure from the crowd and the stakes/­rewards of winning. Therefore, a key chal-
lenge for the fitness practitioner is to maintain and/­develop m ­ atch-​­specific fitness but,
more specifically, the tissue tolerance status of the players who do not start games.
Players that lack “­game” rhythm are more prone to u ­ nder-​­performance and injury
when they are next selected to play a competitive match. Tolerance training that re-
quires eccentric contractions at similar speeds and muscle lengths to extreme actions
in a competitive game, is very important for “­­non-​­starters”. Such training provides op-
timal stimulus for the tissue to maintain/­develop the ability to tolerate ­match-​­specific
volumes and intensities of explosive actions. The question of: “­does the player have a
lack of match exposure” is, therefore, a key a consideration in the resistance training
prescription process.

­Consider – Which
​­ “­future” circumstances could impact the prescription?
Once we have identified what area the player needs to improve and have an insight into
his/­her current training l­oad-​­recovery balance profile, numerous other considerations
will impact upon the detailed prescription process.

Match schedule
In every circumstance, other than a youth development player for which l­ong-​­term
development is prioritised over optimising match performance levels, performance
during match play should be prioritised in any training regime. First and foremost,
recovery from games should be respected, but the practitioner needs to consider the
fixture schedule and when the next competitive game(­s) will be played. Unlike some
Olympic sports, where the athletes are required to peak two or three times a year,
in soccer, senior players are required to peak for every competitive match (­p erhaps
26 Conall Murtagh et al.
Table 2.1 T
 he relationship between factors affecting fixture schedule demands and the
opportunity for resistance training exposures in soccer players in starts and squad
players

including ­pre-​­season friendlies where players are competing for their starting place in
the 1st match of the season). Some players can be required to produce peak physical
performance levels for up to 49 weeks of the year (­see T­ able 2.1). The fixture demands
can also fluctuate for the team and individual player during the season as Cup com-
petitions finish or the team gets knocked out in earlier rounds, and players could be
selected to play more or less frequently. Players and practitioners who have operated
in different teams with contrasting fixture and pitch training demands would argue
that from a resistance training prescription perspective, the demands and factors are
so contrasting, it is like working in different sports. A systematic approach is, there-
fore, vital to enable practitioners to prescribe an appropriate training stimulus while
allowing adequate timing for a certain level of ­super-​­compensation, thus optimising
performance levels whilst reducing injury risk. Resistance training periodisation and
prescription is, therefore, highly dependent on the fixture schedule.

Pitch training ­micro-​­cycle periodisation

Although the match is the highest physical stimulus the player is ever exposed to, the
pitch training loads provide significant biochemical and biomechanical stress. The
periodisation of the pitch training ­m icro-​­cycles is an important consideration when
planning the detail of resistance training interventions. There are many ­m icro-​­cycle
periodisation models employed in elite soccer. Within each of these models, there is
a certain amount of variation for each coaching team employing the specific model.
As we won’t cover this topic in detail in the current chapter, we have simplified m ­ icro-​
­cycle periodisation strategies to two different types: An undulating week whereby there
is a day off or unloading taper day during the week, usually 2 (­or sometimes 3) days
before the game; and a 4­ -​­day week which has no specific unloading day (­other than a
volume taper the day or 2 days before the game) and the players are required to train
with high/­maximal intensities for 4 days leading into the game (­i.e., some application
of the Tactical Periodisation Model; Jankowski, 2016). The strategy for prescribing re-
sistance training can change based on different ­m icro-​­cycle periodisation strategies. In
 Resistance training 27
t­heory, when the player has an unloading day during the week, it is easier to implement
­high-​­cost resistance training exercise as the unloading day, rather than a pitch train-
ing session with explosive actions, helps the player adapt (­­super-​­compensate) quicker
and eradicate any residual fatigue or soreness from resistance training before the next
game.

The cost of resistance training

A consideration of the cost of the resistance training intervention is a crucial part
of the prescription process. Training status and genetic profile (­Baumert, 2019) can
impact upon the muscle damage, adaptation rates, and cost associated with resist-
ance training exercise. This can make it somewhat difficult to predict the exact time
frame which the player requires to adapt. Nevertheless, due to the possibility of con-
gested fixture schedules and prioritisation of pitch training in elite soccer, it is always
important for the practitioner to be able to manipulate the cost associated with the
resistance training stimulus. Choosing exercises methodically according to their cost
can help maximise training opportunities, avoid overload of a tissue/­system that is
in an adaptative state whilst still allowing the player to be in peak physical condition
for the ­up-­​­­and-​­coming match. Whilst respecting the individual response to resistance
training, we have provided a guide of exercise types of varying cost for each specific
resistance category (­i.e., production, application tolerance). Such guidelines allow the
practitioner to manipulate the cost of the resistance training exposure whilst still pre-
scribing a stimulus specific to the goals identified in the needs analysis process (­see
­Figure 2.2).

Equipment available and travel arrangements

To optimise player physical performance levels, the practitioner needs to maxim-
ise windows of training opportunity. Often for teams with congested fixture sched-
ules, the training opportunity comes immediately after the match (­s ee T ­ able 2.1).
With the t­raining-​­load recovery balance in mind and ensuring supercompensation
occurs before the next competitive game, often immediately after the match, is the
only opportunity for players to be exposed to a resistance training session that is
oriented around tolerance or production goals. However, especially at away games,
there is rarely the available facilities to lift the heavy loads required to perform pro-
duction and tolerance exercises. In such cases, the practitioner needs to have their
­post-​­match strategies in place to optimise this training window. Exercises such as
eccentric hamstring slide outs (­resisted), Nordics and reverse Nordics, which expose
the player to a tolerance stimulus at long muscle lengths, have been shown to be
effective and time efficient. Flywheel devices can be utilised and are relatively com-
pliant with team travelling procedures. Adjustable weighted dumbbells can also be
useful, and prescribing single leg training allows higher intensities with less load. As
this is also often an optimal time for energy systems conditioning and an exposure to
biomechanical load on the pitch, all the chosen interventions for the specific player
need to be time efficient and compatible to provide the optimal stimulus to the tissue.
The practitioners “­travelling toolbox” is essential to optimise training windows and
player performance levels, and the extent of toolbox impacts upon the prescription
process.
28 Conall Murtagh et al.
How? Does this all work in practice
The system in practice
We have presented our framework for systematically prescribing resistance training
prescription in elite soccer clubs. To show how such a systematic process works in
practice, F
­ igures 2.­5 –​­2.7 depict three r­ eal-​­world case studies which use specific prin-
ciples to overcome various challenges and provide the most optimal training stimulus
for the player.

Exposure and impact

The systematic, detailed prescription of resistance training can help the soccer player
have a more successful career. We believe that the system presented in this chapter
ensures that the practitioner can maximise training opportunities and have a positive
impact on player match physical performance levels. T ­ able 2.1 illustrates that the fix-
ture schedule, starting status and training ­m icro-​­cycle periodisation can largely dic-
tate the type of resistance training exposures the player can be exposed to throughout
a season in different regimes. Our analysis shows there are many opportunities for
the player to be exposed to specific resistance training interventions. Analysing the
resistance training exposures for specific groups of players shows which types of inter-
ventions the practitioner can prioritise in their resistance training programming. For
example, a regular starter for a Champions League or English Championship team
should invest his time in the most effective ­low-​­cost resistance training interventions

KEY RESISTANCE TRAINING GOALS SUMMARY

Force production levels are outstanding.

TOLERANCE APPLICATION
IDENTIFY

Poor lateral trunk control during functional

movements, stiff landing mechanics & lack of
trunk control, acceleration mechanics limited by Provide perturbations during functional movements to
poor switch speed. Improve the ability of the patella, quads and Achilles improve lateral trunk control (i.e. with use of
tendon to tolerate the load associated with football resistance bands); employ landing activities with
activity i.e. increase tendon stiffness and CSA. perturbations; perform resisted speed training/drills
History of tendon issues i.e. patellar & Achilles encouraging fast switching of limbs.
tendinopathies.
QUANTIFY

High sprint distance and maximal Significantly higher vs average volume of The question mark here is because it
speed on Tues (MD-4) & therefore shooting actions performed in training on depends on the load-recovery balance for
reduced the volume of eccentric Thurs (MD-2) so the tolerance exercises for the player on this day. If they are >2 days
hamstring training exposure in the gym adductors and rectus femoris muscles were post-game then a moderate/low cost
post training. reduced to one set. tolerance could be beneficial here.

AU
CONSIDER

M T W T F S S
M T W T F S S W T F S S
M T

The next day was off and the Due to the high MD-2 pitch session, the MD-1 Application training on the MD+2/-1 was performed with
Low COST tolerance player lacked game the goal of maximizing recovery through (resisted)
session on MD-2 as less application exercises didn’t involve any specific
exposure so performed the stress to the rectus femoris or adductors longus. movement interventions that would enhance lumbo-
than 48 hours from previous MATCH SPECIFIC LONG pelvic control and stimulate any muscles/motor patterns
tolerance session and is 2 This was to reduce negative adaptation promote
MUSCLE LENGTH gym recovery in this tissue for the match the next day. that may have been inhibited/compromised. The aim
days prior to the next match. programme in addition to his was also to ensure the player could train with limited
Tolerance programme. movement dysfunctions.

­Figure 2.5 ­Real-​­world prescription process for player 1 in different match play formats.
 Resistance training 29

KEY RESISTANCE TRAINING GOALS SUMMARY

General force production/strength abilities are good

but lacks power (not a specific goal to improve with
TOLERANCE
IDENTIFY
this age and injury history – see below). APPLICATION
Poor front side mechanics and thoracic side bend
at toe off (acceleration and sprint) - Both thought to
increase risk of hamstring injury. Improve lumbo-pelvic control and optimise length-
Improve the ability of the body and previously injured tension relationship of hip flexors. Movement drills
tissue to tolerate and recover from performing designed for more efficient front side mechanics and
repetitive football specific actions. lateral trunk control during toe off using a constraints
33 yrs old. Extensive history of soft tissue injuries
based learning approach.
specifically hamstring and rectus femoris.
QUANTIFY

The team performed

The team performed The medical staff reported that the players pelvis Application training two days after and one day
extensive work in larger
intensive work in smaller was more anteriorly tilted on Thursday (MD-2) and before the next game was low cost and focused
spaces 3 days before the
spaces on MD-4. Tolerance consequently, the application session was around lumbo-pelvic control and “resetting” the body
game. Tolerance
exercises specific for rectus designed around lumbo-pelvic control and optimal to avoid any movement dysfunction/compensation in
exercises specific for
femoris and adductors were preparation for the tactical session. training or the game the next day.
hamstring were
prescribed.
prescribed.

AU
CONSIDER

M T W T F S S F
M T W T S S M T W T F S S

The two tolerance sessions The acceleration,

The player produced high sprint outputs on Wed The player only played for 55 mins and external load
(MD-4 and MD-3) were deceleration and shooting
(MD-3) and the team were doing tactical work the match data tracked live showed he had limited sprint
relatively moderate cost as demands were high on this
next day (Thurs MD-2) which also was predicted to distance exposure. The next game was 4 days away
the player was still required training day so the tolerance
induce a sprint overload. The hamstring tolerance after two low load recovery days. Therefore, tolerance
to perform high intensity training for rectus femoris
session post training on Weds (MD-3) was training for the hamstrings was performed after the
pitch based actions on all and adductors was limited to
therefore modified to isometric only. game to improve/maintain tissue quality.
four days in the lead into the two sets rather than three.
game.

­Figure 2.6 ­Real-​­world prescription process for player 2 in different match play formats.

KEY RESISTANCE TRAINING GOALS SUMMARY

General force production/strength and power abilities
are poor (below average).
IDENTIFY

Poor acceleration mechanics – lack of hip extension. PRODUCTION APPLICATION

Poor change of direction mechanics – trunk control
poor. Both thought to be driven by inability to produce
absorb force but also on poor co-ordination.
Improve the capacity to produce high magnitudes of Improve ability to extend hip when accelerating
force in key functional movements and muscles through resisted acceleration and specific hip
involved in triple extension actions. Increase trunk extension actions. Improve ability to control trunk
21 yrs old. No soft tissue injury history except ankle during complex deceleration and change of direction
ligament strain. strength.
tasks through perturbation training.
QUANTIFY

The player’s training load-recovery balance was closely

Application and Production training volume was monitored 2 days post game and the cost of the
Player was 3 days post game (MD+3/-4) and
reduced on Thursday (MD-2) as the player application prescription was based on how well the
according to all markers adequately recovered.
reported some subjective fatigue and heart rate player has recovered. The player reported subjective
High-cost production and application sessions
variability was moderately down suggesting body fatigue and low sleep quality; consequently, the cost
were prescribed.
homeostasis was somewhat upset. and volume of the application was kept low.

AU
CONSIDER

M T W T F S S M T W T F S S M T W T F S S

The team travelled on the Friday morning and Production session on the MD-2 was high cost but
Monday of the next micro-cycle was a day off. As
trained on Friday afternoon. The player therefore moderate volume. The player had been performing the
the player lacked game exposure in the previous 4
did not have access to a weighted sled and had to high-cost production exercises twice per week for the
weeks, after the MD+1 training session a production
use resistance bands for the (low volume) resisted previous 4 weeks. A reduced volume prescription
session and a MATCH SPECIFIC LONG MUSCLE
acceleration training. allowed us to maximize a training opportunity but not
LENGTH tolerance session were prescribed.
induce excessive residual fatigue or soreness that could
negatively affect performance in the match on Wed.

­Figure 2.7 ­Real-​­world prescription process for player 3 in different match play formats.
30 Conall Murtagh et al.
to improve the player’s physical profile. If most of this training is to come through low
and moderate intensity application training (­which can be performed regularly during
congested fixture periods), it would be a good idea for this player to perform regular
detailed biomechanical assessments to ensure the programming is as specific as possi-
ble and is being regularly monitored. In contrast, for a squad player who needs to im-
prove tissue tolerance as he is over 30 years old, regularly sustains soft tissue injuries,
and many of his exposures must be after the game, he/­she needs to be prescribed the
most optimal “­travel and changing room friendly” exercises. We must also highlight
that as player and team circumstances can change quickly in soccer, a player’s regime
can also change, which is why the ability to operate a systematic approach (­as we have
presented in the chapter) ensures that every player gets an individual service which
allows them to maximise their physical potential.

Future directions and conclusions

Soccer is a sport where players could be required to be in peak physical condition one
to two times per week for up to 49 weeks in the year. The diverse fixture and pitch
training demands make resistance training periodisation and planning a challenge
for practitioners. The inclusion of resistance training interventions can help players
reduce injury risk and maximise physical performance levels. However, for the prac-
titioner to maximise physical performance in competitive games, the prescription
process should be systematic and detailed. We have presented a prescription model
whereby the soccer practitioner can identify how resistance training could help the
player, continually quantify the player’s training ­load-​­recovery balance, and then go
through a checklist of considerations before providing the most specific and detailed
prescription of resistance training, which attacks the player’s deficiencies and builds
on their strengths. Future developments may enhance methods which enable a greater
understanding of the specific, individual, responses to both training and match play.
This would, in turn, better empower practitioners to make both faster and more in-
formed decisions around a player’s current training l­oad-​­recovery balance in order to
optimally prescribe resistance training programmes. Further to this, the ongoing de-
velopment of strategies to provide a resistance training stimulus whilst “­on the road”
and/­or during periods of fixture congestion, may enhance the practitioner’s ability to
optimise resistance training prescription under these challenging, “­­real-​­world” sce-
narios. Such a specific process should allow s­ uper-​­compensation to occur before the
next match(­es), which will increase the player’s chances of successful performance
and, in the long term, a healthy career whereby the player can maximise their physical
potential.

References
Aagaard, P., Simonsen, E. B., Andersen, J. L., Magnusson, S. P., H ­ alkjaer-​­Kristensen, J., &
Dyhre-​­
­ Poulsen, P. (­2000). Neural inhibition during maximal eccentric and concentric
quadriceps contraction: Effects of resistance training. Journal of Applied Physiology, 89(­6),
­2249–​­2257.
Askling, C. M., Tengvar, M., & Thorstensson, A. (­2013). Acute hamstring injuries in Swedish
elite football: a prospective randomised controlled clinical trial comparing two rehabilita-
tion protocols. British Journal of Sports Medicine, 47(­15), ­953–​­959.
 Resistance training 31
Baar, K. (­2017). Minimizing injury and maximizing return to play: lessons from engineered
ligaments. Sports Medicine, 47(­1), ­5 –​­11.
Barreto, R. V., de Lima, L. C. R., Greco, C. C., & Denadai, B. S. (­2019). Protective effect con-
ferred by isometric preconditioning against ­slow-​­and ­fast-​­velocity eccentric ­exercise-​­i nduced
muscle damage. Frontiers in Physiology, 10, 1203.
Baumert, P. (­2019). The physiological and genetic factors underpinning the response to muscle
damaging exercise (­PhD). Liverpool: John Moores University.
Bloomfield, J., Polman, R., & O’Donoghue, P. (­2007). Physical demands of different positions in
FA Premier League soccer. Journal of Sports Science & Medicine, 6(­1), 63.
Channell, B. T., & Barfield, J. P. (­2008). Effect of Olympic and traditional resistance training
on vertical jump improvement in high school boys. The Journal of Strength & Conditioning
Research, 22(­5), ­1522–​­1527.
Cometti, G., Maffiuletti, N. A., Pousson, M., Chatard, J.-​­C., & Maffulli, N. (­2001). Isokinetic
strength and anaerobic power of elite, subelite and amateur French soccer players. Interna-
tional Journal of Sports Medicine, 22(­01), ­45–​­51.
Daly, C., McCarthy Persson, U., Twycross‐Lewis, R., Woledge, R. C., & Morrissey, D. (­2016).
The biomechanics of running in athletes with previous hamstring injury: a case‐control
study. Scandinavian Journal of Medicine & Science in Sports, 26(­4), ­413–​­420.
Doeven, S. H., Brink, M. S., Kosse, S. J., & Lemmink, K. A. P. M. (­2018). Postmatch recovery
of physical performance and biochemical markers in team ball sports: a systematic review.
BMJ Open Sport & Exercise Medicine, 4(­1), e000264.
Draganidis, D., Chatzinikolaou, A., Avloniti, A., B ­ arbero-​­Álvarez, J. C., Mohr, M., Malliou,
P., … Margonis, K. (­2015). Recovery kinetics of knee flexor and extensor strength after a
football match. PLoS One, 10(­6), e0128072.
Draganidis, D., Chatzinikolaou, A., Jamurtas, A. Z., Carlos Barbero, J., Tsoukas, D., Theodorou,
A. S., … Theodorou, A. (­2013). The t­ ime-​­frame of acute resistance exercise effects on football
skill performance: the impact of exercise intensity. Journal of Sports Sciences, 31(­7), ­714–​­722.
Duclay, J., Martin, A., Robbe, A., & Pousson, M. (­2008). Spinal reflex plasticity during maxi-
mal dynamic contractions after eccentric training. Medicine and Science in Sports and Exer-
cise, 40(­4), ­722–​­734.
Ekstrand, J., Waldén, M., & Hägglund, M. (­2016). Hamstring injuries have increased by 4% an-
nually in men’s professional football, since 2001: a 1­ 3-​­year longitudinal analysis of the UEFA
elite club injury study. British Journal of Sports Medicine, 50(­12), ­731–​­737.
Elumalai, G., Declaro, M., Sanyal, S., Bareng, M. B., & Mohammad, A. (­ 2015). Soccer
­syndrome-​­2: common innominate malalignments and its manual diagnostic techniques in
pelvic malalignments syndrome. American Journal of Sports Science, 3(­6), ­120–​­127.
Erskine, R. M., Fletcher, G., & Folland, J. P. (­2014). The contribution of muscle hypertrophy
to strength changes following resistance training. European Journal of Applied Physiology,
114(­6), ­1239–​­1249.
Erskine, R. M., Jones, D. A., Maffulli, N., Williams, A. G., Stewart, C. E., & Degens, H. (­2011).
What causes in vivo muscle specific tension to increase following resistance training? Exper-
imental Physiology, 96(­2), ­145–​­155. https://­doi.org/­10.1113/­expphysiol.2010.053975
Faude, O., Koch, T., & Meyer, T. (­2012). Straight sprinting is the most frequent action in goal
situations in professional football. Journal of Sports Sciences, 30(­7), ­625–​­631.
Goulart, K. N. de O., Duffield, R., Junior, G. O. C., Passos Ramos, G., Pimenta, E. M., &
Couto, B. P. (­2020). Recovery timeline following resistance training in professional female
soccer players. Science and Medicine in Football, 4(­3), ­233–​­239.
Haugen, T. A., Tønnessen, E., & Seiler, S. (­2013). Anaerobic performance testing of professional soc-
cer players ­1995–​­2010. International Journal of Sports Physiology and Performance, 8(­2), ­148–​­156.
Hegyi, A., Lahti, J., Giacomo, J.-​­P., Gerus, P., Cronin, N. J., & Morin, J.-​­B. (­2019). Impact of hip
flexion angle on unilateral and bilateral nordic hamstring exercise torque and ­h igh-​­density
electromyography activity. Journal of Orthopaedic & Sports Physical Therapy, 49(­8), ­584–​­592.
32 Conall Murtagh et al.
Jakobsen, M. D., Sundstrup, E., Randers, M. B., Kjær, M., Andersen, L. L., Krustrup, P., &
Aagaard, P. (­2012). The effect of strength training, recreational soccer and running exercise
on ­stretch–​­shortening cycle muscle performance during countermovement jumping. Human
Movement Science, 31(­4), ­970–​­986.
Jankowski, T. (­2016). Coaching soccer like Guardiola and Mourinho: the concept of tactical peri-
odization. Europe: Meyer & Meyer Sport.
Killen, N. M., Gabbett, T. J., & Jenkins, D. G. (­2010). Training loads and incidence of injury
during the preseason in professional rugby league players. The Journal of Strength & Condi-
tioning Research, 24(­8), ­2079–​­2084.
King, E., ­Franklyn-​­Miller, A., Richter, C., O’Reilly, E., Doolan, M., Moran, K., … Falvey,
É. (­2018). Clinical and biomechanical outcomes of rehabilitation targeting intersegmental
control in athletic groin pain: prospective cohort of 205 patients. British Journal of Sports
Medicine, 52(­16), ­1054–​­1062.
Krustrup, P., Ørtenblad, N., Nielsen, J., Nybo, L., Gunnarsson, T. P., Iaia, F. M., … Bangsbo,
J. (­2011). Maximal voluntary contraction force, SR function and glycogen resynthesis during
the first 72 h after a ­h igh-​­level competitive soccer game. European Journal of Applied Physi-
ology, 111(­12), ­2987–​­2995.
Lavender, A. P., & Nosaka, K. (­2008). A light load eccentric exercise confers protection against
a subsequent bout of more demanding eccentric exercise. Journal of Science and Medicine in
Sport, 11(­3), ­291–​­298.
Lima, L. C. R., & Denadai, B. S. (­2015). Attenuation of eccentric ­exercise-​­induced muscle dam-
age conferred by maximal isometric contractions: a mini review. Frontiers in Physiology,
6, 300.
Loturco, I., Pereira, L. A., Kobal, R., Maldonado, T., Piazzi, A. F., Bottino, A., … Nakamura,
F. Y. (­2016). Improving sprint performance in soccer: effectiveness of jump squat and Olym-
pic push press exercises. PloS One, 11(­4), e0153958.
Mendiguchia, J., ­Castano-​­Zambudio, A., ­Jimenez-​­Reyes, P., Morin, J., Edouard, P., Conceicao,
F., … Colyer, S. (­2021). Can we modify maximal speed running posture? Implications for
performance and hamstring injuries management. International Journal of Sports Physiology
and Performance, 17(3), 374–383.
Mendiguchia, J., Conceição, F., Edouard, P., Fonseca, M., Pereira, R., Lopes, H., … ­Jiménez-​
­Reyes, P. (­2020). Sprint versus isolated eccentric training: comparative effects on hamstring
architecture and performance in soccer players. PLoS One, 15(­2), e0228283.
Mendiguchia, J., Edouard, P., Samozino, P., Brughelli, M., Cross, M., Ross, A., … Morin, J. B.
(­2016). Field monitoring of sprinting ­power–­​­­force–​­velocity profile before, during and after
hamstring injury: two case reports. Journal of Sports Sciences, 34(­6), ­535–​­541.
Mendiguchia, J., Gonzalez De la Flor, A., ­Mendez-​­Villanueva, A., Morin, J.-​­B., Edouard, P., &
Garrues, M. A. (­2021). T ­ raining-​­induced changes in anterior pelvic tilt: potential implica-
tions for hamstring strain injuries management. Journal of Sports Sciences, 39(­7), ­760–​­767.
Morin, J.-​­B., Petrakos, G., ­Jiménez-​­Reyes, P., Brown, S. R., Samozino, P., & Cross, M. R. (­2017).
­Very-​­heavy sled training for improving ­horizontal-​­force output in soccer players. Interna-
tional Journal of Sports Physiology and Performance, 12(­6), ­840–​­844.
Murtagh, C. F., Brownlee, T. E., OʼBoyle, A., Morgans, R., Drust, B., & Erskine, R. M.
(­2018). Importance of speed and power in elite youth soccer depends on maturation status.
Journal of Strength and Conditioning Research, 32(­2), 297–303. https://­doi.org/­org/­10.1519/­
JSC.0000000000002367
Murtagh, C. F., Naughton, R. J., McRobert, A. P., O’Boyle, A., Morgans, R., Drust, B., &
Erskine, R. M. (­2019). A coding system to quantify powerful actions in soccer match play: a
pilot study. Research Quarterly for Exercise and Sport, 90(­2), 234-243. https://­doi.org/­10.1080/
­02701367.2019.1576838
Murtagh, C. F., Nulty, C., Vanrenterghem, J., O’Boyle, A., Morgans, R., Drust, B., & Erskine,
R. M. (­2018). The neuromuscular determinants of unilateral jump performance in soccer
 Resistance training 33
players are ­direction-​­specific. International Journal of Sports Physiology and Performance,
13(­5), 604–611. https://­doi.org/­10.1123/­ijspp.­2017-​­0589
Murtagh, C. F., Vanrenterghem, J., O’Boyle, A., Morgans, R., Drust, B., & Erskine, R. M. (­2017).
Unilateral jumps in different directions: a novel assessment of ­soccer-​­associated power?
Journal of Science and Medicine in Sport, 20(­11), 1018–1023. https://­doi.org/­10.1016/­j.jsams.
2017.03.016
Nedelec, M., McCall, A., Carling, C., Legall, F., Berthoin, S., & Dupont, G. (­2014). The influ-
ence of soccer playing actions on the recovery kinetics after a soccer match. The Journal of
Strength & Conditioning Research, 28(­6), ­1517–​­1523.
Newton, M. J., Morgan, G. T., Sacco, P., Chapman, D. W., & Nosaka, K. (­2008). Comparison of
responses to strenuous eccentric exercise of the elbow flexors between r­ esistance-​­trained and
untrained men. The Journal of Strength & Conditioning Research, 22(­2), ­597–​­607.
Nosaka, K., Sakamoto, K., Newton, M., & Sacco, P. (­2001). The repeated bout effect of
­reduced-​­load eccentric exercise on elbow flexor muscle damage. European Journal of Applied
Physiology, 85(­1), ­34–​­40.
Petersen, J., Thorborg, K., Nielsen, M. B., B ­ udtz-​­Jørgensen, E., & Hölmich, P. (­2011). Preventive
effect of eccentric training on acute hamstring injuries in men’s soccer: a ­cluster-​­randomized
controlled trial. The American Journal of Sports Medicine, 39(­11), ­2296–​­2303.
Peterson, M. D., Rhea, M. R., & Alvar, B. A. (­2004). Maximizing strength development in ath-
letes: a ­meta-​­analysis to determine the d
­ ose-​­response relationship. The Journal of Strength &
Conditioning Research, 18(­2), ­377–​­382.
Presland, J. D., Timmins, R. G., Bourne, M. N., Williams, M. D., & Opar, D. A. (­2018). The ef-
fect of Nordic hamstring exercise training volume on biceps femoris long head architectural
adaptation. Scandinavian Journal of Medicine & Science in Sports, 28(­7), ­1775–​­1783.
Roig, M., O’Brien, K., Kirk, G., Murray, R., McKinnon, P., Shadgan, B., & Reid, W. D. (­2009).
The effects of eccentric versus concentric resistance training on muscle strength and mass in
healthy adults: a systematic review with m ­ eta-​­analysis. British Journal of Sports Medicine,
43(­8), ­556–​­568.
Schuermans, J., Van Tiggelen, D., Palmans, T., Danneels, L., & Witvrouw, E. (­2017). Deviating
running kinematics and hamstring injury susceptibility in male soccer players: Cause or con-
sequence? Gait & Posture, 57, ­270–​­277.
Timmins, R. G., Bourne, M. N., Shield, A. J., Williams, M. D., Lorenzen, C., & Opar, D. A.
(­2016). Short biceps femoris fascicles and eccentric knee flexor weakness increase the risk
of hamstring injury in elite football (­soccer): a prospective cohort study. British Journal of
Sports Medicine, 50(­24), ­1524–​­1535.
Trecroci, A., Porcelli, S., Perri, E., Pedrali, M., Rasica, L., Alberti, G., … Iaia, F. M. (­2020).
Effects of different training interventions on the recovery of physical and neuromuscular
performance after a soccer match. The Journal of Strength & Conditioning Research, 34(­8),
­2189–​­2196.
Vanrenterghem, J., Nedergaard, N. J., Robinson, M. A., & Drust, B. (­2017). Training load mon-
itoring in team sports: a novel framework separating physiological and biomechanical l­oad-​
­adaptation pathways. Sports Medicine, 47(­11), ­2135–​­2142.
3 Aerobic and anaerobic training
Liam Anderson and Barry Drust

Introduction
Soccer encompasses physiological, technical, tactical, and psychological/­sociological
contributions to performance. It is an intermittent sport consisting of short bouts
of intense activity that are superimposed amongst longer periods of ­low-­​­­moderate-​
i­ ntensity activity (­Reilly, 1997). This intermittent profile makes match demands highly
contextual and complex, requiring players to perform varied actions such as walking,
jogging, or sprinting during match play. Different actions are performed at varying
intensities, altering the contributions from different energy systems. Understanding
the match demands from a locomotion and physiological perspective provides the ba-
sis for a range of interventions, such as those targeted at physical development, talent
identification, and nutrition. In this chapter, we discuss the demands of soccer match
play, how these demands stress the two main energy systems; the aerobic and anaero-
bic energy systems and give some practical information relating to different training
methods for energy system development within soccer.

Demands of the game

The locomotive demands of soccer are well known, with players typically cover-
ing distances of ­10–​­13 km (­D ellal et al., 2011; Di Salvo et al., 2008). Relative to
players overall distance, the vast majority (~­80–​­90%) of this is performed at l­ow-­​
­­to-​­moderate intensities (­speeds <19.8 km h−1) (­Bradley et al., 2009). These speeds
correspond to various types of movement, such as standing, walking, jogging, and
running. For example, in ­elite-​­level soccer players in Denmark, Mohr et al. (­2003)
observed that 19.5% of time was spent standing, 41.8% walking, 16.7% jogging, and
16.8% running. These actions can often consist of forward, backwards, and lateral
movements both in possession (­from an individual and team perspective) and out of
possession. These data provide the basis of understanding that the aerobic energy
system is stressed significantly during match play and can therefore play an impor-
tant role in training strategies.
The remaining ­10–​­20% of distance covered in soccer match play is accounted for with
distances covered at ­h igh-​­intensity (­speeds >19.8 km h−1) and sprinting (­speeds >25.2
km h−1) (­Bradley et al., 2009; Di Salvo et al., 2010). These distances are extremely vari-
able from ­match-­​­­to-​­match in the English Premier League (­EPL) with high coefficients
of variation (~­16–​­30%; Gregson et al., 2010), indicating that energy system contribution

DOI: 10.4324/9781003148418-4
 Aerobic and anaerobic training 35
can be highly variable from let’s be consistent. Also, it appears that the distances cov-
ered within these ­h igh-​­intensity speed zones have increased over time across numerous
leagues. Barnes et al. (­2014) studied consecutive seasons from ­2006–​­2007 to 2­ 012–​­2013
in the EPL and found that distances covered at ­h igh-​­intensity speeds and ­h igh-​­intensity
actions were ~30% and ~50% higher, respectively, in the later years. Similar data from
the Spanish ­La-​­Liga between 2012 and 2019 has identified comparable trends (­­Lago-​
P­ enas et al., 2022). In addition to the distances covered, 90% of individual sprints are
shorter than 5 s in duration, with the average number of sprints being ~11 per match
(­Andrzejewski et al., 2013) during match play. This finding has particular importance
to soccer as ­h igh-​­intensity actions such as sprinting have been observed as the most
common actions in goals scored (­Faude et al., 2012; ­Martinez-​­Hernandez et al., 2022).
Collectively, these Data provide an understanding of the anaerobic demands and the
importance of these actions within the e­ ver-​­evolving demands of soccer match play,
outlining the requirement to train the anaerobic energy system.
In addition to the locomotive demands, there are instances when players are re-
quired to transition from low intensity to ­h igh-​­intensity activities and vice versa.
For example, during an acceleration or deceleration, change of direction or change
of velocity. Within match play, soccer players perform ~305 changes of direction
with an average of 19.2 s between actions. The changes of direction are mostly <90°
(­77%), and peak demands over ­15-​­and ­5 -​­min periods were 62 and 25 actions, respec-
tively (­Morgan et al., 2021). In addition, players perform ~1200 accelerations and
decelerations during match play (­Russell et al., 2016), with a change in activity every
­4 –​­6 s (­Bangsbo, 1994; Mohr et al., 2003). These actions likely contribute to a signifi-
cant proportion of the energy demands, although specific contributions from which
energy system are less clear. This finding complicates the energy demands of soccer,
and although no energy system dominates, there is a significant utilisation of vary-
ing amounts of energy sources from both the aerobic and anaerobic energy systems.
Given that soccer players play in different positions and strategic factors play a huge
part in match performance, it is noteworthy that match demands are not always the
same and can differ from l­et’s be consistent. For example, players who play in central
midfield cover the highest distances during a match and central defenders covering the
least. This difference is likely due to a product of higher levels of fitness associated with
such players and the role which they play in the team (i.e., central midfielders linking
between defence and attack), a role which evidently requires more sustained running
(­Bangsbo, 1994; Bloomfield et al., 2007; Reilly & Thomas, 1976). Wide midfielders and
­full-​­backs have been reported to cover greater distances in h ­ igh-​­intensity running and
sprinting (­Bradley et al., 2009). The greater ­h igh-​­intensity running distance covered
is due to their tactical role in the team and their runs being the longest in distance
(­Bradley et al., 2009). In addition, soccer players have many different situational var-
iables placed upon them, including match status (­i.e., winning, drawing, or losing),
match location (­i.e., home or away), tactical strategy (­i.e., playing formation and
counterattacking), and standard of opposition can significantly influence the match
demands (­­Lago-​­Penas, 2012). Moreover, soccer is played worldwide and in many dif-
ferent environmental climates, which can significantly influence match output and the
physiological demands associated with match play (­Mohr et al., 2012). These factors
further complicate the energy demands of soccer players and highlights the impor-
tance of analysing match demands to design and implement training programmes.
36 Liam Anderson and Barry Drust
Physical capabilities of players
The aerobic energy system is significantly taxed within soccer match play (­Stolen et al.,
2005). Understanding the specific physical capacities of elite soccer players, compared
to others at lower competitive standards, can provide insightful information to which
energy systems are regularly stressed and adapted to meet their demands. This is ev-
ident in ­elite-​­level soccer players who typically possess h ­ igh-​­aerobic test scores com-
pared with ­non-​­elite players (­see ­Table 3.1). Although soccer players’ scores are high
during such tests, the values are much lower than endurance athletes (­i.e., ~70 ml kg−1
V O2max), who rely on the aerobic energy system to a greater extent (­Davies & Thomp-
son, 1979). Soccer is multifactorial in nature, with other different physiological sys-
tems required to be trained to high levels and, therefore, limiting sole development of
the aerobic energy system.
Physical assessments of the aerobic energy system show significant positive correla-
tions with running performance in matches (­Bradley et al., 2011). Additionally, aero-
bic training that subsequently improved V O2max and lactate threshold increased the
total distance covered, and the number of sprints, which led to greater involvements
with the ball during a match (­Helgerud et al., 2001). The increased capacity for exer-
cise and an improved recovery speed from ­h igh-​­intensity exercise during competition,
leads to more repeated h ­ igh-​­intensity efforts (­Tomlin & Wenger, 2001). The higher fre-
quency is likely due to increased aerobic contribution during match play itself, p ­ ost-​
e­ xercise O2, lactate removal, and PCR restoration. Collectively, this evidence outlines
the importance of the aerobic energy system for match play performance.
The anaerobic energy system has significant demands placed on it, with many in-
tense actions being performed within match play. From a testing perspective, profes-
sional soccer players have high levels of anaerobic fitness (­see T ­ able 3.1). These physical
attributes are typically greater in players who play at higher competitive standards,
providing further clarification that the anaerobic energy system is frequently stressed
and is adapted to meet the increasing match demands (­Barnes et al., 2014; ­Lago-​­Penas
et al., 2022). In addition, performing anaerobic training has shown increases in ­soccer-​
s­pecific physical assessments such as ­Yo–​­Yo intermittent recovery tests, repeated
sprint tests, and sprint tests (­Ingebrigtsen et al., 2013; Mohr & Krustrup, 2016; Thom-
assen et al., 2010). These performance tests have been found to be good predictors for
­h igh-​­intensity performance within match play (­Mohr et al., 2016).

Table 3.1 Physical testing results of non-elite and elite soccer

players

Physical test ­Non- ​­elite Elite

V̇O2max (­m l.min−1.kg−1) ­50– ​­60 ­60–​­70

Velocity @ 4 mmol−1 (­k m hr−1) 9.­0 –​­13.3 13.­2 –​­16.6
­Yo–​­Yo IR level 1 average (­m) 1810 2420
­Yo–​­Yo IR level 2 average (­m) 840 1260
Mean repeated sprint time (­s) 4.­5 –​­4.9 4.­3 –​­4.5
5 m sprint time (­s) 1.­01–​­1.1 0.­80–​­0.90
30 m sprint time (­s) 4.­11–​­4.31 3.­92–​­4.21

IR = intermittent recovery, V O2max = maximal oxygen uptake

 Aerobic and anaerobic training 37
Measurements during match play
In intermittent contact sports such as soccer, it is extremely difficult to determine
the aerobic contribution due to a lack of methods to directly measure V O2 during
match play. Therefore, indirect methods are required to estimate the energy systems
contribution. Heart rate (­HR) has emerged as a potential method to assess aerobic
contribution within match play due to the H ­ R-​­V O2 relationship (­Bot & Hollander,
2000). Analysis into HR Anaerobic energy system and oxygen uptake utilising the
K4 apparatus during soccer drills have observed similar HR for a given V O2 as
found during treadmill running, validating this relationship (­Esposito et al., 2004).
Analysis into average and peak heart rates within match play were reported at
around 85 and 98% of maximal, respectively (­K rustrup et al., 2005; ­Suarez-​­Arrones
et al., 2015; Torreno et al., 2016). Based on the individual relationships between heart
rate and V O2 obtained in standardised tests in the laboratory, these values corre-
spond to approximately 70% of V O2max (­Bangsbo et al., 2006), highlighting via an
indirect method the extent to of which the aerobic energy system is stressed during
match play.
­H igh-​­intensity actions in soccer require ATP resynthesis through the breakdown
of creatine phosphate (­CP) and the degradation of muscle glycogen via glycolysis
to lactic acid (­McCartney et al., 1986; Spriet et al., 1989; Withers et al., 1991). To
assess anaerobic energy system contribution, muscle and blood metabolites can be
analysed during different periods of match play (­i.e., ­half-​­time or after an intense
period).
One of the most direct methods for assessing anaerobic contribution is taking
muscle biopsies from soccer players. Analysis of muscle samples indicated that CP
was 30% below resting values after intense periods in the match (­Bangsbo, Mohr, &
Krustrup, 2006). In addition, blood lactate values of up to 10 mmol−1 have been
observed with individual values above 12 mmol−1 (­Bangsbo, 1994; Krustrup et al.,
2006). These data clearly indicate that lactate production is high during match play
but doesn’t yet give a direct measurement of muscle lactate. In a friendly match
between n ­ on-​­professional soccer players, muscle lactate values reached around
15 mmol kg dry weight−1 compared with resting values after both halves, with the
highest value being 35 mmol.kg dry weight−1 (­K rustrup et al., 2006). During ­h igh-​
­intensity anaerobic activity, lactate is metabolised within active muscles (­Brooks,
1987). Lactate that is released from active muscles to the blood is taken up by dif-
ferent tissues such as the heart, liver, kidney, and inactive muscles (­Brooks, 1987).
Therefore, when blood lactate is assessed, it represents the balance of production,
release, and removal of lactate, being an appropriate indirect indicator of anaerobic
energy production.
Muscle lactate values do not correlate with blood lactate in ­short-​­term intermittent
exercise (­K rustrup et al., 2003). Compared to continuous exercise, where blood lactate
levels were lower but reflected the values observed within muscle, this is distinctly
different (­Bangsbo et al., 1993). Reasons for these differences are likely due to the
turnover rates between both muscle and blood lactate, with the rate of clearance being
higher in muscle than in blood. Given that muscle lactate can be low, and blood can
be high, these values aren’t linked to a single action in a game and rather represent an
accumulated/­balanced response to several h ­ igh-​­intensity actions performed across the
entirety of m ­ atch-​­play. These data further support the complex nature of soccer match
38 Liam Anderson and Barry Drust
play and should be considered when interpreting physiological responses and during
the design of training programmes of players.

Practical considerations for training

Information around the aerobic and anaerobic demands of soccer has formed the ba-
sis of specific training methods. The importance of optimally preparing players to
undertake individual and contextual match demands is greater than ever due to the
­ever-​­evolving match demands (­Barnes et al., 2014; ­Lago-​­Penas et al., 2022). Players are
now required to be able to meet these demands repeatedly, with often short recovery
periods (<72 h) over an entire season. The multifactorial nature of soccer makes this
complex and problematic, with training methods often required to develop multiple
physiological systems and needs at once in addition to the technical, tactical, and
physiological aspects of the sport (­see ­Figure 3.1). Therefore, careful planning and de-
livery of training programmes to maximise both individual energy system and holistic
soccer performance are required.
Soccer requires both the individual and simultaneous development of physiologi-
cal, technical, tactical, and psychological characteristics (­see ­Figure 3.1). A mixture of
running drills (­both with and without the ball) and ­soccer-​­specific drills (­i.e., s­ mall-​
­sided games (­SSGs) and technical drills) can be used as a training stimulus for both en-
ergy systems. These methods require the manipulation of basic principles of training:
frequency; intensity; time; type; specificity; progressive overload; and reversibility to

­Figure 3.1 An overview of energy system training guidelines, physiological adaptations,

and performance changes for soccer players. SGG = small sided games
 Aerobic and anaerobic training 39
elicit specific physiological adaptations on energy systems. Training drills can there-
fore be manipulated to achieve the required physical outcome, although they must be
planned into the overall physical loading.

Aerobic training
Aerobic training consists of both ­low-​­and ­h igh-​­intensity training. It can be performed
through traditional running exercises that can involve the ball and through s­ occer-​
­specific training methods utilising SSGs and technical drills. Aerobic training elicits
adaptations within cardiovascular parameters such as heart size (­Ekblom, 1969), blood
flow capacity (­Laughlin & Roseguini, 2008), and artery distensibility (­Rakobowchuk
et al., 2009). These adaptations improve the capacity of the cardiovascular system to
transport oxygen to working muscles, improving V O2 kinetics (­Bailey et al., 2009), V
O2max (­Helgerud et al., 2001; Impellizzeri et al., 2006), and ventilation and lactate
thresholds (­Driller et al., 2009). Further metabolic adaptations include an upregula-
tion of mitochondrial oxidative enzymes and increased muscular glycogen sparing
through greater metabolism of fat (­Iaia et al., 2009; Ross & Leveritt, 2001). These
adaptations lead to players being able to sustain h ­ igh-​­intensity exercise for longer and
recover quicker after intense periods of the game (­Tomlin & Wenger, 2001). Players
are required to exercise at different intensities and durations to both stimulate and
develop the aerobic energy system (­see ­Figure 3.1).

­Low-​­moderate intensity aerobic training

­ ow-​­moderate intensity aerobic training can form an important component of pro-
L
grammes to help form part of the recovery process and maintain aerobic fitness
(­Mohr & Iaia, 2014). For this type of training, intensity should average ~­60–​­80% of
the maximum heart but can range between 5­ 0–​­90% due to intermittent and varied
exercises being performed. A relatively high HR can be achieved with this type of
training without the requirement to perform at high speeds or intense actions. L ­ ow-​
­moderate intensity changes in speed and direction can be used, as well as the inclusion
of technical aspects such as dribbling, passing, and ball control (­Reilly & Ball, 1984).
These movements likely limit muscle damage compared to ­h igh-​­intensity exercise and
actions due to the damaging nature of eccentric muscle contractions (­Clarkson et al.,
1986). Therefore, ­low-​­moderate intensity aerobic training can be optimum during pe-
riods when players are required to maintain aerobic adaptation or when it is difficult
to withstand ­h igh-​­intensity demands (­i.e., as a recovery session, in the ­off-​­season, as a
supplementary part of ­in-​­season loading or returning from an injury). Some examples
of ­low-​­moderate intensity aerobic training are that of some SSGs and technical train-
ing (­see ­Figure 3.2a).

­High-​­intensity aerobic training

­ igh-​­intensity aerobic training can improve the aerobic contribution to ­h igh-​­intensity
H
activities and improve the ability to recover from such actions within game (­Bangsbo,
1994). It requires players to perform at exercise intensities of ~90% maximum HR
(­range = ­80–​­100%), utilising an ­exercise-­​­­to-​­rest ratio of ~2:1 and for durations of ­2 –​­4
min (­Bangsbo, Mohr, Poulsen, et al., 2006; Mohr & Iaia, 2014). When tracking and
40 Liam Anderson and Barry Drust

­Figure 3.2 Some typical training drills for the aerobic energy system. (­a) ­low-​­intensity aer-
obic training in the form of a technical passing exercise and (­b) a ­h igh-​­intensity
aerobic training. (­1) initiate the movement by dribbling around the cone to
2; (­2) perform a ­h igh-​­intensity effort up to the cone and to the following one;
(­3) perform lateral shuffles/­backwards jogging; (­4) perform a ­h igh-​­intensity run
at ~80% maximum speed and decelerate into 5; (­5) dribble around the cones up
to the centre circle before making a turn; (­6) play a pass with a server/ bounce
board and return to leave the ball on the centre circle; (­7) perform a jog to the
next ball and dribble around all three cones; (­8) perform a ­2 –​­3 s sprint; (­9) per-
form jumps over hurdles; and (­10) complete fast feet through the ladders.

monitoring players physical load, this HR zone is typically called the ‘­red zone’, as the
cardiovascular system is significantly stressed during exercise. For optimal aerobic
development, it is important to operate within this red zone from a training and match
play perspective.
The addition of h ­ igh-​­intensity aerobic training is commonplace within most pro-
fessional soccer settings, but research on implementing it within the ‘­normal’ training
programme is limited. In h ­ igh-​­level players in Scandinavian who performed an 8­ -​­week
period of aerobic h ­ igh-​­intensity training, in addition to their usual training load, im-
proved V O2max, lactate threshold and running economy were reported (­Helgerud
et al., 2001). These aerobic adaptations led to a 20% increase in distance covered,
100% increase in number of sprints and 24% increase in number of involvements with
the ball. However, in this study, training was performed on a treadmill, which is not
typical for soccer players as they’re required to undergo specific technical and tacti-
cal training as a team. Practitioners and researchers have overcome this shortcom-
ing through the creation of ­soccer-​­specific dribble tracks and manipulation of SSG
to elicit similar HR responses and likely aerobic adaptations (­­Hill-​­Haas et al., 2011;
Hoff et al., 2002). Given the positive aerobic adaptations when operating at these high
intensities, it seems important for soccer players to spend a significant amount of time
within this red zone. Further evidence to support this concept is evident in Italian
players, where the improved speeds attained at 2 and 4 mmol−1 blood lactate concen-
trations was correlated to time spent >90% maximum HR across a preparatory period
(­Castagna et al., 2011). These data clearly indicate the requirement for ­h igh-​­intensity
 Aerobic and anaerobic training 41
aerobic training, and it is important to consider when designing training programmes
during different stages of the season (­i.e., preparatory phase) and within the weekly ­in-​
s­ eason m
­ icro-​­cycle (­i.e., middle of the week). It must be noted that there doesn’t seem
to be any difference in adaptions whether this type of training is performed as part of
SSG or via traditional ­h igh-​­intensity interval training and should be left down to the
individual coach’s preference (­Impellizzeri et al., 2006). An example of a dribble track
that soccer players can use for aerobic development can be found in F ­ igure 3.2b.

Anaerobic training
Anaerobic training can be split into speed and speed endurance training (­Bangsbo,
1994; see ­Figure 3.1). It can be performed in running drills (­both with and without a
ball) and in the form of SSG or technical drills. Key adaptations to anaerobic training
include an increase in activity of anaerobic enzymes (­Ross & Leveritt, 2001), improved
K+ handling (­Bangsbo et al., 2009), ­lactate-​­H+ transport capacity (­Gunnarsson et al.,
2013), H+ regulation (­Skovgaard et al., 2014) and muscle capillarisation (­Jensen et al.,
2004). Many of these adaptations improve the rate of anaerobic energy turnover dur-
ing exercise and reduce the inhibitory effects of H+ within the muscle cell. These fac-
tors may improve the ability to produce power rapidly, for longer periods and improve
recovery after a h ­ igh-​­intensity exercise bout allowing soccer players a greater ability to
perform ­h igh-​­intensity actions for longer durations and repeat them, with less fatigue,
over the duration of the match.

Anaerobic speed training

Speed training specifically aims to improve the ability to produce a rapid force that im-
proves acceleration and maintains a high force to obtain high peak velocities (­Spinks
et al., 2007; Tonnessen et al., 2011). It requires players to perform at their maximum
for short periods of time (­­2–​­10 s) and sufficient rest. It is important to allow sufficient
rest in between repetitions so that players can fully recover, and maximal force can
be produced in the following repetition (­Reilly & Bangsbo, 1998). Therefore, recovery
between repetitions should be high (­i.e., 1:6 ­exercise-­​­­to-​­rest ratio), repetitions should
be low (<10) and should be performed early in the training session when players fatigue
levels are low, but players are prepared with an adequate ­warm-​­up.
Given that sprinting is the most frequent mechanism associated with hamstring in-
juries (­Ekstrand et al., 2011), careful consideration should be taken in making players
familiar with this type of training through gradual increases in the intensity and vol-
ume, as well as appropriate management of training when administering. It is im-
portant for speed training to be integrated into the s­occer-​­specific training to help
maximise transfer into match play (­i.e., counterattacking, crossing, and finishing).
This also helps training efficiency by reducing overall training time and limiting un-
necessary, ­low-​­quality exposures.
The addition of sprint training should occur in addition to (­or carefully placed into
the training design) other training load to which players are exposed. An examination
into a short sprint training programme that was performed in addition to team sport
athletes planned training load proved an effective method for improving short sprint
durations (­sprinting distance ≤30 m) (­Spinks et al., 2007). Spinks and colleagues found
improvements in short sprint durations when team sport athletes undertook sprint
42 Liam Anderson and Barry Drust

Figure 3.3 S
 ome typical training drills for the anaerobic energy system. Players perform
both drills at maximum intensity. (a) Speed training, where three players per-
form maximal sprints by timing their run into the box. Wide player initiates the
drill and performs an overlap of the server to receive the ball while two central
players make a curved run into the penalty area (one to the front post and one
to the back), the wide player delivers a ball into the area for one of the two cen-
tral players to score. Alternate left and right wide players for each repetition.
(b) Speed endurance training where players perform a diagonal run around the
pole and into a 2v2. All four players perform a diagonal run prior to commenc-
ing the 2v2, with the winning team into the playing area receiving the ball first.
Goalkeepers on both teams and points after each repetition being recorded to
increase competition and intensity.

training consisting of 5, 10, 15, and 20 m sprints, 2× per week for 8 weeks. In addition,
longer sprints (~40 m) seem to improve maximal sprinting velocity when performed as
an addition to the training programme (­Tonnessen et al., 2011). Given that soccer play-
ers typically sprint for <5 s in match play, these training modalities should account
for a large proportion of sprints performed in match play (­Andrzejewski et al., 2013).
However, to prepare players for some ­worst-​­case scenarios (­i.e., counterattacking from
a corner kick, recovery runs), frequent speed training of 2­ –​­10 s in duration seems per-
tinent in eliciting an adaptive response. An example of a sprint training drill specific
to soccer can be found in ­Figure 3.3.

Anaerobic speed endurance training

Match demands are becoming more ­h igh-​­intensity, meaning players must perform at
such intensities for longer and repeatedly to meet match demands (­Barnes et al., 2014;
­Lago-​­Penas et al., 2022). Speed endurance training is a form of anaerobic training per-
formed at maximal intensities with the aim to increase physical performance during
the most intense periods of match play (­Iaia et al., 2009; Mohr & Iaia, 2014). Training
with a short exercise-to-rest ratio (1:1-1:3) with durations of 10-90 seconds is termed
speed endurance maintenance (SEM), whereas reducing the exercise duration (10-40
 Aerobic and anaerobic training 43
s) and increasing the exercise-to-rest ratio (1:≥5) is termed speed endurance produc-
tion (SEP) (Bangsbo, 2015; Mohr & Iaia, 2014; see Figure 3.1). Both training methods
are designed to improve ­h igh-​­intensity performance. Specifically, SEM improves the
ability to perform repeated h ­ igh-​­intensity efforts, while SEP improves the ability to
perform maximally for a relatively short period of time (­Bangsbo, 2015)
Speed endurance training can be performed in SSG (­Mohr & Krustrup, 2016), run-
ning without or minimal contact with the ball (­Gunnarsson et al., 2012; Iaia et al.,
2015) and in p ­ osition-​­specific individual running drills (­Ade et al., 2021). These studies
examined the differences in physiological responses to SEM and SEP training. Due to
the reduced rest periods, SEM training typically has a higher cardiovascular response,
whereas SEP has a higher external output and blood lactate response due to being able
to operate at higher intensities (­Ade et al., 2014; Castagna et al., 2017; Iaia & Bangsbo,
2010). These data indicate that the anaerobic energy system has a greater involve-
ment in SEP, and there is some crossover of the aerobic energy system in SEM (­see
­Figure 3.1). In disagreement with these findings, Mohr and Krustrup (­2016) performed
4 weeks of either individual running drills with balls to reflect game situations or 2v2
SSG for SEP and SEM, respectively. The SEP training protocol elicited greater peak
and average running speeds as expected, however, this was accompanied by greater
peak heart rate responses compared to the SEM protocol. These findings highlight
the importance of the mode of exercise chosen in reflecting the training characteristics
and the monitoring of training responses and adaptations.
Several researchers have identified ­high-​­intensity performance improvements with
both SEM and SEP training (­Iaia & Bangsbo, 2010; Iaia et al., 2015; Mohr & Krustrup,
2016; Vitale et al., 2018). Iaia et al. (­2015) performed 3 weeks of either SEP or SEM train-
ing 3× per week as part of a reduced volume training programme at the conclusion of
the competitive season. SEP improved repeated sprint and ­high-​­intensity exercise per-
formance, whereas SEM increased the ability to maximise fatigue tolerance and main-
tain speed development during both repeated maximal and continuous ­short-​­duration
maximal exercises. However, Mohr and Krustrup (­2016) found that SEP training re-
sulted in superior performance improvements in both ­high-​­intensity intermittent run-
ning capacity and during a repeated sprint test. Given that other research have found
an enhanced ability to sustain exercise at high intensities in SEM training, these find-
ings are conflicting (­Iaia & Bangsbo, 2010; Iaia et al., 2015; Vitale et al., 2018). These
conflicting findings further highlight the importance of eliciting the correct physiolog-
ical response by altering the mode of training (­i.e., running vs. SSG), whilst continuing
monitoring physiological responses and adaptations to training. While there are many
positives and negatives associated with each training method, for specific control of
physiological responses during training, individual ­position-​­specific running drills that
involve the ball may be a potential ‘­m iddle ground’ training method (­Ade et al., 2021).
An example of a speed endurance drill can be found in ­Figure 3.3b.

Training methods
Soccer is multifactorial, and there are often many different methods to improve both the
aerobic and anaerobic energy systems. SSG (­also known as ­small-​­sided and conditioned
games) are manipulated to account for different aspects of a game to help achieve a
specific tactical/­technical objective while changing physiological, physical, and psycho-
logical demands (­­Bujalance-​­Moreno et al., 2019; Clemente et al., 2021; Davids et al.,
2013). These training methods have been found to improve both aerobic (­Impellizzeri
44 Liam Anderson and Barry Drust
et al., 2006) and anaerobic (­Chaouachi et al., 2014) fitness. In addition, this type of train-
ing provides a stimulus for muscle groups that are actively engaged during match play
(­Bangsbo, 1994). They can be performed extensively across the entire season with spe-
cific focus on the preparatory period and manipulation of variables across the ­in-​­season
training week to elicit a form of training periodisation (­Anderson, Orme, Di Michele,
Close, Morgans, et al., 2016; ­Martin-​­Garcia et al., 2018). These SSG offer exponential
benefits for the development of holistic soccer performance (­i.e., training technical, tac-
tical, physiological, and psychological development) and have become a key tool to use
for soccer training and conditioning programmes (­­Hill-​­Haas et al., 2011).
SSG, in brief can produce a wide range of physiological responses depending on their
format. For example, reducing player numbers, increasing pitch sizes (­higher individual
playing area per player), a limited number of ball touches, ­man-­​­­to-​­man marking, or the
use of ­small-​­goals or ball possession drills tend to increase the heart rate responses and
blood lactate concentrations of players from different age groups (­­Bujalance-​­Moreno
et al., 2019; H­ ill-​­Haas et al., 2011; Sarmento et al., 2018). To increase distances covered
in h
­ igh-​­intensity speed zones (­and increasing the ­high-​­intensity aerobic training), SSGs
can be played on large pitches (­Clemente et al., 2021). Increasing player number and the
pitch size can result in specific movement patterns that incorporate s­ tretch-­​­­shortening-​
­cycle (­SSC) activities as well develop both the anaerobic and aerobic energy system and
­position-​­specific capabilities based around the team’s tactical strategy (­Morgans et al.,
2014). Although SSGs seem an effective training strategy, the variability, and complex
nature of soccer may not allow all players to reach desired intensities required for adap-
tation. Consequently, ­r unning-​­based drills (­inclusive of drills with and without the ball)
can be performed to ensure that players are obtaining the desired intensities.
Despite the clear advantages of SSGs to offer a potential ‘­all in one’ solution to train-
ing, there are potential instances when r­ unning-​­based conditioning can be used to focus
on specific adaptation or when desired intensities aren’t able to be matched, such as the
preparatory period (­Faude et al., 2013), returning from an injury (­Taberner et al., 2019)
or when players are deemed not to have received enough match minutes (­Anderson,
Orme, Di Michele, Close, Milsom, et al., 2016; Hills et al., 2020). Typically, ­r unning-​
­based conditioning is in the form of h ­ igh-​­intensity interval training targeting aerobic
(­Buchheit & Laursen, 2013a) and anaerobic (­Buchheit & Laursen, 2013b) systems. Clear
advantages of this type of conditioning are that intensity can be based off current fit-
ness levels (­i.e., a percentage of V O2max, lactate threshold, or maximum speed) and
coaches have a direct control over the volume and intensity of exercise. Aerobic and
anaerobic training can be performed utilising singular or a hybrid of SSG and r­ unning-​
­based conditioning within the training programme. It is down to coach preference and
applicability of specific methods into other aspects of the training programme that may
decide which method is chosen and when. Utilising monitoring techniques can allow
coaches to understand the training stimulus, the physiological response, and adapta-
tions better to gain awareness of when specific methods may be required.

Monitoring soccer training

While understanding the demands of soccer and training prescription for the develop-
ment of both aerobic and anaerobic energy systems, these physical training sessions
have their own external (­the nature of the exercise) and internal (­anatomical, physio-
logical, biochemical, and functional adaptations) load (­Impellizzeri et al., 2004, 2005;
 Aerobic and anaerobic training 45
Viru & Viru, 2000). The external load is that which is prescribed by the coaches (­i.e.,
the conditioning drill, technical drill, or SSG). The internal load is the consequence
of the external load provided to players and its associated level of physiological stress
that imposes on any given individual player (­Viru & Viru, 2000). Internal training load
is particularly important to assess (­via multiple methods) as this is particularly impor-
tant in stimulating adaptations and specific to different energy system development
(­Booth & Thomason, 1991; Viru & Viru, 2000). Monitoring can be used in an acute
(­i.e., drill by drill and session by session) and chronic (­i.e., assessing longitudinal load-
ing and adaptations) sense to provide feedback to coaches to help plan and implement
improved training practices.

Future directions and conclusions

The demands of soccer are continuing to increase with greater reliance on the anaero-
bic energy system during match play. These developments are likely due to numerous
factors that are associated with improved training methods, greater adaptations, and
improved talent identification. It is not clear yet where the training demands are in
relation to the match demands and why these demands have increased. Future work
into the training demands is anticipated to specifically examine how the manipulation
of the training stimulus (­i.e., increased volume) can elicit optimal adaptation and when
different stimuli should be performed with regards to the overall training plan. This
­dose-​­response type research will aid the development of eliciting an effective training
process by utilising adaptative measurements and assessing them against a desired
outcome. In addition, molecular investigations to understanding specific signalling
responses to different types of soccer training (­i.e., ­h igh-​­intensity aerobic vs. SEP) are
yet to be performed. Specific understanding of the signalling responses (­and the en-
ergy cost) could allow for training and nutritional programmes to be tailored.
Soccer is a highly complex sport that requires multiple energy systems to be trained.
Understanding the match demands and how they stress the aerobic and anaerobic en-
ergy system are important for implementing training strategies that are aimed at energy
system development within soccer. Due to the complex nature of the sport, this training
is formed of multiple concepts that elicit different physiological adaptations. Implement-
ing training strategies into the overall periodised plan can allow for optimal physical
development and improved performance. Caution should be taken when implementing
training strategies due to the scheduling of other ­high-​­intensity training sessions or a con-
gested fixture schedule where players are required to perform m ­ atch-​­play every 2­ –​­3 days.
Eliciting a significant training stimulus during these periods may lead to ­non-​­functional
overreaching and injury occurrence. Monitoring strategies can be utilised to ensure play-
ers are training specific energy systems in the correct moments (­i.e., h ­ igh-​­intensity work
when players are recovered from match play and still have significant time before the next
competitive match), in the optimal form (­i.e., SSG vs. running) and amount.

References
Ade, J. D., Drust, B., Morgan, O. J., & Bradley, P. S. (­2021). Physiological characteristics
and acute fatigue associated with ­p osition-​­specific speed endurance soccer drills: produc-
tion vs maintenance training. Sci Med Footb, 5(­1), ­6 –​­17. https://­doi.org/­10.1080/­24733938.
2020.1789202
46 Liam Anderson and Barry Drust
Ade, J. D., Harley, J. A., & Bradley, P. S. (­2014). Physiological response, ­time-​­motion charac-
teristics, and reproducibility of various s­ peed-​­endurance drills in elite youth soccer players:
­small-​­sided games versus generic running. Int J Sports Physiol Perform, 9(­3), ­471–​­479. https://­
doi.org/­10.1123/­ijspp.­2013- ​­0390
Anderson, L., Orme, P., Di Michele, R., Close, G. L., Milsom, J., Morgans, R., Drust,
B., & Morton, J. P. (­2016). Quantification of ­s easonal-​­long physical load in soccer play-
ers with different starting status from the English premier league: implications for main-
taining squad physical fitness. Int J Sports Physiol Perform, 11(­8), ­1038–​­1046. https://­doi.
org/­10.1123/­ijspp.­2015-​­0672
Andrzejewski, M., Chmura, J., Pluta, B., Strzelczyk, R., & Kasprzak, A. (­2013). Analysis of
sprinting activities of professional soccer players. J Strength Cond Res, 27(­8), ­2134–​­2140.
https://­doi.org/­10.1519/­JSC.0b013e318279423e
Bailey, S. J., Wilkerson, D. P., Dimenna, F. J., & Jones, A. M. (­2009). Influence of repeated
sprint training on pulmonary O2 uptake and muscle deoxygenation kinetics in humans. J
Appl Physiol (­1985), 106(­6), ­1875–​­1887. https://­doi.org/­10.1152/­japplphysiol.00144.2009
Bangsbo, J. (­1994). The physiology of ­soccer–​­with special reference to intense intermittent ex-
ercise. Acta Physiol Scand Suppl, 619, ­1–​­155. https://­w ww.ncbi.nlm.nih.gov/­pubmed/­8059610
Bangsbo, J. (­2015). Performance in s­ ports–​­with specific emphasis on the effect of intensified
training. Scand J Med Sci Sports, 25(­Suppl 4), ­88–​­99. https://­doi.org/­10.1111/­sms.12605
Bangsbo, J., Gunnarsson, T. P., Wendell, J., Nybo, L., & Thomassen, M. (­2009). Reduced vol-
ume and increased training intensity elevate muscle Na+-​­K+ pump alpha2-​­subunit expres-
sion as well as ­short-​­and ­long-​­term work capacity in humans. J Appl Physiol (­1985), 107(­6),
­1771–​­1780. https://­doi.org/­10.1152/­japplphysiol.00358.2009
Bangsbo, J., Johansen, L., Graham, T., & Saltin, B. (­1993). Lactate and H+ effluxes from human
skeletal muscles during intense, dynamic exercise. J Physiol, 462, ­115–​­133. https://­doi.org/­
10.1113/­jphysiol.1993.sp019546
Bangsbo, J., Mohr, M., & Krustrup, P. (­2006). Physical and metabolic demands of train-
ing and ­match-​­play in the elite football player. J Sports Sci, 24(­7), ­665–​­674. https://­doi.
org/­10.1080/­02640410500482529
Barnes, C., Archer, D. T., Hogg, B., Bush, M., & Bradley, P. S. (­2014). The evolution of physi-
cal and technical performance parameters in the English premier league. Int J Sports Med,
35(­13), ­1095–​­1100. https://­doi.org/­10.1055/­­s-­​­­0 034-​­1375695
Bloomfield, J., Polman, R., & O’Donoghue, P. (­2007). Physical demands of different posi-
tions in fa premier league soccer. J Sports Sci Med, 6(­1), ­63–​­70. https://­w ww.ncbi.nlm.nih.
gov/­pubmed/­24149226
Booth, F. W., & Thomason, D. B. (­1991). Molecular and cellular adaptation of muscle in re-
sponse to exercise: perspectives of various models. Physiol Rev, 71(­2), ­541–​­585. https://­doi.
org/­10.1152/­physrev.1991.71.2.541
Bot, S. D., & Hollander, A. P. (­ 2000). The relationship between heart rate and oxygen
uptake during ­ non-​­ steady state exercise. Ergonomics, 43(­10), ­1578–​­1592. https://­doi.
org/­10.1080/­0 01401300750004005
Bradley, P. S., Mohr, M., Bendiksen, M., Randers, M. B., Flindt, M., Barnes, C., Hood, P.,
Gomez, A., Andersen, J. L., Di Mascio, M., Bangsbo, J., & Krustrup, P. (­ 2011). S­ ub-​
­maximal and maximal ­Yo-​­Yo intermittent endurance test level 2: heart rate response, re-
producibility and application to elite soccer. Eur J Appl Physiol, 111(­6), ­969–​­978. https://­doi.
org/­10.1007/­­s00421-­​­­010-­​­­1721-​­2
Bradley, P. S., Sheldon, W., Wooster, B., Olsen, P., Boanas, P., & Krustrup, P. (­2009). H ­ igh-​
­i ntensity running in English FA premier league soccer matches. J Sports Sci, 27(­2), ­159–​­168.
https://­doi.org/­10.1080/­02640410802512775
Brooks, G. A. (­1987). Amino acid and protein metabolism during exercise and recovery. Med
Sci Sports Exe, 19, ­150–​­156.
 Aerobic and anaerobic training 47
Buchheit, M., & Laursen, P. B. (­2013a). H ­ igh-​­intensity interval training, solutions to the pro-
gramming puzzle: Part I: cardiopulmonary emphasis. Sports Med, 43(­5), ­313–​­338. https://­doi.
org/­10.1007/­­s40279-­​­­013-­​­­0 029-​­x
Buchheit, M., & Laursen, P. B. (­2013b). ­High-​­intensity interval training, solutions to the pro-
gramming puzzle. Part II: anaerobic energy, neuromuscular load and practical applications.
Sports Med, 43(­10), ­927–​­954. https://­doi.org/­10.1007/­­s40279-­​­­013-­​­­0 066-​­5
­Bujalance-​­Moreno, P., ­Latorre-​­Roman, P. A., & ­Garcia-​­Pinillos, F. (­2019). A systematic review
on ­small-​­sided games in football players: acute and chronic adaptations. J Sports Sci, 37(­8),
­921–​­949. https://­doi.org/­10.1080/­02640414.2018.1535821
Castagna, C., Francini, L., Povoas, S. C. A., & D’Ottavio, S. (­2017). ­Long-​­sprint abilities in
soccer: ball versus running drills. Int J Sports Physiol Perform, 12(­9), ­1256–​­1263. https://­doi.
org/­10.1123/­ijspp.­2016-​­0565
Castagna, C., Impellizzeri, F. M., Chaouachi, A., Bordon, C., & Manzi, V. (­2011). Effect of
training intensity distribution on aerobic fitness variables in elite soccer players: a case study.
J Strength Cond Res, 25(­1), ­66–​­71. https://­doi.org/­10.1519/­JSC.0b013e3181fef3d3
Chaouachi, A., Chtara, M., Hammami, R., Chtara, H., Turki, O., & Castagna, C. (­2014).
Multidirectional sprints and s­mall-​­sided games training effect on agility and change of
direction abilities in youth soccer. J Strength Cond Res, 28(­11), ­3121–​­3127. https://­doi.
org/­10.1519/­JSC.0000000000000505
Clarkson, P. M., Byrnes, W. C., McCormick, K. M., Turcotte, L. P., & White, J. S. (­1986). Mus-
cle soreness and serum creatine kinase activity following isometric, eccentric, and concentric
exercise. Int J Sports Med, 7(­3), ­152–​­155. https://­doi.org/­10.1055/­­s-­​­­2008-​­1025753
Clemente, F. M., R ­ amirez-​­Campillo, R., Sarmento, H., Praca, G. M., Afonso, J., Silva, A. F.,
Rosemann, T., & Knechtle, B. (­2021). Effects of ­s mall-​­sided game interventions on the tech-
nical execution and tactical behaviors of young and youth team sports players: a system-
atic review and ­meta-​­a nalysis. Front Psychol, 12, 667041. https://­doi.org/­10.3389/­f psyg.2021.
667041
Davids, K., Araujo, D., Correia, V., & Vilar, L. (­2013). How ­small-​­sided and conditioned games
enhance acquisition of movement and ­decision-​­making skills. Exerc Sport Sci Rev, 41(­3),
­154–​­161. https://­doi.org/­10.1097/­JES.0b013e318292f3ec
Davies, C. T., & Thompson, M. W. (­1979). Aerobic performance of female marathon and
male ultramarathon athletes. Eur J Appl Physiol Occup Physiol, 41(­4), ­233–​­245. https://­doi.
org/­10.1007/­BF00429740
Dellal, A., Chamari, K., Wong del, P., Ahmaidi, S., Keller, D., Barros, R., Bisciotti, G. N., &
Carling, C. (­2011). Comparison of physical and technical performance in European soc-
cer m ­ atch-​­play: FA Premier League and La Liga. Eur J Sports Sci, 11(­1), ­51–​­59. https://­doi.
org/­10.1080/­17461391.2010.481334
Di Salvo, V., Baron, R., G ­ onzalez-​­Haro, C., Gormasz, C., Pigozzi, F., & Bachl, N. (­2010).
Sprinting analysis of elite soccer players during European Champions League and UEFA
Cup matches. J Sports Sci, 28(­14), ­1489–​­1494. https://­doi.org/­10.1080/­02640414.2010.521166
Di Salvo, V., Benito, P. J., Calderon, F. J., Di Salvo, M., & Pigozzi, F. (­2008). Activity profile
of elite goalkeepers during football ­match-​­play. J Sports Med Phys Fitness, 48(­4), ­443–​­446.
https://­w ww.ncbi.nlm.nih.gov/­pubmed/­18997646
Driller, M. W., Fell, J. W., Gregory, J. R., Shing, C. M., & Williams, A. D. (­2009). The effects
of ­h igh-​­i ntensity interval training in ­well-​­trained rowers. Int J Sports Physiol Perform, 4(­1),
­110–​­121. https://­doi.org/­10.1123/­ijspp.4.1.110
Ekblom, B. (­1969). Effect of physical training in adolescent boys. J Appl Physiol, 27(­3), ­350–​­355.
https://­doi.org/­10.1152/­jappl.1969.27.3.350
Ekstrand, J., Hagglund, M., & Walden, M. (­2011). Epidemiology of muscle injuries in pro-
fessional football (­ soccer). Am J Sports Med, 39(­6), ­1226–​­1232. https://­doi.org/­10.1177/
­0363546510395879
48 Liam Anderson and Barry Drust
Esposito, F., Impellizzeri, F. M., Margonato, V., Vanni, R., Pizzini, G., & Veicsteinas, A. (­2004).
Validity of heart rate as an indicator of aerobic demand during soccer activities in amateur
soccer players. Eur J Appl Physiol, 93(­­1–​­2), ­167–​­172. https://­doi.org/­10.1007/­­s 00421-­​­­0 04-­​­­
1192-​­4
Faude, O., Koch, T., & Meyer, T. (­ 2012). Straight sprinting is the most frequent ac-
tion in goal situations in professional football. J Sports Sci, 30(­7), ­625–​­631. https://­doi.
org/­10.1080/­02640414.2012.665940
Faude, O., Schnittker, R., ­Schulte-​­Zurhausen, R., Muller, F., & Meyer, T. (­2013). High in-
tensity interval training vs. h ­ igh-​­volume running training during p ­ re-​­season conditioning
in ­h igh-​­level youth football: a ­cross-​­over trial. J Sports Sci, 31(­13), ­1441–​­1450. https://­doi.
org/­10.1080/­02640414.2013.792953
Gregson, W., Drust, B., Atkinson, G., & Salvo, V. D. (­2010). M ­ atch-­​­­to-​­match variability of
­h igh-​­speed activities in premier league soccer. Int J Sports Med, 31(­4), ­237–​­242. https://­doi.
org/­10.1055/­­s-­​­­0 030-​­1247546
Gunnarsson, T. P., Christensen, P. M., Holse, K., Christiansen, D., & Bangsbo, J. (­2012). Effect
of additional speed endurance training on performance and muscle adaptations. Med Sci
Sports Exerc, 44(­10), ­1942–​­1948. https://­doi.org/­10.1249/­MSS.0b013e31825ca446
Gunnarsson, T. P., Christensen, P. M., Thomassen, M., Nielsen, L. R., & Bangsbo, J. (­2013).
Effect of intensified training on muscle ion kinetics, fatigue development, and repeated ­short-​
­term performance in ­endurance-​­trained cyclists. Am J Physiol Regul Integr Comp Physiol,
305(­7), ­R811– ​­821. https://­doi.org/­10.1152/­ajpregu.00467.2012
Helgerud, J., Engen, L. C., Wisloff, U., & Hoff, J. (­2001). Aerobic endurance training improves
soccer performance. Med Sci Sports Exerc, 33(­11), ­1925–​­1931. https://­doi.org/­10.1097/­­0 0005768-­​­­
200111000-​­0 0019
­Hill-​­Haas, S. V., Dawson, B., Impellizzeri, F. M., & Coutts, A. J. (­2011). Physiology of s­ mall-​
­sided games training in football: a systematic review. Sports Med, 41(­3), ­199–​­220. https://­doi.
org/­10.2165/­­11539740-­​­­0 00000000-​­0 0000
Hills, S. P., Barrett, S., Busby, M., Kilduff, L. P., Barwood, M. J., Radcliffe, J. N., Cooke, C.
B., & Russell, M. (­2020). Profiling the p ­ ost-​­match ­top-​­up conditioning practices of profes-
sional soccer substitutes: an analysis of contextual influences. J Strength Cond Res, 34(­10),
­2805–​­2814. https://­doi.org/­10.1519/­JSC.0000000000003721
Hoff, J., Wisloff, U., Engen, L. C., Kemi, O. J., & Helgerud, J. (­2002). Soccer specific aerobic
endurance training. Br J Sports Med, 36(­3), ­218–​­221. https://­doi.org/­10.1136/­bjsm.36.3.218
Iaia, F. M., & Bangsbo, J. (­2010). Speed endurance training is a powerful stimulus for phys-
iological adaptations and performance improvements of athletes. Scand J Med Sci Sports,
20(­Suppl 2), ­11–​­23. https://­doi.org/­10.1111/­j.­1600-​­0838.2010.01193.x
Iaia, F. M., Fiorenza, M., Perri, E., Alberti, G., Millet, G. P., & Bangsbo, J. (­2015). The effect
of two speed endurance training regimes on performance of soccer players. PLoS One, 10(­9),
e0138096. https://­doi.org/­10.1371/­journal.pone.0138096
Iaia, F. M., Hellsten, Y., Nielsen, J. J., Fernstrom, M., Sahlin, K., & Bangsbo, J. (­2009). Four
weeks of speed endurance training reduces energy expenditure during exercise and main-
tains muscle oxidative capacity despite a reduction in training volume. J Appl Physiol (­1985),
106(­1), ­73–​­80. https://­doi.org/­10.1152/­japplphysiol.90676.2008
Impellizzeri, F. M., Marcora, S. M., Castagna, C., Reilly, T., Sassi, A., Iaia, F. M., & Ramp-
inini, E. (­2006). Physiological and performance effects of generic versus specific aerobic
training in soccer players. Int J Sports Med, 27(­6 ), ­483–​­492. https://­doi.org/­10.1055/­­s -­​­­2005-
​­865839
Impellizzeri, F. M., Rampinini, E., Coutts, A. J., Sassi, A., & Marcora, S. M. (­2004). Use of
­RPE-​­based training load in soccer. Med Sci Sports Exerc, 36(­6), ­1042–​­1047. https://­doi.org/­
10.1249/­01.mss.0000128199.23901.2f
Impellizzeri, F. M., Rampinini, E., & Marcora, S. M. (­ 2005). Physiological assess-
ment of aerobic training in soccer. J Sports Sci, 23(­6 ), ­583–​­592. https://­doi.org/­10.1080/­
02640410400021278
 Aerobic and anaerobic training 49
Ingebrigtsen, J., Shalfawi, S. A., Tonnessen, E., Krustrup, P., & Holtermann, A. (­2013). Per-
formance effects of 6 weeks of aerobic production training in junior elite soccer players. J
Strength Cond Res, 27(­7), ­1861–​­1867. https://­doi.org/­10.1519/­JSC.0b013e31827647bd
Jensen, L., Bangsbo, J., & Hellsten, Y. (­2004). Effect of high intensity training on capillariza-
tion and presence of angiogenic factors in human skeletal muscle. J Physiol, 557(­Pt 2), ­571–​
­582. https://­doi.org/­10.1113/­jphysiol.2003.057711
Krustrup, P., Mohr, M., Amstrup, T., Rysgaard, T., Johansen, J., Steensberg, A., Pedersen,
P. K., & Bangsbo, J. (­2003). The ­yo-​­yo intermittent recovery test: physiological response,
reliability, and validity. Med Sci Sports Exerc, 35(­4), ­697–​­705. https://­doi.org/­10.1249/­01.
MSS.0000058441.94520.32
Krustrup, P., Mohr, M., Ellingsgaard, H., & Bangsbo, J. (­2005). Physical demands during an
elite female soccer game: importance of training status. Med Sci Sports Exerc, 37(­7), ­1242–​
­1248. https://­doi.org/­10.1249/­01.mss.0000170062.73981.94
Krustrup, P., Mohr, M., Steensberg, A., Bencke, J., Kjaer, M., & Bangsbo, J. (­2006). Muscle and
blood metabolites during a soccer game: implications for sprint performance. Med Sci Sports
Exerc, 38(­6), ­1165–​­1174. https://­doi.org/­10.1249/­01.mss.0000222845.89262.cd
­Lago-​­Penas, C. (­2012). The role of situational variables in analysing physical performance in
soccer. J Hum Kinet, 35, ­89–​­95. https://­doi.org/­10.2478/­­v10078- ­​­­012- ­​­­0 082-​­9
­Lago-​­Penas, C., L ­ orenzo-​­Martinez, M., L ­ opez-​­Del Campo, R., Resta, R., & Rey, E. (­2022).
Evolution of physical and technical parameters in the Spanish LaLiga ­2012–​­2019. Sci Med
Footb, 7, ­1–​­6. https://­doi.org/­10.1080/­24733938.2022.2049980
Laughlin, M. H., & Roseguini, B. (­2008). Mechanisms for exercise t­ raining-​­induced increases
in skeletal muscle blood flow capacity: differences with interval sprint training versus aero-
bic endurance training. J Physiol Pharmacol, 59(­Suppl 7), ­71–​­88. https://­w ww.ncbi.nlm.nih.
gov/­pubmed/­19258658
­Martin-​­Garcia, A., Gomez Diaz, A., Bradley, P. S., Morera, F., & Casamichana, D. (­2018).
Quantification of a professional football team’s external load using a microcycle structure. J
Strength Cond Res, 32(­12), ­3511–​­3518. https://­doi.org/­10.1519/­JSC.0000000000002816
­Martinez-​­Hernandez, D., Quinn, M., & Jones, P. (­2022). Linear advancing actions followed by
deceleration and turn are the most common movements preceding goals in male professional
soccer. Sci Med Footb, 7, ­1–​­9. https://­doi.org/­10.1080/­24733938.2022.2030064
McCartney, N., Spriet, L. L., Heigenhauser, G. J., Kowalchuk, J. M., Sutton, J. R., & Jones,
N. L. (­1986). Muscle power and metabolism in maximal intermittent exercise. J Appl Physiol
(­1985), 60(­4), ­1164–​­1169. https://­doi.org/­10.1152/­jappl.1986.60.4.1164
Mohr, M., & Iaia, F. M. (­2014). Physiological basis of fatigue resistance training in competitive
football. Sports Sci Exchange, 27, ­1–​­9.
Mohr, M., & Krustrup, P. (­2016). Comparison between two types of anaerobic speed en-
durance training in competitive soccer players. J Hum Kinet, 51, ­183–​­192. https://­doi.
org/­10.1515/­­hukin-­​­­2015-​­0181
Mohr, M., Krustrup, P., & Bangsbo, J. (­2003). Match performance of h ­ igh-​­standard soccer
players with special reference to development of fatigue. J Sports Sci, 21(­7), ­519–​­528. https://­
doi.org/­10.1080/­0264041031000071182
Mohr, M., Nybo, L., Grantham, J., & Racinais, S. (­2012). Physiological responses and physi-
cal performance during football in the heat. PLoS One, 7(­6), e39202. https://­doi.org/­10.1371/­
journal.pone.0039202
Mohr, M., Thomassen, M., Girard, O., Racinais, S., & Nybo, L. (­2016). Muscle variables of
importance for physiological performance in competitive football. Eur J Appl Physiol, 116(­2),
­251–​­262. https://­doi.org/­10.1007/­­s00421-­​­­015-­​­­3274-​­x
Morgan, O. J., Drust, B., Ade, J. D., & Robinson, M. A. (­2021). Change of direction frequency
off the ball: new perspectives in elite youth soccer. Sci Med Footb. 6, 473–482 https://­doi.
org/­10.1080/­24733938.2021.1986635
Morgans, R., Orme, P., Anderson, L., & Drust, B. (­2014). Principles and practices of training
for soccer. J Sport Health Sci, 3, ­251–​­257.
50 Liam Anderson and Barry Drust
Rakobowchuk, M., Stuckey, M. I., Millar, P. J., Gurr, L., & Macdonald, M. J. (­2009). Effect of
acute sprint interval exercise on central and peripheral artery distensibility in young healthy
males. Eur J Appl Physiol, 105(­5), ­787–​­795. https://­doi.org/­10.1007/­­s00421-­​­­0 08-­​­­0964-​­7
Reilly, T. (­1997). Energetics of h ­ igh-​­intensity exercise (­soccer) with particular reference to fa-
tigue. J Sports Sci, 15(­3), ­257–​­263. https://­doi.org/­10.1080/­026404197367263
Reilly, T., & Ball, D. (­1984). The net physiological cost of dribbling a soccer ball. Res Quart Exe
Sport, 55(­3), ­267–​­271. https://­doi.org/­10.1080/­02701367.1984.10609363
Reilly, T., & Bangsbo, J. (­1998). Anaeroibc and aerobic training. Chichester: Wiley.
Reilly, T., & Thomas, V. (­1976). A motion analysis of ­work-​­rate in different positional roles in
professional football ­match-​­play. J Human Movem Studies, 2, ­87–​­97.
Ross, A., & Leveritt, M. (­2001). ­Long-​­term metabolic and skeletal muscle adaptations to s­ hort-​
­sprint training: implications for sprint training and tapering. Sports Med, 31(­15), ­1063–​­1082.
https://­doi.org/­10.2165/­­0 0007256-­​­­200131150-​­0 0003
Russell, M., Sparkes, W., Northeast, J., Cook, C. J., Love, T. D., Bracken, R. M., & Kilduff,
L. P. (­ 2016). Changes in acceleration and deceleration capacity throughout profes-
sional soccer ­match-​­play. J Strength Cond Res, 30(­10), ­2839–​­2844. https://­doi.org/­10.1519/
­JSC.0000000000000805
Sarmento, H., Clemente, F. M., Harper, L. D., da Costa, I. T., Owen, A., & Figueiredo, A. J.
(­2018). Small sided games in soccer: a systematic review. Intl J Perf Anal Sport, 18(­5), ­693–​­749.
Skovgaard, C., Christensen, P. M., Larsen, S., Andersen, T. R., Thomassen, M., & Bangsbo, J.
(­2014). Concurrent speed endurance and resistance training improves performance, running
economy, and muscle NHE1 in moderately trained runners. J Appl Physiol (­1985), 117(­10),
­1097–​­1109. https://­doi.org/­10.1152/­japplphysiol.01226.2013
Spinks, C. D., Murphy, A. J., Spinks, W. L., & Lockie, R. G. (­2007). The effects of re-
sisted sprint training on acceleration performance and kinematics in soccer, rugby un-
ion, and Australian football players. J Strength Cond Res, 21(­1), ­77–​­85. https://­doi.
org/­10.1519/­­0 0124278-­​­­200702000-​­0 0015
Spriet, L. L., Lindinger, M. I., McKelvie, R. S., Heigenhauser, G. J., & Jones, N. L. (­1989). Mus-
cle glycogenolysis and H+ concentration during maximal intermittent cycling. J Appl Physiol
(­1985), 66(­1), ­8 –​­13. https://­doi.org/­10.1152/­jappl.1989.66.1.8
Stolen, T., Chamari, K., Castagna, C., & Wisloff, U. (­2005). Physiology of soccer: an update.
Sports Med, 35(­6), ­501–​­536. https://­doi.org/­10.2165/­­0 0007256-­​­­200535060-​­0 0004
Suarez-​­
­ Arrones, L., Torreno, N., Requena, B., Saez De Villarreal, E., Casamichana, D.,
­Barbero-​­A lvarez, J. C., & ­Munguia-​­Izquierdo, D. (­2015). ­Match-​­play activity profile in
professional soccer players during official games and the relationship between external
and internal load. J Sports Med Phys Fitness, 55(­12), ­1417–​­1422. https://­w ww.ncbi.nlm.nih.
gov/­pubmed/­25289717
Taberner, M., Allen, T., & Cohen, D. D. (­ 2019). Progressing rehabilitation after injury:
consider the ‘­­control-​­chaos continuum’. Br J Sports Med, 53(­18), ­1132–​­1136. https://­doi.
org/­10.1136/­­bjsports-­​­­2018-​­100157
Thomassen, M., Christensen, P. M., Gunnarsson, T. P., Nybo, L., & Bangsbo, J. (­2010). Effect
of 2­ -​­wk intensified training and inactivity on muscle Na+-​­K+ pump expression, phospholem-
man (­FXYD1) phosphorylation, and performance in soccer players. J Appl Physiol (­1985),
108(­4), ­898–​­905. https://­doi.org/­10.1152/­japplphysiol.01015.2009
Tomlin, D. L., & Wenger, H. A. (­2001). The relationship between aerobic fitness and re-
covery from h ­igh-​­
intensity intermittent exercise. Sports Med, 31(­1), ­1–​­11. https://­doi.
org/­10.2165/­­0 0007256-­​­­200131010-​­0 0001
Tonnessen, E., Shalfawi, S. A., Haugen, T., & Enoksen, E. (­2011). The effect of ­40-​­m repeated
sprint training on maximum sprinting speed, repeated sprint speed endurance, vertical
jump, and aerobic capacity in young elite male soccer players. J Strength Cond Res, 25(­9),
­2364–​­2370. https://­doi.org/­10.1519/­JSC.0b013e3182023a65
 Aerobic and anaerobic training 51
Torreno, N., M ­ unguia-​­Izquierdo, D., Coutts, A., de Villarreal, E. S., A­ sian-​­Clemente, J., &
­Suarez-​­Arrones, L. (­2016). Relationship between external and internal loads of profes-
sional soccer players during full matches in official games using global positioning sys-
tems and ­heart-​­rate technology. Int J Sports Physiol Perform, 11(­7), ­940–​­946. https://­doi.
org/­10.1123/­ijspp.­2015-​­0252
Viru, A., & Viru, M. (­2000). Nature of training effects. In W. Garret & D. Kirkendall (­Eds.),
Exercise and Sport Science (­p­­p. ­67–​­95). Lippincott: Williams & Williams.
Vitale, J. A., Povia, V., Vitale, N. D., Bassani, T., Lombardi, G., Giacomelli, L., Banfi, G., & La
Torre, A. (­2018). The effect of two different speed endurance training protocols on a multiple
shuttle run performance in young elite male soccer players. Res Sports Med, 26(­4), ­436–​­449.
https://­doi.org/­10.1080/­15438627.2018.1492402
Withers, R. T., Sherman, W. M., Clark, D. G., Esselbach, P. C., Nolan, S. R., Mackay, M.
H., & Brinkman, M. (­1991). Muscle metabolism during 30, 60 and 90 s of maximal cycling
on an ­air-​­braked ergometer. Eur J Appl Physiol Occup Physiol, 63(­5), ­354–​­362. https://­doi.
org/­10.1007/­BF00364462
4 Soccer in the heat
Performance and mitigation
Caroline Sunderland, Stacey Cowe and,
Rachel Malcolm

Introduction
Soccer is one of the world’s most popular sports and is played across all seven con-
tinents, resulting in highly variable environmental conditions across competitions.
This phenomenon is becoming increasingly important due to global warming. Al-
though understanding of thermoregulation has improved, the complexities of team
sports, specifically soccer, makes understanding the influence of heat on different
components extremely difficult. In recent years, a number of competitions have
taken place in extreme environments, such as the Tokyo Olympics and the FIFA
World Cup in Qatar (­anticipated 29oC and 59% relative humidity; Chodor et al.,
2021). As a result, it is imperative that coaches, players, governing bodies, and med-
ical staff have an adequate awareness of the risks associated with hyperthermia and
the potential influences on performance.
Performance incorporates a combination of factors, including tactical, technical,
physical, and psychological (­Slattery & Coutts, 2019). Few researchers have investi-
gated how heat effects a combination of these components, however, a number of stud-
ies have assessed the individual effects of heat on each of these components. These
studies have shown that a range of these elements can be negatively influenced by
heat stress, including cognitive function (­Bandelow et al., 2010), the ability to perform
repeated sprints (­Maxwell, Aitchison, & Nimmo, 1996), and the perception of effort
(­Duffield, Coutts, & Quinn, 2009). This emphasises the need for w ­ ell-​­designed strate-
gies to cool and acclimate athletes to minimise the effect on performance. Consider-
ations must also be made with regards to the timing of matches, whereby in extreme
environmental conditions, match times will need to avoid peak d ­ ay-​­time tempera-
tures to protect athletes against hyperthermia. A significant amount of individual
variation occurs with regards to thermoregulation, often influenced by sex, age, body
composition, and disability status, all of which must be considered when planning for
performance.
In this chapter, we examine the influence of high external temperatures on different
components of soccer performance. These will include the effects on physical output
and cognitive function, whilst detailing the effects on different populations, includ-
ing female players, youth players, referees, and disabled athletes. Also, we aim to de-
tail some the strategies utilised to counteract these effects and help optimise soccer
performance.

DOI: 10.4324/9781003148418-5
 Soccer in the heat 53
Physical performance
Performance in soccer tends to be divided into tactical aspects and physical elements,
with power, speed, and endurance being instrumental to success (­Figueira, Goncalves,
Masiulis, & Sampaio, 2018; Rösch et al., 2000). In research related to soccer, these
physical elements are a common measurement used to quantify how certain variables
may affect performance, such as hot environmental conditions.
One of the main concerns when exercising in the heat is the negative effect it could
have on an athlete’s performance. A potential reason for these performance decre-
ments is that an increase in core body temperature causes a reduction in exercise ca-
pacity (­Nybo, Rasmussen, & Sawka, 2014). In a study carried out by Aldous et al.
(­2015), which utilised an intermittent soccer performance test in a control (­18oC) and
hot environment (­30oC), participant’s total and sprint distance covered was signifi-
cantly less when completing the test in the heat (­see F ­ igures 4.1 and 4.2). Similarly,
Mohr, Nybo, Grantham, and Racinais (­2012) found that participants completed less
­h igh-​­speed running when playing soccer in the heat (­43oC) in comparison to a control
environment (­21oC) (­­Figure 4.3). These findings highlight the negative effect increases
in core body temperature may have on performance.
As well as increases in core body temperature and dehydration causing an individ-
ual to become fatigued resulting in poorer performance (­Shirreffs, Sawka, & Stone,
2006), perceptual responses, such as thermal sensation, can play a role. Previously, re-
searchers have demonstrated that ratings of thermal sensation are significantly higher
when exercising in a hot environment (­34oC), which is accompanied by a rise in skin
temperature (­Periard et al., 2014). Due to perceptual measures being heightened when
exercising in the heat, it can result in physiological and perceptual strain as well as

9500

9400
Total Distance Covered (m)

9300

9200

9100

9000

8900

8800

8700

8600
CONTROL HOT
Condition

­Figure 4.1 The total distance covered in a simulated soccer match in control (­18oC) and
hot (­30oC) environmental conditions (­control vs hot: P < 0.05). Redrawn from
Aldous et al. (­2015).
54 Caroline Sunderland et al.

1100
Sprint Distance Covered (m) 1095
1090
1085
1080
1075
1070
1065
1060
1055
1050
1045
CONTROL HOT
Condition

­Figure 4.2 The sprint distance covered in a simulated soccer match in control (­18oC) and
hot (­30oC) environmental conditions (­control vs hot: P < 0.05). Redrawn from
Aldous et al. (­2015).

1200
High Speed Running Distance (m)

1000

800

600

400

200

0
CONTROL HOT
Condition

­Figure 4.3 The h ­ igh-​­speed running distance completed during a soccer match in con-
trol (­21oC) and hot (­43oC) environmental conditions (­control vs hot: P < 0.05).
Redrawn from Mohr et al. (­2012).
 Soccer in the heat 55
­ eat-​­related illnesses, such as heat exhaustion (­Sawka et al., 2007). In addition, an in-
h
crease in thermal sensation ratings causes individuals to adjust their physical activity
patterns to ensure core temperature is kept within safe levels and minimise discomfort
(­Duffield et al., 2009; Periard et al., 2014). This finance indicates that an individu-
al’s performance may worsen when exercising in the heat due to increased thermal/­
perceptual strain. Therefore, because of this potential effect perceptual responses to
exercise in the heat may have on performance, it is imperative to understand how to
attenuate the rise in subjective perceptual ratings.
The influence of heat stress on soccer players is not only important for our un-
derstanding of performance, but it is essential for preventing ­heat-​­related illness.
­Heat-​­related illness can be ­life-​­threatening if not treated promptly. During a soccer
tournament played in the heat, in total, 34 players collapsed due to heat exhaustion,
highlighting the serious consequences of hyperthermia (­K irkendall, 1993). Knowledge
of a­ t-​­risk players and signs of ­heat-​­related illness is essential.

Cognitive function and ­decision-​­making

Performance in team sport is dictated by the ability to produce skilful actions consist-
ently across a prolonged period, whilst under significant physical stress. The ability
to produce skilful actions depends upon optimal functioning of various cognitive do-
mains, controlled by different regions of the brain (­Schmitt, Benton, & Kallus, 2005).
Due to heat influencing different brain regions variably, this becomes a complex as-
pect of performance to assess and optimise.
Cognitive performance has previously been linked with changes in stress and arousal,
whereby the different domains of cognitive function each have an optimal zone of func-
tioning in terms of the level of arousal experienced in response to a specific stressor. Opti-
mising arousal levels allows athletes to narrow their attention to focus on ­task-​­relevant
cues and process that information more efficiently (­Lee et al., 2014; Schlader et al., 2015;
Simmons, Saxby, McGlone, & Jones, 2008). Whereas when arousal is too low, the focus
of the athlete may be too broad, taking in too many stimuli and reducing their ability to
process and act quickly enough. Similarly, if arousal is too high, and attention narrows
too much, then an athlete may miss task relevant information (­Gaoua, Racinais, Gran-
tham, & El Massioui, 2011; Liu et al., 2013; Racinais, Gaoua, & Grantham, 2008). Practi-
cally speaking, this may be the difference between a pass being completed or intercepted
by a defender. Therefore, due to the influence of various domains of cognition on the
overall performance in sport, it is imperative to understand the effects of heat on these
domains (­Malcolm, Cooper, Folland, Tyler, & Sunderland, 2018), to provide adequate
advice for soccer players and referees competing in hot environments.
Specific domains of cognitive function have greater relevance to soccer than others.
Visual perception is a player’s ability to pick up cues in their visual field, for exam-
ple, the ability to pick up and react to a defender or ball quickly. Executive function
refers to ­h igher-​­level functioning, which requires an athlete to suppress an automatic
response to select the correct one when faced with conflicting stimuli, for example
suppressing the desire to dribble when the correct option is to pass to a teammate.
Working memory refers to the ability to store information, which is beneficial when
recalling tactical information and previous experience from within a game. Finally,
sustained attention is relevant due to the length of time required for soccer players to
produce skilful actions within a game.
56 Caroline Sunderland et al.
In further research by Malcolm (­2018), which examined s­ occer-​­specific exercise in
the heat, response times on a visual search test (­representing a player’s ability to pick
up visual cues) slowed across a match in the heat (­­Figure 4.4). Similarly, accuracy got
worse across the match in the heat, whilst improving throughout the trial in moderate
conditions (­­Figure 4.5). Bandelow et al. (­2010) also found that soccer in the heat neg-
atively influenced response times across cognitive domains. Cognition is influenced
by several factors, such as rise in core temperature, negative subjective feelings to-
wards the heat as well as substantial increases in skin temperature (­Gaoua, Grantham,

400

380

360
Response Time (ms)

340

320 Hot
Moderate
300

280

260
Pre HT FT
Time Point

­Figure 4.4 The baseline level response times for visual search.

Data are mean ± SD. Pre, prior to the match simulation; HT, half time; FT, full time. Main effect of
trial P<0.01; and trial time interaction P<0.01. Redrawn from Malcolm (2018).

106

104

102
Proportion correct (%)

100

98
Hot
96
Moderate
94

92

90
Pre HT FT
Time Point

­Figure 4.5 The proportion correct on the baseline level of the visual search test.
Data are mean ± SD. Pre, prior to the match simulation; HT, half time; FT, full time. Main effect of
trial P<0.01;main effect of time P<0.01. Trial time interaction, P<0.01. Redrawn from Malcolm (2018).
 Soccer in the heat 57
Racinais, & El Massioui, 2012; Lieberman et al., 2005; Morley et al., 2012). Negative
perceptual feeling and rises in skin temperature can detrimentally impact cognition,
in the absence of changes in core temperature, due to providing a distracting influence
on athletes and limiting their ability to process task relevant cues (­Gaoua et al., 2012;
Malcolm et al., 2018). Introducing cooling methods (­such as neck cooling), can posi-
tively influence cognition and resulting performance by improving thermal comfort,
whereas changes in core temperature require more extreme intervention such as pre-
cooling and acclimation to be altered. These interventions will be discussed in greater
detail in future sections.
The research to date examining soccer in the heat and cognitive function has em-
ployed task generic cognitive function assessments due to their reliability in repeated
measure designs, ease of use during and immediately after soccer simulations or
matches, and their extensive use in sport and physical activity research across the age
range. In contrast, ­task-​­specific measures, which may include videos of soccer players
with areas occluded or videos stopped at pertinent moments and then asking players
to decide how to react, have not been used and should be explored. Further, studying
skills during matches in the heat versus temperate conditions is warranted, but the var-
iation between matches and the limited control must be considered from the research
perspective. However, from an applied perspective, employing performance analysts
to record player skill success and d ­ ecision-​­making during matches in different climatic
conditions will provide the coach with important information about how players per-
form in the heat.

Female players
Due to the hormonal changes that occur during the menstrual cycle and with oral
contraceptive use, deep body temperature fluctuates across an approximately monthly
cycle. Thus, when playing or training in a hot environment, performance, and ther-
moregulatory responses may be at risk of being affected due to these cyclic variations
in deep body temperature.
Due to the large ­inter-​­match variation in performance, research relating to the
effects of the menstrual cycle and oral contraceptive use has focussed on l­ aboratory-​
­ ased studies. During simulated s­ occer-​­specific running in the heat (­31oC), there was
b
no difference in distance ran by unacclimatised players between the follicular and
luteal phases of the menstrual cycle, however in monophasic oral contraceptive us-
ers, distance ran was greater by 21% in the q ­ uasi-​­luteal phase (­Sunderland & Nevill,
2003). It was postulated that this related to the change in hormonal milieu observed
when in the first couple of days of starting to ­re-​­take the oral contraceptive follow-
ing the p
­ ill-​­free week. For both eumenorrheic players and those take oral contracep-
tives, there were no differences in sprint performance, heart rate or plasma lactate,
or ammonia across the menstrual cycle (­Sunderland & Nevill, 2003). To date, there is
no research relating to changes in ­soccer-​­specific performance across the menstrual
cycle in acclimatised players, and this clearly warrants further investigation.
Although there is limited research relating to heat acclimation, the data have
shown that females adapt efficiently to improve performance (­Sunderland, Morris, &
Nevill, 2008). However, compared with their male counterparts, adaptation rate has
been shown to differ (­Mee, Gibson, Doust, & Maxwell, 2015; Wickham, Wallace, &
Cheung, 2021) (­s ee Acclimation and Acclimatisation section for further details).
58 Caroline Sunderland et al.
In summary, for eumenorrheic females, the stress of the heat appears to override
any potential differences in performance across the menstrual cycle. However, in oral
contraceptive users, consideration should be given relating to the initial days following
the ­pill-​­free week. Whether menstrual cycle or oral contraceptive hormonal changes
will impact upon soccer performance in acclimatised players remains to be elucidated.
However, changes across the menstrual cycle and during different phases of oral con-
traceptive use should be considered on an individual player basis. Symptoms, whether
physical or psychological, differ, considerably between players, so this should be dis-
cussed with the players as the additional stress from playing in the heat may further
exacerbate these symptoms (­e.g., nausea and feeling flushed). A suitable individual
player strategy can then be put in place to optimise their performance.

Disability players
Since the start of the Paralympic Games in 1948, the competition has experienced
rapid growth, with over 4,000 athletes participating at the Games in Rio, Brazil, in
2016 (­International Paralympic Committee, 2016). As a result of this growth, and the
importance of preparing ­ para-​­
athletes for challenging environmental conditions,
there has been an increased pressure placed on coaches and support staff to under-
stand disability sports in the heat (­Griggs, Stephenson, Price, & ­Goosey-​­Tolfrey, 2020;
O’Brien, Lunt, Stephenson, & ­Goosey-​­Tolfrey, 2022). The physiological characteristics
of various disabilities pose a risk when exercising in a hot environment. Therefore, to
recognise and lessen the risk of heat injury in an effective manner, an increased aware-
ness and the educating of support staff is imperative for athletes who are physically
and/­or visually impaired (­Webborn, 1996).
­Para-​­athletes who suffer from spinal cord injuries may be at greater risk of heat
injury because of a loss of autonomic function (­Webborn, 2004), which also causes
problems relating to temperature regulation. The reason for this is due to a reduction
in the heat loss mechanisms and working peripheral receptors that are responsible
for sweating (­Webborn, 1996). As a result, spinal cord injury athletes may experience
complications with heat dissipation whilst exercising in hot environmental conditions.
This, however, is dependent on the severity of the injury. Generally, the worse the
injury or, the higher the level of lesion, the greater the problems are regarding temper-
ature control (­Dawson, Bridle, & Lockwood, 1994; Fitzgerald, Sedlock, & Knowlton,
1990; Petrofsky, 1992).
Another disability that poses a risk when exercising in the heat is amputation. Fol-
lowing a bilateral leg amputation, there is a reduced surface area that leads to a re-
duction in evaporative cooling during exercise in the heat. In other words, bilateral
amputees sweat and lose heat less due to a reduced surface area following their injury
(­Webborn, 1996). In addition to a reduced surface area posing problems related to
evaporative heat loss, gait asymmetry present in these individuals also cause eleva-
tions in heat production (­Ghoseiri & Safari, 2014). Another aspect of this injury that
could worsen the risks of exercising in the heat is the use of prosthetics. The effects of
friction and compression when using a prosthetic have been said to result in possible
risks to the residual limb (­Webborn, 2004). Elements, such as a rise in skin tempera-
ture, that are present when exercising in a hot environment could worsen these risks,
posing more danger for the athletes. As a result, considerations must be made regard-
ing cooling strategies for disability athletes.
 Soccer in the heat 59
Youth
Young players thermoregulate differently to their adult counterparts, having lower
sweat rates and are therefore less able to use evaporative heat loss, however, they have
an increased skin blood flow and a higher surface area to mass ratio. In addition,
young players have less experience, respond to thermal strain differently and cogni-
tively are still developing (­Falk & Dotan, 2011). These factors make them more sus-
ceptible to heat illness and injury, and therefore it is imperative that coaches, monitor
young players very closely in hot environments, providing frequent cooling and fluid
breaks, training in the cooler parts of the day and in shade, ensuring sun cream is ap-
plied, and hats are worn whenever possible.
Young players acclimatise successfully but at a slower rate than adults, so this
should be considered by increasing the period for acclimation and the number of ses-
sions completed prior to match or tournament play in the heat.

Strategies to improve performance

Acclimation and acclimatisation

Heat acclimation which takes place in an artificial environment, or acclimatisation
outside is the recommended preparation strategy prior to any soccer match or tour-
nament in the heat. This process is essential for those players who have not recently
regularly trained or competed in similar environmental conditions, specifically tem-
perature and humidity. Heat acclimation or acclimatisation involves repeated ex-
posures to heat stress which increase core and skin temperature and results in high
sweat rates. Consecutive day and intermittent day are both beneficial for performance
(­­Duvnjak-​­Zaknich, Wallman, Dawson, & Peeling, 2019). In addition, acclimatisation
can reduce the chance of h ­ eat-​­related illness.
­Short-​­term heat acclimation of ­5 –​­7 days of both intermittent running mimicking
soccer and ­steady-​­state cycling have been shown to improve performance in the heat.
The completion of four ­30-​­to 4­ 5-​­min sessions of ­soccer-​­specific running in the heat
(­30oC, 27% RH) in a 1­ 0-​­day period increased running capacity by 33% in female team
sport athletes, due to a lower rectal temperature and improved thermal comfort and
an ability to tolerate a higher end core temperature (­Sunderland et al., 2008). This heat
acclimation protocol has been shown to improve field hockey skill performance in the
heat and is, therefore, likely to help with the maintenance of soccer skill (­unpublished
observations). Similarly, five consecutive days of heat acclimation of 9­ 0-​­min cycling us-
ing the controlled hyperthermia technique (­maintaining a rectal temperature of 38.5oC)
resulted in performance improvements in repeated cycle sprinting interspersed with
intermittent running, and reduced rectal, skin, and body temperature, and heart rate
(­Garrett et al., 2019). The controlled hyperthermia method requires continuous mon-
itoring and therefore is most suited to players who can only acclimate in laboratory
conditions or those players who are rehabilitating from injury prior to a tournament in
the heat. Acclimation can take the form of passive heating through sauna use and hot
baths following training sessions in moderate conditions if players don’t have access to
environmental chambers (­Zurawlew, Mee, & Walsh, 2019).
Recently, researchers have examined how players acclimatise to the heat prior to in-
ternational tournaments providing evidence of its efficacy in elite players. International
60 Caroline Sunderland et al.
female players completed 6 days of heat acclimatisation (­34.5oC), which compromised
of their normal soccer training prior to the World Cup in France. Core temperature,
via ingestible telemetric pills, was monitored to ensure that it was maintained >38.5oC
throughout the acclimatisation sessions. The acclimatisation induced thermoregula-
tory and cardiovascular benefits that lasted for at least 2 weeks and enhanced perfor-
mance. Both male and female players benefit from heat acclimatisation, however, there
is evidence they adapt at different rates. Mee and colleagues (­2015) demonstrated that
after 5 days of heat acclimation, rectal temperature and heart rate were decreased in
men and not women, whereas sweat rate increased in females and not males. Follow-
ing a further 5 days heat acclimation, rectal temperature and heart rate decreased for
the females but remained unchanged in the males, for whom sweat rate did increase.
This difference between the sexes may relate to differences in the thermal load experi-
enced by males and females during acclimation (­Wickham et al., 2021).
In summary, heat acclimation and acclimatisation should be specific to the envi-
ronmental conditions where the players are competing as well as being ­soccer-​­specific.
Where possible, acclimatisation should take place so that technical as well as physical
training, in the heat can take place. This should consist of ­h igh-​­intensity ­soccer-​­specific
training drills and s­ mall-​­sided games that last 3­ 0–​­45 min for at least four sessions in
the ­7–​­10 days prior to the first match in the heat. Where acclimatisation can’t take
place, acclimation in environmental chambers will be very beneficial for physiologi-
cal adaptation and should compromise of ­h igh-​­intensity intermittent running, rather
than cycling whenever possible, as this results in a greater acclimation stimulus. For
female soccer players, you should try to complete additional acclimatisation sessions
compared with their male counterparts to maximise performance benefits. Females
could also increase the thermal load by increasing session length or completing passive
heating before or after sessions. Whether undertaking acclimatisation or acclimation,
monitor core temperature and heart rate whenever possible, watch closely for signs
of ­heat-​­related illness and ensure hydration replaces all fluid losses after sessions. If
acclimatisation occurs in sunny environments, then it is imperative to apply ­sports-​
s­ pecific sun lotion to prevent burning.

Cooling strategies

­Pre-​­cooling
During ­intermittent-​­sprint exercise completed in hot conditions, it has been reported
that ­pre-​­cooling can be beneficial at slowing the elevation in core temperature as well
as perceptual stress (­Duffield & Marino, 2007; Price, Boyd, & ­Goosey-​­Tolfrey, 2009).
Researchers tend to highlight both the physiological and performance benefits of ­pre-​
­cooling before ­intermittent-​­sprint exercise (­Duffield & Marino, 2007). For example,
­pre-​­cooling has been found to reduce core and skin temperatures during a simulated
soccer match (­Price et al., 2009). As discussed previously, elevated skin temperature
can lead to negative perceptual feelings and a distracting influence for players, whereas
elevated core temperature can result in early onset of fatigue and decreased drive to
the muscle.
Examples of p ­ re-​­cooling include muscle and torso cooling, cold water immersion
and systemic ­pre-​­cooling. In a study investigating the effects of p­ re-​­cooling on leg
muscle on intermittent sprint performance in hot, humid conditions, it was reported
 Soccer in the heat 61
that peak power output was negatively affected only when completing exercise in the
heat without p ­ re-​­cooling (­control) (­Castle et al., 2006). It was also found that heat
strain and muscle temperature were reduced when utilising a combination of local
muscle cooling through ice packs and c­ old-​­water immersion for 20 min (­Castle et al.,
2006). Internal cooling through ice slurry or cold drink ingestion (­­5–​­15oC) can also
decrease core temperature prior to exercise and increase thermal comfort, though
may result in increased heat storage through altered sweating responses (­Gibson
et al., 2020).

Cooling/­drinks breaks
In recent years, cooling/­drink breaks have been introduced when temperatures are
at least 32oC. These occur approximately m ­ id-​­way through each half and can last
between 2 and 5 min depending on league rules and regulations. These allow for the
intake of additional fluid as well as an opportunity to reduce core temperature and/­or
thermal sensation and comfort (­Chalmers et al., 2019). Researchers have demonstrated
that cooling breaks coupled with various methods of cooling (­cold water and cold tow-
els) during a simulated match reduced thermal strain in comparison to when they wer-
en’t included (­Chalmers et al., 2019). However, it was also found that no one method
was more successful at reducing core body temperature than another. During breaks,
ice slurry or cold fluids should be drunk, neck collars/­ice towels should be applied,
and fans with misting sprays can be used, with the further addition of ice vests at h
­ alf-​
t­ ime (­Gibson et al., 2020). During matches, substitutes should ensure they remain cool
through both internal and external cooling as required.
In summary, when incorporating ­pre-​­cooling or ­m id-​­match cooling strategies, it
is important to apply these techniques within training settings prior to completing
during matches. Cold water or ice slurry ingestion can be uncomfortable or cause
gastrointestinal problems for some players, menthol spray can be a skin irritant, and
ice towels placed around the neck can cause players to suffer from ‘­brain freeze’. In
addition, players will have highly variable sweat rates and core temperature responses
to matches, and therefore hydration and cooling strategies must be individualised. An
important consideration is also the ­warm-​­up period which should be modified for hot
environmental conditions to maintain a low core temperature prior to match onset.

Disability players
As mentioned above, cooling strategies have great benefits when performing intermit-
tent exercise in the heat, and a lot of research has focused on a­ ble-​­bodied athletes. As
a result, there are limited amounts of research on cooling strategies for disability ath-
letes, and in particular, a vast majority of investigations conducted focus on cooling
methods for spinal cord injury athletes as they experience both motor and neurologi-
cal difficulties (­Price, 2015). This lack of research leads to a hindrance in the develop-
ment of guidelines for athletes competing in competitions with difficult environmental
conditions, such as the Paralympic Games (­­Goosey-​­Tolfrey, Swainson, Boyd, Atkin-
son, & Tolfrey, 2008). Nevertheless, it has been found that, overall, cooling reduced
spinal cord injury athlete’s core temperature as well as thermal sensation during exer-
cise (­O’Brien et al., 2022). More specifically, ­pre-​­cooling strategies were seen to reduce
athlete’s core temperature to a greater extent in comparison to cooling during exercise,
62 Caroline Sunderland et al.
as well as the greatest benefits of cooling mainly being seen in individuals with a more
severe spinal cord injury (­O’Brien et al., 2022).
Griggs, Price, and ­Goosey-​­Tolfrey (­2015), highlighted that wearing an ice vest dur-
ing intermittent exercise led to a reduction in thermal strain and improvements in
performance in spinal cord injury athletes. The reduction witnessed in thermal strain
is beneficial as this could lead to a reduction in the psychological stress of exercising
in a hot environment (­­Goosey-​­Tolfrey et al., 2008), thus potentially improving per-
formance. It has been found that the use of an ice vest before and during exercise
increased spinal cord injury athlete’s ability to perform repeated sprints and total
exercise capacity, which was indicated through an increase in the number of sprints
completed (­Webborn, Price, Castle, & ­Goosey-​­Tolfrey, 2010).
Whilst these findings demonstrate the benefits of cooling garments on intermittent
exercise and sprint performance, the fit of these garments has been a cause for concern
within the sporting world. Many of these garments tend to be made for ­able-​­bodied
athletes, therefore, in the future, there needs to be considerations of how these gar-
ments will fit disability athletes (­Griggs et al., 2020). In addition to the future consid-
erations regarding the fit of cooling garments, more research must be conducted to aid
the direction of guidelines provided to disability athletes and their support staff. Due
to the nature of differing physiological characteristics of various disabilities, it is im-
perative that research is carried out to investigate the use of different cooling strategies
on different disabilities.

Future directions and conclusions

As the global temperature continues to rise and soccer competitions continue to be
scheduled in hot environments, it is more important than ever for care to be taken in
the planning of strategies to optimise the health and performance of athletes. Due
to the known variability in individual responses of athletes to heat stress, future
directions will look at the most appropriate means to test and monitor athletes.
Although heat tolerance testing is currently used in many elite settings, the appli-
cation of the data is limited. Coaches should endeavour to use substitutions more
strategically when competing in the heat, specifically altering strategies for athletes
more susceptible to heat stress. In line with this, due to the known effects of passive
heat stress on cognitive function (­Malcolm et al., 2018), practitioners should look at
specific interventions for substitutes to prevent them entering the pitch in a below
optimal state.
The use of telemetric pills to get live feedback on temperature status of competing
athletes may be the next step in health and performance optimisation (­Gosselin et al.,
2019). This approach will enable coaches to remove individuals who are at risk of hy-
perthermia or underperformance.
Further development of intervention strategies to improve the various aspects of
soccer performance is required. One of these, which is currently in its infancy, is the
use of ‘­cooling breaks’ (­Chalmers et al., 2019). At present, UEFA rules state that these
breaks are only allowed when pitch side temperatures reach 32°C, at which point a
­90-​­s break is permitted 25 min into each half. Research must be done to assess the
efficacy of the current strategy in promoting the health and performance of athletes,
and improvements must be researched and implemented.
 Soccer in the heat 63
In conclusion, soccer performance in hot environmental conditions is impaired,
both in terms of physical and cognitive performance. This performance decrease
can be reduced by the completion of s­ occer-​­specific acclimation or acclimatisation
prior to competing in heat, and this should be tailored specifically to the needs of
the playing group as well as the individual. On match days, acute cooling strate-
gies should be applied before and during matches, and these should be practised
during the acclimation period to determine player tolerance and response. During
recovery, fluid and electrolyte replacement should be closely monitored, and this
is particularly important when matches are in close proximity. Whether training
or playing matches in hot environmental conditions, players’ heart rates and core
temperatures should be monitored whenever possible, along with signs of heat
illness.

References
Aldous, J. W., Chrismas, B. C., Akubat, I., Dascombe, B., Abt, G., & Taylor, L. (­2015). Hot and
hypoxic environments inhibit simulated soccer performance and exacerbate performance
decrements when combined. Front Physiol, 6, 421. doi:10.3389/­fphys.2015.00421
Bandelow, S., Maughan, R., Shirreffs, S., Ozgunen, K., Kurdak, S., Ersoz, G., ... Dvorak, J. (­2010).
The effects of exercise, heat, cooling and rehydration strategies on cognitive function in foot-
ball players. Scand J Med Sci Sports, 20(­Suppl 3), ­148–​­160. doi:10.1111/­j.­1600–​­0838.2010.01220.x
Castle, P. C., Macdonald, A. L., Philp, A., Webborn, A., Watt, P. W., & Maxwell, N. S. (­2006).
Precooling leg muscle improves intermittent sprint exercise performance in hot, humid con-
ditions. J Appl Physiol, 100(­4), ­1377–​­1384.
Chalmers, S., Siegler, J., Lovell, R., Lynch, G., Gregson, W., Marshall, P., & Jay, O. (­2019). Brief
­in-​­play cooling breaks reduce thermal strain during football in hot conditions. J Sci Med
Sport, 22(­8), ­912–​­917. doi:10.1016/­j.jsams.2019.04.009
Chodor, W., Chmura, P., Chmura, J., Andrzejewski, M., Jowko, E., Buraczewski, T., ... Kone-
fal, M. (­2021). Impact of climatic conditions projected at the World Cup in Qatar 2022 on
repeated maximal efforts in soccer players. Peer J, 9, e12658. doi:10.7717/­p eerj.12658
Dawson, B., Bridle, J., & Lockwood, R. J. (­1994). Thermoregulation of paraplegic and able
bodied men during prolonged exercise in hot and cool climates. Paraplegia, 32(­12), ­860–​­870.
doi:10.1038/­sc.1994.132
Duffield, R., Coutts, A. J., & Quinn, J. (­2009). Core temperature responses and match running
performance during ­i ntermittent-​­sprint exercise competition in warm conditions. J Strength
Cond Res, 23(­4), ­1238–​­1244. doi:10.1519/­JSC.0b013e318194e0b1
Duffield, R., & Marino, F. E. (­ 2007). Effects of ­
pre-​­
cooling procedures on ­ i ntermittent-​
sprint exercise performance in warm conditions. Eur J Appl Physiol, 100(­6), ­727–​­735.
­
doi:10.1007/­­s00421-­​­­0 07-­​­­0468-​­x
­Duvnjak-​­Zaknich, D. M., Wallman, K. E., Dawson, B. T., & Peeling, P. (­2019). Continuous and
intermittent heat acclimation and decay in team sport athletes. Eur J Sport Sci, 19(­3), ­295–​
­304. doi:10.1080/­17461391.2018.1512653
Falk, B., & Dotan, R. (­2011). Temperature regulation and elite young athletes. Med Sport Sci,
56, ­126–​­149. doi:10.1159/­0 00320645
Figueira, B., Goncalves, B., Masiulis, N., & Sampaio, J. (­2018). Exploring how playing football
with different age groups affects tactical behaviour and physical performance. Biol Sport,
35(­2), ­145–​­153. doi:10.5114/­biolsport.2018.71603
Fitzgerald, P. I., Sedlock, D. A., & Knowlton, R. G. (­1990). Circulatory and thermal adjust-
ments to prolonged exercise in paraplegic women. Med Sci Sports Exerc, 22(­5), ­629–​­635.
doi:10.1249/­­0 0005768–­​­­199010000-​­0 0014
64 Caroline Sunderland et al.
Gaoua, N., Grantham, J., Racinais, S., & El Massioui, F. (­2012). Sensory displeasure reduces
complex cognitive performance in the heat. J Environ Psychol, 32(­2), ­158–​­163. doi:10.1016/­j.
jenvp.2012.01.002
Gaoua, N., Racinais, S., Grantham, J., & El Massioui, F. (­2011). Alterations in cognitive per-
formance during passive hyperthermia are task dependent. Int J Hyperthermia, 27(­1), ­1–​­9. do
i:10.3109/­02656736.2010.516305
Garrett, A. T., Dodd, E., Biddlecombe, V., G ­ leadall-​­Siddall, D., Burke, R., Shaw, J., ... Gritt, J.
(­2019). Effectiveness of ­short-​­term heat acclimation on intermittent sprint performance with
moderately trained females controlling for menstrual cycle phase. Front Physiol, 10, 1458.
doi:10.3389/­fphys.2019.01458
Ghoseiri, K., & Safari, M. R. (­2014). Prevalence of heat and perspiration discomfort inside pros-
theses: literature review. J Rehabil Res Dev, 51(­6), ­855–​­868. doi:10.1682/­JRRD.2013.06.0133
Gibson, O. R., James, C. A., Mee, J. A., Willmott, A. G. B., Turner, G., Hayes, M., & Maxwell,
N. S. (­2020). Heat alleviation strategies for athletic performance: a review and practitioner
guidelines. Temperature (­Austin), 7(­1), ­3 –​­36. doi:10.1080/­23328940.2019.1666624
­Goosey-​­Tolfrey, V., Swainson, M., Boyd, C., Atkinson, G., & Tolfrey, K. (­2008). The effective-
ness of hand cooling at reducing e­ xercise-​­induced hyperthermia and improving d ­ istance-​
­race performance in wheelchair and ­able-​­bodied athletes. J Appl Physiol (­1985), 105(­1),
­37–​­43. doi:10.1152/­japplphysiol.01084.2007
Gosselin, J., Beliveau, J., Hamel, M., Casa, D., Hosokawa, Y., Morais, J. A., & Goulet, E. D. B.
(­2019). Wireless measurement of rectal temperature during exercise: comparing an ingestible
thermometric telemetric pill used as a suppository against a conventional rectal probe. J
Therm Biol, 83, ­112–​­118. doi:10.1016/­j.jtherbio.2019.05.010
Griggs, K. E., Price, M. J., & ­Goosey-​­Tolfrey, V. L. (­2015). Cooling athletes with a spinal cord
injury. Sports Med, 45(­1), ­9 –​­21. doi:10.1007/­­s40279-­​­­014-­​­­0241–​­3
Griggs, K. E., Stephenson, B. T., Price, M. J., & ­Goosey-​­Tolfrey, V. L. (­2020). ­Heat-​­related is-
sues and practical applications for paralympic athletes at Tokyo 2020. Temperature (­Austin),
7(­1), ­37–​­57. doi:10.1080/­23328940.2019.1617030
International Paralympic Committee. (­2016). Rio 2016 paralympic games. Retrieved from
https://­w ww.paralympic.org/­­r io-​­2016. Accessed 2/3/22.
Kirkendall, D. T. (­1993). Effects of nutrition on performance in soccer. Med Sci Sports Exerc,
25(­12), ­1370–​­1374.
Lee, J. K., Koh, A. C., Koh, S. X., Liu, G. J., Nio, A. Q., & Fan, P. W. (­2014). Neck cooling and
cognitive performance following ­exercise-​­induced hyperthermia. Eur J Appl Physiol, 114(­2),
­375–​­384. doi:10.1007/­­s00421-­​­­013-­​­­2774-​­9
Lieberman, H. R., Bathalon, G. P., Falco, C. M., Kramer, F. M., Morgan, C. A., 3rd, & Niro,
P. (­2005). Severe decrements in cognition function and mood induced by sleep loss, heat,
dehydration, and undernutrition during simulated combat. Biol Psychiatry, 57(­4), ­422–​­429.
doi:10.1016/­j.biopsych.2004.11.014
Liu, K., Sun, G., Li, B., Jiang, Q., Yang, X., Li, M., ... Liu, Y. (­2013). The impact of passive
hyperthermia on human attention networks: an fMRI study. Behav Brain Res, 243, ­220–​­230.
doi:10.1016/­j.bbr.2013.01.013
Malcolm, R. (­2018). The influence of intermittent exercise and heat exposure on neuromuscular
and cognitive function. (­PhD), Nottingham Trent University, UK.
Malcolm, R. A., Cooper, S., Folland, J. P., Tyler, C. J., & Sunderland, C. (­ 2018). Pas-
sive Heat Exposure Alters Perception and Executive Function. Front Physiol, 9, 585.
doi:10.3389/­fphys.2018.00585
Maxwell, N. S., Aitchison, T. C., & Nimmo, M. A. (­1996). The effect of climatic heat stress on
intermittent supramaximal running performance in humans. Exper Physiol, 81(­5), ­833–​­845.
Mee, J. A., Gibson, O. R., Doust, J., & Maxwell, N. S. (­2015). A comparison of males and
females’ temporal patterning to ­short-​­and l­ong-​­term heat acclimation. Scand J Med Sci
Sports, 25(­Suppl 1), ­250–​­258. doi:10.1111/­sms.12417
 Soccer in the heat 65
Mohr, M., Nybo, L., Grantham, J., & Racinais, S. (­2012). Physiological responses and physi-
cal performance during football in the heat. PLoS ONE, 7(­6), e39202. doi:10.1371/­journal.
pone.0039202
Morley, J., Beauchamp, G., Suyama, J., Guyette, F. X., Reis, S. E., Callaway, C. W., & Hostler,
D. (­2012). Cognitive function following treadmill exercise in thermal protective clothing. Eur
J Appl Physiol, 112(­5), ­1733–​­1740. doi:10.1007/­­s00421-­​­­011-­​­­2144-​­4
Nybo, L., Rasmussen, P., & Sawka, M. N. (­2014). Performance in the ­heat-​­physiological factors
of importance for ­hyperthermia-​­induced fatigue. Compr Physiol, 4(­2), ­657–​­689. doi:10.1002/­
cphy.c130012
O’Brien, T. J., Lunt, K. M., Stephenson, B. T., & ­Goosey-​­Tolfrey, V. L. (­2022). The effect of ­pre-​
­cooling or ­p er-​­cooling in athletes with a spinal cord injury: a systematic review and ­meta-​
­analysis. J Sci Med Sport. 25(7), 606–614. doi:10.1016/­j.jsams.2022.02.005
Periard, J. D., Racinais, S., Knez, W. L., Herrera, C. P., Christian, R. J., & Girard, O. (­2014).
Thermal, physiological and perceptual strain mediate alterations in m ­ atch-​­play tennis under
heat stress. Br J Sports Med, 48(­Suppl 1), ­i32–​­i38. doi:10.1136/­­bjsports-­​­­2013–​­093063
Petrofsky, J. S. (­1992). Thermoregulatory stress during rest and exercise in heat in patients with a
spinal cord injury. Eur J Appl Physiol Occup Physiol, 64(­6), ­503–​­507. doi:10.1007/­BF00843758
Price, M. J. (­2015). Preparation of paralympic athletes; environmental concerns and heat accli-
mation. Front Physiol, 6, 415. doi:10.3389/­fphys.2015.00415
Price, M. J., Boyd, C., & G ­ oosey-​­Tolfrey, V. L. (­2009). The physiological effects of p ­ re-​­event and
midevent cooling during intermittent running in the heat in elite female soccer players. Appl
Physiol Nutr Metab, 34(­5), ­942–​­949. doi:10.1139/­­H09–​­078
Racinais, S., Gaoua, N., & Grantham, J. (­2008). Hyperthermia impairs ­short-​­term mem-
ory and peripheral motor drive transmission. J Physiol, 586(­19), ­4751–​­4762. doi:10.1113/
­jphysiol.2008.157420
Rösch, D., Hodgson, R., Peterson, L., G ­ raf-​­Baumann, T., Junge, A., Chomiak, J., & Dvorak, J.
(­2000). Assessment and evaluation of football performance. Amer J Sports Medi, 28(5 S29–S39).
Sawka, M. N., Burke, L. M., Eichner, E. R., Maughan, R. J., Montain, S. J., & Stachenfeld, N.
S. (­2007). American college of sports medicine position stand: exercise and fluid replacement.
Med Sci Sports Exerc, 39(­2), ­377–​­390. doi:10.1249/­mss.0b013e31802ca597
Schlader, Z. J., Gagnon, D., Adams, A., Rivas, E., Cullum, C. M., & Crandall, C. G. (­2015).
Cognitive and perceptual responses during passive heat stress in younger and older adults.
Am J Physiol Regul Integr Comp Physiol, 308(­10), ­R847–​­854. doi:10.1152/­ajpregu.00010.2015
Schmitt, J. A., Benton, D., & Kallus, K. W. (­2005). General methodological considerations for
the assessment of nutritional influences on human cognitive functions. Eur J Nutr, 44(­8),
­459– ​­464. doi:10.1007/­­s00394-­​­­0 05-­​­­0585-​­4
Shirreffs, S. M., Sawka, M. N., & Stone, M. (­2006). Water and electrolyte needs for football
training and ­match-​­play. J Sports Sci, 24(­7), ­699–​­707.
Simmons, S. E., Saxby, B. K., McGlone, F. P., & Jones, D. A. (­2008). The effect of passive heat-
ing and head cooling on perception, cardiovascular function and cognitive performance in
the heat. Eur J Appl Physiol, 104(­2), ­271–​­280. doi:10.1007/­­s00421-­​­­0 08-­​­­0677-​­y
Slattery, K., & Coutts, A. J. (­2019). The application of heat stress to team sports: football/­soccer,
Australian football and rugby. In J. D. Periard & S. Racinais (­Eds.), Heat Stress in Sport and
Exercise: Thermophysiology of Health and Performance (­p­­p. ­181–​­202). Switzerland: Springer.
Sunderland, C., Morris, J. G., & Nevill, M. E. (­2008). A heat acclimation protocol for team
sports. Br J Sports Med, 42(­5), ­327–​­333. doi:10.1136/­bjsm.2007.034207
Sunderland, C., & Nevill, M. (­2003). Effect of the menstrual cycle on performance of inter-
mittent, ­h igh-​­intensity shuttle running in a hot environment. Eur J Appl Physiol, 88(­­4 –​­5),
­345–​­352.
Webborn, A. D. J. (­1996). H ­ eat-​­related problems for the Paralympic Games, Atlanta 1996. Br J
Ther Rehab, 3(­8), ­429–​­435.
Webborn, N. (­2004). Sport and disability. Br Med J, 12(­329), 0407275.
66 Caroline Sunderland et al.
Webborn, N., Price, M. J., Castle, P., & G ­ oosey-​­Tolfrey, V. L. (­2010). Cooling strategies improve
intermittent sprint performance in the heat of athletes with tetraplegia. Br J Sports Med,
44(­6), ­455–​­460. doi:10.1136/­bjsm.2007.043687
Wickham, K. A., Wallace, P. J., & Cheung, S. S. (­2021). Sex differences in the physiological ad-
aptations to heat acclimation: a ­state-­​­­of-­​­­the-​­art review. Eur J Appl Physiol, 121(­2), ­353–​­367.
doi:10.1007/­­s00421-­​­­020-­​­­04550-​­y
Zurawlew, M. J., Mee, J. A., & Walsh, N. P. (­2019). ­Post-​­exercise hot water immersion elicits
heat acclimation adaptations that are retained for at least two weeks. Front Physiol, 10, 1080.
doi:10.3389/­fphys.2019.01080
5 Nutrition for match play and training
James P. Morton, Liam Anderson, Hannah Sheridan
and Graeme L. Close

Introduction
The importance of nutrition is now widely recognised by professional soccer play-
ers, support staff, and coaches. In 2021, UEFA published an expert group statement
on nutrition in elite football (­Collins et al., 2021). A specific call was made for clubs
to adopt an integrated and ­evidence-​­based nutrition support programme that pos-
itively affects the performance, health, and w ­ ell-​­being of players (­Wenger, 2021). In
the coming decade, it is likely that professional soccer clubs worldwide will employ
accredited sports nutritionists and dieticians on a ­full-​­time basis, with the remit of
delivering an ­evidence-​­based nutrition service to adult and academy soccer players.
The primary focus of the performance nutritionist should be to formulate nutri-
tional strategies that ensure that players’ daily energy requirements are being met by
sufficient energy and macronutrient intake. Using the gold standard technique of dou-
bly labelled water, the energy expenditures of adult players have been quantified as
­40–​­60 kcal kg−1 f­at-​­free mass (­FFM), whereas players undergoing growth and mat-
uration tend to exhibit higher relative energy expenditures of ­60–​­80 kcal kg−1 FFM
(­see ­Figure 5.1). In accordance with changes in loading patterns as well as individual
player training objectives, a player’s nutritional requirements are not static and likely
change throughout the ­m icro-​­, m ­ eso-​­, and ­macro-​­cycles. For this reason, the concept
of nutritional periodisation is gaining increased popularity amongst academics and
practitioners (­Stellingwerff et al., 2019; Anderson et al., 2022).
In this chapter, we provide an overview of the scientific basis of performance nutri-
tion in terms of the key macronutrient (­i.e., carbohydrates (­CHOs) and protein), mi-
cronutrient (­i.e., iron, vitamin D, and calcium), and fluid requirements for professional
players. Additionally, we discuss nutritional considerations for female and adolescent
players before outlining some ­evidence-​­based ergogenic aids (­i.e., caffeine, creatine,
­beta-​­alanine, and nitrate) that may enhance aspects of physical performance. We close
by offering critical reflections from applied practice.

Carbohydrate (­CHO) requirements

The importance of CHO and muscle glycogen availability for ­soccer-​­specific physical
performance was recognised in the 1970s (­Saltin, 1973). It was demonstrated that com-
mencing match play with low versus high muscle glycogen (<200 versus >400 mmol kg−1
dw) reduced the total distance covered by 20% (­9.7 km versus 12 km, respectively). Krus-
trup et al. (­2006) observed that match play decreases muscle glycogen by approximately

DOI: 10.4324/9781003148418-6
68 James P. Morton et al.

­Figure 5.1 The energy expenditure of elite soccer players, as assessed using the doubly
labelled water method. Data presented in panels A and B represent male adult
and adolescent players from the English Premier League (­EPL) and are re-
drawn from Anderson et al. (­2017a, 2018, 2019) and Hannon et al. (­2021). Adult
female players are representative of international standard (­Morehen et al.,
2022). Data presented in panels C and D represent adult male players from the
Dutch Premier League (­data redrawn from Brinkmans et al., 2019).

50%, with ­pre-​­game values decreasing from 449 ± 23 mmol kg−1 dw to 225 ± 23 mmol
kg−1 dw immediately after match play. Although ­post-​­game glycogen values suggest
sufficient availability to continue exercising, analysis of individual muscle fibre types
revealed that 50% of fibres are classified as empty or almost empty. This pattern of de-
pletion or near depletion was evident in type IIa and IIx fibres, the fibres responsible for
sprinting and ­high-​­intensity activity. As such, glycogen depletion is cited as a contrib-
uting factor for the progressive reduction in ­high-​­intensity running and sprinting that
occurs throughout the course of a game (­Mohr et al., 2003). For this reason, CHO is
considered the most important macronutrient to promote s­ occer-​­specific physical per-
formance. An overview of CHO recommendations is presented in ­Table 5.1.
­Table 5.1 A n overview of CHO recommendations for soccer match play and training

Scenario Nutritional and physiological objectives Suggested CHO Practical considerations

range

CHO recommendations for match play

­MD-​­1 • To facilitate muscle glycogen storage ­6 –​­8 g kg−1 BM Emphasise ­low-​­fibre foods that are moderate to high
glycaemic in nature so as to promote digestion, absorption,
and glycogen storage. ­CHO-​­containing fluids and snacks
are a practical approach to achieving daily CHO intakes.
Breakfast/­­pre-​­match • To facilitate liver and muscle ­1–​­3 g kg−1 BM Emphasise ­low-​­fibre foods that are moderate to high
meal glycogen storage glycaemic in nature so as to promote digestion, absorption,
and glycogen storage. ­CHO-​­containing fluids and snacks
are a practical approach to achieving CHO intakes at this
time.
­In-​­game • To maintain plasma glucose ­30–​­60 g h−1 Total CHO intake for a 9­ 0–​­95 min match may equate to 6­ 0–​
concentration ­120 g. Consider distributing CHO intake in equal 2­ 0–​­30 g
• To reduce liver glycogen utilization doses before the ­warm-​­up, end of ­warm-​­up, ­half-​­time, and
• To maintain ­whole-​­body rates of ­m id-​­second half. Consider using a combination of isotonic
CHO oxidation gels and fluids to achieve these targets. Practice and refine
each player’s individual strategy during training.
­Post-​­game • To facilitate muscle and liver 1.2 g kg−1 h−1 Emphasise l­ow-​­fibre foods and fluids that are highly
glycogen resynthesis for ­3 –​­4 h glycaemic in nature so as to promote digestion, absorption,
and s­ hort-​­term glycogen storage. The provision of fructose
may also promote liver glycogen storage.
Daily CHO recommendations for training
­Pre-​­season training • Increase aerobic and anaerobic ­4 –​­8 g kg−1 BM Suggested range accommodates likely variations in loads
fitness (­e.g., potential twice per day sessions, recovery days) as
• Increase/­maximise strength, speed, well as individual training goals (­e.g., manipulation of
power for performance, and injury body composition to accommodate weight loss and fat loss
prevention or weight gain and lean mass gain). For example, twice per
• Increase lean mass/­reduce fat mass day training structures would likely require higher CHO
intakes (­e.g., ­6 –​­8 g kg−1 BM/­day) whereas lower absolute
intakes may be required where players are aiming for body
fat loss or training intensity and duration are reduced (­e.g.,
Nutrition for match play and training

­4 –​­6 g kg−1 BM/­day).

69

(Continued)
 70

Scenario Nutritional and physiological objectives Suggested CHO Practical considerations

range

­In-​­season training • Maintain (­or increase) aerobic and ­3 –​­8 g kg−1 BM Suggested range accommodates likely variations in loads
James P. Morton et al.

(­one game per week) anaerobic fitness across the ­m icro-​­cycle (­e.g., low load days and ­MD-​­1 CHO
• Maintain (­or increase) strength, loading protocols) as well as individual training goals (­e.g.,
power, and speed manipulation of body composition). For example, ­MD-​­1
• Maintain (­or increase) lean body and MD+1 would require higher CHO intakes (­e.g., ­6 –​­8
mass g kg−1 BM/­day) whereas lower absolute intakes may be
required on other days of the week (­e.g., 3­ –​­6 g kg−1 BM/­
day) depending on training intensity, duration, and ­player-​
­specific goals.
­In-​­season training • Restore muscle function as quickly ­6 –​­8 g kg−1 BM Suggested range accommodates the requirement to replenish
(­congested fixture as possible muscle glycogen stores in the ­48–​­72 h period between
periods) • Promote glycogen resynthesis games. During this time, it is suggested that players
• Rehydration consistently consume CHO within this range so as to
• Alleviate mental fatigue promote glycogen availability.
­Off-​­season training • Minimise the loss of aerobic and <4 g kg−1 BM Suggested intake accommodates the cessation of normal
anaerobic capacity training loads, to avoid gains in fat mass. Note, for players
• Minimise decrements in strength, who may be undergoing higher training loads (­e.g., ­off-​
power, and speed ­season training programmes) CHO intake should be
• Minimise decreases in lean mass increased accordingly.
and increases in fat mass
 Nutrition for match play and training 71
CHO requirements on match day minus 1 (­­MD-​­1)
In accordance with the role of muscle glycogen in promoting h ­ igh-​­intensity intermit-
tent exercise performance (­Saltin, 1973; Bangsbo et al., 1992; Balsom et al., 1999), the
major goal of nutritional interventions in the day prior to the game (­often referred to
­MD-​­1) should be to ensure sufficient ­pre-​­game muscle and liver glycogen stores. Pro-
fessional players are likely to achieve high glycogen stores with as little as ­24–​­36 h of a
­CHO-​­rich diet (­Bussau et al., 2002) providing that training intensity and duration are
significantly reduced on M ­ D-​­1 (­Anderson et al., 2015). To help promote muscle gly-
cogen storage, it is recommended players consume larger portion sizes and frequency
of high glycaemic index foods and drinks (­Burke et al., 1993), where daily intakes
should at least equate to 6–​­8 g.kg−1 BM. It is noteworthy, however, that professional
players from the English Premier League (­EPL) are reported to consume as little as 4
g.kg−1 BM on ­MD-​­1, values that may reduce the total distance covered on match day
when compared with 8 g.kg−1 (­Souglis et al., 2013). Further research is required to
verify the glycogen cost of match play in elite professional players and the associated
effects of muscle glycogen availability on physical and technical performance during
match play.

CHO requirements for the ­pre-​­match meal

In contrast to increasing muscle glycogen storage, the p ­ re-​­match meal is important for
augmenting liver glycogen storage, a goal that becomes particularly relevant for late
morning or l­unch-​­time ­kick-​­offs (Nicholas et al. 1995 and Foskett et al. 2008). Liver
glycogen may be depleted by as much as 50% after an overnight fast and may not fully
recover until early evening, depending on the frequency and dose of CHO consumed
(­Iwayma et al., 2020). Although the ergogenic effects of ­pre-​­exercise CHO availability on
endurance performance are documented, the topic has been largely ­under-​­researched
in team sport athletes. Nonetheless, research from academy EPL soccer demonstrates
improved dribbling performance during the second half of a ­90-​­min soccer match play
simulation when a breakfast containing 80 g versus 40 g of CHO was consumed (­Briggs
et al., 2017). It is recommended that this meal be consumed approximately 3 h before
­kick-​­off and contains at least ­1–​­3 g.kg−1 BM. Professional players from the EPL have
been reported to consume CHO intakes equating to 1­ –​­1.5 g.kg−1 BM in the p ­ re-​­match
meal, values that could be s­ ub-​­optimal for performance when considered with insuffi-
cient CHO intakes on ­MD-​­1 (­Anderson et al., 2017a).

­In-​­game CHO requirements

There is sufficient evidence to demonstrate that CHO feeding during exercise is likely
to improve elements of ­match-​­day performance (­Baker et al., 2015; Russell & Kingsley,
2014) when fed at a rate of 3­ 0–​­60 g h−1. Such ingestion rates have been shown to im-
prove physical aspects of performance such as total distance (­­Rodriguez-​­Giustiniani
et al., 2019) and sprint distance (­Harper et al., 2017) covered as well as the technical
actions of passing (­Currell et al., 2009), dribbling (­Currell et al., 2009), and shooting
(­Russell et al., 2012). When considering the duration of the ­warm-​­up (­e.g., ­20–​­30 min)
and match play itself (­e.g., ­90–​­95 min), this ingestion rate is likely to correspond to an
absolute dose of CHO equating to 6­ 0–​­120 g. We suggest that players may benefit from
72 James P. Morton et al.
CHO intake at the beginning (­e.g., 2­ 0–​­30 g) and end of the w ­ arm-​­up period (­­20–​­30 g) as
well as the ­half-​­time period (­­30–​­40 g) and if possible, during the second half (­­20–​­30 g).
We acknowledge, however, that larger boluses of 30 g before the match itself and at
­half-​­time may facilitate performance (­Harper et al., 2017). The provision of CHO gels,
as opposed to fluids, may prove advantageous owing to the flexibility of achieving
CHO targets in those instances where players may not tolerate or require such large
volumes of fluid from sports drinks. Like ­MD-​­1 and p ­ re-​­match meal, we observed that
professional players from the EPL do not readily achieve ­in-​­game CHO guidelines
(­Anderson et al., 2017a), with most players consuming <30 g h−1.

­Post-​­game CHO requirements

In relation to acute muscle glycogen ­re-​­synthesis, the consensus is that consuming
1.2 g.kg−1 h−1 of high glycaemic CHO for 3­ –​­4 h is optimal to facilitate ­short-​­term
glycogen ­re-​­synthesis (­Burke et al., 2016). P ­ ost-​­match feeding should begin immedi-
ately after match play (­i.e., in the changing room) as this is when the muscle is most
receptive to glucose uptake and the enzymes responsible for glycogen synthesis are
most active (­Ivy et al., 1988). P­ ost-​­match intake of CHO has also been identified as
an area where players may not adhere to best practice guidelines, especially in recov-
ery from evening games. For example, in recovery from a match commenced at 8:15
pm, EPL players reported consuming <1 g.kg−1 h−1 in the initial 2­ -​­h recovery period
whereas CHO intake in recovery from a 4:15 pm k ­ ick-​­off increased to 1­ –​­1.5 g.kg−1
−1
h (­A nderson et al., 2017b). Such differences between ­k ick-​­off times may be because
players do not feel like eating or drinking after ­late-​­night games and/­or the logistical
challenges of ensuring food availability, especially where recovery corresponds with
­late-​­n ight travel schedules.
Given the time course required to fully replenish muscle glycogen (­i.e., 2­ 4–​­72 h),
there is a requirement to consume adequate CHO on the day(­s) after the match, often
referred to as MD+1. In the previously cited study, the EPL players were required to
compete in another competitive game 72 h later and yet, daily CHO intake in the 4­ 8-​­h
period between games was only 4 g.kg−1 (­Anderson et al., 2017a). These intakes are
considerably less than the range of ­6 –​­9 g.kg−1 that has been documented to facilitate
glycogen r­e-​­synthesis in a cohort of Danish players within ­2 –​­3 days of match play
(­K rustrup et al., 2011; Gunnarsson et al., 2013). Nonetheless, while recovery of glyco-
gen appeared complete when assessed in whole muscle homogenate and type I fibres
at 48 h ­post-​­match play, complete restoration of type II fibres was still not apparent
(­Gunnarrson et al., 2013). Such data clearly highlight the need for high daily CHO
intakes in recovery from match play, especially in those situations of two and three
games per week ­m icro-​­cycles.

CHO requirements for training

Based on different physical loads associated with training and match play (­see T
­ able 5.2),
daily CHO and ­within-​­day CHO distribution patterns should differ accordingly. Profes-
sional players report consuming less CHO on training days versus match days. Brink-
mans et al. (­2019) reported daily CHO intakes of <4 g.kg−1 in professional players from
the Dutch Premier League on training and rest days. Additionally, we observed compara-
ble CHO intakes of 4 g.kg−1 in EPL players during training days (­Anderson et al., 2017a).
­Table 5.2 A suggested practical model of the “­fuel for the work required” CHO periodisation paradigm as applied to professional soccer players
during a ­one-­​­­game-­​­­per-​­week schedule with match day on Saturday. Representative loads are taken from Anderson et al. (­2015)

Typical external load Breakfast During training Lunch Snack(­s) Dinner

Monday (­MD+2) No training Medium CHO No training Medium CHO Medium CHO Medium CHO
0.­5 –​­1 g kg −1 1 g kg −1 0.­5 –​­1 g kg−1 1 g kg−1
Tuesday (­­MD-​­4) Duration = ­70–​­80 min Medium CHO No CHO High CHO Medium CHO Medium CHO
TD = ~5000 m 1 g kg−1 1.­5 –​­2 g kg−1 0.­5 –​­1 g kg−1 1 g kg−1
HSR = <100 m
Wednesday (­­MD-​­3) Duration = ­80–​­90 min High CHO No CHO High CHO Medium CHO Medium CHO
TD = 6500 m 1.­5 –​­2 g kg−1 1.­5 –​­2 g kg−1 0.­5 –​­1 g kg−1 0.­5 –​­1 g kg−1
HSR = ­300–​­600 m
Thursday (­­MD-​­2) Duration = <70 min Low CHO No CHO High CHO Medium CHO Medium CHO
TD = <4500 m 0.5 g kg−1 1.­5 –​­2 g kg−1 0.­5 –​­1 g kg−1 0.­5 –​­1 g kg−1
HSR = <100 m
Friday (­­MD-​­1) Duration = <60 min High CHO High CHO High CHO High CHO High CHO
TD = <3000 m 2 g kg−1 60 g hr−1 2 g kg−1 1.5 g kg−1 2 g kg−1
HSR = <50 m
Breakfast ­Pre-​­match meal During game ­Post-​­match
Saturday (­MD) Duration = ­90–​­95 min High CHO High CHO High CHO High CHO
TD ~11 km 2 g kg−1 2 g kg−1 ­30–​­60 g hr−1 1.2 g kg hr−1 for
HSR = ~1000 m 3h
Breakfast During training Lunch Snack Dinner
Sunday (­MD+1) Recovery session High CHO High CHO High CHO High CHO High CHO
2 g kg−1 60 g hr−1 2 g kg−1 1.5 g kg−1 2 g kg−1

MD = Match day, TD = Total distance, HSR = ­High-​­speed running, CHO = Carbohydrate.

Nutrition for match play and training
73
74 James P. Morton et al.
The assessment of energy expenditure in these studies (­i.e., approximately ­3000–​­3500 kcal
d−1, equivalent to ~­47–​­55 kcal kg−1 FFM) provides a basis from which to formulate daily
CHO requirements (­Anderson et al. 2017a; Brinkmans et al. 2019). Since daily protein
recommendations range from 1.6 to 2.2 g kg−1, and that recommended fat intakes are
equivalent to 30% of total energy intake (­Collins et al., 2021), an average daily CHO intake
of ­3–​­6 g kg−1 would be sufficient to meet the daily energy requirements that encompass
the typical range in training intensity and duration associated with i­n-​­season training
schedules. When considered in combination with the requirement to promote glycogen
storage on ­MD-​­1 and MD+1, we suggest that daily CHO requirements for training should
operate on a sliding scale of ­3–​­8 g kg−1 body mass per day depending on the specific train-
ing scenario, fixture schedule, and p ­ layer-​­specific training goals (­see T
­ able 5.1).

Practical CHO periodisation strategies

In addition to simply matching energy intake to energy demands, the rationale for prac-
tical application of CHO periodisation strategies has been developed on the premise
that commencing and/­or recovering from exercise with reduced CHO availability ­up-​
r­ egulates cell signalling pathways that regulate oxidative adaptations of human skeletal
muscle. While research has largely been explored using protocols relevant to endur-
ance athletes (­see Impey et al., 2018), such adaptations may manifest in h ­ igh-​­intensity
intermittent exercise protocols. Commencing h ­ igh-​­intensity intermittent running with
reduced ­pre-​­exercise muscle glycogen (­and without provision of CHO during exercise)
augments ­training-​­induced ­up-​­regulation of oxidative enzyme activity in both the gas-
trocnemius and vastus lateralis muscle, as compared with conditions of normal muscle
glycogen and consumption of CHO during training (­Morton et al., 2009). The principle
of “­fueling for the work required” is a practical framework to adjust CHO intake ­day-­​
­­by-​­day and ­meal-­​­­by-​­meal according to the metabolic demands and training goals of the
upcoming training sessions (­Impey et al., 2018). On this basis, we provide a theoretical
overview of ­day-­​­­by-​­day and ­meal-­​­­by-​­meal CHO intakes in ­Table 5.2. In this scenario,
a ­one-­​­­game-­​­­per-​­week ­micro-​­cycle is presented, whereby daily CHO intake on training
days is equivalent to 4 g kg−1 but increased to 8 g kg−1 on ­MD-​­1, MD, and MD+1. In
accordance with the lower physical loading on training days, CHO intake is reduced at
breakfast and no CHO is consumed during training. On such days, the largest portion of
CHO is consumed in the ­post-​­training meal (­i.e., lunch) to facilitate glycogen ­re-​­synthesis
(­Ivy et al., 1988). Finally, CHO intake is reduced in the evening meal because the upcom-
ing physical load on the subsequent day does not likely require high CHO availability to
complete the desired training demands. In contrast to a ­one-­​­­game-­​­­per-​­week ­micro-​­cycle,
daily CHO intake should be increased to at least 6­ –​­8 g kg−1 during those instances where
consecutive games are interspersed with only 2­ –​­3 days of recovery. A critical discussion
of CHO periodisation for soccer is also provided by Anderson et al. (­2022).

Protein requirements
Protein does not provide a substantial contribution towards energy production during
exercise. The amino acids we obtain from dietary protein sources are used to support
whole body and muscle protein synthesis throughout the day. In this way, protein plays
an important modulatory role in remodelling of musculoskeletal and tendinous struc-
tures in response to training. Although exercise itself stimulates muscle protein synthesis,
 Nutrition for match play and training 75
when completed in the fasted state muscle protein degradation occurs such that a net
negative protein balance is present. In the presence of adequate protein feeding, however,
the combined effects of exercise and protein ingestion augment muscle protein synthesis
such that a net protein balance occurs. It is these repeated changes in protein turnover (­in
favour of protein synthesis to yield a positive protein balance) which form the molecular
basis of how skeletal muscle and related tissues adapt to the demands of training.

Daily protein requirements

A daily intake of 1.­6 –​­2.2 g kg−1 per day is recommended for endurance and strength
athletes (­Morton et al., 2018); a value twice that of the RDA for Europeans. Profes-
sional players from the EPL habitually exceed these daily targets with intakes of 2.5 g
kg−1 reported during a ­two-­​­­game-­​­­per-​­week ­m icro-​­cycle (­Anderson et al., 2017a). The
reported absolute daily protein intakes (­205 ± 30 g) are like those reported (­­150–​­200 g)
in adult professional players from the Dutch Premier League (­Bettonviel et al., 2016),
but are higher than that reported over two decades ago (Maughan, 1997) in British
professional players (­108 ± 26 g). Such differences between eras are potentially driven
by the increased practitioner, player, and coach awareness of the role of protein in fa-
cilitating training adaptations and recovery from both aerobic and strength training
(­MacNaughton et al., 2016). Additionally, the higher daily protein intakes reported
may be driven by the increased use of protein supplements, a practice that seems to be
commonplace amongst players. This is especially the case in acute recovery from train-
ing and match play where ­20–​­30 g boluses are often consumed (­Anderson et al., 2017b).

Daily protein distribution

The pattern of daily protein distribution may be important in modulating protein
synthesis. A total of 20 g boluses consumed every 3 h is superior to larger boluses
consumed less frequently, as is the case for both whole body (­Moore et al., 2012) and
muscle protein synthesis (­Areta et al., 2013). It is recommended that daily protein in-
takes be distributed across four meals each containing 0.4 g kg−1 per meal (­Collins
et al., 2021). Such a pattern of intake would readily achieve the lower end of the total
daily requirement cited above and is likely to align with traditional meal timings of
breakfast, lunch, and dinner. In relation to exercise, protein should be consumed near
the cessation of the training session or match so as to stimulate remodelling of tissues.
­Dose-​­response studies demonstrate that 30 g (­0.49 g kg−1) is optimal in stimulating
muscle protein synthesis (­­Churchward-​­Venne et al., 2020). In practice, ­post-​­exercise
ingestion of protein in the immediate recovery period is often achieved by protein sup-
plements in the form of drinks or bars. Given its higher leucine content and rapid di-
gestion, whey protein supplements are superior to casein and s­ oy-​­based formulations
for activating muscle protein synthesis (­Tang et al., 2009). Liquid forms of protein
induce a more rapid rise in plasma amino acids than solid foods and may therefore be
considered a superior strategy in the ­post-​­exercise period (­Burke et al., 2012).

Additional considerations
Given that sleep is effectively a period of prolonged fasting (­e.g., ­6 –​­10 h) which in-
duces muscle protein degradation, there is a rationale to ingest a suitable quantity of
76 James P. Morton et al.
protein prior to bed. Ingestion of 0.4 g kg−1 of protein within 1­ –​­2 h before sleep stimu-
lates muscle protein synthesis and improves overnight protein balance when compared
with no protein feeding (­Trommelen et al., 2018; Snijders et al., 2015). Consuming pro-
tein prior to sleep augments t­ raining-​­induced increases in muscle mass and strength
(­Snijders et al., 2015). Professional EPL players reported an intake of only 0.1 g kg−1
at this t­ ime-​­point (­Anderson et al., 2017b), thus highlighting an important feeding op-
portunity for those players aiming to gain and/­or maintain muscle mass. In relation
to the latter, the requirement to manipulate body composition (­i.e., reduce fat mass in
tandem with maintaining or increasing muscle mass) is often a fundamental training
objective, especially during the p ­ re-​­season period. To offset the effects of energy re-
striction on protein catabolism, increasing daily protein intake to 3 × RDA (­i.e., 2.4
g kg−1), alongside a resistance training programme, can maintain or increase muscle
mass despite a reduction in daily energy intake (­Longland et al., 2016). Increased daily
protein intake may prove beneficial in reducing muscle atrophy (­Anderson et al., 2019)
that can occur during times of prolonged injury. In such conditions, the absolute load-
ing of skeletal muscle is significantly reduced, and players are prone to reducing their
total daily energy intake in the belief that it will prevent gains in fat mass during a time
of reduced training load (­Milsom et al., 2014).

Fluid requirements

Dehydration and performance

Metabolic heat production can increase rectal and muscle temperature to >39oC dur-
ing match play (­Mohr et al., 2004). Sweat losses of 2 L have been observed during both
match play and training (­Rollo et al., 2021), even when ambient temperature is <10oC
(­Maughan et al., 2007). Dehydration >2% body mass loss reduces repeated sprint capac-
ity (­Mohr et al., 2010) as well as dribbling performance (­McGregor et al., 1999). Potential
mechanisms underpinning ­dehydration-​­induced decrements in physical and mental per-
formance include increased core temperature, cardiovascular strain, muscle glycogen
depletion, and impaired brain function (­­Gonzalez-​­Alonso, 2007). From observations
of players during training and match play, sweat loss appears to be lower in temperate
(<15oC) compared with warm environments (­­25–​­35oC) (­Kurdak et al., 2010; Rollo et al.,
2021). To compensate for the warmer conditions, players consume significantly more
fluid during training (­Rollo et al., 2021). The development of fatigue during match play
is more pronounced during high ambient temperatures (­Mohr et al., 2010). In addition
to fluid loss, sweat contains electrolytes such as sodium, chloride, potassium, calcium,
and magnesium. Loss of sodium is the most significant for athletes (­given its role in pro-
moting fluid retention) and players can lose between 2 and 3 g during training or match
play (­Kurdak et al., 2010; Maughan et al., 2007). It is, therefore, important to identify
players who are salty sweaters to develop individually tailored hydration strategies.

Practical assessment of hydration status

­ re-​­training or ­pre-​­match assessments of urine osmolality and colour provides rea-
P
sonably inexpensive and informative measures. Osmolality values <700 m Osmol kg−1
 Nutrition for match play and training 77
are suggestive of euhydration as is a urine colour that is pale yellow. Urine indices of
hydration are sensitive to changes in posture, food intake, and body water content
and for these reasons, a urine sample passed upon waking is often advised as the
criterion sample. However, values indicative of dehydration at this time (­e.g., 7:00
am) may not mean the player is dehydrated upon commencing training at 10:30 am,
assuming that appropriate fluid intake has been consumed upon waking and with
breakfast. The same can be said for match day in that samples suggestive of dehy-
dration collected prior to the p ­ re-​­match meal may not mean players are dehydrated
at ­k ick-​­off. Players should be assessed at both the former and latter ­time-​­points to
initially identify players who are causes for concern and to verify that any subse-
quent hydration strategies implemented are effective to ensure euhydration prior
to competition. Soccer players studied prior to an evening ­k ick-​­off have exhibited
­pre-​­game osmolality values >900 m Osmol kg−1 (­Maughan et al., 2007), despite the
fact that they would have had the morning and afternoon to hydrate. Such values
are indicative of 2% dehydration and effectively mean that players are commenc-
ing the game dehydrated thereby running the risk of impaired physical and mental
performance.

Fluid requirements
It is difficult to provide fixed prescriptive fluid recommendations for soccer players
due to differences in workload, heat acclimatisation, training status, and ­match-­​­­to-​
m
­ atch variations in ambient temperatures. The American College of Sports Medicine
advises fluid ingestion at a rate that limits body mass loss to <2% of p ­ re-​­exercise
values (­Thomas et al., 2016). Players should not aim to drink to gain mass during
exercise as this can lead to water intoxification, a condition known as hyponatremia
(­a serum sodium concentration <135 mmol L−1) which in extreme cases is fatal. It is
recommended that ­5 –​­7 ml kg−1 of fluid is consumed at least ­3 –​­4 h prior to the game.
Additionally, if the individual does not produce urine or the urine remains dark in
colour, a further ­3 –​­5 ml kg−1 could be consumed 2 h before ­k ick-​­off. Consumption of
sports drinks, as opposed to water, is beneficial given that they contain electrolytes
and CHO. For training days, fluid intake should be consumed upon waking (­before
travelling to training) and with breakfast, where the latter is often consumed at the
training ground.
To promote a drinking strategy which prevents weight losses >2%, players should
routinely weigh themselves nude before and after exercise to ascertain if their ha-
bitual drinking patterns are effective. Cold beverages (­10oC as opposed to 37oC or
50oC) are beneficial to attenuate the rise in body temperature during exercise (­L ee &
Shirreffs, 2007). It is important that players practice with different fluid intake strat-
egies during training so as to develop individually suited approaches which max-
imise gastric emptying, fluid absorption, and CHO delivery but yet are suited for
taste and do not cause gastrointestinal discomfort during ­match-​­play. Finally, there
is likely no need for aggressive ­re-​­hydration strategies ­post-​­training (­u nless there
is an afternoon training session and ambient temperature is high) or match play as
the normal schedule would allow for appropriate ­re-​­hydration within several hours
­post-​­exercise. Nevertheless, those players identified as salty sweaters may benefit
78 James P. Morton et al.
from the addition of sodium to drinks or foods or the provision of salty snacks so as
to promote fluid retention.

Nutritional considerations for female players

Based on current evidence (­Moore et al., 2021), it is premature to substantiate that
a female player requires specific guidelines in relation to the macronutrient require-
ments described previously. The primary focus is to ensure female players consume
sufficient energy, macronutrient, and micronutrient intake to reduce the risk of nega-
tive symptoms associated with the Female Athlete Triad or Relative Energy Deficiency
in Sport (­­RED-​­S) syndrome (­Mountjoy et al., 2014). Low energy availability (­LEA) is
one of three ­inter-​­related components of the Female Athlete Triad and is purported
to be the contributory cause of impaired menstrual function and bone health (­Loucks
et al., 2011). Energy availability (­EA) is expressed relative to FFM and is defined as
the amount of energy that is available to support body functions after subtracting the
amount of energy that is expended during exercise. In considering the ­RED-​­S model
(­Mountjoy et al., 2014), the consequence of LEA is thought to extend to multiple health
(­e.g., reduced immune function, cardiovascular function, and protein synthesis) and
performance (­e.g., reduced strength, power, and endurance), indices beyond that of
menstrual function and bone health.
When classifying values >45, ­30–​­45, and <30 kcal kg−1 FFM as optimal, reduced,
and LEA (­Loucks et al., 2011), it was recently identified that only 15% of professional
players from a Women’s Super League team were deemed optimal (­Moss et al., 2020).
It was observed that players did not adjust daily energy or CHO intake on harder
training or match days (­i.e., exercise energy expenditure >700 kcal) when compared
with lighter training (­i.e., exercise energy expenditure <400 kcal) or complete rest days.
As such, the prevalence of players presenting with LEA increased from 40% on light
training days to 70% on harder training days. In studying a cohort of adult female
players of international standard, Morehen et al. (­2022) reported that only one player
(­from a sample of 23) consumed CHO on ­MD-​­1 that was greater than 6 g kg−1 body
mass. Such data clearly highlight the necessity for practitioners to emphasise appro-
priate “­fuelling” in female players. In using the doubly labelled water technique, these
researchers also observed a relative energy expenditure (40-60 kcal kg−1 FFM) that
was comparable to male players (­Morehen et al., 2022).
Given that exercise performance may be trivially impaired in the early follicular
phase (­McNulty et al., 2020), and that negative physical symptoms are often re-
ported at the onset or during menses (­Findlay et al., 2020), specific attention should
be given to CHO availability during this phase of the cycle. This is especially rele-
vant in congested fixture schedules or intense training periods where glycogen avail-
ability may be limiting to performance. At present, practitioners should adopt an
individualised approach that considers ­player-​­specific training and match schedules
whilst considering personal symptoms associated with the menstrual cycle. Fur-
ther assessments of the energetic requirements of adult and academy female players
(­a longside prevalence of R ­ ED-​­S) is a recommended area for future research. When
assessing the efficacy of any novel nutritional strategy, researchers should also
adopt s­ occer-​­specific competition and t­ raining-​­related exercise protocols that rigor-
ously control for prior exercise, CHO/­energy intake, contraceptive use, and phase of
menstrual cycle.
 Nutrition for match play and training 79
Nutritional considerations for adolescent players
In the adolescent player, prolonged periods of insufficient energy intake can compro-
mise growth and maturation as well as affect the ability to tolerate daily loading. An
increase in resting metabolic rate (­RMR) of ~400 kcal day−1 occurs between ages 12
and 16, thus highlighting the requirement to adjust daily energy intake to support
growth and maturation (­see F ­ igure 5.2). In addition, daily total energy expenditure
(­TEE) progressively increases as players transition through the academy pathway (­see
­Figure 5.1). For example, U18 players presented with a TEE (­3586 ± 487 kcal day−1)
that was approximately 600 and 700 kcal day−1 higher than both the U15 (­3029 ± 262
kcal day−1) and U12/­13 players (­2859 ± 265 kcal day−1), respectively (­Hannon et al.,
2021). Such differences in TEE are likely due to differences in anthropometric profile,
RMR, and physical loading between squads. Some individuals (­in all age groups) have
presented a TEE that is comparable to, or exceeds that, previously reported in adult
Premier League soccer players. Clearly, the practice of nutritional periodisation and
reduced periods of energy intake (­to reduce fat mass) is not recommended for players
who are not yet fully mature. The principle of ensuring consistent daily energy, CHO,

­Figure 5.2 (­a) Resting metabolic rate (­RMR), (­b) f­at-​­free mass, (­c) fat mass, and (­d) per-
cent body fat between in adolescent male soccer players (­­U12–​­U23 age groups;
n = 99) from an English Premier League academy.
a significant difference from the U12 age group, bsignificant difference from the U13 age group,
c
significant difference from the U14 age group, dsignificant difference from the U15 age group, all
P < 0.05. Data redrawn from Hannon et al. (­2020). Black dots represent individual players.
80 James P. Morton et al.
and protein availability should be practised. From observations of academy players
who did not display any loss in body mass over a 2­ -​­week period, daily CHO, protein,
and fat intakes ranging from 5 to 8, 1.6 to 2.2, and 1.5 to 2.5 g kg−1 body mass, respec-
tively, appear appropriate to meet daily energy requirements (­Hannon et al., 2021).

Micronutrient considerations
Micronutrients (­typically classified as vitamins and minerals) are compounds that
are required in small quantities (<1 g) to maintain normal physiological function.
Although they do not directly supply energy, micronutrients play essential roles in
several metabolic pathways. Most micronutrients will be obtained comfortably in a
player’s everyday diet without the need for supplementation. However, there may be
specific situations that could contribute to a player presenting with micronutrient defi-
ciency. These include players who consciously eliminate food groups (­because of food
dislikes, allergies, or moral/­ethical and religious reasons), LEA (­may occur when play-
ers are attempting to reduce body fat or during intense training and/­or fixture sched-
ules), a lack of variety in the diet or a lack of sunlight exposure (­including constant use
of sunscreens or protective clothing).
It has been suggested that soccer players should pay specific attention to vitamin D,
calcium, and iron status (­Collins et al., 2021). Vitamin D is a unique vitamin given that
it is predominantly synthesised in the skin via sunlight exposure, with only around 10%
of our daily needs coming from the diet (­Owens et al., 2018). Given that many coun-
tries have low sunlight exposure (­especially in the winter months), it is not surprising
that players present with vitamin D deficiencies. EPL players exhibit a 50% decline in
vitamin D between August and December (­Morton et al., 2012). Inadequate vitamin
D concentrations can impair muscle function and recovery (­Owens et al., 2015) as well
as compromise immune health (­He et al., 2013). Vitamin D is assessed by measuring
serum 25(­OH)­D and whilst there is controversy as to what defines a true vitamin D de-
ficiency, it is generally accepted that <50 nmol L−1 is deficient with emerging research
suggesting that 75 nmol L−1 may be a suitable target concentration for players.
Iron is the functional component of haemoglobin and myoglobin as well as being
an essential constituent of mitochondrial enzymes. Iron deficiencies, even without
anaemia, can have major effects on aerobic performance (­DellaValle & Haas, 2011).
Although iron deficiency is common in many athletes (­Clenin et al., 2015) (­w ith a prev-
alence of 1­ 5–​­35% in female athletes and 5­ –​­11% in male athletes), the iron status of
professional soccer players at various stages of the season is not well characterised.
Iron deficiencies present as lethargy and reduce athletic performance and, like vita-
min D, are usually identified through routine blood screening. It has been suggested
that female athletes should be assessed for iron deficiency at least biannually and even
quarterly if there are any suspicions of factors that could indicate low iron status such
as LEA, irregular menses, and high training loads (­Sim et al., 2019).
Calcium status is somewhat difficult to assess since serum calcium concentration
is tightly regulated regardless of acute calcium intake. The largest store of calcium
is in skeleton, and it is this store that is utilised as an immediate supply of calcium
when dietary intake is inadequate. The consequence of this mobilisation of calcium
is demineralisation of bone tissue through the action of parathyroid hormone which
 Nutrition for match play and training 81
long term could lead to numerous health problems including stress fractures. Specific
attention should be given to those players who eliminate food sources such as dairy
products and those presenting with LEA. The function, recommended nutrient intake
(­RNI), food sources, and potential supplement strategy for vitamin D, calcium, and
iron are displayed in ­Table 5.3.

Supplement considerations
There are hundreds of commercially available supplements that are purported to im-
prove muscle strength, power, speed, and endurance as well as prevent (­and promote
recovery from) illness and injury. It is unsurprising that elite players, coaches, and
sport science staff are often overwhelmed when faced with the challenge of develop-
ing a practical and ­evidence-​­based supplement strategy that is ergogenic for soccer
match play and training. Additionally, many of the sports supplements commonly
used by professional players are commercially driven (­as opposed to ­evidence-​­based)
and based on lucrative sponsorship deals to the individual player, club, and/­or the
governing body of the professional league in question. Most importantly, the chosen
approach to supplementation should adhere to the World A ­ nti-​­Doping Association
(­WADA) code of conduct in that all supplements are free from contamination with
prohibited substances. ­Table 5.4 provides an overview of those supplements that we
consider suitable for practical use for match play and training (­for further reading, see
Collins et al., 2021).

Practitioner reflections

Critical reflections on the soccer environment

Translating the relevant science into a practical performance nutrition program should,
in principle, be a relatively straightforward process. In practice, however, there are
many cultural, organisational, financial, and political factors that occur in the ­day-­​­­to-​
d
­ ay running of a professional soccer club which greatly affect the quality and extent of
the service provided. The initial challenge is to establish sound working relationships
with the wider m ­ ulti-​­disciplinary sports science and medical team (­e.g., club doctors,
fitness and conditioning staff, and physiotherapists), club catering staff and of course,
those influential players who can act as positive role models (­e.g., team captain and sen-
ior professionals). It is common for many individuals to have prior beliefs and biases
as to what constitutes the “­best” diet for a soccer player. The performance nutritionist
will often be challenged by the unqualified opinions of others, some of which can be
greatly impacted by the “­Twitter” and “­Netflix” culture of changing rooms. Getting
everyone “­on the same page” as to the performance benefits of e­ vidence-​­based nutri-
tion is therefore an essential element of the role. Unlike traditional endurance sports
(­e.g., cycling and running), however, demonstrating a measurable impact of the perfor-
mance nutrition programme is not always easy. Commencing match play with optimal
muscle glycogen concentration may not necessarily translate to more passes completed
or games won. Rationalising the financial investment required to deliver a h ­ igh-​­quality
nutrition programme can therefore be hard to justify to those key stakeholders above
 82

­Table 5.3 A n overview of specific vitamin and minerals that have been highlighted as a potential cause for concern for soccer players (­Collins
et al., 2021), including their physiological function, recommended nutrient intake (­RNI), typical food sources, and potential supplement
strategy if required. Note that RNIs vary for different countries, and for differing ages, therefore, the numbers provided here may not be
precise for all countries and all situations
James P. Morton et al.

RNI Food sources Supplement strategy (­if required)

Male Female
Vitamin D NO DRVs because of ­sun-​­related Oily fish, eggs, and fortified Studies have suggested 2000 iU will safely correct
synthesis foods. deficiencies. Safe upper limit is 4000 iU per day.
Calcium* ­11–​­18 years ­11–​­18 years Dairy products including milk, Approximately 1350 mg of calcium consumed 90 min
(­1000 mg) (­800 mg) cheese, and yoghurt. Small prior to exercise has been shown to attenuate the
19+ years 19+ years fish with bones (­e.g., sardines), deleterious changes in bone turnover (­Haakonssen
(­700 mg) (­700 mg) beans, and broccoli. et al., 2015)
Iron ­11–​­18 years 11 18 years Red meat, liver broccoli, spinach, If a deficiency has been identified, iron supplements
(­11.3 mg) (­14.8**) fortified cereals, eggs, dried may be considered, following consultation with
­19–​­49 years ­19–​­49 years fruits, nuts, and seeds. a dietician or doctor. These supplements should
(­8.7 mg) (­14.8 mg**) be the most bioavailable forms including iron
sulphate, iron gluconate, and iron fumarate.
Routine iron supplementation without deficiency
is not recommended and can induce toxicity.

* Suggested that an athlete’s diet should contain 1500 mg per day (­Collins et al., 2021).
** Approximately 10% of females with high menstrual losses may need more iron than the RNI. These athletes should seek appropriate advice and may need to
consider iron supplements.
 Nutrition for match play and training 83
A n overview of supplements that may be ergogenic to s­occer-​­
­Table 5.4  specific physical
performance

Supplement Suggested dosing strategy Reported physiological and ergogenic

benefits

Caffeine ­2 –​­4 mg kg−1 BM at 4­ 5–​­60 min Central nervous stimulant which acts
before match play or training. as an adenosine antagonist thereby
Usually consumed in capsule, reducing perception of effort.
concentrated drink, or CHO gel Reported to improve repeated
format. May reduce sleep quality sprint performance on the Y ­ o–​­Yo
when consumed prior to night intermittent recovery test 2, agility,
games. jump performance, and passing
accuracy.
Creatine ­4 –​­5 days of loading dose of 20 g Increases the creatine stores of skeletal
(­4 × 5 g per day) followed by muscle which enhances capacity to
maintenance dose of ­3 –​­5 g daily. generate ATP through the ­ATP-​­PCr
Should be consumed with CHO system. Reported to enhance power
so as to enhance muscle creatine output during single and repeated
uptake. Usually consumed in sprints and promotes PCr resynthesis
powder format mixed with CHO between sprints. May also augment
and/­or protein beverages. increases in ­fat-​­free mass, strength,
and power when combined with
an appropriate strength training
programme.
­β-​­alanine 4 weeks of loading dose of ­3 –​­6 g per Increases carnosine stores of skeletal
day (­­3–​­6 × 1 g servings) followed muscle which acts an intracellular
by maintenance dose of 3 g per buffer to protect against the fatiguing
day. Usually consumed in capsule effects associated with metabolic
format although powder can acidosis induced by ­h igh-​­i ntensity
also be mixed with CHO and/­or exercise. Reported to improve repeated
protein beverages. Side effects sprint performance on the Y ­ o–​­Yo
often include “­tingling” of the intermittent recovery test 2 and may
skin. also improve the capacity to perform
­h igh-​­i ntensity training thus augmenting
training adaptations.
Nitrate 1 g on M
­ D-​­1 (­e.g., 2 × 500 mg Improves exercise efficiency by reducing
servings served with breakfast the oxygen cost to perform a given
and dinner) followed by 500 mg workload. Reported to improve
with ­pre-​­match meal and 250 mg repeated sprint performance on the ­Yo–​
at start of ­warm-​­up period. Often ­Yo intermittent recovery test 1 as well as
consumed in the form of beetroot 5, 10, and 20 m sprint times.
juice, concentrated drinks or gels.

and below your position in the organizational hierarchy. With the inevitable high turn-
over of club staff and players, the process of education and stakeholder management
is n
­ ever-​­ending. The ability to adapt and adopt a personalised approach when dealing
with individual players and staff (­i.e., coaching and leadership skills) is a prerequisite
for success for the applied practitioner specialising in performance nutrition.

Practical reflections on critical performance priorities

With the intense competitive and travel schedule inherent to elite soccer, the profes-
sional player is required to possess optimal body composition whilst simultaneously
84 James P. Morton et al.
adhering to best practice fuelling and recovery strategies for 10 months of the year. An
essential role of the performance nutritionist is to, therefore, ensure that players are
nutritionally prepared for match play, especially in those instances with short turn-
around (­e.g., ­48–​­72 h) between games. As such, the practical challenge of ensuring
players consume sufficient CHO intake (­w ithout the fear of consuming excessive cal-
ories) is a critical performance priority. The performance nutritionist should “­bring
this to life” by ensuring that M­ D-​­1 is accompanied by a plentiful and varied supply of
­CHO-​­rich foods, snacks, and drinks such that the boredom of mundane food offerings
does not retract from what remains the most fundamental nutrition priority. Similarly,
given the role of CHO intake in promoting ­post-​­match muscle glycogen resynthesis,
the provision of such foods in the changing room environment and when travelling
home from games (­especially after night games) is also a critical element of practice.
Where possible, it is encouraged that practitioners collect detailed and individual die-
tary intake data over the course of ­MD-​­1, MD, and MD+1.

Critical reflections on the role of the performance chef

The club catering staff play an essential role in “­activating” the performance nutrition
programme by creating a positive eating and dining environment for players. From
a practical perspective, this includes support with menu innovation, trialling of new
performance foods and service of appropriate macronutrient portions to achieve some
of the performance priorities described above. For this reason, building strong rela-
tionships with club chefs and catering personnel is perhaps one of the most critical
working relationships. This process can often be challenging in scenarios where clubs
employ ­long-​­standing chefs who may lack enthusiasm for “­p erformance” nutrition and
are resistant to change. It is now common for teams to have the luxury of travelling
to away games with their own chef. This approach helps to create a consistent din-
ing experience to that of the training ground environment and instils a sense of trust
and familiarity amongst the players and coaching staff. Away games present an ad-
ditional opportunity to work collaboratively with the performance chef by assisting
with logistical challenges of working in an unfamiliar kitchen environment as well as
assisting with food service provision on the coach home from games. The latter sce-
nario presents an opportunity to align the chef on elements of performance nutrition
by assisting with recovery in action. If the performance nutritionist is the “­architect”
of ­evidence-​­based nutritional strategies, it is the performance chef who “­builds” the
plates.

Future directions and conclusions

In relation to soccer match play, it is well documented that CHO availability can
promote components of both physical and technical performance. Additionally,
sufficient energy and macronutrient intake in the hours and days after match play
is necessary to promote recovery between games. Although our understanding of
nutrition for training is less advanced than nutrition for match play, it is recog-
nised that manipulation of energy, macronutrient and micronutrient availability
can readily affect training adaptations associated with strength, power, and endur-
ance. It is noteworthy that much of our current understanding is based on labora-
tory trials and fi
­ eld-​­based studies largely conducted on recreationally active male
 Nutrition for match play and training 85
players. It is hoped that the coming decade will see a growth of studies specifically
conducted on adult and adolescent players from both the men’s and women’s pro-
fessional game. The energetic and substrate demands of match play and the typical
training sessions completed by these players remain to be accurately quantified.
Where possible, randomised control trials should be completed (­e.g., ­short-​­term
manipulation of macronutrient and micronutrient availability, utilisation of sup-
plements and ergogenic aids) to ascertain the effects of nutrition more accurately
on modulating training adaptation. Significant attention should also be given to
the adolescent and female soccer player to provide e­ vidence-​­based strategies that
promote growth and maturation and reduce the risk of negative consequences as-
sociated with LEA.

References
Anderson, L., Close, G. L., Konopinski, M., Rydings, D., Milsom, J., Hambly, C., … Morton,
J. P. (­2019). Case study: muscle atrophy, hypertrophy, and energy expenditure of a premier
league soccer player during rehabilitation from anterior cruciate ligament injury. Interna-
tional Journal of Sports Nutrition and Exercise Metabolism, 29, ­559–​­566.
Anderson, L., Close, G. L., Morgans, R., Hambly, C., Speakman, J. R., Drust, B., & Morton,
J. P. (­2018). Assessment of energy expenditure of a professional goalkeeper from the English
premier league using the doubly labeled water method. International Journal of Sports Phys-
iology and Performance, 14(­5), ­681– ​­684.
Anderson, L., Drust, B., Close, G. L., & Morton, J. P. (­2022). Physical loading in professional
soccer players: implications for contemporary guidelines to encompass carbohydrate perio-
dization. Journal of Sports Sciences, 40(­9), ­1000–​­1019.
Anderson, L., Orme, P., Di Michele, R., Close, G. L., Morgans, R., Drust, B., & Morton, J. P.
(­2015). Quantification of training load during ­one-​­, ­two-​­and ­three-​­game week schedules in
professional soccer players from the English premier league: implications for carbohydrate
periodization. Journal of Sports Sciences, 4, ­1–​­10.
Anderson, L., Orme, P., Naughton, R. J., Close, G. L., Milsom, J., Rydings, D., … Morton, J. P.
(­2017a). Energy intake and expenditure of professional soccer players of the English premier
league: evidence of carbohydrate periodization. International Journal of Sports Nutrition and
Exercise Metabolism, 27, ­228–​­238.
Anderson, L., Naughton, R. J., Close, G. L., Di Michele, R., Morgans, R., Drust, B., & Morton,
J. P. (­2017b). Daily distribution of macronutrient intakes of professional soccer players from
the English premier league. International Journal of Sports Nutrition and Exercise Metabo-
lism, 27, ­491–​­498.
Areta, J. L., Burke, L. M., Ross, M. L., Camera, D. M., West, D. W., Broad, E. M., Coffey, V. G.
(­2013). Timing and distribution of protein ingestion during prolonged recovery from resist-
ance exercise alters myofibrillar protein synthesis. The Journal of Physiology, 591, ­2319–​­2331.
Baker, L. B., Rollo, I., Stein, K. W., & Jeukendrup, A. E. (­2015). Acute effects of carbohydrate
supplementation on intermittent sports performance. Nutrients, 7, ­5733–​­5763.
Balsom, P. D., Wood, K., Olsson, P., & Ekblom, B. (­1999). Carbohydrate intake and multiple
sprint sports: with special reference to football (­soccer). International Journal of Sports Med-
icine, 20, ­48–​­52.
Bangsbo, J., Nørregaard, L., & Thorsøe, F. (­1992). The effect of carbohydrate diet on intermit-
tent exercise performance. International Journal of Sports Medicine, 13, ­152–​­157.
Bettonviel, A. E. O., Brinkmans, N. Y. J., Russcher, K., Wardenaar, F. C., & Witard, O. C.
(­2016). Nutritional status and daytime pattern of protein intake on match, ­post-​­match, rest
and training days in senior professional and youth elite soccer players. International Journal
of Sports Nutrition and Exercise Metabolism, 26(­3), ­285–​­293.
86 James P. Morton et al.
Briggs, M. A., Harper, L. D., McNamee, G., Cockburn, E., Rumbold, P. L. S., Stevenson, E.
J., & Russell, M. (­2017). The effects of an increased calorie breakfast consumed prior to sim-
ulated ­match-​­play in academy soccer players. European Journal of Sport Science, 17, ­858–​­866.
Brinkmans, N. Y. J., Iedema, N., Plasqui, G., Wouters, L., Saris, W. H. M., van Loon L. J. C., &
van Dijk, J. W. (­2019). Energy expenditure and dietary intake in professional football play-
ers in the Dutch premier league: implications for nutritional counselling. Journal of Sports
Sciences, 16, ­1–​­9.
Burke, L. M., Collier, G. R., & Hargreaves, M. (­1993). Muscle glycogen storage after prolonged
exercise: effect of the glycemic index of carbohydrate. Journal of Applied Physiology, 75,
­1019–​­1023.
Burke, L. M., van Loon, L. J. C., & Hawley, J. A. (­2016). Postexercise muscle glycogen resynthe-
sis in humans. Journal of Applied Physiology, 122, ­1055–​­1067.
Burke, L. M., Winter, J. A., C ­ ameron-​­Smith, D., Enslen, M., Farnfield, M., & Decombaz, J.
(­2012). Effects of different dietary protein sources on plasma amino acid profiles at rest and af-
ter exercise. International Journal of Sports Nutrition and Exercise Metabolism, 22(­6), ­452–​­462.
Bussau, V. A., Fairchild, T. J., Rao, A., Steele, P., & Fournier, P. A. (­2002). Carbohydrate load-
ing in human muscle: an improved 1 day protocol. European Journal of Applied Physiology,
87(­3), ­290–​­295.
­Churchward-​­Venne, T. A., Pinckaers, P. J. M., Smeets, J. S. J., Betz, M. W., Senden, J. M., Goes-
sens, J. P. B., Gijsen, A. P., Rollo, I., Verdijk, L. B., & van Loon, L. J. C. (­2020). D
­ ose-​­response
effects of dietary protein on muscle protein synthesis during recovery from endurance exercise in
young men: a ­double-​­blind randomized trial. American Journal of Clin Nutrition, 112(­2), ­303–​­317.
Clenin, G., Cordes, M., Huber, A., Schumacher, Y. O., Noack, P., Scales, J., & Kriemier, S.
(­2015). Iron deficiency in sports: definition, influence on performance and therapy. Swiss
Medical Weekly, 145, w14196.
Collins, J., Maughan, R. J., Gleeson, M., Bilsborough, J. C., Jeukendrup, J. E., Morton, J. P., …
McCall, A. (­2021). UEFA Expert group statement on nutrition in elite football. Part 1: cur-
rent evidence to inform practical recommendations and future directions. British Journal of
Sports Medicine. 55(8), 416.
Currell, K., Conway, S., & Jeukendrup, A. E. (­2009). Carbohydrate ingestion improves perfor-
mance of a new reliable test of soccer performance. International Journal of Sports Nutrition
and Exercise Metabolism, 19, ­34–​­46.
DellaValle, D. M., & Haas, J. D. (­2011). Impact of iron depletion without anemia on performance
in trained endurance athletes at the beginning of a training season: a study of female collegiate
rowers. International Journal of Sports Nutrition and Exercise Metabolism, 21(­6), ­501–​­506.
Findlay, R. J., Macrae, E. H. R., Whyte, I. Y., Easton, C., & Forrest Née Whyte, L. J (­2020).
How the menstrual cycle and menstruation affect sporting performance: experiences and
perceptions of elite female rugby players. Br J Sports Med, 54(­18), ­1108–​­1113.
Foskett, A., Williams, C., Boobis, L., & Tsintzas, K. (­2008). Carbohydrate availability and muscle
energy metabolism during intermittent running. Medicine & Science in Sport & Exercise, 40(­1),
­96–​­103.
­Gonzalez-​­Alonso, J. (­2007). Hyperthermia impairs brain, heart and muscle function in exercis-
ing humans. Sports Medicine, 37(­­4 –​­5), ­371–​­373.
Gunnarsson, T. P., Bendiksen, M., Bischoff, R., Christensen, P. M., Lesivig, B., Madsen, K., …
Bangsbo, J. (­2013). Effect of whey ­protein-​­and ­carbohydrate-​­enriched diet on glycogen re-
synthesis during the first 48 h after a soccer game. Scandinavian Journal of Medicine & Sci-
ence in Sports, 23, ­508–​­515.
Haakonssen, E. C., Ross, M. L., Knight, E. J., Cato, L. E., Nana, A., Wluka, A. E., Cicuttini,
F. M., Wang, B. H., Jenkins, D. G., & Burke, L. M. (­2015). The effects of a ­calcium-​­rich
­pre-​­exercise meal on biomarkers of calcium homeostasis in competitive female cyclists: a
randomised crossover trial. PLoS One, 10(­5), e0123302.
 Nutrition for match play and training 87
Hannon, M. P., Parker, L. J. F., Carney, D. J., McKeown, J., Speakman, J. R., Hambly, C.,
Drust, B., Unnithan, V. B., Close, G. L., & Morton, J. P. (­2021). Energy requirements of
male academy soccer players from the English premier league. Medicine & Science in Sport &
Exercise, 53(­1), ­200–​­210.
Hannon, M. P., Carney, D. J., Floyd, S., McKeown, J., Drust, B., Unnithan, V. B., Close, G.
L., & Morton, J. P. (­2020). ­Cross-​­sectional comparison of body composition and resting met-
abolic rate in premier league academy soccer players: implications for growth and matura-
tion. Journal of Sports Science, 38(­­11–​­12), ­1326–​­1334.
Harper, L. D., Stevenson, E. J., Rollo, I., & Russell, M. (­2017). The influence of a 12%
­carbohydrate-​­electrolyte beverage on ­self-​­paced ­soccer-​­specific exercise performance. Jour-
nal of Science and Medicine in Sport, 20(­12), ­1123–​­1129.
He, C. S., Handzlik, M., Fraswer, W. D., Muhamad, A., Preston, H., Richardson, A., & Glee-
son, M. (­2013). Influence of vitamin D status on respiratory infection incidence and immune
function during 4 months of winter training in endurance sport athletes. Exercise Immunol-
ogy Review, 19, ­86–​­101.
Impey, S. G., Hearris, M. A., Hammond, K. M., Bartlett, J. D., Louis, J., Close, G. G., & Mor-
ton, J. P. (­2018). Fuel for the work required: a theoretical framework for carbohydrate perio-
dization and the glycogen threshold hypothesis. Sports Medicine, 48, ­1031–​­1048.
Ivy, J. L., Katz, A. L., Cutler, C. L., Sherman, W. M., & Coyle, E. F. (­1988). Muscle glycogen
synthesis after exercise: effect of time of carbohydrate ingestion. Journal of Applied Physiol-
ogy, 64, ­1480–​­1485.
Iwayma, K., Onishi, T., Maruyama, K., & Takahashi, H. (­2020). Diurnal variation in the glyco-
gen content of human liver using 13C MRS. NMR in Biomedicine, 33(­6), e4289.
Krustrup, P., Mohr, M., Steensberg, A., Bencke, J., Kjer, M., & Bangsbo, J. (­2006). Muscle and
blood metabolites during a soccer game: implications for sprint performance. Physical Fit-
ness and Performance, 38, ­1165–​­1174.
Krustrup, P., Ørtenblad, N., Nielsen, J., Nybo, L., Gunnarsson, T. P., Iaia, F. M., … Bangsbo,
J. (­2011). Maximal voluntary contraction force, SR function and glycogen resynthesis during
the first 72 h after a ­h igh-​­level competitive soccer game. European Journal of Applied Physi-
ology, 111, ­2987–​­2995.
Kurdak, S. S., Shirreffs, S. M., Maughan, R. J., Ozgunen, K. T., Zeren, C., Korkmaz, S., ...
Dvorak, J. (­2010). Hydration and sweating responses to ­hot-​­weather football competition.
Scandinavian Journal of Medicine & Science in Sports, 20(­3), ­133–​­139.
Lee, J. K., & Shirreffs, S. M. (­2007). The influence of drink temperature on thermoregulatory
responses during prolonged exercise in a moderate environment. Journal of Sports Science,
25(­9), ­975–​­985.
Longland, T. M., Oikawa, S. Y., Mitchell, C. J., Devries, M. C., & Phillips, S. M. (­2016). Higher
compared with lower dietary protein during an energy deficit combined with intense exercise
promotes greater lean mass gain and fat mass loss: a randomized trial. American Journal of
Clinical Nutrition, 103(­3), ­738–​­746.
Loucks, A. B., Kiens, B., & Wright, H. H. (­2011). Energy availability in athletes. Journal of
Sports Sciences, 29(­1), ­S7–​­15.
MacNaughton, L. S., Wardle, S., Witard, O. C., McGlory, C., Hamilton, D. L., Jeromson, S.,
Lawrence, C. E., Walls, G. A., & Tipton, K. D. (­2016). The response of muscle protein syn-
thesis following w ­ hole-​­body resistance exercise is greater following 40 g than 20 g of ingested
whey protein. Physiological Reports, 4(­15), e12893.
Maughan, R. J. (­1997). Energy and macronutrient intakes of professional football (­soccer) play-
ers. Br Journal of Sports Medicine, 31, ­45–​­47.
Maughan, R. J., Watson, P., Evans, G. H., Broad, N., & Shirreffs, S. M. (­2007). Water balance
and salt losses in competitive football. International Journal of Sports Nutrition and Exercise
Metabolism, 17(­6), ­583–​­594.
88 James P. Morton et al.
McGregor, S. J., Nicholas, C. W., Lakomy, H. K., & Williams, C. (­1999). The influence of in-
termittent ­h igh-​­intensity shuttle running and fluid ingestion on the performance of a soccer
skill. Journal of Sports Science, 17(­11), ­895–​­903.
McNulty, K. L., ­Elliott-​­Sale, K. J., Dolan, E., Swinton, P. A., Ansdell, P., Goodall, S., ... Hicks,
K. M. (­2020). The effects of menstrual cycle phase on exercise performance in eumenor-
rheic women: a systematic review and ­meta-​­analysis. Sports Medicine, 50(­10), ­1813–​­1827. doi:
10.1007/­­s40279-­​­­020-­​­­01319-​­3
Milsom, J., Barreira, P., Burgess, D. J., Iqbal, Z., & Morton, J. P. (­2014). Case study: muscle
atrophy and hypertrophy in a premier league soccer player during rehabilitation from ACL
injury. International Journal of Sports Nutrition and Exercise Metabolism, 24, ­543–​­552.
Mohr, M., Krustrup, P., & Bangsbo, J. (­2003). Match performance of ­h igh-​­standard soccer play-
ers with special reference to development of fatigue. Journal of Sports Sciences, 21, ­439–​­449.
Mohr, M., Krustrup, P., Nybo, L., Nielsen, J. J., & Bangsbo, J. (­2004). Muscle temperature
and sprint performance during soccer ­matches-​­-​­beneficial effect of ­re-­​­­warm-​­up at ­half-​­time.
Scandinavian Journal of Medicine & Science in Sports, 14(­3), ­156–​­162.
Mohr, M., Mujika, I., Santisteban, J., Randers, M. B., Bischoff, R., Solano, R., ... Krustrup,
P. (­2010). Examination of fatigue development in elite soccer in a hot environment: a ­multi-​
­experimental approach. Scandinavian Journal of Medicine & Science in Sports, 20(­3), ­125–​­132.
Moore, D. R., Sygo, J. & Morton, J. P. (­2021). Fuelling the female athlete: carbohydrate and
protein considerations. European Journal of Sports Sciences, 22(5), 684-696.
Moore, D. R., Areta, J., Coffey, V. G., Stellingwerff, T., Phillips, S. M., Burke, L. M., Cléroux,
M., Godin, J. P., & Hawley, J. A. (­2012). Daytime of ­post-​­exercise protein intake affects
­whole-​­body protein turnover in ­resistance-​­trained males. Nutrition & Metabolism, 9(­1), 91.
Morehen, J. C., Rosimus, C., Cavanagh, B. P., Hambly, C., Speakman, J. R., E ­ lliot-​­Sale, K. J., Han-
non, M. P., & Morton, J. P. (­2022). Energy expenditure of female international standard soccer
players: a doubly labeled water investigation. Medicine Science, Sports, & Exercise, 54(­5), ­769–​­779.
Morton, J. P., Croft, L., Bartlett, J. D., Maclaren, D. P. M., Reilly, T., Evens, L., … Drust, B.
(­2009). Reduced carbohydrate availability does not modulate t­raining-​­induced heat shock
protein adaptations but does up regulate oxidative enzyme activity in human skeletal muscle.
Journal of Applied Physiology, 106, ­1513–​­1521.
Morton, J. P., Iqbal, Z., Drust, B., Burgess, D., Close, G. L., & Brukner, P. D. (­2012). Seasonal
variation in vitamin D status in professional soccer players of the English premier league.
Applied Physiology Nutrition, and Metabolism, 37(­4), ­798–​­802.
Morton, R. W., Murphy, K. T., McKellar, S. R., Schoenfeld, B. J., Henselmans, M., Helms,
E., … Phillips, S. M. (­2018). A systematic review, ­meta-​­analysis and ­meta-​­regression of the
effect of protein supplementation on resistance ­training-​­induced gains in muscle mass and
strength in healthy adults. British Journal of Sports Medicine, 52(­6), ­376–​­384.
Moss, S. L., Randell, R. K., Burgess, D., Ridley, S., ÓCairealláin, C., Allison, R., & Rollo, I.
(­2020). Assessment of energy availability and associated risk factors in professional female
soccer players. European Journal of Sports Sciences, 6, ­1–​­10.
Mountjoy, M., ­Sundgot-​­Borgen, J., Burke, L., Carter, S., Constantini, N., Lebrun, C., Meyer,
N., Sherman, R., Steffen, K., Budgett, R., & Ljungqvist, A. (­2014). The IOC consensus state-
ment: beyond the female athlete ­triad-​­relative energy deficiency in sport (­­RED-​­S). British
Journal of Sports Medicine, 48, ­491–​­497.
Nicholas, C. W., Williams, C., Lakomy, H. K., Phillips, G., & Nowitz, A. (­1995). Influence
of ingesting a c­ arbohydrate-​­electrolyte solution on endurance capacity during intermittent,
­h igh-​­i ntensity shuttle running. Journal of Sports Sciences, 13(­4), ­283–​­290.
Owens, D. J., Allison, R., & Close, G. L. (­2018). Vitamin D and the athlete: current perspectives
and new challenges. Sports Medicine, 48(­1), ­3 –​­16.
Owens, D. J., Sharples, A. P., Polydorou, I., Alwan, N., Donovan, T., Tang, J., Fraser, W.,
Cooper, R. G., Morton, J. P., Stewart, C., & Close, G. L. (­2015). A systems based investigation
 Nutrition for match play and training 89
into vitamin d and skeletal muscle repair, regeneration and hypertrophy. American Journal of
Physiology Endocrinology and Metabolism, 309(­12), ­E1019–​­1031.
­Rodriguez-​­Giustiniani, P., Rollo, I., Witard, O. C., & Galloway, S. D. R. (­2019). Ingesting a 12%
­carbohydrate-​­electrolyte beverage before each half of a soccer match simulation facilitates
retention of passing performance and improves ­h igh-​­intensity running capacity in academy
players. International Journal of Sports Nutrition and Exercise Metabolism, 29, ­397–​­405.
Rollo, I., Randell, R. K., Baker, L., Leyes, J. Y., Leal, D. M., Lizarraga, A., Mesalles, J., Jeu-
kendrup, A. E., James, L. J., & Carter, J. M. (­2021). Fluid balance, sweat Na+ losses, and car-
bohydrate intake of elite male soccer players in response to low and high training intensities
in cool and hot environments. Nutrients, 13, 401.
Russell, M., Benton, D., & Kingsley, M. (­2012). Influence of carbohydrate supplementation
on skill performance during a soccer match simulation. Journal of Science and Medicine in
Sport, 15, ­348–​­354.
Russell, M., & Kingsley, M. (­2014). The efficacy of acute nutritional interventions on soccer
skill performance. Sports Medicine, 44, ­957–​­970.
Saltin, B. (­1973). Metabolic fundamentals in exercise. Medicine and Science in Sports, 5, ­137–​­146.
Sim, M., ­Garvican-​­Lewis, L. A., Cox, G. R., Govus, A., McKay, A. K. A., Stellingwerff, T., &
Peeling, P. (­2019). Iron considerations for the athlete: a narrative review. European Journal of
Applied Physiology, 119(­7), ­1463–​­1478.
Snijders, T., Res, P. T., Smeets, J. S. J., van Vliet, S., van Kranenburg, J., Maase, K., Kies, A.
K., Verdijk, L. B., & van Loon, L. J. C. (­2015). Protein ingestion before sleep increases muscle
mass and strength gains during prolonged r­ esistance-​­type exercise training in healthy young
men. The Journal of Nutrition, 145(­6), ­1178–​­1184.
Souglis, A. G., Chryssanthopoulos, C. I., Travlos, A. K., Zorzou, A. E., Gissis, I. T., Papado-
poulos, C. N., & Sotiropoulos, A. A. (­2013). The effect of high vs. low carbohydrate diets on
distances covered in soccer. Journal of Strength and Conditioning Research, 27, ­2235–​­2247.
Stellingwerff, T., Morton J. P., & Burke, L. M. (­2019). A framework for periodized nutrition for
athletes. International Journal of Sports Nutrition and Exercise Metabolism, 29(­2), ­141–​­151.
Tang, J. E., Moore, D. R., Kujbida, G. W., Tarnopolsky, M. A., & Phillips, S. M. (­2009). Inges-
tion of whey hydrolysate, casein, or soy protein isolate: effects on mixed muscle protein syn-
thesis at rest and following resistance exercise in young men. Journal of Applied Physiology,
107(­3), ­987–​­992.
Thomas, D. T., Erdman, K. A., & Burke, L. M. (­2016). Position of the academy of nutrition and
dietetics, dieticians of Canada, and the American college of sports medicine: nutrition and
athletic performance. Journal of the Academy of Nutrition Dietetics, 116(­3), ­501–​­528.
Trommelen, J., Kouw, I. W. K., Holwerda, A. M., Snijders, T., Halson, S. L., Rollo, I., Verdijk,
L. B., & van Loon, L. J. C. (­2018). Presleep dietary p ­ rotein-​­derived amino acids are incor-
porated in myofibrillar protein during post exercise overnight recovery. American Journal of
Physiology Endocrinology & Metabolism, 314(­5), ­457–​­467.
Wenger, A. (­2021). Importance of nutrition in football: the coach’s perspective. British Journal
of Sports Medicine, 55(­8), 409.
6 Recovery strategies
Warren Gregson, Gregory Dupont,
­Abd-​­Elbasset Abaidia and Robin Thorpe

Introduction
In this chapter, we bring together the latest scientific research as well as r­ eal-​­world ex-
perience of implementing recovery strategies in elite soccer to provide a contemporary
overview of the key concepts. The initial section serves to contextualise the growing
importance of recovery for elite players. Next, we provide an overview of the key phys-
iological mechanisms which underpin the recovery process which serve as the targets
for strategies which aim to optimise the recovery process. The final section examines
the important recovery strategies employed in the elite game. We focus on the scien-
tific basis of recovery interventions rather than monitoring strategies used to evalu-
ate whether the player is adapting positively or negatively to the collective stresses of
training and competition. Information on the latter can be found in several excellent
previous reviews (­e.g., Thorpe et al., 2017).

The rising importance of recovery in the modern elite game

The typical season is structured around a short preparation period (~6 weeks) fol-
lowed by a long competitive season lasting approximately 40 weeks. Players are, there-
fore, exposed to extended time periods where the combined demands of training and
­match-​­play can induce a high degree of physical and mental stress. In the modern
game, the increasing physical demands of competition (­Barnes et al., 2014), together
with a high frequency of competition, particularly in those players representing the
most successful teams, has further accentuated the physical and mental load incurred
by players. Players are now routinely exposed to two to three games per week with
leading players often competing 70 matches per season interspersed with 4­ –​­5 days of
recovery between matches. These demands are further increased in those players com-
peting in leagues such as the English Premier League due to the absence of a winter
break (­Ekstrand et al., 2018). Similarly, international competitions taking place during
the ­off-​­season period, which typically reduces the rest period available to players, fur-
ther increasing the cumulative load experienced by players.
Soccer involves many ­h igh-​­intensity activities such as ­h igh-​­speed running, sprint-
ing, changing direction, jumping, and shooting which can lead to fatigue. Fatigue is
defined as an inability to complete a task that was once achievable within a recent
time frame (­Pyne & Martin, 2011; Halson, 2014). During a match, fatigue can arise
temporarily at any time following a ­short-​­term intense period, towards the end of the
match and following the match (­Nedelec et al., 2012). Many n ­ on-​­contact injuries occur

DOI: 10.4324/9781003148418-7
 Recovery strategies 91
during the latter stages of each half (­Ekstrand et al., 2011), suggesting that fatigue may
be a risk factor for injury.
In recent years, increasing evidence has highlighted the potential impact of ­match-​
r­ elated fatigue on injury risk. During periods where the match schedule is congested
(­e.g., two to three matches per week over several weeks), recovery time between suc-
cessive matches (­­2–​­3 days) may be insufficient to allow the player to fully regenerate
(­Dupont et al., 2010). Under such conditions, injury rates in e­ lite-​­level players partici-
pating in the UEFA Champions League were more than six times higher when players
played two matches per week compared to one match per week despite similar phys-
ical performance levels (­Dupont et al., 2010). In a large cohort of elite players, total
injury rates and muscle injury rates were increased in matches where the recovery time
was less than or equal to 4 days compared with matches where the recovery time was
more than or equal to 6 days (­Bengtsson et al., 2013). The absence of a winter break in
leagues such as the English Premier League increases the risk of injury. For example,
elite European club teams without a winter break (­English clubs) lost on average 303
days more per season due to injuries across the entire season compared with teams
with a winter break (­Ekstrand et al., 2018).
Increased availability of players for selection, because of a reduction in injuries,
substantially increases a team’s chance of success (­Hagglund et al., 2013). Changes in
injury occurrence have a significant impact on the financial performance of the club.
During the ­2016–​­2017 season, the average English Premier League team lost approxi-
mately £45 million per season due to ­injury-​­related (­team underachievement and player
salaries) decrements in performance (­Eliakim et al., 2020). Consequently, the impor-
tance of managing player loading with respect to fatigue and subsequent injury risk
has increased attention on the area of recovery both in the form of academic research
together with attempts in the field to develop strategies which optimise player recovery.

Overview of the physiological and psychological mechanisms

underpinning recovery
Recovery is regarded as a multifaceted (­e.g., physiological and psychological) restora-
tive process relative to time (­Kellmann et al., 2018). Under conditions where a player’s
recovery status is disturbed by external or internal factors, fatigue as a condition of
augmented tiredness arises due to physical and mental effort (­Halson, 2014; Kellmann
et al., 2018). A certain degree of fatigue resulting in functional overreaching is required
to mediate adaptations to training which drive performance enhancement (­Pyne &
Martin, 2011). On the contrary, excessive fatigue through ­under-​­recovery may increase
the players’ susceptibility to ­non-​­functional ­over-​­reaching, injury, and illness (­Nimmo
et al., 2007). Fatigue can be compensated with recovery strategies which serve to r­ e-​
e­ stablish the invested resources on a physiological and psychological level (­Kellmann
et al., 2018).
Due to the nature of the eccentric actions performed during a match, soccer is a
sport inducing a high level of muscle damage (­Nédélec et al., 2013). This impact is
characterised by a decrease in neuromuscular function, an increase in the blood con-
centrations of intramuscular proteins and an increase in muscle soreness (­Warren
et al., 1999). In this context, following a game, a period of rest is needed to return to
a homeostatic state (­Nédélec et al., 2013). Scientists have analysed the time needed to
recover following a match. The results have been compiled in a systematic review with
92 Warren Gregson et al.

a Time

Baseline Post 24h 48h 72h

–3%
Relative decrease of performance

–4%
–5%

–6%

–8%

Knee flexors isometric force

–12% Countermovement Jump Height

b
Creatine Kinase concentration
180%
Relative increase of parameters values

Muscle soreness

90%

80%

50%
40%
30%

Baseline Post 24h 48h 72h

Time

­Figure 6.1a and 6.1b Recovery of knee flexor isometric force, c­ounter-​­movement jump
height (­1a) and ratings of subjective muscle soreness and creatine ki-
nase concentrations (­1b) throughout the ­72-​­h period following ­match-​
p
­ lay. Redrawn from Silva et al. (­2018).

­ eta-​­analysis and showed that a period of 72 h is insufficient for performance param-

m
eters to return to baseline values (­­Figure 6.1a and b; Silva et al., 2018). Some perceptual
or physiological parameters may recover faster. However, contrary to neuromuscular
performance, these parameters are not sensitive nor representative enough to be con-
sidered as good markers of muscle damage (­Warren et al., 1999).
 Recovery strategies 93
­Post-​­exercise recovery is a complex process which involves several phenomena. Some
mechanisms of the recovery process have been observed and described in the scientific
literature. These mechanisms centre on the role of muscle damage, inflammation, and
regeneration, the repeated bout effect, energetic substrates, and psychological aspects.

The role of muscle damage, inflammation, and regeneration

The mechanical stress induced by eccentric actions is considered one of the dominant
factors mediating muscle damage (­Tee et al., 2007). The ultrastructure of the muscle,
the extracellular matrix and probably the capillaries are damaged (­Clarkson & Hubal,
2002). This muscle damage constitutes a stimulus for an acute inflammatory response
that may last for several days (­Cannon & St Pierre, 1998; Malm, 2001; Smith et al.,
2000; Suzuki et al., 2002). The inflammation process is mediated by proteins such as
interleukins, tumour necrosis ­factor-​­α (­­TNF-​­α), and C ­ -​­reactive protein (­CRP). The
role of these proteins is to regulate the migration of immune cells (­neutrophils and
macrophages) into the injured area of the muscle and to initiate the repair (­Cannon &
St Pierre, 1998; Suzuki et al., 2002; Peake et al., 2005).
In soccer, match participation is characterised by an increase in ­interleukine-​­6 (­­IL-​
­6), ­TNF-​­α, and CRP concentrations (­Silva et al., 2018). While I­ L-​­6 and ­TNF-​­α peak
immediately after the match, CRP peaks 24 h after the match. In addition, the immu-
nological response is characterised by a substantial increase of leucocytes, monocytes,
macrophages, and lymphocytes 24 and 48 h following the match (­Silva et al., 2018).
This process stimulates muscle regeneration in coordination with hormonal aspects.
Some hormones such as testosterone, growth hormone, and i­ nsulin-​­like growth f­ actor-​
1­ directly stimulate the satellite cells involved in the process of muscle repair (­Hawke &
Garry, 2001; Chakravarthy et al., 2000; ­Sinha-​­Hikim et al., 2013; Schoenfeld, 2013).
Muscle regeneration is accelerated in the presence of these hormones. Inducing an in-
crease in these hormones may accelerate recovery kinetics following e­ xercise-​­induced
muscle damage (­Abaïdia et al., 2017; Crewther & Cook, 2012).

The repeated bout effects

The repetition of an exercise has a protective effect which can be influenced by several
variables including intensity, velocity of contraction, number of damaging contrac-
tions, muscle length, muscle group, age, and sex (­Hyldahl et al., 2017). Potential mech-
anisms underpinning the repeated bout effect include neural adaptations, alterations
to muscle mechanical properties, structural remodelling of the extracellular matrix
and biochemical signalling (­Hyldahl et al., 2017; McHugh et al., 1999; McHugh, 2003).
From a practical point of view, athletes previously exposed to an exercise modality are
likely to recover faster than athletes who have not been previously exposed.
For global activities such as soccer, researchers have reported conflicting results
as to whether match exposure provides a protective effect. Although data on the re-
peated bout effect after a match are sparse, scientists have analysed the influence of
the repeated bout effect on recovery kinetics following other team sports and global
activities. Following a repeated intermittent sprint exercise, Leeder et al. (­2014) ob-
served lower muscle soreness following the second bout of exercise but no significant
difference in recovery kinetics of muscle function and blood creatine kinase concen-
trations between the two bouts. These results differ from those obtained by Verma
94 Warren Gregson et al.
et al. (­2016), who reported accelerated recovery kinetics following the second bout
compared with the first for strength, soreness, blood creatine kinase, and lactate dehy-
drogenase concentrations.
The repeated bout effect may also be associated with the player’s experience and
the aptitude to cope with a given level of load during a season. Sterczala et al. (­2014)
evaluated the recovery response of ten American Football players after two games
separated by one season. Blood creatine kinase and myoglobin concentrations were
assessed, and the authors found no difference at any time point between the two
matches. The ability to recover may also be different between young players acced-
ing to elite level and players having years of experience. During an entire season of
Australian Football Rules, Hunkin et al. (­2014) showed higher levels of blood creatine
kinase concentrations in less experienced players. This finding may be associated with
residual muscle damage resulting from an intense training period.

Energetic substrates
­ ost-​­match fatigue in soccer is also associated with a decrease in glycogen stores.
P
Match participation may induce up to a 50% decrease in muscular glycogen concen-
trations (­K rustrup et al., 2006). Furthermore, muscle glycogen stores may not be fully
replenished at ­48–​­72 h following a soccer match (­Jacob et al., 1982). The decline in mus-
cle glycogen may impact recovery kinetics following ­exercise-​­induced muscle damage
(­Gavin et al., 2016). For example, a reduced maximal voluntary contraction has been
observed 48 h following eccentric exercise in a reduced glycogen state (­Gavin et al.,
2016). To counteract the deleterious effects of muscle glycogen depletion, it has been
observed that an elevated muscle glycogen content through a carbohydrate diet may
enhance the replenishment of glycogen stores 48 h ­post-​­match (­K rustrup et al., 2011).

Psychologic aspects
Psychological factors may also influence ­ post-​­ match recovery kinetics. ­ Stults-​
K­ olehmainen et al. (­2014) studied the effects of chronic stress on recovery kinetics
following ­exercise-​­induced muscle damage. After answering a questionnaire to eval-
uate their level of stress, 31 participants were divided into h ­ igh-​­stress and ­low-​­stress
groups. The level of force was assessed every 24 h over a period of 96 h following
­exercise-​­induced muscle damage with the h ­ igh-​­stress group demonstrating slower re-
covery of their muscle force.

Key interventions to drive the recovery process

Researchers and practitioners alike have investigated the efficacy of commonly used
interventions to combat the physical and mental stress associated with training and
­match-​­play (­Nédélec et al., 2012). A recent investigation reviewing commonly used
recovery strategies in the Spanish top Division (­Spanish La Liga) reported that all
teams utilised at least one recovery strategy following ­match-​­play, however, the range
of interventions adopted was substantially different between teams with water immer-
sion (­cold and hot), massage, and foam rolling accounting for 74%, 70%, and 57%, re-
spectively (­­Altarriba-​­Bartes et al., 2020). Nedelec and colleagues (­2013) reported that
active recovery, stretching, compression garments, and ­cold-​­water immersion were the
 Recovery strategies 95

­Figure 6.2 An example of an active recovery strategy.

most prevalent recovery interventions used by practitioners working in the top French
League (­France Ligue 1). The following section will briefly review the efficacy of such
interventions.

Active recovery
Active recovery can be performed via multiple modalities including ­sub-​­maximal cy-
cling and running including exercising in water (­­Figure 6.2; Nédélec et al., 2013; Pooley
et al., 2020). In France, 81% of professional teams reported that they prescribed active
recovery modalities immediately following games (­Nédélec et al., 2013). The purported
mechanism associated with ­aerobic-​­based active recovery is centred on the removal
of disruptive metabolites from areas of muscular exertion via an increase in circula-
tion (­Nédélec et al., 2013; Pooley et al., 2020). The majority of data have shown active
recovery to accelerate the removal of blood lactate (­Fairchild et al., 2003), however,
in a study of professional female players, no improvements in physical performance
(­countermovement jump, sprint time, maximal isokinetic knee flexion, and extension)
or blood markers (­creatine kinase, uric acid, and inflammatory) was observed when
comparing active recovery and passive recovery following ­match-​­play (­Andersson
et al., 2008).
A more recent study in younger players showed that active recovery improved
perceptual recovery and reduced creatine kinase compared to static stretching p ­ ost-​
m
­ atch and for 48 h thereafter (­Pooley et al., 2020). Other forms of active recovery such
as hydrotherapy and resistance training of the upper limbs have become popular with
practitioners. It is thought the associated hormonal and anabolic response alongside a
global increase in blood flow may be favourable to recovery in soccer players (­Yarrow
et al., 2007). Overall, active recovery may have beneficial effects on perceptual re-
covery and has clear mechanistic effects on blood flow and circulation. Therefore,
96 Warren Gregson et al.
during periods of high metabolic cost/­fatigue, active recovery is a suitable modality.
Active recovery utilisation in the immediate timeframe ­post-​­exercise, particularly, in
the event of mechanical disruption is still unclear.

Stretching
Stretching has been practised by players for decades as a method perceived to improve
flexibility and recovery and prevent injury (­Nédélec et al., 2013). The proposed mech-
anisms include an increase in joint range of motion and a reduction in musculotendi-
nous stiffness (­Nédélec et al., 2013). In the English Premier League, players reportedly
spend 40% of training time stretching, while in France in Ligue 1 50% of the time is
spent using stretching for recovery purposes (­Dadebo et al., 2004). In England, static
stretching was the most prevalent form of stretching consisting of typically 30 s per
muscle group for ­2–​­5 sets per session (­Nédélec et al., 2013). Although the use of stretch-
ing and in particular static stretching is widespread, there is no evidence to date to
support the use of stretching in enhancing the recovery process in elite soccer (­Herbert
et al., 2011; Kinugasa & Kilding, 2009). A recent investigation of professional youth
soccer players from a Premier League team found no differences in muscle damage
markers ­24–​­48 h following m ­ atch-​­play when static stretching was performed (­Pooley
et al., 2020). In a similar cohort, and similar study design, active recovery, and cold wa-
ter immersion improved recovery markers significantly greater than static stretching
(­Pooley et al., 2020). Lund and colleagues (­1998) suggested that static stretching may
even hinder the recovery process following eccentric muscle damage. In summary,
despite the widespread use of stretching across all levels of professional soccer, there
is little evidence to support its effect on recovery and under certain conditions (­e.g.,
muscle damage) caution should be taken.

­Self-​­myofascial ­release – ​­foam rolling

­ elf-​­myofascial release or foam rolling is performed as a recovery strategy by 91% of
S
clubs in La Liga (­­Altarriba-​­Bartes et al., 2020). S
­ elf-​­myofascial release has been likened
to traditional massage, however, many investigations have shown greater improvements
in joint range of motion following ­self-​­myofascial release compared to a limited number
studying traditional massage techniques (­Cheatham et al., 2015). Recent investigations
have found that short bouts of foam rolling (­30 s per muscle group) on ­soft-​­tissue areas
may lead to a significant increase in the joint range of movement (­MacDonald et al.,
2013). Furthermore, the use of foam rolling as a means of ­self-​­myofascial release has
shown positive effects on perceived muscle soreness following exercise (­Cheatham et al.,
2015). Although mainly adopted in the training process as a recovery strategy, the use of
­self-​­myofascial release largely serves to improve joint range of motion and in some cases
perceptions of recovery; hence, it is advantageous during all periods of the training
process especially following games and intense strenuous training sessions (­­Figure 6.3).

Massage
Massage, including its various forms, such as effleurage, petrissage, tapotement,
friction, and vibration, was used by 78% of players in France’s Ligue 1 teams with
handheld percussion devices increasingly used (­Nédélec et al., 2013). A common belief
 Recovery strategies 97

­Figure 6.3 An example of a foam rolling exercise.

among practitioners and players alike has been that massage enhances muscle blood
flow and, therefore, the removal of disruptive metabolites from fatigued muscle re-
gions. However, researches have shown that massage has a limited effect on blood flow
or the removal of waste products from the muscle (­Massage et al., 2010; Fuller et al.,
2015; Thomson et al., 2015). Furthermore, Wiltshire and Colleagues (­2010) showed a
detrimental effect of massage on blood flow by reducing the mechanical processes of
muscle fibres, glycogen r­ e-​­synthesis and in turn reducing recovery. Additionally, Vii-
tasaslo et al. (­1995) observed a potentially debilitating rise in muscle damage proteins
following strength exercise with the addition of immediate massage (­Viitasalo et al.,
1995). Small positive psychological and perceptual effects have been shown in n ­ on-​
t­ rained individuals following tissue massage (­Viitasalo et al., 1995). There seems to be
a small positive subjective response to massage; however, the physiological effect of
massage remains unclear and lacks strong support.

Cryotherapy
­Cold-​­water immersion has been shown to be the most common ­cryotherapy-​­based
recovery strategy amongst the top tier of Ligue 1 in France with 88% of teams us-
ing ­cold-​­water immersion in an attempt to enhance recovery (­Nédélec et al., 2013).
Athletes use c­ old-​­water immersion immediately following games and throughout the
recovery process. Similarly, short durations (­30 s to 1 min) of ­cold-​­water immersion in-
terspersed with short durations of h ­ ot-​­water immersion, known as contrast water ther-
apy, is popular among athletes (­­Altarriba-​­Bartes et al., 2020). The literature has shown
­cold-​­water immersion alone to be more effective for accelerating surrogate markers of
recovery (­Elias et al., 2013), therefore, this chapter will only discuss c­ old-​­water immer-
sion as a standalone strategy.
A cascade of mechanisms starting with a reduction in tissue temperature, metab-
olism, and blood flow has been shown following c­ old-​­water immersion (­Bleakley &
Davison, 2010; Mawhinney et al., 2020). Protocols differ substantially both in the
98 Warren Gregson et al.
literature and in the field, ranging from 5 to 20 min and temperatures of ­6 –​­22oC, how-
ever, recent data suggest that a dose of 1­ 0–​­11 min at ­12–​­15oC may be most effective
for reducing muscle tissue temperature and muscle blood flow (­Vromans et al., 2019;
Mawhinney et al., 2020). ­Cold-​­water immersion has been shown to be more effec-
tive in enhancing physical performance markers (­maximal strength, sprint time, and
countermovement jump) and biological metrics of muscle damage (­creatine kinase
and ­myoglobin) compared to other common strategies such as contrast water therapy
and passive recovery in individual athletes (­Ingram et al., 2009; Vaile et al., 2008).
Similar improvements in physical performance assessments, as well as s­ elf-​­reported
ratings and objective markers of muscle damage, have also been observed when com-
paring c­ old-​­water immersion to static stretching and passive recovery in soccer players
(­Elias et al., 2013; Pooley et al., 2020). Recently, c­ old-​­water immersion has been shown
as an effective and safe method to improve autonomic modulation by improving para-
sympathetic reactivation, which in theory, may be seen as advantageous for the global
recovery of athletes (­A lmeida et al., 2015; Buchheit et al., 2009; Douglas et al., 2015).
However, more data are required to fully understand the role of c­ old-​­water immersion
in the inflammatory cascade following soccer (­Peake et al., 2020).
­W hole-​­body cryotherapy has attracted a lot of interest regarding athlete recovery
in recent years, with athletes normally exposed to 1­ –​­3 min durations ­of –​­110 ­to –​­160oC
air temperatures (­Costello et al., 2016). Costello et al. (­2016) concluded there was in-
sufficient evidence to support the use of ­whole-​­body cryotherapy in alleviating muscle
damage in athletes (­Costello et al., 2016). The majority of positive effects have been
solely related to the players’ perceptions of recovery (­Wilson et al., 2018). Moreover,
greater reductions in tissue temperatures and blood flow are promoted by alternative
cooling strategies such as c­ old-​­water immersion (­Costello et al., 2012; Abaïdia et al.,
2017; Mawhinney et al., 2017; Wilson et al., 2018). ­W hole-​­body cryotherapy has also
been shown to effect hormonal alterations (­steroid hormone and testosterone) and
shift autonomic nervous system function to a more parasympathetic status (­Louis
et al., 2020). However, no data currently exist showing these promising biological
fluctuations influence recovery markers in soccer players (­Grasso et al., 2014; Russell
et al., 2017). Overall, there is a lack of support for ­whole-​­body cryotherapy as a recov-
ery modality in soccer players. Alternative cryotherapy methods such as c­ old-​­water
immersion demonstrate greater efficacy for improving recovery. Potential positive
endocrine and immune alterations following ­whole-​­body cryotherapy require further
investigation (­­Figure 6.4).

­Hot-​­water immersion
water immersion typically involves shoulder depth submergence in 36oC or
­ ot-​­
H
more and is commonly used by 71% of La Liga teams in Spain as a recovery strat-
egy (­­Altarriba-​­Bartes et al., 2020). Practically, hot or thermoneutral water immersion
recovery may be used to increase the range of movement at specific joints whilst re-
ducing load and utilising the hydrostatic pressure to increase blood flow (­Ménétrier
et al., 2013). To date, there is a lack of data on athletes, particularly, team sports in
relation to the performance recovery outcomes of h ­ ot-​­water immersion. Versey et al.
(­2013) observed no beneficial effects on recovery compared to other more commonly
used variations of water immersion (­cold, thermoneutral, and contrast). The theory
underpinning the possible beneficial effects of h ­ ot-​­water immersion is plausible. The
 Recovery strategies 99

­Figure 6.4 ­Cold-​­water immersion.

combination of the hydrostatic pressure of water and increased temperatures have

been shown to substantially improve tissue temperature and blood flow, which may
provide an unloaded method through which to remove disruptive metabolites follow-
ing strenuous exercise/­­match-​­play (­Ménétrier et al., 2013). Furthermore, promising
data exist showing the accelerative healing effects of heat application to exercised mus-
cle alongside systemic ­pro-​­inflammatory and haemodynamic properties of ­hot-​­water
immersion in n ­ on-​­athletic populations (­Hoekstra et al., 2008; Cheng et al., 2017; Fran-
cisco et al., 2021). Similarly, increasing in popularity among athletes, sauna bathing,
performed for decades and with positive associations with cardiovascular and mental
health in the general population, worsened performance in elite swimmers when used
as a recovery strategy between races (­Skorski et al., 2020). On the contrary, sauna
bathing improved neuromuscular performance in trained men following resistance
exercise (­Mero et al., 2015). Although there is currently a lack of supporting evidence
for enhanced recovery in soccer, augmented circulatory, perceptual, and healing re-
sponses following ­post-​­exercise heating remains plausible.

Compression garments
Compression garments have been used for decades in the clinical setting and have be-
come increasingly popular in athletic environments. Around 25% of teams in France
and 74% of teams in Spain’s top divisions use compression garments for recovery pur-
poses (­Nédélec et al., 2013; A
­ ltarriba-​­Bartes et al., 2020). Compression garments apply
external mechanical pressure to the skin, thereby, providing tissue structural support
and possibly stabilisation (­MacRae et al., 2011). Other potential mechanisms include
enhanced venous return through superficial veins and improved capillary filtration
which may reduce venous pooling in the lower limbs following exercise (­Partsch &
Mosti, 2008). This effect is achieved by applying a pressure gradient which is the highest
100 Warren Gregson et al.

­Figure 6.5 Compression garments.

in the foot/­ankle region and lowest in the upper calf (­stockings) and quad (­tights). As a
result, the increase in venous return is thought to aid in the removal of waste products
promoting a quicker return to blood gas homeostasis (­Davies et al., 2009). Moreo-
ver, advantageous hemodynamic mechanisms have been observed following the use of
compression garments after physically exerting exercise (­Lee et al., 2018).
Recent reviews have shown a positive effect of compression garments on recovery in
elite athletes (­Hill et al., 2014). In particular, ­custom-​­fitted compression garments im-
proved the recovery of perceptual and muscle damage markers in team sports athletes
(­Upton et al., 2017). Moreover, the efficacy of pneumatic sequential compression for
increased blood flow has been demonstrated in clinical populations (­Feldman et al.,
2012). In athlete populations, pneumatic sequential compression has been seen to in-
crease circulating lactate ­post-​­exercise, however, there is a lack of evidence support-
ing improved recovery or reduced muscle damage markers (­Zelikovski et al., 1993).
Overall, there is sufficient evidence to support the use of compression garments for
accelerating recovery in soccer (­­Figure 6.5).

Sleep
In a survey performed in a soccer team participating in the UEFA Europa League,
95% of the players highlighted poor sleep following night matches (­Nédélec et al.,
2015). This may be a consequence of the heightened physical and mental load involved
during ­match-​­play (­Nédélec et al., 2015). The recovery process may be affected, and
 Recovery strategies 101
recovery kinetics slowed, following a perturbed sleep at night (­Nédélec et al., 2015).
In addition, poor sleep at night may accentuate muscle damage or limit muscle repair,
which slows muscle performance recovery kinetics (­Skein et al., 2013; Nédélec et al.,
2015). Central function plays a key role in fatigue perception but also in muscle func-
tion. It has been hypothesised that this cognitive aspect may be negatively affected
when the period of sleep is insufficient or when the quality of sleep is bad (­Nédélec
et al., 2015).
Scientists have shown a possible negative effect of a lack of sleep on glycogen resyn-
thesis (­Skein et al., 2011). A poor night’s sleep may be compensated by a short p ­ ost-​
l­unch nap. Waterhouse et al. (­2007) found that a nap, followed by a 3­ 0-​­min recovery
period, improved alertness and aspects of mental and physical performance following
partial sleep loss. The ability to nap for short periods during the day may be a useful
skill for players to acquire especially during a congested fixture schedule. Recom-
mendations for sleep induction include adopting a dark and quiet environment using
eyeshades and earplugs, listening to relaxing music, and adopting regular s­ leep-​­wake
schedules. Conversely, consumption of caffeine prior to the match for performance
enhancement, alcohol as a means of celebrating after the match, and h ­ yper-​­hydration
could lead to sleep disturbance.

Psychological aspects
Psychological aspects are an important consideration in the process of recovery. It
is important to consider these aspects by individually monitoring the factors lead-
ing to detrimental effects on recovery. A high level of stress impairs the recovery
process (­­Stults-​­Kolehmainen et al., 2014). The speech delivered by the coach may
also influence the psychobiological response of the players. Comparing positive and
negative feedback of the coach showed different physiological responses the day after
a match (­Crewther & Cook, 2012). More specifically, the use of video feedback from
the previous match alongside positive coach feedback leads to beneficial effects on
testosterone secretions (­Crewther & Cook, 2012). Psychological aspects are also in-
volved when applying recovery strategies. Players’ perceptions of recovery are linked
to psychological and social aspects (­Venter, 2014). For instance, prayer, relaxation
strategies, and discussions with teammates and friends are considered as important
recovery strategies by elite soccer players (­Venter, 2014). Removing a recovery strat-
egy perceived as effective by a player could also impair the recovery process. Beliefs
and expectations from a strategy may have a beneficial or deleterious effect on recov-
ery (­Abaïdia et al., 2017). These placebo and nocebo effects are individual processes
that should be known when applying a recovery strategy. From a practical point of
view, questioning the players about their habits and beliefs at the beginning of the
season may be an interesting approach to educate and individualise the recovery
protocol.
An array of different strategies are used by professional teams and players in an
attempt to alleviate the deleterious symptoms associated with training and games
(­Nédélec et al., 2013; ­Altarriba-​­Bartes et al., 2020). However, there is currently a lack of
efficacy for several strategies in improving the multifactorial systems which underpin
recovery. ­Cold-​­water immersion, compression garments, ­self-​­myofascial release, and
active or ­hot-​­water recovery appear able to promote specific physiological changes at
various time points to accelerate the players’ return towards their p ­ re-​­training/­match
102 Warren Gregson et al.
state. These include a reduction in tissue temperature and blood flow together with an
increase in joint range of motion, blood flow, and venous return.

Future directions and conclusions

The physical and mental stress induced by ­match-​­play and training lead to increased
levels of fatigue in the player. Recovery is a complex and multifaceted process involv-
ing physiological and psychological parameters which need to be regenerated at cer-
tain time points to reduce susceptibility to ­non-​­functional overreaching, injury, and
illness. A recovery intervention strategy should serve to match a given stress with the
most effective intervention at a given time point on the recovery continuum. A pleth-
ora of recovery strategies are commonly applied in the field despite limited scientific
evidence to support their efficacy. The foundation of any intervention strategy should
be based on quality sleep and rest along with nutrition and hydration. Beyond this,
there is sufficient scientific evidence to advocate the use of c­ old-​­water immersion and
compression garments to further accelerate the recovery process. ­Self-­​­­myo-​­fascial re-
lease and heating modalities may support specific physiological processes at various
time points though more research is needed to fully support their efficacy. Finally,
an optimal recovery intervention strategy likely reflects a balance between e­ vidence-​
­based prescription and individual athlete preferences.
In future, research is needed to better understand the efficacy of different recovery
modalities in isolation together with the interaction between various interventions at
relevant time points on the recovery continuum. This integrated focus should centre
on the influence of different interventions on the restoration of physical performance
alongside studies using advanced laboratory techniques (­e.g., assessment of muscle per-
fusion and cellular and molecular responses) to foster a better understanding of the
mechanisms which mediate their effects. Finally, recovery remains one of the least un-
derstood aspects of the ­exercise-​­adaptation cycle (­Peake & Gandevia, 2017). More work
is, therefore, needed to better understand the impact of the varied intervention strate-
gies on the balance between accelerating recovery and mediating ­long-​­term adaptation.

References
Abaïdia, A. E., Lamblin, J., Delecroix, B., Leduc, C., McCall, A., Nédélec, M., Dawson, B.,
Baquet, G., & Dupont, G. (­2017). Recovery from e­xercise-​­induced muscle damage: ­cold-​
­water immersion versus ­whole-​­body cryotherapy. Int J Sports Physiol Perform, 12(­3), ­402–​
­409. https://doi.org/­10.1123/­ijspp.­2016- ​­0186.
Almeida, A. C., Machado, A. F., Albuquerque, M. C., Netto, L. M., Vanderlei, F. M., Van-
derlei, L. C. M., Junior, J. N., & Pastre, C. M. (­2015). The effects of cold water immersion
with different dosages (­duration and temperature variations) on heart rate variability ­post-​
­exercise recovery: a randomized controlled trial. J Sci Med Sport, 19(­8), ­676 –​­81. doi: 10.1016/­j.
jsams.2015.10.003.
­A ltarriba-​­Bartes, A., Peña, J., ­Vicens-​­Bordas, J., Casals, M., Peirau, X., & ­Calleja-​­González, J.
(­2020). The use of recovery strategies by Spanish first division soccer teams: a ­cross-​­sectional
survey. Physician Sports Med, 15, ­1–​­11. https://doi.org/­10.1080/­0 0913847.2020.1819150.
Andersson, H., Raastad, T., Nilsson, J., Paulsen, G., Garthe, I., & Kadi, F. (­2008). Neuromus-
cular fatigue and recovery in elite female soccer: effects of active recovery. Med Sci Sports
Exerc, 40(­2), ­372–​­380. https://doi.org/­10.1249/­mss.0b013e31815b8497.
 Recovery strategies 103
Bengtsson, H., Ekstrand, J., & Hägglund, M.(­2013). Muscle injury rates in professional football
increase with fixture congestion: an ­11-​­year ­follow-​­up of the UEFA champions league injury
study. Br J Sports Med, 47(­12), ­743 –​­747. doi: 10.1136/­­bjsports-­​­­2013-​­092383.
Barnes, C., Archer, D., Hogg, B., Bush, M. & Bradley, P. S. The evolution of physical and tech-
nical performance parameters in the English Premier League. International journal of sports
medicine 35, 1095–1100 (2014).
Bleakley, C. M., & Davison, G. W. (­2010). What is the biochemical and physiological rationale
for using ­cold-​­water immersion in sports recovery? A systematic review. Br J Sports Med,
44(­3), ­179–​­187. https://doi.org/­10.1136/­bjsm.2009.065565
Buchheit, M., Peiffer, J. J., Abbiss, C. R., & Laursen, P. B. (­2009). Effect of cold water immer-
sion on postexercise parasympathetic reactivation. Am J Physiol Heart Circ Physiol, 296(­2),
­H421–​­H427. https://doi.org/­10.1152/­ajpheart.01017.2008.
Cannon, J. G., & St Pierre, B. A. (­1998). Cytokines in e­ xertion-​­induced skeletal muscle injury.
Mol Cell Biochem, 179(­­1–​­2), ­159 –​­167. https://doi.org/­10.1023/­a:1006828425418.
Chakravarthy, M. V., Davis, B. S., & Booth, F. W. (­2000). ­IGF-​­1 restores satellite cell prolifer-
ative potential in immobilized old skeletal muscle. J Appl Physiol, 89, ­1365 –​­1379. https://doi.
org/­10.1152/­jappl.2000.89.4.1365.
Cheatham, S. W., Kolber, M. J., Cain, M., & Lee, M. (­2015). The effects of s­elf-​­myofascial
release using a foam roll or roller massager on joint range of motion, muscle recovery, and
performance: a systematic review. Int J Sports Phys Ther, 10(­6), ­827–​­838.
Cheng, A. J., Willis, S. J., Zinner, C., Chaillou, T., Ivarsson, N., Ørtenblad, N., Lanner, J. T.,
Holmberg, H. C., & Westerblad, H. (­2017). ­Post-​­exercise recovery of contractile function
and endurance in humans and mice is accelerated by heating and slowed by cooling skeletal
muscle. J Physiol, 595(­24), ­7413–​­7426. https://doi.org/­10.1113/­JP274870.
Clarkson, P. M., & Hubal, M. J. (­2002). E ­ xercise-​­induced muscle damage in humans. Am J of
Phys Med Rehab, 81(­11 Suppl), ­S52 –​­S69. https://doi.org/ 10.1097/­­0 0002060-­​­­200211001-​­0 0007
Costello, J. T., Algar, L. A., & Donnelly, A. E. (­2012). Effects of ­whole-​­body cryotherapy (–​­110
°C) on proprioception and indices of muscle damage. Scand J Med Science Sports, 22(­2),
­190–​­198. https://doi.org/­10.1111/­j.­1600-​­0838.2011.01292.x
Costello, J. T., Baker, P. R., Minett, G. M., Bieuzen, F., Stewart, I. B., & Bleakley, C. (­2016).
Cochrane review: ­ whole-​­body cryotherapy (­ extreme cold air exposure) for preventing
and treating muscle soreness after exercise in adults. J Evid Med, 9(­1), ­43–​­44. https://doi.
org/­10.1111/­jebm.12187.
Crewther, B. T., & Cook, C. J. (­2012). Effects of different ­post-​­match recovery interventions on
subsequent athlete hormonal state and game performance. Physiol Behav, 106(­4), ­471 –​­475.
doi: 10.1016/­j.physbeh.2012.03.015.
Dadebo, B., White, J., & George K. P. (­2004). A survey of flexibility training protocols and
hamstring strains in professional football clubs in England. Br J Sports Med, 38(­4), ­388 –​­394.
doi: 10.1136/­bjsm.2002.000044.
Davies, V., Thompson, K. G., & Cooper, S.-​­M. (­2009). The effects of compression garments on
recovery. J Strength Cond Res, 23(­6), ­1786–​­1794. https://doi.org/­10.1519/­JSC.0b013e3181b42589
Douglas J, Plews DJ, Handcock PJ, Rehrer NJ. The Beneficial Effect of Parasympathetic Re-
activation on Sympathetic Drive During Simulated Rugby Sevens. Int J Sports Physiol Per-
form. 2016 May;11(4):480-8. doi: 10.1123/ijspp.2015-0317. Epub 2015 Sep 10. PMID: 26356254.
Dupont, G., Nedelec, M., McCall, A., McCormack, D., Berthoin, S., & Wisløff, U. (­2010).
Effect of 2 soccer matches in a week on physical performance and injury rate. Am J Sports
Med, 38(­9), ­1752 –​­1758. doi: 10.1177/­0363546510361236.
Ekstrand J, Hägglund M, Fuller CW. Scand J Med Sci Sports. 2011 Dec;21(6):824–32. doi:
10.1111/j.1600-0838.2010.01118.
Ekstrand, J., Spreco, A., & Davison, M. (­2018). Elite football teams that do not have a winter
break lose on average 303 p ­ layer-​­days more per season to injuries than those teams that do: a
104 Warren Gregson et al.
comparison among 35 professional European teams. Br J Sports Med, 53(­19), ­1231 –​­1235. doi:
10.1136/­­bjsports-­​­­2018-​­099506.
Eliakim, T., Morgulev, E., & Lidor, R. and Meckel, M. (­2020). Estimation of injury costs: finan-
cial damage of English Premier League teams’ underachievement due to injuries. BMJ Open
Sport Exerc Med, 6(­1), e000675. doi: 10.1136/­­bmjsem-­​­­2019-​­0 00675corr1.
Elias, G. P., Wyckelsma, V. L., Varley, M. C., Mckenna, M. J., & Aughey, R. J. (­2013).Effective-
ness of water immersion on postmatch recovery in elite professional footballers. Int J Sports
Physiol Perform, 8(­3), ­243–​­254. doi: 10.1123/­ijspp.8.3.243.
Fairchild, T. J., Armstrong, A. A., Rao, A., Liu, H., Lawrence, S., & Fournier, P. A. (­2003). Gly-
cogen synthesis in muscle fibers during active recovery from intense exercise. Med Sci Sports
Exerc, 35(­4), ­595–​­602. https://doi.org/­10.1249/­01.MSS.0000058436.46584.8E
Feldman, J. L., Stout, N. L., Wanchai, A., Stewart, B. R., Cormier, J. N., & Armer, J. M. (­2012).
Intermittent pneumatic compression therapy: a systematic review. Lymphology, 45(­1), ­13–​­25.
Francisco, M. A., Colbert, C., Larson, E. A., Sieck, D. C., Halliwill, J. R., & Minson, C. T. (­2021).
Hemodynamics of ­post-​­exercise vs. post hot water immersion recovery. J Appl P ­ hysiol., 30,
1362–1372. https://doi.org/­10.1152/­japplphysiol.00260.2020. Online ahead of print.
Fuller, J. T., Thomson, R. L., Howe, P. R. C., & Buckley, J. D. (­2015). Vibration therapy is no
more effective than the standard practice of massage and stretching for promoting recovery
from muscle damage after eccentric exercise. Clin J Sport Med, 25(­4), ­332–​­337. https://doi.
org/­10.1097/­JSM.0000000000000149.
Gavin, J. P., Myers, S. D., & Willems, M. E. (­2016). Effect of eccentric exercise with reduced mus-
cle glycogen on plasma ­interleukin-​­6 and neuromuscular responses of musculus quadriceps
femoris. J Appl Physiol (­1985), 121(­1), ­173 –​­184. https://doi.org/­10.1152/­japplphysiol.00383.2015.
Grasso, D., Lanteri, P., Di Bernardo, C., Mauri, C., Porcelli, S., Colombini, A., Zani, V., Bonomi,
F. G., Melegati, G., Banfi, G. & Lombardi, G. (­2014). Salivary steroid hormone response to
­whole-​­body cryotherapy in elite rugby players. J Biol Regul Homeost Agents, 28(­2), ­291–​­300.
Hägglund, M., Waldén, M., Magnusson, H., Kristenson, K., Bengtsson, H., & Ekstrand, J.
(­
2013). Injuries affect team performance negatively in professional football: an ­ 11-​­
year
­follow-​­up of the UEFA Champions League injury study. Br J Sports Med, 47(­12), ­738 –​­742.
doi: 10.1136/­­bjsports-­​­­2013-​­092215. Epub 2013 May 3.
Halson, S. L. (­2014). Monitoring training load to understand fatigue in athletes. Sports
Med, 44(­Suppl 2), ­S139–​­S147.
Hawke, T. J., & Garry, D. J. (­2001). Myogenic satellite cells: physiology to molecular biology.
J Appl Physiol, 91, ­534 –​­551. https://doi.org/­10.1152/­jappl.2001.91.2.534.
Herbert, R. D., de Noronha, M., & Kamper, S. J. (­2011). Stretching to prevent or reduce muscle
soreness after exercise. Coch Datab System Rev, 7, CD004577. https://doi.org/­10.1002/­14651858.
CD004577.
Hill, J., Howatson, G., van Someren, K., Leeder, J., & Pedlar, C. (­2014). Compression gar-
ments and recovery from e­ xercise-​­induced muscle damage: a m ­ eta-​­analysis. Br J Sports Med,
48(­18), ­1340–​­1346. https://doi.org/­10.1136/­­bjsports-­​­­2013-​­092456
Hoekstra, S. P., Bishop, N. C., Faulkner, S. H., Bailey, S. J., & Leicht, C. A. (­2008–2018). Acute and
chronic effects of hot water immersion on inflammation and metabolism in sedentary, over-
weight adults. J Appl Physiol, 125. https://doi.org/­10.1152/­japplphysiol.00407.2018.-​­Regular.
Hunkin, S. L., Fahrner, B., & Gastin, P. B. (­2014). Creatine kinase and its relationship with
match performance in elite Australian Rules football. J Sci Med Sport, 17(­3), ­332 –​­336. doi:
10.1016/­j.jsams.2013.05.005.
Hyldahl, R. D., Chen, T. C., & Nosaka, K. (­ 2017). Mechanisms and mediators of the
skeletal muscle repeated bout effect. Exerc Sport Sci Rev, 45(­1), ­24 –​­33. https://­doi.
org/­10.1249/­JES.0000000000000095.
Ingram, J., Dawson, B., Goodman, C., Wallman, K., & Beilby, J. (­2009). Effect of water immer-
sion methods on p ­ ost-​­exercise recovery from simulated team sport exercise. J Sci Med Sport,
12(­3), ­417–​­421. https://doi.org/­10.1016/­j.jsams.2007.12.011.
 Recovery strategies 105
Jacobs, I., Westlin, N., Karlsson, J., Rasmusson, M., & Houghton, B. (­1982). Muscle glycogen
and diet in elite soccer players. Eur J Appl Physiol, 48(­3), ­297–​­302. https://doi.org/­10.1007/
­BF00430219.
Kellmann, M., Bertollo, M., Bosquet, L., Brink, M., Coutts, A. J., Dufffield, R., Erlacher, D.,
Halson, S. L., Hecksteden, A., Heidari, J., Kallus, W., Meeusen, R., Mujika, I., Robazz, C.,
Skorski, S., Venter, R., and Beckmann, J. (­2018). Recovery and performance in sport: consen-
sus statement. Int J Sports Physiol Perform, 13(­2), ­240–​­245.
Kinugasa, T., & Kilding, A. E. (­2009). A comparison of ­post-​­match recovery strategies in youth soc-
cer players. J Strength Cond Res, 23(­5), ­1402–​­1407. https://doi.org/­10.1519/­JSC.0b013e3181a0226a.
Krustrup, P., Mohr, M., Steensberg, A., Bencke, J., Kjaer, M., & Bangsbo, J. (­2006) Muscle and
blood metabolites during a soccer game: implications for sprint performance. Med Sci Sports
Exerc, 38(­6), ­1165 –​­1174. https://doi.org/­10.1249/­01.mss.0000222845.89262.cd
Krustrup, P., Ortenblad, N., Nielsen, J., Nybo, L., Gunnarsson, T.P., Iaia, F.M., Madsen, K.,
Stephens, F., Greenhaff, P., & Bangsbo, J. (­2011). Maximal voluntary contraction force, SR
function and glycogen resynthesis during the first 72 h after a h ­ igh-​­level competitive soccer
game. Eur J Appl Physiol, 111(­12), ­2987 –​­2995. https://doi.org/­10.1007/­­s00421-­​­­011-­​­­1919-​­y
Lee, D. C. W., Lee, S. W. Y., Khaw, K., Ali, A., Sheridan, S. E., & Wong, S. H. S. (­2018). Haemo-
dynamic responses of wearing ­low-​­pressure sports compression tights during an orthostatic
challenge in healthy individuals. J Sci Med Sport, 21(­10), ­1062–​­1067. https://doi.org/­10.1016/­j.
jsams.2017.12.004
Leeder, J., van Someren, K. A., Gaze, D., Jewell, A., Deshmukh, N. I. K., Shah, I., Barker, J., &
Howatson, G. (­2014). Recovery and adaptation from repeated i­ntermittent-​­sprint exercise.
Int J Sports Physiol Perform, 9(­3), ­489 –​­496. doi: 10.1123/­ijspp.­2012-​­0316.
Louis, J., Theurot, D., Filliard, J. R., Volondat, M., Dugué, B., & Dupuy, O. (­2020). The use
of ­whole-​­body cryotherapy: ­time-​­and d ­ ose-​­response investigation on circulating blood cat-
echolamines and heart rate variability. Eur J Appl Physiol, 120(­8), ­1733–​­1743. https://doi.
org/­10.1007/­­s00421-­​­­020-­​­­04406-​­5
Lund, H., ­Vestergaard-​­Poulsen, P., Kanstrup, I. L., & Sejrsen, P. (­1998). The effect of passive
stretching on delayed onset muscle soreness, and other detrimental effects following eccen-
tric exercise. Scand J Med Sci Sports, 8(­4), ­216–​­221.
MacDonald, G. Z., Penney, M. D. H., Mullaley, M. E., Cuconato, A. L., Drake, C. D. J., Behm,
D. G., & Button, D. C. (­2013). An acute bout of s­ elf-​­myofascial release increases range of mo-
tion without a subsequent decrease in muscle activation or force. J Strength Cond Res, 27(­3),
­812–​­821. https://doi.org/­10.1519/­JSC.0b013e31825c2bc1
MacRae, B. A., Cotter, J. D., & Laing, R. M. (­2011). Compression garments and exercise: gar-
ment considerations, physiology and performance. Sports Med, 41(­10), ­815–​­884. https://doi.
org/­10.2165/­­11591420-­​­­0 00000000-​­0 0000.
Malm, C. (­2001). E ­ xercise-​­induced muscle damage and inflammation: fact or fiction? Acta
Physiol Scand, 171(­3), ­233–​­239. https://doi.org/ 10.1046/­j.­1365-​­201x.2001.00825.
Massage, I., Water, C., Herrera, E., Sandoval, M. C., Camargo, D. M., & Salvini, T. F. (­2010).
Motor and sensory nerve conduction are affected differently by ice pack. Phys Therap, 90(­4),
­581–​­591. doi: 10.2522/­ptj.20090131.
Mawhinney, C., Heinonen, I., Low, D. A., Han, C., Jones, H., Kalliokoski, K. K., Kirjavainen,
A., Kemppainen, J., Di Salvo, V., Weston, M., Cable, T., & Gregson, W. (­2020). Changes in
quadriceps femoris muscle perfusion following different degrees of c­ old-​­water
immersion. J Appl Physiol, 128(­5), ­1392–​­1401. https://doi.org/­10.1152/­JAPPLPHYSIOL.00833.2019
Mawhinney, C., Low, D. A., Jones, H., Green, D. J., Costello, J. T., & Gregson, W. (­2017). Cold
water mediates greater reductions in limb blood flow than whole body cryotherapy. Med Sci
Sports Exerc, 49(­6), ­1252–​­1260. https://doi.org/­10.1249/­MSS.0000000000001223.
McHugh, M. P. (­2003). Recent advances in the understanding of the repeated bout effect: the
protective effect against muscle damage from a single bout of eccentric exercise. Scand J Med
Sci Sports, 13(­2), ­88–​­97. https://doi.org/­10.1034/­j.­1600-​­0838.2003.02477.x.
106 Warren Gregson et al.
McHugh, M. P., Connolly, D. A., Eston, R. G., Gleim, G. W. (­1999). ­Exercise-​­induced muscle
damage and potential mechanisms for the repeated bout effect. Sports Med, 27(­3), ­157–​­170.
https://doi.org/­10.2165/­­0 0007256-­​­­199927030-​­0 0002.
Ménétrier, A., Béliard, S., Ravier, G., Mourot, L., Bouhaddi, M., Regnard, J., & Tordi, N.
(­2013). Changes in femoral artery blood flow during thermoneutral, cold, and ­contrast-​­water
therapy. J Sports Med Phys Fit, 55(­­7–​­8), ­768–​­775.
Mero, A., Tornberg, J., Mäntykoski, M., & Puurtinen, R. (­2015). Effects of f­ ar-​­infrared sauna
bathing on recovery from strength and endurance training sessions in men. SpringerPlus,
4(­1), ­1–​­7. https://doi.org/­10.1186/­­s40064- ­​­­015-­​­­1093-​­5.
Nimmo MA, Ekblom B; International Association of Athletics Federations. J Sports Sci.
2007;25 Suppl 1:S93-102. doi: 10.1080/02640410701607379.
Nédélec, M., Halson, S., Delecroix, B., Abaidia, A. E., Ahmaidi, S., & Dupont G. (­2015). Sleep
hygiene and recovery strategies in elite soccer players. Sports Med, 45(­11), ­1547–​­1559. doi:
10.1007/­­s40279-­​­­015-­​­­0377-​­9.
Nédélec, M., McCall, A., Carling, C., Legall, F., Berthoin, S., & Dupont, G. (­2012). Recovery in
soccer: part I­ -​­­post-​­match fatigue and time course of recovery. Sports Med, 42(­12), ­997–​­1015.
https://doi.org/­10.2165/­­11635270-­​­­0 00000000-​­0 0000.
Nédélec, M., McCall, A., Carling, C., Legall, F., Berthoin, S., & Dupont, G. (­2013). Recovery in
soccer : part ­i i-​­recovery strategies. Sports Med, 43(­1), ­9 –​­22. https://doi.org/­10.1007/­­s40279- ­​­­012-
­​­­0 002-​­0
Partsch, H., & Mosti, G. (­2008). Thigh compression. Phlebol Ven Forum Royal Soc Med, 23(­6),
­252–​­258. doi.org/­10.1258/­phleb.2008.008053.
Peake, J. M., & Gandevia, S. C.(­2017). Replace, restore, revive: the keys to recovery after exer-
cise. J Appl Physiol, 122(­3), ­531–​­532. doi: 10.1152/­japplphysiol.00086.2017.
Peake, J. M., Markworth, J. F., Cumming, K. T., Aas, S. N., Roberts, L. A., Raastad, T.,
­Cameron-​­Smith, D., & Figueiredo, V. C. (­2020). The effects of cold water immersion and
active recovery on molecular factors that regulate growth and remodeling of skeletal muscle
after resistance exercise. Front Physiol, 11. https://doi.org/­10.3389/­fphys.2020.00737.
Peake, J., Nosaka, K., & Suzuki, K. (­2005). Characterization of inflammatory responses to
eccentric exercise in humans. Exer Immunol Rev, 11, ­64–​­85.
Pooley, S., Spendiff, O., Allen, M., & Moir, H. J. (­2020). Comparative efficacy of active recovery
and cold water immersion as ­post-​­match recovery interventions in elite youth soccer. J Sports
Sci, 38(­­11–​­12), ­1423–​­1431. https://doi.org/­10.1080/­02640414.2019.1660448
Pyne, D. B., & Martin, D. T. (­2011). Fatigue insights from individual and team sports. In
Marino, F. E. (­ed.), Regulation of Fatigue in Exercise, p­p. 1­ 77–​­185. New York: Nova Science.
Russell, M., Birch, J., Love, T., Cook, C. J., Bracken, R. M., Taylor, T., Swift, E., Cockburn,
E., Finn, C., Cunningham, D., Wilson, L., & Kilduff, L. P. (­2017). The effects of a single
­whole-​­body cryotherapy exposure on physiological, performance, and perceptual responses
of professional academy soccer players after repeated sprint exercise. J Strength Cond Res,
31(­2), ­415– ​­421. doi: 10.1519/­JSC.0000000000001505.
Schoenfeld, B. J. (­2013). ­Post-​­exercise hypertrophic adaptations: a r­ e-​­examination of the hor-
mone hypothesis and its applicability to resistance training program design. J Strength Cond
Res, 27(­6), ­1720–​­1730. https://doi.org/­10.1519/­JSC.0b013e31828ddd53.
Silva, J. R., Rumpf, M. C., Hertzog, M., Castagna, C., Farooq, A., Girard, O., Hader, K. (­2018).
Acute and residual soccer ­match-​­related fatigue: a systematic review and ­meta-​­analysis.
Sports Med, 48(­3), ­539–​­583. https://doi.org/­10.1007/­­s40279-­​­­017-­​­­0798-​­8.
­Sinha-​­Hikim, I., Roth, S. M., Lee, M. I., & Bhasin, S. (­2013). ­Testosterone-​­induced muscle
hypertrophy is associated with an increase in satellite cell number in healthy, young men.
Am J ­Physiol-​­E ndocrinol Metab, 285, ­E197–​­E205. https://doi.org/­10.1152/­ajpendo.00370.2002.
Skein, M., Duffield, R., Edge, J., Short, M. J., & Mündel, T. (­2011). I­ ntermittent-​­sprint per-
formance and muscle glycogen after 30 h of sleep deprivation. Med Sci Sports Exerc, 43(­7),
­1301–​­1311. doi: 10.1249/­MSS.0b013e31820abc5a.
 Recovery strategies 107
Skein, M., Duffield, R., Minett, G. M., Snape, A., & Murphy, A. (­2013). The effect of overnight
sleep deprivation after competitive rugby league matches on postmatch physiological and
perceptual recovery. Int J Sports Physiol Perform, 8(­5), ­556–​­564. doi: 10.1123/­ijspp.8.5.556.
Skorski, S., Schimpchen, J., Pfeiffer, M., Ferrauti, A., Kellmann, M., & Meyer, T. (­2020). Effects
of postexercise sauna bathing on recovery of swim performance. Int J Sports Physiol Per-
form, 15(­7), ­934–​­940. https://doi.org/­10.1123/­ijspp.­2019-​­0333.
Smith, L. L., Anwar, A., Fragen, M., Rananto, C., Johnson, R., & Holbert, D. (­2000). Cytokines
and cell adhesion molecules associated with ­h igh-​­intensity eccentric exercise. Eur J Appl
Physiol, 82(­­1–​­2), ­61– ​­67. https://doi.org/­10.1007/­s004210050652.
Sterczala, A. J., Flanagan, S. D., Looney, D. P., Hooper, D. R., Szivak, T. K., Comstock, B. A.,
DuPont, W. H., Martin, G. J., Volek, J. S., Maresh, C. M., & Kraemer, W. J. (­2014). Similar
hormonal stress and tissue damage in response to National Collegiate Athletic Association
Division I football games played in two consecutive seasons. J Strength Cond Res, 28(­11),
­3234–​­3238. https://doi.org/­10.1519/­JSC.0000000000000467.
­Stults-​­Kolehmainen, M. A., Bartholomew, J. B., & Sinha, R. (­2014). Chronic psychological
stress impairs recovery of muscular function and somatic sensations over a 9­ 6-​­hour period. J
Strength Cond Res, 28(­7), ­2007–​­2017. doi: 10.1519/­JSC.0000000000000335.
Suzuki, K., Nakaji, S., Yamada, M., Totsuka, M., Sato, K., & Sugawara, K. (­2002). Systemic
inflammatory response to exhaustive exercise: cytokine kinetics. Exer Immunol Rev, 8,
­6 – ​­48.
Tee, J. C., Bosch, A. N., & Lambert, M. I. (­2007). Metabolic consequences of ­exercise-​­i nduced mus-
cle damage. Sports Med, 37(­10), ­827–​­836. https://doi.org/­10.2165/­­0 0007256-­​­­200737100-​­0 0001
Thomson, D., Gupta, A., Arundell, J., & Crosbie, J. (­2015). Deep ­soft-​­tissue massage applied
to healthy calf muscle has no effect on passive mechanical properties: a randomized, s­ ingle-​
­blind, ­cross-​­over study. BMC Sports Science, Med Rehab, 7, 21. https://­doi.org/­10.1186/­­s13102-­​­­
015-­​­­0 015-​­8
Thorpe, R. T., Atkinson, G., Drust, B., & Gregson, W. (­2017). Monitoring fatigue status in
elite team sport athletes: implications for practice. Int J Sports Physiol Perform, 12(­Suppl 2),
­S227–​­S234. doi: 10.1123/­ijspp.­2016-​­0434.
Upton, C. M., Brown, F. C. W., & Hill, J. A. (­2017). Efficacy of compression garments on re-
covery from a simulated rugby protocol. J Strength Cond Res, 31(­11), ­2977–​­2982. https://doi.
org/­10.1519/­JSC.0000000000002145.
Vaile, J., Halson, S., Gill, N., & Dawson, B. (­2008). Effect of hydrotherapy on the signs and
symptoms of delayed onset muscle soreness. Eur J Appl Physiol, 102(­4), ­447–​­455. https://doi.
org/­10.1007/­­s00421-­​­­0 07-­​­­0605-​­6.
Venter, R. E. (­2014). Perceptions of team athletes on the importance of recovery modalities.
Eur J Sport Sci, 14(­Suppl 1), ­S69–​­S76. doi: 10.1080/­17461391.2011.643924.
Verma, S., Moiz, J. A., Shareef, M. Y., & Husain, M. E. (­2016). Physical performance and mark-
ers of muscle damage following s­ port-​­specific sprints in male collegiate soccer players:
repeated bout effect. J Sports Med Phys Fitness, 56(­6), ­765–​­774.
Versey, N. G., Halson, S. L., & Dawson, B. T. (­2013). Water immersion recovery for athletes: ef-
fect on exercise performance and practical recommendations. Sports Med, 43(­11), ­1101–​­1130.
https://doi.org/­10.1007/­­s40279- ­​­­013- ­​­­0 063-​­8
Viitasaslo, J. T., Niemelä, K., Kaappola, R., Korjus, T., Levola, M., Mononen, H. V, Rusko,
H. K., & Takala, T. E. (­1995). Warm underwater w ­ ater-​­jet massage improves recovery from
intense physical exercise. Eur J Appl Physiol, 71(­5), ­431–​­438.
Vromans, B. A., Thorpe, R. T., Viroux, P. J., & Tiemessen, I. J. (­2019). Cold water immersion
settings for reducing muscle tissue temperature: a linear ­dose-​­response relationship. J Sports
Med Phys Fitness, 59(­11), ­1861–​­1869. https://doi.org/­10.23736/­­S0022-​­4707.19.­09398-​­8.
Warren, G. L., Lowe, D. A., & Armstrong, R. B. (­1999). Measurement tools used in the study of ec-
centric ­contraction-​­i nduced injury. Sports Med, 27(­1), ­43–​­59. https://doi.org/­10.2165/­­0 0007256-
­​­­199927010-​­0 0004.
108 Warren Gregson et al.
Waterhouse, J., Atkinson, G., Edwards, B., Reilly, T. (­2007). The role of a short ­post-​­lunch nap
in improving cognitive, motor, and sprint performance in participants with partial sleep dep-
rivation. J Sports Sci, 25(­14), ­1557–​­1566. doi: 10.1080/­02640410701244983.
Wilson, L. J., Cockburn, E., Paice, K., Sinclair, S., Faki, T., Hills, F. A., Gondek, M. B., Wood,
A., & Dimitriou, L. (­2018). Recovery following a marathon: a comparison of cold water im-
mersion, whole body cryotherapy and a placebo control. Eur J Appl Physiol, 118(­1), ­153–​­163.
https://doi.org/­10.1007/­­s00421- ­​­­017-­​­­3757-​­z.
Wiltshire, E. V., Poitras, V., Pak, M., Hong, T., Rayner, J., & Tschakovsky, M. E. (­2010). Mas-
sage impairs postexercise muscle blood flow and “­lactic acid” removal. Med Sci Sports Exerc,
42(­6), ­1062–​­1071. doi: 10.1249/­MSS.0b013e3181c9214f.
Yarrow, J. F., Borsa, P. A., Borst, S. E., Sitren, H. S., Stevens, B. R., & White, L. J. (­2007). Neu-
roendocrine responses to an acute bout of ­e ccentric-​­enhanced resistance exercise. Med Sci
Sports Exerc, 39(­6), ­941–​­947. https://doi.org/­10.1097/­mss.0b013e318043a249.
Zelikovski, A., Kaye, C. L., Fink, G., Spitzer, S. A., & Shapiro, Y. (­1993). The effects of the mod-
ified intermittent sequential pneumatic device (­MISPD) on exercise performance following
an exhaustive exercise bout. Br J Sports Med, 27(­4), ­255–​­259.
Section B

Social and Behavioural Sciences

7 Psychological characteristics of
players
Geir Jordet and Tynke Toering

Introduction
In 1958, Brazil wins the World Cup, and a spectacular 1­ 7-­​­­year-​­old named Pele scores
six goals, including two in the final. Brazil had a team psychologist on staff, Dr Joao
Carvalhaes (­for full story, see FIFA, 2016). Ahead of departure to the tournament in
Sweden, he strongly advised against Pele featuring, saying: “­He is too young to feel
aggression and respond with appropriate force. In addition to that, he does not possess
the sense of responsibility necessary for a team game.” However, Brazil coach Feola
rejected the psychologist’s advice with these words: “­You may be right. The thing is
you don’t know anything about football. If Pele’s knee is ready, he plays.” Since this
historical encounter between a psychologist and a soccer coach, the integration of
psychology and soccer knowledge may still be an “­Achilles heel” for psychologists.
However, the field has made substantial strides, and in this chapter, we attempt to
point this out.
In a survey of soccer coaches in the Netherlands about what they want from sports
science, the area that most identified as of interest was “­mental skills” and the area
that they had the least knowledge of was “­mental skills” (­Brink et al., 2018). Further-
more, in the previous edition of this book, Pain and Harwood (­2013) pointed out that
the research and general interest in the mental side of the game had increased a lot over
the past decade. This growth has continued since then. A search for p ­ eer-​­reviewed
articles in the database Sport Discus (­in February 2021) with keywords “­soccer” and
“­psychology” generated 2,538 publications. This reflects a doubling of outputs in only
7 years (­from the 1,167 hits that were found in the same search in May 2014, Jordet,
2016) (­for an overview of the y­ ear-­​­­by-​­year development in published articles on soccer
and psychology, see ­Figure 7.1).
In this chapter, we primarily review and discuss research published over the last
­5 –​­8 years (­since Jordet, 2016; Pain & Harwood, 2013). We will not be able to review
everything, but we cover a selection of topics that will have an impact on the field for
the years to come. Our major distinction is between performance and development.
Where possible, we aim to move beyond the traditional s­ elf-​­report research in sport
psychology (­i.e., questionnaires and interviews) to report more observation and exper-
imental research.

DOI: 10.4324/9781003148418-9
112 Geir Jordet and Tynke Toering

­Figure 7.1 The number of peer review articles from a search with keywords “­psychology”
and “­soccer”, registered in the bibliographic database SPORT Discus between
2001 and 2020.

Performance
In this section, we examine some of the recent knowledge that has emerged about the
psychology of game performance, presenting what we know about skilled players’ re-
sponses to game events, location, confidence, and emotions.

Game events
Soccer players’ ­decision-​­making is reported to be highly influenced by transient and
dynamic aspects of the game that they play, such as their own performance, the score,
and the momentum in the game, which makes them vulnerable to external factors
beyond their own control (­Levi & Jackson, 2018). Psychological momentum can be
described as a state of mind where a performer senses that events are going his or her
way, and the accompanied perceived competitive superiority, attribution of success
to oneself, and increased confidence contributes to an experience of a psychological
force that enables a performer to achieve levels ordinarily not possible (­­Iso-​­Ahola &
Dotson, 2014). Whether momentum in sport is a real phenomenon has been heavily
debated by scientists, with cases being made for this simply being an illusion (­e.g.,
Avugos, Köppen, Czienskowski, Raab, & ­Bar-​­Eli, 2013). However, in a relatively re-
cent and thorough review, it is argued that methodological and statistical problems
have tended to preclude what probably is a real effect, and that psychological momen-
tum exists as a powerful empirical phenomenon, yet one that is occurring occasionally
and temporarily (­­Iso-​­Ahola & Dotson, 2014).
With that said, there are few comprehensive and ­well-​­designed empirical tests of
momentum and individual or team performance in or across soccer games. However,
in a study of all soccer penalty shootouts in the World Cup and European Champion-
ships between 1976 and 2006 (­Jordet, Hartman, & Vuijk, 2011), there was evidence of
historical dependency, where players on teams who had lost their preceding shootout
in one of these tournaments performed worse than players on teams with a preceding
 Psychological characteristics of players 113
win. Although this effect took place over years, sometimes even decades, it is possible
that the emotional magnitude of these events (­p enalty shootouts) would constitute a
type of momentum. In another recent study, an analysis of a vast number of games
(­N = 72,426) shows that scoring right before h ­ alf-​­time increases the chances of the
scoring team to win (­Greve, Nesbø, Rudi, & Salikhov, 2020). This is not evidence of
momentum per se, but it is an indication that certain game events carry particularly
high importance for future game events and the outcome.
Recently, researchers obtained the perceptions of psychological momentum from
a total of 85 professional soccer players (­­Redwood-​­Brown, Sunderland, Minniti, &
O’Donoghue, 2018). They found that goals were the game events most frequently asso-
ciated with momentum. Confidence, positive attitude, and team cohesion were impor-
tant for positive momentum, whereas low confidence and high anxiety were important
for negative momentum. Moreover, an experiment with 40 experienced French soccer
coaches (­w ith UEFA A or Pro licenses) showed that momentum was a strong influen-
tial factor in strategic game decisions (­Briki & Zoudji, 2019). Specifically, the study
documented that changes in ball possession affected the coaches’ perception of mo-
mentum, and this again influenced their strategic decisions, with the interesting obser-
vation that negative events had a stronger affective effect than positive events.
From these studies, it seems certain game events carry the potential to influence
psychological factors, which in turn will influence performance. However, it is sur-
prising that more research has not been conducted to identify specific game events and
conditions that might affect the outcome of soccer games via psychological processes.

Game location
Another focus of research has been on the home advantage. This can be defined as
the tendency that the home team is taking more points than the away team, which is
­well-​­known and documented in soccer (­at the top level, Pollard & Gomez, 2014; and at
the youth level, Staufenbiel, Riedl, & Strauss, 2018). Some of the reasons hypothesized
to produce home advantage have received empirical support in soccer, such as crowd
support (­Ponzo & Scoppa, 2018), venue familiarity (­van Ours, 2019), travel fatigue
(­Oberhofer, Philippovich, & Winner, 2010), and territoriality (­Neave & Wolfson, 2003).
These reasons were all supported in interviews with ­professional-​­level soccer players
and coaches, from which also, notably, there was a united agreement that crowd sup-
port was very important (­Forthergill, Wolfson, & Little, 2014).
In perhaps the most comprehensive study to date, Pollard and Gomez (­2014) ana-
lysed a total of 157 national soccer leagues in the period ­2006–​­2012 (­spanning about
170,000 games). The results showed a robust home advantage across the world. Among
the most contributing factors were the FIFA ranking (­proxy for crowd size), distance
between game locations, altitude difference between game locations, the occurrence
of a civil war, and perception of corruption. The five countries with the highest home
advantage in the world (­i.e., #1 Nigeria, #2 B ­ osnia-​­Herzegovina, #3 Guatemala, #4
Indonesia, and #5 Algeria) all have regional ethnic division and/­or a history of civil
wars, which supports a view that territoriality is an influential factor for home ad-
vantage. This adds to the findings by Neave and Wolfson (­2003) that players for home
teams (­in the United Kingdom) have increased testosterone levels compared to away
team players (­indicating that territoriality or an intention to protect the home turf is
a factor). Recently, this was elaborated on in a study where observers were asked to
114 Geir Jordet and Tynke Toering
assess whether randomly collected photos taken prior to UEFA Champions League
(­and amateur) games showed home or away players (­Furley, Schweizer, & Memmert,
2018). The observers were indeed able to identify the players who played home or away,
and home players were perceived to have a more dominant body language (­significantly
more assertive, confident, and aggressive) than the ­away-​­players.
­Covid-​­19 made it possible for researchers to conduct natural experiments on the
effects of playing without crowds. In certain leagues, the home advantage without
crowds dropped significantly, and occasionally turned into a home disadvantage (­e.g.,
in the German Bundesliga, where teams took 54% of the points with crowds and 44%
without crowds, Tilp & Thaller, 2020). A report comparing 63 major soccer leagues on
the number of h ­ ome-​­wins with normal crowds (­January 2­ 015–​­March 2020) and with-
out crowds (­­April–​­August 2020) shows more variation across leagues, but with h ­ ome-​
­w ins dropping in 65% of the leagues (­41 of 63) and a total of 2.1% drop in ­home-​­wins
when playing without crowd (­CIES Football Observatory, 2020). This finding suggests
that crowd support is a considerable factor to explain the home advantage. Moreover,
a study of Red Bull Salzburg players’ behaviours with and without crowds, showed
that the players were involved in about 20% fewer emotional situations in games with-
out crowd, than with crowd (­e.g., s­ elf-​­reproaching, protesting, and discussions, Leit-
ner & Richlan, 2021). The researchers argue that without the impact of supporters,
players, and staff behaved less emotionally.

Confidence
There seems to be a robust link between s­ elf-​­confidence and performance in soccer
players (­e.g., Bray, Balaguer, & Duda, 2003). Interviews show that players’ confidence
in a game is most impacted by a player’s own game performance, the result in that
game, and game momentum, with positive events leading players to more risky de-
cisions and negative events to more conservative decisions (­Levi & Jackson, 2018).
Academy soccer players (­­12–​­15 years of age) were most confident about aspects of their
skill execution, compared to physical and psychological aspects, whereas c­ onfidence-​
­debilitative factors cited were lack of social support, weak performances, bad prepa-
ration, pressure and expectations, and injury/­illness (­Thomas, Thrower, Lane, &
Thomas, 2019).
Most research on confidence has relied on s­ elf-​­report measures, and we now turn
to a perspective focusing on ­on-​­pitch behaviours. In major soccer penalty shootouts,
it has been shown that players taking ­so-​­called positive shots (­where a potential goal
immediately would secure the win) score considerably more goals than players with
negative shots (­where a miss immediately would cement a loss) (­Jordet & Hartman,
2008). This says something quite powerful about the indirect and likely influence of
­pre-​­performance hopes, fears, and/­or expectations on performance in h ­ igh-​­pressure
moments. In addition, in the leadup to their shots, players with positive shots showed
significantly more approach behaviours (­maintained their gaze looking forward and
took time after the referee’s whistle to start the r­ un-​­up), than did the players with neg-
ative shots (­who showed more avoidance b ­ ehaviours – ​­diverted their gaze and rushed
their shot preparations).
Furley, Dicks, Stendke, and Memmert (­2012) exposed 20 experienced goalkeepers to
­point-​­light video clips of penalty shooters exhibiting these exact approach and avoid-
ance behaviours. The results supported and added to the results from the field studies,
 Psychological characteristics of players 115
as the goalkeepers’ impressions of the shooters were less favourable, and they were
more confident in saving penalties, against shooters that turned their back towards
them and rushed through their preparation. In further studies, it is ­well-​­documented
that soccer players with a dominant body language (­e.g., erect posture, limbs slightly
spread to occupy space, eyes looking directly at the viewer, and maintaining that gaze)
are viewed more positively, are expected to perform better (­Furley, Dicks, & Mem-
mert, 2012; Bijlstra, Furley, & Nieuwenhuys, 2020), and inspire more confidence in
­teammates – ​­even when additional (­and even contradictory) information is introduced
about teammates’ performance capability (­Seiler, Schweizer, & Seiler, 2018) than those
with a submissive body language. Moreover, additional experiments showed that those
feeling confident displayed a more dominant, confident, and composed body language
compared to those feeling more under threat (­task demands exceeded their coping re-
sources) (­Brimmel, Parker, Furley, & Moore, 2018) and professional Bundesliga soccer
referees who made decisions on ambiguous situations showed a less confident body
language than referees making decisions about less ambiguous situations (­Furley &
Schweizer, 2016). These studies strongly document the impact of soccer players’ confi-
dence on performance, one’s own and that of others (­both teammates and opponents)
and the behavioural signs that one can look for when assessing confidence.

Emotions
Emotional expressions in soccer have been studied in different ways, some quite cre-
ative. For example, researchers found that displays of anger and happiness in 4,318
portrait pictures of players from 304 participating teams in all the FIFA World Cup
tournaments between 1970 and 2014 were positively correlated with team performance
in the World Cup (­Hopfensitz & Mantilla, 2019). Specifically, teams whose players
displayed more anger conceded significantly fewer goals, and teams whose players dis-
played more happiness scored significantly more goals. Furthermore, teams whose
players’ national anthem singing (­N = 102 anthems) were rated by observers as more
passionate and intense were less likely to concede goals, and more likely to win their
subsequent game (­in the knockout stage) in the 2016 European Championships (­Slater,
Haslam, & Steffens, 2018). The researchers argue that these effects may have occurred
as a result of increased social identity in the teams whose national anthems are deliv-
ered with a strong passion.
Focusing on the impact of p ­ ost-​­performance behaviours, it was shown that play-
ers celebrating a goal increase their chance of ultimately ending up on the winning
team in major penalty shootouts (­Moll, Pepping, & Jordet, 2010). Certain celebratory
gestures significantly reduced the chance that the subsequent opponent would score
a goal, and there was a ­non-​­significant trend that the next teammate’s probability of
scoring a goal would go up. These results were supported across four experiments,
where observing opponents and teammates showing pride after their shots had the
expected effect on stress, confidence, and focus (­Furley, Moll, & Memmert, 2015). For
example, observing teammates displaying pride made players expect to be more confi-
dent and perform better on upcoming shots than when observing teammates display-
ing a neutral expression. Recent studies extend these findings by showing that coach
expressions of emotions influence their players’ emotions, and the coach’s expressions
of pride and happiness were associated with increased player performance (­Moll &
Davies, 2021; van Kleef, Chesin, Koning, & Wolf, 2019). The practical implication
116 Geir Jordet and Tynke Toering
of these studies is that soccer players, teams, and coaches can benefit from showing
happiness and pride, as these expressions are likely to affect performance positively.

Development
Researchers have identified many psychological characteristics potentially related to
talent development (­TD) in soccer; and a recent review revealed 22 psychological fac-
tors: “­discipline, ­self-​­control, ­self-​­awareness, adaptive perfectionism, ­self-​­acceptance,
task/­mastery orientation, commitment, determination, intrinsic motivation, ­ self-​
r­egulation, resilience, grit, ­ non-​­ verbal intelligence, fear of failure, psychological
wellbeing, reflective skills, enjoyment, perceived competence, anticipatory skills,
­decision-​­making skills, delaying gratification and coping strategies” (­Gledhill, Har-
wood, & Forsdyke, 2017, ­p. 105). However, it remains largely unknown how these psy-
chological factors eventually relate to adult performance.

Lack of knowledge about underlying mechanisms

Being aware that psychological factors are just one part of the puzzle, important
reasons for the limited knowledge about the psychology of development seem to be
that the majority of studies have been conducted solely with youth participants (­e.g.,
Erikstad, Høigaard, Johansen, Kandala, & Haugen, 2018; Zuber, Zibung, & Conzel-
mann, 2015), have based their predictions of eventual adult performance on players’
score as an academy player years ago (­e.g., Forsman, Blomqvist, Davids, Liukko-
nen & Konttinen, 2016; Van Yperen, 2009), and have primarily focused on the success
stories rather than the “­failures” (­exceptions are Holt & Mitchell, 2006; Taylor &
Collins, 2019). Longitudinal studies about the exact relationship between psycho-
logical factors and the outcomes of transitions along the talent pathway to fi ­ rst-​­team
soccer are lacking, as confirmed by a recent ­meta-​­analysis based on 11 prospective
studies, 10 of which were conducted solely with youth players (­three studies predicted
adult performance based on academy scores; Ivarsson, K ­ ilhage-​­Persson, Martin-
dale, Priestley, Huijgen, Ardern, & McCall, 2020). The lack of knowledge about
mechanisms underpinning successful transition into the senior professional context
warrants questions, such as whether a specific combination of predictors is equally
important throughout development and across individuals and contexts. Alterna-
tively, we agree with several other researchers that a broad range of psychological
attributes is needed to face these transitions regardless (­cf., Collins, MacNamara &
Cruickshank, 2019; Jordet, 2016).

Transition to professional soccer

It has been pointed out before that the context of professional soccer is very different
from academy soccer (­e.g., Røynesdal, Toering, & Gustafsson, 2018; Swainston, Wil-
son, & Jones, 2020); young players move from a relatively supportive, d ­ evelopment-​
­
focused environment in the academy to the brutal, ­ short-​­
term s­uccess-​­
driven
environment of professional soccer. The chances of succeeding and becoming a pro-
fessional soccer player are small, knowing that only 0.04% of all people playing soccer
are professional players (­Haugaasen & Jordet, 2012). To further complicate the pro-
cess, the age range in which the transition to professional soccer takes place comes
 Psychological characteristics of players 117
around the same time as several other developmental challenges, such as growing from
adolescence into young adulthood and dual career demands, while pressure from par-
ents, coaches, and support staff to continuously perform well may impact on players’
performance and wellbeing (­e.g., Morris, Tod, & Eubank, 2017; Morris, Tod & Oliver,
2016). In line with this, a ­meta-​­study on factors positively associated with a success-
ful ­junior-­​­­to-​­senior transition in sports included a long list of psychological aspects
(­Drew, Morris, Tod, & Eubank, 2019).
Specifically, soccer research has shown that, while male youth players tend to be
aware that men’s soccer is going to be completely different than academy soccer in
terms of physical demands, playing style, ­decision-​­making demands, and fitting in
socially (­e.g., Morris et al., 2017; Swainston et al., 2020), dealing with several of these
challenges for real often turns out to be difficult (­e.g., Champ, Nesti, Ronkainen,
Tod, & Littlewood, 2020). Players’ experiences being part of the first squad for a while
are characterized by frustration related to being on the bottom of the pile, as well
as motivation to improve as a player (­e.g., Mitchell, Gledhill, Nesti, Richardson, &
Littlewood, 2020; Swainston et al., 2020). To not be prioritized as challenging and can
affect player confidence. They try to find out what the ­fi rst-​­team coach wants from
players in their position. Being sent on loan could be a good or bad experience, largely
dependent on the received amount of playing time and availability of psychological
skills to handle switching clubs (­Champ et al., 2020; Mitchell et al., 2020; Swainston
et al., 2020). If a club is happy to have you and you get to play, it boosts your confi-
dence; if not, being a soccer player can be very lonely. Furthermore, impression man-
agement could be essential; young players must make sure that senior professionals
perceive them as credible cases (­Røynesdal et al., 2018). Other challenges could be
dealing with the fact that you have to grasp an opportunity once you get it, pressure
from parents and friends, living away from home, and dealing with success (­new sta-
tus, media attention, friends/­g irlfriends; e.g., Champ et al., 2020; Mitchell et al., 2020;
Morris et al., 2017).
Social support seems particularly important for successful transitions to profes-
sional. For example, being on a U23 team may help, given that others in the team are
in the same situation (­transitioning) and talking about experiences is experienced as
helpful (­e.g., Swainston et al., 2020). Some players seem hesitant to speak with ­first-​
t­ eam players or the ­first-​­team coach for fear of being regarded as weak. Support from
coaches seems to become more important later in the process (­Morris et al., 2017) and
it has been suggested that organizational support by clubs should be improved (­e.g.,
Champ et al., 2020; Morris et al., 2017; Røynesdal et al., 2018). Although female players
transitioning to the professional level report similar factors affecting their transition
as their male counterparts, one difference seems to be that they do seek social support
from senior players (­McGreary, Morris, & Eubank, 2021). The latter could be related
to a less masculine culture within women’s football, with different key values. Another
key aspect is that dual career issues were pertinent due to the recent professionali-
zation of women’s soccer, meaning that young players could spend less time on their
education given that more time was devoted to their sport (­McGreary et al., 2021).

Behavioural outcomes
It is clear then that the development of a broad range of psychological attributes is
necessary to help players develop throughout the academy pathway and transition
118 Geir Jordet and Tynke Toering

9.
Cope with
pressure

10.
11. Perceive and 7.
Cope with control game Cope with
success dynamics adversity

6. 8.
Manage Manage
relationships transitions

3. 4. 5. 2.
Self-regulate Embrace the Optimize Aspire to
learning joy of playing energy football
process the game balance excellence

1.
Confidently
express identity
and values

­Figure 7.2 The ­11-​­model. Behavioural outcomes that are important to successfully transi-
tion from youth academy to professional first team. Adapted from Jordet, 2016.

into professional soccer. ­Figure 7.2 presents an updated model with behavioural out-
comes we suggest is important to successfully traverse the bumpy path from youth
academy to professional soccer (­cf., Jordet, 2016). These behavioural outcomes are
underpinned by a broad range of psychological attributes. Researchers have indicated
the importance of confidence, its relationship with body language, and expressing
one’s identity and values (­e.g., Brimmel et al., 2018; Champ et al., 2020), as well as opti-
mally balancing one’s energy (­e.g., McLoughlin, Fletcher, Slavich, Arnold, & Moore,
2021). Together with embracing the joy of playing the game (­e.g., Zuber, Zibung, &
Conzelmann, 2015), taking care of and resonating optimal mental and physical fit-
ness, and a healthy sense of self are essential building blocks for both performance
and w ­ ell-​­being. Additionally, players must aspire to excellence, which sometimes
means sacrificing s­ hort-​­term comfort (­e.g., Toering & Jordet, 2015), s­ elf-​­regulate their
learning (­e.g., Toering, in press), manage transitions (­e.g., Roynesdal et al., 2018), man-
age relationships (­e.g., Taylor & Collins, 2019), perceive and control game dynamics
(­e.g., Jordet et al., 2020), cope with adversity (­e.g., Ivarsson et al., 2020), cope with
pressure (­e.g., Furley, Dicks, & Jordet, 2020), and cope with success (­e.g., Taylor &
Collins, 2019). Academy players need to be educated and supported in developing all
these behavioural outcomes to flexibly deal with transitions and key events on their
pathway to professional soccer.
The capacity to display the behavioural outcomes in ­ Figure 7.2 is expected
to increase players’ ability to ­self-​­regulate their behaviour, in that the increased
 Psychological characteristics of players 119
c­ ognitive-​­behavioural flexibility frees up resources that now can be used to optimally
perform or pick up the lessons to be learned (­Toering, in press). One specific way
to work on the latter is v­ ideo-​­feedback which coaches and youth players reported to
regard as beneficial for several psychological processes previously highlighted in the
literature (­Middlemas & Harwood, 2018), such as imagery and ­self-​­regulation (­Collins
et al., 2019; Toering, ­Elferink-​­Gemser, Jordet, & Visscher, 2009), as well as contrib-
ute to the encouragement of ­self-​­regulatory skills. Reflective thinking was specifi-
cally identified as a key process in coping with setbacks and learning from mistakes
(­Middlemas & Harwood, 2018, 2020).

Future directions and conclusions

There has been a considerable growth in research on psychology in soccer this past
decade, but some biases are still at play t­hough – ​­with substantially more research
on male players compared to women, and as this review reflects, there is a lot of re-
search from the United Kingdom, Germany, the Netherlands, and Scandinavia, and
less from many other parts of the world. Recently, a case was made that in the future
psychology research will be more s­ occer-​­specific, explore more the integration with
analytics, and rely more on technology (­Jordet, 2019). Here, we will elaborate and add
some nuance to some of these points.
Generally, there is still too little research on psychology in soccer where the game
itself is the centre of attention. Traditionally, sport psychology researchers are more
interested in the psychological process in question, rather than how the process relates
to the game itself (­for more on this issue, see Jordet & Pepping, 2019). This is one of
the reasons that the penalty kick has been researched quite extensively; it is a closed
skill executed under relatively controlled conditions, lending itself well to psycholog-
ical experiments and analyses. Going forward, we hope to see more research on the
ways that psychological aspects support and facilitate performance in dynamic, open
play games. To achieve this, researchers need to embrace the game and ask research
questions that originate from people in soccer. Game location and momentum are
good examples of areas where the game can drive research questions, because those
involved in the sport will easily recognize the impact of these areas on performance
and results. However, there is still very limited knowledge about both the specific be-
havioural mechanisms at play, and ways to address this in practice for players, teams,
and coaches. In this chapter, we have presented some studies that have started to close
this gap (­e.g., Furley et al. 2018).
We have also shown how analyses of behaviours have become more popular, in-
cluding some impressive work on ­non-​­verbal communication. However, much more
research is needed on physical manifestations of psychology, observable, and measur-
able, which can enable and support ­on-​­field observations and measurements (­Shiperd
et al., 2018). It is long overdue that psychology meets game analytics, to give analyses of
individual and team behaviours in soccer games, combining psychological constructs
with the methodological precision and rigour from analytics, which would be useful
for both performance and development. A recent example is our own study on visual
perception in a Premier League team, where videos of real games were filmed and a
behavioural indication of perception prior to receiving the ball (­i.e., scanning, where
the face and eyes are moved away from the ball to detect information relevant for en-
gaging with the ball) was analysed with the help of game analysts and data analysts at
120 Geir Jordet and Tynke Toering
the club (­Jordet et al., 2020). This research produced a detailed understanding of how
scanning systematically varies in games and how it is linked to performance.
Finally, we are likely to see much more sophisticated use of technology to better un-
derstand and affect players’ psychology. Computer vision (­to automatically code be-
haviours), artificial intelligence (­to more effectively interpret patterns in behavioural
data), and virtual/­augmented reality (­to more effectively simulate and train game sit-
uations) are all technologies that not only belong to the future, but they are also cur-
rently used now. More research is needed into the effective use of this technology, to
benefit the research and applied field.
In conclusion, all these points stress the increasing importance of the context. It also
indicates that more interdisciplinary research is necessary to enable a useful trans-
lation of findings to the practice field because only then we will be able to capture
enough of the complexity of the context. This will help advance the psychological side
of the game as well as the psychological development of soccer players from the acad-
emy to professional environments.

References
Avugos, S., Koppen, J., Csienskowski, U., Raab, M., & ­Bar-​­Eli, M. (­2013). The “­hot hand” recon-
sidered: a ­meta-​­analytic approach. Psychology of Sport and Exercise, 14, ­21–​­27. doi:10.1016/­j.
psychsport.2012.07.005
Bijlstra, G., Furley, P., & Nieuwenhuys, A. (­2020). The power of nonverbal behavior: ­p enalty-​
­takers’ body language influences impression formation and anticipation performance in
goalkeepers in a simulated soccer penalty task. Psychology of Sport and Exercise, 46, 1.
Bray, S. R., Balaguer, I., & Duda, J. (­2003). The relationship of task ­self-​­efficacy and role efficacy
beliefs to role performance in Spanish youth soccer. Journal of Sports Sciences, 22, ­429–​­437.
Briki, W., & Zoudji, B. (­2019). Gaining or losing team ball possession: the dynamics of momen-
tum perception and strategic choice in football coaches. Frontiers in Psychology, 10, 1019.
Brimmell, J., Parker, J. K., Furley, P., & Moore, L. J. (­2018). Nonverbal behavior accompanying
challenge and threat states under pressure. Psychology of Sport and Exercise, 39, ­90–​­94.
Brink, M., Kuyvenhoven, Toering, T. T., Jordet, G., & Frencken, W. (­2018). What do football
coaches want from sport science? Kinesiology, 50(­Suppl 1), ­150–​­154.
Champ, F. M., Nesti, M. S., Ronkainen, N. J., Tod, D. A., & Littlewood, M. A. (­2020). An ex-
ploration of the experiences of elite youth footballers: the impact of organizational culture.
Journal of Applied Sport Psychology, 32(­2), ­146–​­167.
CIES Football Observatory (­2020). What About the Home Advantage After the C ­ OVID-​­19
Pandemic? Switzerland: International Centre for Sports Studies (CIES) https://­­ football-​
­observatory.com/­IMG/­sites/­b5wp/­2020/­w p304/­en/
Collins, D., MacNamara, Á., & Cruickshank, A. (­2019). Research and practice in talent iden-
tification and d ­ evelopment—​­Some thoughts on the state of play. Journal of Applied Sport
Psychology, 31(­3), ­340–​­351.
Drew, K., Morris, R., Tod, D., & Eubank, M. (­2019). A ­meta-​­study of qualitative research on
the ­junior-­​­­to-​­senior transition in sport. Psychology of Sport and Exercise, 45, 101556.
Erikstad, M. K., Høigaard, R., Johansen, B. T., Kandala, N. B., & Haugen, T. (­2018). Child-
hood football play and practice in relation to s­ elf-​­regulation and national team selection; a
study of Norwegian elite youth players. Journal of sports sciences, 36(­20), ­2304–​­2310.
FIFA (­2016). Behind the World Cup record: Pele. Switzerland: FIFA. https://­ w ww.fifa.
com/­worldcup/­news/­­behind-­​­­the-­​­­world- ­​­­cup-­​­­record-­​­­p ele-​­2852661
Forsman, H., Blomqvist, M., Davids, K., Liukkonen, J., & Konttinen, N. (­2016). Identifying
technical, physiological, tactical and psychological characteristics that contribute to career
progression in soccer. International Journal of Sports Science & Coaching, 11, ­505–​­513.
 Psychological characteristics of players 121
Fothergill, M., Wolfson, S., & Little, L. (­2014). A qualitative analysis of perceptions of venue:
do professional soccer players and managers concur with the conceptual home advantage
framework? International Journal of Sport and Exercise Psychology, 12(­4), ­316–​­332.
Furley, P., Dicks, M., & Jordet, G. (­2020). The influence of emotions on penalty taker and goal-
keeper performance. In J. G. Dixon, J. B. Barker, R. C. Thelwell, & I. Mitchell (­eds.), The
Psychology of Soccer (­p­­p. ­29–​­43). New York: Routledge.
Furley, P., Dicks, M., Stendke, F., & Memmert, D. (­2012). ‘­Get it out the way. The wait’s killing
me’ hastening and hiding during soccer penalty kicks. Psychology of Sport and Exercise,
13(­4), ­454–​­465.
Furley, P., Moll, T., & Memmert, D. (­2015). Put your hands up in the air’? the interpersonal
effects of pride and shame expressions on opponents and teammates. Frontiers in Psychology,
6, 1361.
Furley, P., & Schweizer, G. (­2016). Nonverbal communication of confidence in soccer referees:
an experimental test of Darwin’s leakage hypothesis. Journal of Sport & Exercise Psychol,
38(­6), ­590–​­597.
Furley, P., Schweizer, G., & Memmert, D. (­2018). Thin slices of athletes’ nonverbal behavior
give away game location: testing the territoriality hypothesis of the home game advantage.
Evolutionary Psychology, 16(­2). ArtID: 1474704918776456
Gledhill, A., Harwood, C., & Forsdyke, D. (­2017). Psychosocial factors associated with talent
development in football: a systematic review. Psychology of Sport and Exercise, 31, ­93–​­112.
Greve, H. R., Nesbø, J., Rudi, N., & Salikhov, M. (­2020). Are goals scored just before half-
time worth more? An old soccer wisdom statistically tested. PLoS One, 15(­10), e0240438.
doi:10.1371/­journal.pone.0240438. eCollection 2020.
Haugaasen, M., & Jordet, G. (­2012). Developing football expertise: a ­football-​­specific research
review. International Review Sport Exercise Psychology, 5(­2), ­177–​­201.
Holt, N. L., & Mitchell, T. (­2006). Talent development in English professional soccer. Interna-
tional Journal of Sport Psychology, 37(­2/­3), 77.
Hopfensitz, A., & Mantilla, C. (­2019). Emotional expressions by sports teams: An analysis of
World Cup soccer player portraits. Journal of Economic Psychology, 75, 102071.
­Iso-​­Ahola, S. E., Dotson, C. O. (­2014). Psychological momentum: why success breeds success.
Rev Gen Psychol, 18(­1), ­19–​­33. doi:10.1037/­a0036406
Ivarsson, A., ­K ilhage-​­Persson, A., Martindale, R., Priestley, D., Huijgen, B., Ardern, C., &
McCall, A. (­2020). Psychological factors and future performance of football players: a sys-
tematic review with ­meta-​­analysis. Journal of Science and Medicine in Sport, 23, ­415–​­420.
Jordet, G. (­2016). Psychology and elite soccer performance. In T. Strudwick (­Ed.), Soccer Sci-
ence: Using Science to Develop Players and Teams (­p­­p. ­367–​­388). Champaign, IL: Human
Kinetics
Jordet, G. (­2019). Working with psychology in professional football. In D. Collins, A. Cruick-
shank, & G. Jordet (­Eds.), Routledge Handbook of Elite Sport Development (­p­­p. ­114–​­132).
London: Routledge
Jordet, G., Aksum, K. M., Pedersen, D. N., Walvekar, A., Trivedi, A., McCall, A., Ivarsson, A., &
Priestley, D. (­2020). Scanning, contextual factors, and association with performance in English
Premier League footballers: an investigation across a season. Frontiers in Psychology, 11, 2399.
Jordet, G., & Hartman, E. (­2008). Avoidance motivation and choking under pressure in soccer
penalty shootouts. Journal of Sport andExercise Psychology, 30, ­450–​­457.
Jordet, G., Hartman, E., & Jelle Vuijk, P. (­2011). Team history and choking under pressure in
major soccer penalty shootouts. British Journal of Psychology, 103, ­268–​­283.
Jordet, G., & Pepping, G. J. (­2019). Flipping sport psychology theory into practice: a ­context-​­
and ­behaviour-​­centered approach. In M. L. Cappuccio (­Ed.), Handbook of Embodied Cogni-
tion and Sport Psychology. Boston, MA: MIT Press
Leitner, M. C., & Richlan, F. (­2021). Analysis system for emotional behavior in football (­­aseb-​­f ):
matches of fc red bull salzburg without supporters during the C ­ OVID-​­19 pandemic. Human-
ities and Social Sciences Communications, 8, 14. https://­doi.org/­10.1057/­­s41599- ­​­­020- ­​­­0 0699-​­1
122 Geir Jordet and Tynke Toering
Levi, H. R., & Jackson, R. C. (­2018). Contextual factors influencing decision making: percep-
tions of professional soccer players. Psychology of Sport &Exercise, 37, ­19–​­25.
McGreary, M., Morris, R., & Eubank, M. (­2021). Retrospective and concurrent perspectives of
the transition into senior professional female football within the United Kingdom. Psychol-
ogy of Sport andExercise, 53, 101855.
McLoughlin, E., Fletcher, D., Slavich, G. M., Arnold, R., & Moore, L. J. (­2021). Cumulative
lifetime stress exposure, depression, anxiety, and ­well-​­being in elite athletes: a ­m ixed-​­method
study. Psychology of Sport and Exercise, 52, 101823.
Middlemas, S., & Harwood, C. (­2018). No place to hide: football players’ and coaches’ per-
ceptions of the psychological factors influencing video feedback. Journal of Applied Sport
Psychology, 30(­1), ­23–​­44.
Middlemas, S., & Harwood, C. (­2020). A p ­ re-​­match video ­self-​­modeling intervention in elite
youth football. Journal of Applied Sport Psychology, 32(­5), ­450–​­475.
Mitchell, T., Gledhill, A., Nesti, M., Richardson, D., & Littlewood, M. (­2020). Practitioner
perspectives on the barriers associated with ­youth-­​­­to-​­senior transition in elite youth soccer
academy players. International Sport Coaching Journal, 7(­3), ­273–​­282.
Moll, T., & Davies, G. L. (­2021). The effects of coaches’ emotional expressions on players’ per-
formance: experimental evidence in a football context. Psychology of Sport andExercise, 54.
Moll, T., Jordet, G., & Pepping, G.-​­J. (­2010). Emotional contagion in soccer penalty shootouts:
celebration of individual success is associated with ultimate team success. Journal of Sports
Sciences, 28, ­983–​­992. doi:10.1080/­02640414.2010.484068
Morris, R., Tod, D., & Eubank, M. (­2017). From youth team to first team: an investigation into
the transition experiences of young professional athletes in soccer. International Journal of
Sport andExercise Psychology, 15(­5), ­523–​­539.
Morris, R., Tod, D., & Oliver, E. (­2016). An investigation into stakeholders’ perceptions of the
­youth-­​­­to-​­senior transition in professional soccer in the United Kingdom. Journal of Applied
Sport Psychology, 28(­4), ­375–​­391.
Neave, N., & Wolfson, S. (­2003). Testosterone, territoriality and the ‘­home advantage’. Physiol-
ogy and Behavior, 78, ­269–​­275.
Oberhofer, H., Philippovich, T., & Winner, H. (­2010). Distance matters in away games: evidence
from German football league. Journal of Economic Psychology, 31, ­200–​­211.
Pain, M., & Harwood, C. (­2013). Stress, coping and the mental qualities of elite players. In:
M. Williams (­Ed.), Science and Soccer: Developing Elite Performers (­p­­p. ­154–​­169). London:
Routledge.
Pollard, R., & Gomez, M.A. (­2014). Components of home advantage in 157 national soccer
leagues worldwide. International Journal of Sport and Exercise Psychology, 12(­3), ­218–​­233.
Ponzo, M., & Scoppa, V. (­2018). Does the home advantage depend on crowd support? Evi-
dence from ­same-​­stadium derbies. Journal of Sports Economics, 19(­4), ­562–​­582. doi:10.1177/­
1527002516665794
­Redwood-​­Brown, A. J., Sunderland, C. A., Minniti, A. M., & O’Donoghue, P. G. (­2018). Percep-
tions of psychological momentum of elite soccer players. International Journal of Sport and
Exercise Psychology, 16(­6), ­590–​­606.
Røynesdal, Ø., Toering, T., & Gustafsson, H. (­2018). Understanding players’ transition from
youth to senior professional football environments: a coach perspective. International Jour-
nal of Sports Science & Coaching, 13(­1), ­26–​­37.
Seiler, K., Schweizer, G., & Seiler, R. (­2018). Do the effects of nonverbal behaviour on team
outcome confidence in team sports depend on the availability of additional performance
information? Psychology of Sport and Exercise, 36, ­29–​­40.
Shipherd, A. M., Basevitch, I., Filho, E., & Gershgoren, L. (­2018). A ­scientist-​­practitioner ap-
proach to an ­on-​­field assessment of mental skills in collegiate soccer s­ tudent-​­athletes. Journal
of Sport Psychology in Action, 9(­3), ­196–​­205.
 Psychological characteristics of players 123
Slater, M. J., Haslam, S. A., & Steffens, N. K. (­2018). Singing it for ‘­us’: team passion displayed
during national anthems is associated with subsequent success. European Journal of Sport
Science, 18(­4), ­541–​­549.
Staufenbiel, K., Riedl, D., & Strauss, B. (­2018). Learning to be advantaged: the development
of home advantage in h ­ igh-​­level youth soccer. International Journal of Sport and Exercise
Psychology, 16(­1), ­36–​­50.
Swainston, S. C., Wilson, M. R., & Jones, M. I. (­2020). Player experience during the junior to
senior transition in professional football: a longitudinal case study. Frontiers in Psychology,
11, 1672.
Taylor, J., & Collins, D. (­2019). Shoulda, coulda, ­didnae—​­Why don’t ­h igh-​­potential players
make it? The Sport Psychologist, 33(­2), ­85–​­96.
Thomas, O., Thrower, S. N., Lane, A., & Thomas, J. (­2019). Types, sources, and debilitating fac-
tors of sport confidence in elite early adolescent academy soccer players. Journal of Applied
Sport Psychology, 33, 192-217. doi:10.1080/­10413200.2019.1630863
Tilp, M., & Thaller, S. (­2020). C ­ ovid-​­19 has turned home advantage into home disadvantage in the
German soccer Bundesliga. Frontiers in Psychology, 2. https://­doi.org/­10.3389/­fspor.2020.593499
Toering, T. (­i n press). S ­ elf-​­regulation. In D. Collins & A. Cruickshank (­Eds.), Sport Psychology
Essentials. Champaign, IL: Human Kinetics.
Toering, T. T., ­Elferink-​­Gemser, M. T., Jordet, G., & Visscher, C. (­2009). ­Self-​­regulation and
performance level of elite and ­non-​­elite youth soccer players. Journal of Sports Sciences,
27(­14), ­1509–​­1517.
Toering, T., & Jordet, G. (­2015). S ­ elf-​­control in professional soccer players. Journal of Applied
Sport Psychology, 27(­3), ­335–​­350.
Van Kleef, G. A., Cheshin, A., Koning, L. F., & Wolf, S. A. (­2019). Emotional games: how
coaches’ emotional expressions shape players’ emotions, inferences, and team performance.
Psychology of Sport and Exercise, 41, ­1–​­11.
Van Ours, J. C. (­2019). A note on artificial pitches and home advantage in Dutch professional
football. De Economist, 167, ­89–​­103. https://­doi.org/­10.1007/­­s10645-­​­­019-­​­­09332-​­2
Van Yperen, N. W. (­2009). Why some make it and others do not: identifying psychological
factors that predict career success in professional adult soccer. The Sport Psychologist, 23(­3),
­317–​­329.
Zuber, C., Zibung, M., & Conzelmann, A. (­2015). Motivational patterns as an instrument for
predicting success in promising young football players. Journal of Sports Sciences, 33(­2),
­160–​­168.
8 Anticipation and ­decision-​­making
A. Mark Williams, Jospeh L. Thomas, Geir Jordet,
and Paul R. Ford

Introduction
The ability to anticipate what opponents will do next and to make the most appropri-
ate decision as to how to respond are important components of performance in soccer
(­Williams & Jackson, 2020). These attributes become more important to performance
at the highest level in soccer when compared with anthropometric or physiological
characteristics (­e.g., Reilly et al., 2000). Tactical ability (­e.g., anticipation and ­decision-​
­making), in conjunction with the technical ability (­e.g., ball control and passing skill)
and psychological characteristics (­e.g., mental toughness, resilience, and grit), are the
factors that most likely discriminate players at the very highest level.
In this chapter, we focus on anticipation and ­decision-​­making. In colloquial or lay
terms, coaches, and pundits often refer to these attributes using phrases such as ‘­game
intelligence’ or ‘­the ability to read the game’. Anticipation necessitates players to per-
ceive ahead of the event itself what opponents and teammates are likely to do in any
situation. ­Decision-​­making is the ability to select and execute the appropriate action
based on the current circumstances on the field of play, as well as the demands of the
game strategically and tactically. Scientists have consistently shown that skilled soc-
cer players are quicker and more accurate in anticipation and ­decision-​­making when
compared to their ­lesser-​­skilled counterparts (­e.g., Roca, Ford, McRobert, & Wil-
liams, 2011; Williams & Davids, 1998). We have two main aims. First, we identify how
players anticipate and make decisions in soccer and in so doing, illustrate how these
attributes are measured. Second, we assess how players develop superior anticipation
and ­decision-​­making and how interventions can be developed to create more ‘­­game-​
i­ ntelligent’ players.

Anticipation and ­decision-​­making

Over the last 50 years, researchers have successfully identified several ­p erceptual-​
c­ ognitive skills that underpin successful anticipation and ­decision-​­making (­Williams &
Jackson, 2020). Although there is a substantive research base involving other sports
(­Williams & Ericsson, 2005; Williams, Ford, Eccles, & Ward, 2010), we focus solely on
research involving adult and youth male soccer players. Unfortunately, there remains
relatively limited research on female players and special population groups. However,
while these remain important gaps in understanding, it is likely that the specific nature
of the skills identified does not differ greatly, if at all, due to differences in gender,
ethnicity, or disability, over and beyond the accumulation of experience/­practice in

DOI: 10.4324/9781003148418-10
 Anticipation and ­decision-­making 125
soccer. In the opening part of the first section, we review research that has highlighted
the processes and skills underpinning superior anticipation in soccer. In the second
part, we review how skilled players are better than their ­lesser-​­skilled counterparts at
making correct and timely decisions.

‘­Reading the game’: anticipation

The importance of looking and seeing

When observing a soccer match, one can witness skilled players consistently moving
their eyes and heads to ‘­look around’ the pitch, at the ball, the movements of oppo-
nents and teammates, and areas of space that may be exploited or exposed. Scientists
have demonstrated that skilled soccer players use the visual system in a systematically
different manner when compared to l­esser-​­skilled players. The earliest studies exam-
ining visual search or gaze behaviours in soccer focused on goalkeepers attempting to
predict the direction of a ­p enalty-​­kicks (­e.g., Tyldesley, Bootsma, & Bomhoff, 1982; for
subsequent work on this theme, see Dicks, Button, & Davids, 2010a, b; Savelsbergh,
Williams, van der Kamp, & Ward, 2002; Savelsbergh, van der Kamp, Williams, &
Ward, 2005). However, advances in technology have led to progressive improvements
in the methods employed to measure such behaviours, enabling data capture in in-
creasingly more realistic scenarios. Gaze behaviours have been evaluated as soccer
players attempt to anticipate the actions of opponents in outfield scenarios involving 1
vs. 1 situations, in various micro phases of defensive play involving 3 vs. 3 simulations,
and in more macro phases involving larger groups of outfield players (­Roca et al., 2011,
2013; Williams & Davids, 1998; Williams, Davids, Burwitz, & Williams, 1994). Sim-
ilarly, scientists have measured gaze in situations that require players to make deci-
sions during various phases of play, in offensive situations involving s­ et-​­plays, and in
sequences of play that traverse the length of the playing field and involve numerous in-
teractions between players (­Helsen & Starkes, 1999; Roca et al., 2011; Vaeyens, Lenoir,
Williams, Mazyn, & Philippaerts, 2007a, b). The broad conclusion is that skilled play-
ers generally look at different areas of the display, for varying periods of time, using
different search strategies when compared with ­less-​­skilled counterparts.
As an illustration, Roca et al. (­2011) recorded the gaze behaviours of skilled and ­less-​
­skilled soccer players while moving and interacting with l­ife-​­size video sequences of
11 vs. 11 soccer situations filmed from the perspective of a central defender. The video
clips were occluded just prior to the main offensive action (­e.g., final pass). Participants
were required to anticipate the action of the player in possession of the ball and to
decide what course of action they should take (­e.g., maintain position or move right
or left). Skilled defenders were more accurate in anticipating what the opponent was
going to do next and in deciding what action to take when compared to l­ess-​­skilled
players. Skilled players employed more fixations of shorter duration and oriented gaze
on significantly more locations in the display compared with less skilled players. They
spent more time fixating on the opposing team players and areas of space compared to
less skilled players who, in contrast, spent more time fixating the player in possession
and ball (i.e., ball watching). Skilled players use vision in a fundamentally different
manner compared to l­esser-​­skilled players to p ­ ick-​­up the key information needed to
guide anticipation and ­decision-​­making. Yet, in some studies, no specific differences
in gaze characteristics have been reported across skill groups. In these latter instances,
126 A. Mark Williams et al.
variations in performance between skilled and ­less-​­skilled players are likely due to
more effective pick up of information using peripheral vision or differences in the
amount or quality of information extracted per fixation (­Williams & Davids, 1998).
Scientists have examined how stressors such as anxiety and fatigue influence gaze
behaviours (­Causer, Holmes, Smith, & Williams, 2011; Vickers & Williams, 2007; Wil-
son, Wood, & Vine, 2009). Wilson et al. (­2009; see also Wood & Wilson, 2011) exam-
ined the gaze behaviours of players as they completed penalty kicks under ­low-​­and
­h igh-​­threat conditions. In the ­h igh-​­threat condition, the ­penalty-​­takers made faster
first fixations and fixated for longer periods on the goalkeeper, with these changes in
gaze leading to reductions in shooting accuracy and an increased likelihood of placing
the ball nearer the goalkeeper when compared to the ­low-​­threat condition. In similar
vein, Casanova and colleagues (­2013) reported that workload/­fatigue built up over the
course of a match negatively impacted the information processed by outfield players in
the early and late stages of each half in a soccer match. The current evidence suggests
that skilled athletes are more robust to the negative effects of stressors such as anxiety
and fatigue.
While technology has improved significantly over recent decades, it has historically
been difficult to record accurate gaze data during actual match situations. An alterna-
tive approach has been to record player head movements in matches as a rough proxy
for visual search and scanning. When closely observing individual players in a soccer
game, one can observe players turning their heads to look around, especially prior
to receiving the ball. Scientists have measured the active head movements of players
where the face (­and hence, the eyes) is temporarily directed away from the ball, with
the assumed intention of gathering information about teammates and/­or opponents,
to prepare for subsequently engaging with the ball (­e.g., Jordet, 2005b; Jordet et al.,
2020). ­Figure 8.1 presents an illustration of this scanning behaviour.
Jordet (­2005a, b) started filming soccer players in matches to generate ­close-​­shot
videos for analysis. Several published reports have subsequently presented data gath-
ered using these video recordings of players (­e.g., Eldridge et al., 2013; Jordet, Hei-
jmerikx, & Bloomfield, 2013). In the largest study to date, 27 players in the English
Premier League (­EPL) were filmed across a total of 21 games, which produced an
analysis of almost 10,000 individual ball possessions (­Jordet et al., 2020). A statistical
model that accounted for context, pass difficulty, and player differences showed that
scanning plays a robust and positive, albeit small, role in performance. Furthermore,

­Figure 8.1 A scan (­fi lmed from the position of the ball), where a player’s face is temporarily
directed away from the ball.
Photo credit: Karl Marius Aksum and Lars Brotangen.
 Anticipation and ­decision-­making 127
player scanning varied with different contextual conditions (­i.e., playing position,
pitch location, opponent pressure, and state of the game). Midfielders scanned the
most, followed by central defenders, full backs, wingers, and forwards. Similar find-
ings emerged for players during the U17 and U19 European Championships (­Aksum,
Pokolm, Bjørndal, Rein, Memmert, & Jordet, 2021). Aksum and colleagues (­2021) re-
port a significant positive relationship between scanning frequency and pass comple-
tion rates. Moreover, the U19 players scanned significantly more frequently than the
U17 players.
Another innovative approach has been to use a headband containing an inertial
measurement unit to examine the links between h ­ ead-​­turning frequency or excursion
(­i.e., extent of ­head-​­turning and measured in degrees) and turning with ball, as well
as switching play from one side of the pitch to the other (­McGuckian, Cole, Jordet,
Chalkley, & Pepping, 2018). In a study of U13 and U23 players performing at a Ger-
man Bundesliga club, the U23 players had a significantly higher head turn frequency
prior to ball possession and a lower frequency during ball possession, when compared
to the U13 players (­McGuckian, Beavan, Mayer, Chalkley, & Pepping, 2020). Higher
head turn frequency (­for the U13 players) and higher excursion (­for the U23 players)
were related to turning and switching performance.
Most recently, gaze tracking data have been gathered during actual matches. In
one such study, players fixated most often around the ball, and fixation duration to
any type of information increased when more information sources (­i.e., ball, team-
mates, and opponents) were available (­Aksum, Magnaguagno, Bjørndal, & Jordet,
2020). ­Figure 8.2 illustrates the approach employed. The average fixation durations
were considerably shorter than previously reported in laboratory studies, which could
be because field conditions place different constraints on visual behaviours com-
pared to laboratory settings. Another study focused on the scan itself, showing that

­Figure 8.2 Some images from ­eye-​­tracking goggles worn by a central midfielder in an 11

vs. 11 match, with the small circle indicating the player’s foveal gaze location in
a scan (­scan starting at 1, ending at 5).
Photo credit: Karl Marius Aksum and Geir Jordet.
128 A. Mark Williams et al.
approximately 2% of scans contained visual fixations, suggesting that a scan does not
typically result in the recognition of detailed information, but blurred impressions of
positions, movements, and colours (­Aksum, Brotangen, Bjørndal, Magnaguagno, &
Jordet, 2021). Findings support other research showing that when vision is blurred
skilled players are still able to anticipate accurately based on very course and global
(­i.e., spread across the display) information rather than local sources (­e.g., a single cue;
Ryu, Mann, Abernethy, & Poolton, 2016; Ryu, Abernethy, Park, & Mann, 2018).

­Picking-​­up postural cues

A related body of research exists to suggest that skilled soccer players extract early
arising information from the postural movements of opponents (­and probably team-
mates) before they execute a pass or shot. This body of work has not recorded gaze
behaviours per se, but rather has used an alternative approach based on manipulating
the information in the display to identify the information used during skilled antici-
pation. Williams and Burwitz (­1993) used the ­so-​­called ‘­temporal occlusion approach’
to measure the ability of skilled and ­less-​­skilled goalkeepers to predict ­p enalty-​­kick
direction. Several players were filmed from the perspective of a goalkeeper facing the
penalty. These action sequences were then selectively edited to present varying extents
of early and late information relative to f­ oot-​­ball contact; the video sequences were oc-
cluded 120 ms before ball contact, 80 ms before ball contact, at ­foot-​­ball contact, and
120 ms after f­ oot-​­ball contact. ­Figure 8.3 presents an illustration of the film sequences

­Figure 8.3 The ­p enalty-​­taker as presented in a ­temporal-​­occlusion condition where in-

formation is available up to ­foot-​­ball contact (­left side) and a spatial occlu-
sion condition where only the hips are presented (­r ight side) (­from Causer &
­Williams, 2015).
 Anticipation and ­decision-­making 129
presented when using temporal occlusion techniques. Players viewed the action se-
quences on a near ­life-​­size screen and were required to indicate which corners of the
goal the ­penalty-​­k icks were directed towards using a ­p en-­​­­and-​­paper response. Skilled
players recorded response accuracy scores above chance levels even in the p ­ re-­​­­foot-­​
to-​­
­­ ball contact conditions, illustrating their ability to process advanced information
from the penalty taker during the ­r un-​­up and kicking action. The accuracy of predict-
ing ball height increased significantly after viewing the first portion of the ball flight.
Some researchers have simultaneously recorded gaze data as players view these
­fi lm-​­based simulations (­Dicks et al., 2010a; Savelsbergh et al., 2002, 2005) or as they
perform the task in situ (­Dicks et al., 2010a; Piras & Vickers, 2011). Moreover, there
have been efforts to describe biomechanically the kinematic information available
to the goalkeeper (­Dicks et al., 2010b; Lees & Owens, 2011). Savelsbergh et al. (­2002)
used a very similar temporal occlusion methodology to Williams and Burwitz (­1993),
but in addition, they recorded eye movement data. Skilled goalkeepers were more
accurate at anticipating penalty direction, making fewer visual fixations of longer
duration to a smaller number of locations when compared with the ­less-​­skilled goal-
keepers. During the early stages of the penalty kick, the skilled goalkeepers spent
more time fixating on the face of the kicker (­which may give them early informa-
tion as to the direction of the kick) compared to ­less-​­skilled keepers who fixated on
‘­u nclassified’ regions. In the moments before ­foot-​­ball contact, the skilled keepers
fixated on the kicking leg, ­non-​­kicking leg, and ball regions, whereas less skilled
keepers fixated on the trunk, arm, and hip regions. The search strategies used by
the skilled goalkeepers, and their ability to recognise advanced postural cues ema-
nating from the movements of the taker, led to them being more successful at saving
penalties.

Recognising patterns and detecting familiarity in sequences of play

Another ­p erceptual-​­cognitive skill that appears to be important when ‘­reading the
game’ is the ability to recognise familiarity or patterns in evolving sequences of play.
Skilled players identify familiarity through structures or patterns in play as sequences
unfold (­e.g., 2 vs. 1 situation, triangle or diamond shape forming between players in
possession) and this ability enables them to anticipate the likely outcome ahead of time.
Players are typically presented with filmed clips from competitive matches lasting ­3 –​­10
s involving either structured (­i.e., footage involving a typical offensive move) or un-
structured sequences (­e.g., players warming up before a match). In a subsequent recog-
nition phase, players are presented with a combination of clips that were presented in
the earlier viewing phase and some that were novel. Skilled players are more accurate
than ­less-​­skilled players in recognising previously viewed structured sequences, but
not unstructured sequences. Several published studies illustrate this ability in soccer
(­e.g., North, Williams, Ward, Hodges, & Ericsson, 2009; North, Ward, Ericsson, &
Williams, 2011; Williams, Hodges, North, & Barton, 2006). A combination of visual
search recording, t­ hink-​­aloud verbal reports, and different manipulations of the film
displays (­e.g., occlusion of players and removal of superficial display features) has been
used to identify the specific sources of information used when making these judge-
ments (­see Williams & North, 2009).
One proposal is that skilled players initially extract relational information from
the positions and movements of players and the ball and match these stimulus
130 A. Mark Williams et al.
characteristics with their previous knowledge and experience (­Dittrich, 1999). Skilled
players recognise familiar patterns of play based upon structural relations between
features (­e.g., teammates, opponents, and the ball), as well as the tactical and strategic
significance of these relations. In contrast, ­lesser-​­skilled players are unable to pick up
important relational information and have less knowledge constraining them to em-
ploy more distinctive surface or background features (­e.g., pitch condition and colour
of playing uniforms) when making such decisions.

Predicting likely event occurrences

Another p ­ erceptual-​­cognitive skill that has received attention over the past decade has
been the use of situational probabilities or more broadly, contextual information or
priors in anticipation. It has been reported that players assign a hierarchy of probabil-
ities to potential events as the action unfolds (­i.e., they weigh up the likely options and
their potential of occurring). These probabilities could exist across a broad range of sit-
uations, as well as being task, player/­opponent, and ­context-​­specific (­Williams, 2000).
In recent studies, different sources of contextual information have been identified that
can influence perception of the most likely situational occurrence. These sources in-
clude the positions of players (­Roca, Ford, McRobert, & Williams, 2013), the score of
the game (­Runswick, Roca, Williams, Bezodis & North, 2018), and prior knowledge
of opponent action tendencies (­Gredin, Bishop, Broadbent, Tucker & Williams, 2018).
Navia, van der Kemp, and Ruiz (­2013) assessed goalkeepers during ­on-​­field ­penalty-​
k­ ick scenarios under distinct situational information conditions that differed on the
strength of the probabilistic information. When goalkeepers are informed that the
penalty taker has a high probability of shooting to the left or right, performance with
respect to diving to the correct side is significantly enhanced, whereas this is not the
case when taker preferences are ambiguous.
Another emphasis has been on measuring how the possession of a priori infor-
mation related to the most likely behaviours of opponents influences anticipation.
These investigations have manipulated how this contextual prior information is pro-
vided either by explicit ­i nstruction – ​­as a performance analyst might do in a tactical
­report – ​­or more implicitly by providing access to this information through expo-
sure to previous actions of the opponent. Gredin et al. (­2018) examined the ability of
skilled and novice soccer players to anticipate a final action from videos of dynamic
2 vs. 2 counterattacks. The players were provided stable contextual prior informa-
tion about the action tendencies of the attacker in possession of the ball that were
dependent on the positioning of the secondary attacker. Thus, the final prediction ne-
cessitated integrating the previously acquired situational knowledge with the visual
information from the unfolding movement of the secondary attacker. The provision
of explicit contextual priors altered how the expert players allocated visual attention
towards more situationally relevant information (­i.e., the secondary attacker off the
ball). As such, trials in which the final action was congruent, or aligned, with oppo-
nent action tendencies led to enhanced performance. When the outcome was incon-
gruent with the contextual prior information, anticipation performance in novices
suffered, whereas experts maintained their performance. However, this was an unex-
pected finding considering evidence in other sporting domains has reported expert
performance often suffers when action outcomes do not align with contextual prior
information.
 Anticipation and ­decision-­making 131
‘­Making the right choices’: ­decision-​­making
An equally important challenge for players is to select and execute the correct re-
sponse to positively influence the current and evolving situation in the match. In this
section, we review current understanding of d ­ ecision-​­making in soccer. We separate
action selection and execution for descriptive purposes, with the former providing de-
scription of the choice made and the latter whether the decision selected is successfully
executed; in reality, these are a single variable during performance in matches.
Scientists have used representative v­ ideo-​­based tasks (­e.g., Roca et al., 2011; Vaeyens
et al., 2007a; b) to provide empirical evidence supporting the observation that expert
players make more successful decisions in a variety of representative soccer situations
compared to l­esser-​­skilled players. More recently, other researchers using perfor-
mance analysis techniques have assessed the selection and execution of decisions by
players in ­match-​­play. Serrano et al. (­2017) used the Game Performance Evaluation
Tool (­GPET) to assess success in both the selection and execution of passing, drib-
bling, and shooting skills across 30 matches involving skilled Spanish youth soccer
players aged ­U10–​­U19. The GPET requires observers to assign a single value to each
decision selection deemed appropriate across a game and separately for a successful
execution, with zero allocated for each inappropriate and unsuccessful decision. They
found an average of 69% of ball possessions involved appropriate selections and 47%
were successfully executed. In comparison, players in the EPL have higher success
rates for executing ball possessions, although to our knowledge selections have not
been assessed in this cohort. An analysis of matches demonstrated that the proportion
of successful executions of ball possessions for 15 players across 9 matches was 75%
(­W helan, 2021), whereas the success of passing executions for 570 players across 376
EPL matches was 74%, with higher values when the score line for the team was ahead
or behind compared to drawing (­­Redwood-​­Brown et al., 2019). It is likely that the
percentage of appropriate action selections in EPL players on the ball exceeds the 75%
found for executions (­e.g., Serrano et al., 2017). Moreover, it may be that successful
ball possession executions of 75% and above demonstrates skilled performance in the
game. In the future, researchers should test these hypotheses and assess the appropri-
ateness and success of decisions ‘­off the ball’.
The data gathered on the success of action executions and appropriateness of action
selections by players in matches provide us with important descriptive information,
but unfortunately, such an approach does not explain how ­decision-​­making occurs in
matches. Gallivan et al. (­2018) describe the basic nature of ­decision-​­making as involv-
ing ‘­a sequence of ­sub-​­actions that are performed to achieve a ­h igh-​­level goal’ (­­p. 519).
Certainly, observations of players in matches confirm this idea, in that players select
and execute actions to achieve a h ­ igher-level goal or intention, such as shooting to
score, pressing an opponent to regain possession, or manipulating the ball to avoid a
tackle to maintain possession. Moreover, often, a few ­sub-​­actions or changes of action
occur in service of achieving that ­h igher-​­level goal or intention, for example, a jog to
a sideways curved cruise to a backward sidestep to achieve the goal of pressing an op-
ponent and channelling them toward a teammate (­W helan, 2021).
Several contextual factors influence how actions are selected and executed during
matches. Levi and Jackson (­2018) conducted ­semi-​­structured interviews to identify the
contextual factors affecting ­decision-​­making with eight professional soccer players.
Players revealed that during a match their decisions were influenced by the dynamic
132 A. Mark Williams et al.
contextual variables or ­self-​­perceptions of their own current performance, match score,
team momentum (­e.g., periods of attacking play by their team), and concurrent in-
struction from coaches. Moreover, their d ­ ecision-​­making in the match was influenced
by static variables related to match importance, personal pressures (­e.g., gaining a new
contract), and preparation from coaches and in training (­e.g., tactical plans). These find-
ings support those reported by McPherson and colleagues (­e.g., McPherson & Kernodle,
2003) who showed ‘­­in-​­game’ d­ ecision-​­making is influenced by contextual factors that are
situational (­e.g., score or time in a match), player characteristics (­e.g., age and skill level),
phase of play (­e.g., team in possession), opponent characteristics (­e.g., shot tendencies),
and environmental characteristics (­e.g., pitch, weather) (­McPherson & Kernodle, 2003).
Overall, there remains a paucity of research relating to how players make decisions
in matches and the factors that impact these processes. The work is largely descrip-
tive highlighting the frequency and type of decisions made rather than attempting to
explain and predict how skilled players make these judgments during matches. In the
future, more controlled and systematic research is needed using ­process-​­tracing meas-
ures such as verbal reports and s­ emi-​­structured interviews to improve understanding
of the mechanisms underlying ­decision-​­making (­Williams & Jackson, 2020).

The acquisition of anticipation and d­ ecision-​­making

The activities engaged in during development

Scientists have examined whether players who exhibit varying levels of anticipation and
­decision-​­making ability differ in the amount and type of activity they have engaged in
during development. Although initial attempts focused on sports such as ­field-​­hockey,
netball, basketball, Australian rules football, and cricket (­Baker, Côté, & Abernethy,
2003a, b; Berry, Abernethy, & Côté, 2008; Ford, Low, McRobert, & Williams, 2010a),
there are reports involving soccer. Williams Ward, B ­ ell-​­Walker, and Ford (­2012) catego-
rised skilled soccer players aged 18 years into ‘­­high-​­performing’ and ‘­­low-​­performing’
based on their performance on established tests of ­perceptual-​­cognitive expertise in-
volving anticipation and situational assessment tasks. A group of ­non-​­elite soccer play-
ers acted as controls. A Career Practice Questionnaire was completed by all players to
elicit information about their participation history profiles (­Ward, Hodges, Starkes, &
Williams, 2007). The ‘­­high-​­performing group’ had accumulated more hours in ­soccer-​
s­ pecific play activity over their last 6 years of engagement in the sport compared to their
­low-​­performing counterparts and the ­non-​­elite controls. No differences were reported
for hours accumulated in s­occer-​­specific practice or competition. The mean hours in
each type of activity for the different groups and across each age category are presented

­Table 8.1 T
 he average hours per year in three soccer
activities for soccer players aged 18 years in
the six years prior to the ­p erceptual-​­cognitive
test (­Williams et al., 2012)

Group ­Match-​­play Practice Play

Elite ­h igh-​­p erforming 47.6 270.6 245.9

Elite ­low-​­p erforming 1.0 285.9 172.5
Recreational 78.5 222.1 92.2
 Anticipation and ­decision-­making 133
in ­Table 6.1. Players who had superior ‘­game intelligence’ had accumulated significantly
more hours in ­soccer-​­specific, ­peer-​­led play activity (­i.e., street soccer).
In a f­ ollow-​­up study, Roca, Williams, and Ford (­2012) categorised skilled adult soc-
cer players into ‘­­high-​­performing’ and ‘­­low-​­performing’ groups based on their per-
formance on an interactive test that measured the ability of players to anticipate and
make decisions. A group of recreational players acted as controls. The Participation
History Questionnaire (­Ford et al., 2010b) was used to collect retrospectively recalled
developmental activity data across participants. During childhood (­­6–​­12 years), the
­h igh-​­performing skilled group averaged more hours per year in ­soccer-​­specific, ­p eer-​
l­ed play compared to the other two groups. During adolescence (­­13–​­18 years), both
skilled groups engaged in more hours of ­soccer-​­specific practice and competition
compared to the recreational group. Statistical analysis showed that 21.8% of the vari-
ance in performance on the test was accounted for by the average hours per year accu-
mulated in ­soccer-​­specific play activity during childhood, with a further 13.2% of the
variance being due to the hours spent in ­soccer-​­specific practice during adolescence.
A key question is why s­ occer-​­specific play would facilitate game intelligence more
so than practice. An argument might be that during play, players recreate realistic
practice conditions that mimic what they see during matches. The absence of overly
prescriptive coaching, in conjunction with challenging and realistic scenarios, may
create more opportunities for ­match-​­like perceptions and decisions. In contrast, there
is evidence to suggest that during ­coach-​­led practice, too much time may be spent in
drill and ­g rid-​­based practices that might not mimic the scenarios that exist in ­match-​
p ­ lay, coupled also with more prescriptive instructional approaches (Ford et al., 2010b).
­Skill-​­based differences in ‘­game intelligence’ and in hours accumulated in soccer ac-
tivity arise as early as 8 years of age in soccer (­Ward & Williams, 2003). The structure
and conditions of s­ occer-​­specific p ­ eer-​­led play create the opportunity for players to ex-
periment with different skills and tactics against opponents and with teammates, which
likely leads to the acquisition of superior anticipation and ­decision-​­making. No evidence
exists to suggest that engagement in sports other than soccer during the developmental
years may lead to p ­ erceptual-​­cognitive expertise in the sport (­e.g., players in Roca et al.,
in prep, engaged in two other sports to a minimal degree). However, some support exists
for the notion that p ­ erceptual-​­cognitive skills transfer across sports of a similar nature
(­Rosalie & Müller, 2014; Christopher & Müller, 2014), yet, in contrast, research exists to
suggest that skills may be specific to a particular position (­Williams, Ward, Smeeton, &
Ward, 2008) or role (­Catteeuw, Helsen, Gilis, & Wagemans, 2009) within a sport.

Simulation training
An important issue for coaches and practitioners is how to develop structured training
interventions to improve anticipation and ­decision-​­making. Certainly, coaches can
structure practice in a manner that facilitates the acquisition of these attributes (­see
Ford & O’Connor, 2019). In this section, we discuss how s­ imulation-​­based training in
its various guises (­e.g., ­video-​­based, virtual reality (­VR)) can be used to facilitate the
acquisition of anticipation and ­decision-​­making. A detailed review of this broad field
of research is available elsewhere (­e.g., see Miles, Pop, Watt, Lawrence, & John, 2012;
Neumann et al., 2017; Gray, 2019).
Most researchers have focused on using simulation to train goalkeepers in the p ­ enalty-​
k
­ ick. Williams and Burwitz (­1993) used video training to develop anticipation in a group
134 A. Mark Williams et al.
of inexperienced goalkeepers. P ­ enalty-​­takers were filmed from the perspective of the
goalkeeper and the footage presented in conjunction with instruction and feedback.
The instruction highlighted key postural cues (­e.g., orientation of the lower leg in pen-
alty kicks), as well as critical relationships between these display features and subsequent
performance. Significant improvements in performance were observed following 90 min
of video training. Savelsbergh, Van Gastel, and Van Kampen (­2010) modified the visual
search behaviours employed by inexperienced soccer goalkeepers using video training. An
intervention group viewed clips where key information from the ­run-​­up was highlighted,
whereas a training group watched unedited sequences and a control group only completed
the ­pre-​­and ­post-​­tests. The visual search behaviours of participants in the intervention
group changed significantly from ­pre-​­to ­post-​­test, leading to earlier initiation of move-
ment and significant improvements in anticipation when compared with the training and
control groups.
Williams, Heron, Ward, and Smeeton (­2005) attempted to improve the ability of
players to use situational probabilities when attempting to predict pass destination in
soccer. Players were assessed, p ­ re-​­and ­post-​­training, on their ability to identify the
passing options available to the player in possession of the ball, and then to determine
the relative threat posed to the participant’s team for each highlighted option. An in-
tervention group received 45 min of video training in which they received instruction
regarding the passing options facing a specific player in possession of the ball, areas
of space that could be exploited or exposed, runs made by forward players, and the
importance of defensive shape and organization in the specific context. Participants
in a placebo group were instructed on standard defensive soccer techniques using the
video simulation. The training group improved their ability to highlight key passing
options over and above that of the placebo group, implying that these c­ ontext-​­specific
skills may be amenable to simulation training and instruction.
Although such training interventions have significant potential, there are many un-
answered questions and considerable scope exists for further empirical work (­Carling,
Reilly, & Williams, 2009). The key question is whether improvements found in these
simulation training studies transfer to enhanced performance on the pitch (­Williams,
Ward, Knowles, & Smeeton, 2002). Thus far, there have been no reported attempts to
improve the ability of players to recognise sequences or patterns of play in soccer or to
change the visual search behaviours or thought processes that may be engaged during
performance using s­ imulation-​­based training. However, simulation training has po-
tential to improve the performance of players.
A major advantage of simulation training is that players can engage when injured or
resting and recovering from physical activity. Moreover, players can experience multiple
soccer situations in a short space of time compared to when physically playing the game.
Advances in technology enable performance to be captured relatively easily offering
varied opportunities to use simulation in all its various guises for performance en-
hancement (­e.g., c­ ave-​­based VR, smartphones, and w ­ eb-​­based applications). Published
reports (­e.g., Wulf, Raupach, & Pfeiffer, 2005) show the learning that occurs from obser-
vational practice provides strong support for the use of simulation training with players.

Training with feedback (­­computer-​­aided and VR)

With modern technology becoming increasingly prevalent in professional sports, many
practitioners have turned to use performance analysis and augmented, or VR to gain a
 Anticipation and ­decision-­making 135
cutting edge (­see McRobert & Williams, 2019). Wright, Atkins, Jones, and Todd (­2013)
surveyed 48 performance analysts working in elite soccer and found that 88% of the clubs
used ­self-​­coded platforms for performance analysis. These tools allow coaches and sup-
port staff to provide players with feedback p ­ ost-​­match, ­feed-​­forward information p ­ re-​
m
­ atch, live analysis, and practice opportunities. ­Video-​­based feedback is a useful tool
for both coaches and players. For coaches, v­ ideo-​­based performance analysis is seen as a
support tool that can assist in learning (­i.e., anticipation/­­decision-​­making) and towards
developing a mutual understanding between coaches and players (­Groom, Cushion, &
Nelson, 2011). Elite youth academy players were interviewed on their perceived impact
performance analysis stating that ­video-​­based feedback was useful for identifying dis-
crepancies between positive and negative performances (­Reeves & Robert, 2013).
­Video-​­based feedback has also been used as a training intervention to develop
­perceptual-​­cognitive skills. Nimmerichter, Weber, Wirth, and Haller (­2015) assigned
34 youth players from a national academy to either a training group or a control group.
The training group underwent a ­6 -​­week intervention during which they used video
feedback to draw their attention to the most informative stimulus during 1 vs. 1 situa-
tions, in order to identify opponent actions quickly and accurately. The video training
group significantly improved both the accuracy and speed of their d ­ ecision-​­making
over the 6­ -​­week period, and demonstrated superior performance compared to the con-
trol group, which did not show a significant improvement after 6 weeks. Moreover, the
relative effectiveness of s­ elf-​­controlled, tactical v­ ideo-​­based feedback has been tested
using o ­ n-​­field performances via 3 vs. 2 s­ mall-​­sided games. Van Maarseveen, Oudejans,
and Savelsbergh (­2018) examined whether elite youth soccer players who had autonomy
when feedback was provided benefited compared to a control group that was tethered
to the feedback frequency of another player. The s­ elf-​­controlled group requested more
feedback after good trials (­e.g., after a goal was scored) and demonstrated higher levels
of perceived performance. ­Self-​­regulated video feedback increased involvement in the
learning process and, subsequently, improved performance.
VR simulations can augment training environments by allowing adaptive difficulty
levels (­Lammfromm & Gopher, 2011) and controlling feedback (­Sigrist et al., 2015). Pro-
fessional clubs are known to use systems, such as Rezzil, Beyond Sports, and Be Your
Best to practice VR scenario drills, for player and match analysis, and for pressure testing
(­Thatcher, Ivanov, Szerovay, & Mills, 2020). Thatcher et al. (­2020) interviewed elite coaches
and performance analysts about barriers and opportunities when implementing VR. The
interviewees reported that VR could serve as a useful tool for demonstrating models of
gameplay representative of team tactics; a factor that could be helpful for individual player
development and during rehabilitation. However, the practicality of using VR and the lack
of empirical evidence highlighting its usefulness were seen as potential barriers. However,
Wood et al. (­2020) have reported that a ­soccer-​­specific VR platform was successfully able
to differentiate between professional, academy, and novice players, providing a modicum
of construct validity. With an increasing number of VR soccer platforms entering the mar-
ket, it suggests that simulations will continue to improve potentially providing increasing
realism that better replicates the actual demands of actual ­match-​­play.

Future directions and conclusions

We reviewed research that has focused on anticipation and d ­ ecision-​­making in soc-
cer. We highlighted the key ­p erceptual-​­cognitive skills and processes that differentiate
136 A. Mark Williams et al.
those with exceptional levels of these attributes compared to those with less exceptional
ability. Those with superior levels of anticipation and ­decision-​­making are better able
to pick up postural information from the orientation of opponents and teammates,
identify structure and familiarity in sequences of play, and predict more accurately
the likely opportunities available during play. These skills are underpinned by more
refined gaze strategies and more ­forward-​­thinking rather than reactive thought pro-
cesses. The ability to anticipate and to make decisions develops progressively through
extensive engagement in ­soccer-​­specific practice and play activities. Thus far, no pre-
dictors of progression on these attributes have been identified, beyond specific practice
on related tasks and playing experience. Physical and simulation training interventions
to facilitate the acquisition of anticipation and d­ ecision-​­making skill were discussed
with the overall aim being to develop players with superior abilities. This area of work
appears to offer considerable scope for performance enhancement in coming years.

References
Aksum, K. M., Pokolm, M., Bjørndal, C. T., Rein, R., Memmert, D., & Jordet, G. (­2021). Visual
exploratory scanning activity in elite youth football players. Journal of Sports Sciences,
Advanced online publication.
Aksum, K. M., Magnaguagno, L., Bjørndal, C. T., & Jordet, G. (­2020). What do football play-
ers look at? An ­eye-​­tracking analysis of the visual fixations of players in 11 v 11 elite football
match play. Frontiers in Psychology, Advanced online publication.
Baker, J., Côté., J., & Abernethy, B. (­2003a). Learning from the experts: practice activities of
expert decision makers in sport. Research Quarterly for Exercise and Sport, 74, ­342–​­347.
Baker, J., Côté., J., & Abernethy, B. (­2003b). ­Sport-​­specific practice and the development of
expert decision making in team ball sports. Journal of Applied Sport Psychology, 15, ­12–​­25.
Berry, J., Abernethy, B., & Côté., J. (­2008). The contribution of structured activity and delib-
erate play to the development of expert perceptual and ­decision-​­making skill. Journal of
Sport & Exercise Psychology, 30, ­685–​­708.
Carling, C., Reilly, T. P., & Williams, A. M. (­2009). Performance Assessment in Field Sports.
London: Routledge.
Casanova, F., Garganta, J., Silva, G., Alves, A., Oliveira, J., & Williams, A. M. (­2013). Effects
of prolonged intermittent exercise on ­p erceptual-​­cognitive processes. Medicine and Science
in Sports and Exercise, 45(­8), ­1610–​­1617.
Catteeuw, P., Helsen, W. F., Gilis, B., & Wagemans, J. (­2009). ­Decision-​­making skills, role spec-
ificity, and deliberate practice in association football refereeing. Journal of Sports Sciences,
27, ­1125–​­1136.
Causer, J., & Williams, A. (­2015). The use of patterns to disguise environmental cues during an
anticipatory judgment task. Journal of Sport & Exercise Psychology, 37, ­74–​­82.
Causer, J., Holmes, P. S., Smith, N. J., & Williams, A. M. (­2011). Anxiety, visual attention, and
movement kinematics in e­ lite-​­level performers. Emotion, 11, ­595–​­602.
Christopher, G. M., & Müller, S. (­2014). Transfer of expert visual anticipation to a similar do-
main. Quarterly Journal of Experimental Psychology, 67, ­186–​­196.
Dicks, M., Button, C., & Davids K. (­2010a). Examination of gaze behaviours under in situ and
video simulation task constraints reveals differences in information pickup for perception
and action. Attention Perception & Psychophysics, 72 ­706–​­720.
Dicks, M., Davids, K., & Button, C., (­2010b). Individual differences in the visual control of
intercepting a penalty kick in association football. Human Movement Science, 29, ­401–​­411.
Dittrich, W. H. (­1999). Seeing biological motion: Is there a role for cognitive strategies? In A.
Braffort, R. Gherbi, S. Gibet, J. Richardson, & D. Teil (­Eds.), ­G esture-​­based Communication
in ­Human-​­computer Interaction (­p­­p. ­3 –​­22). Berlin, Germany: ­Springer-​­Verlag.
 Anticipation and ­decision-­making 137
Eldridge, D., Pulling, C., & Robins, M. T. (­2013). Visual exploratory activity and resultant behav-
ioural analysis of youth midfield soccer players. Journal of Human Sport and Exercise, 8, ­560–​­577.
Ford, P. R., Low, J., McRobert, A. P., & Williams, A. M. (­2010a). Developmental activities that
contribute to high or low performance by elite cricket batters at recognizing type of delivery
from advanced postural cues. Journal of Sport and Exercise Psychology, 32, ­638–​­654.
Ford P. R., & O’Connor D. (­2019). Practice and sports activities in the acquisition of antici-
pation and decision making. In: A. M. Williams & R. C. Jackson (­Eds.), Anticipation and
Decision Making in Sport (­p­­p. ­269–​­285). London: Routledge.
Ford, P. R., Yates, I. & Williams, A.M. (­2010b). An analysis of practice activities and instruc-
tional behaviours used by youth soccer coaches during practice: exploring the link between
science and application. Journal of Sports Sciences, 28, ­483–​­495.
Gallivan, J. P., Chapman, C. S., Wolpert, D. M., & Randall Flanagan, J. (­2018). D ­ ecision-​
­ aking in sensorimotor control. Nature Reviews: Neuroscience, 19, ­219–​­534.
m
Gray, R. (­2019). Sports training technologies. In A. M. Williams & N. J. Hodges (­Eds.), Skill
Acquisition in Sport: Research, Theory and Practice. London: Routledge.
Gredin, V. G., Bishop, D. T., Broadbent, D. P., Tucker, A., & Williams, A. M. (­2018). Experts in-
tegrate contextual priors and environmental information to improve anticipation efficiency.
Journal of Experimental Psychology, 24, ­509–​­520.
Groom, R., Cushion, C., & Nelson, L. (­2011) The delivery of v­ ideo-​­based performance analysis
by England youth soccer coaches: towards a grounded theory. Journal of Applied Sport Psy-
chology, 23, ­16–​­30.
Helsen, W. F., & Starkes, J. L. (­1999). A multidimensional approach to skilled perception and
performance in sport. Applied Cognitive Psychology, 13, ­1–​­27.
Jordet, G. (­2005a). Applied cognitive sport psychology in team ball sports: an ecological ap-
proach. In R. Stelter & K. K. Roessler (­Eds.), New Approaches to Sport and Exercise Psychol-
ogy (­p­­p. ­147–​­174). Europe: Meyer & Meyer Sport.
Jordet, G. (­2005b). Perceptual training in soccer: An imagery intervention study with elite play-
ers. Journal of Applied Sport Psychology, 17, ­140–​­156.
Jordet, G., Aksum, K. M., Pedersen, D. N., Walvekar, A., Trivedi, A., McCall, A., Ivarsson,
A., & Priestley, D. (­2020). Scanning, contextual factors, and association with performance
in English Premier League footballers: an investigation across a season. Frontiers in Psychol-
ogy, 11, 2399.
Jordet, G., Bloomfield, J., & Heijmerikx, J. (­2013). The hidden foundation of field vision in Eng-
lish Premier League (­EPL) soccer players. In Proceedings of the MIT Sloan Sports Analytics
Conference London: Routledge.
Lammfromm, R., & Gopher, D. (­2011). Transfer of skill from a virtual reality trainer to real
juggling. Bio Web Conf, 1, 0054.
Lees, A., & Owens, L. (­2011). Early visual cues associated with a directional place kick in soc-
cer. Sports Biomechanics, 10, ­125–​­134.
Levi, H. R., & Jackson, R. C. (­2018). Contextual factors influencing decision making: percep-
tions of professional soccer players. Psychology of Sport & Exercise, 37, ­19–​­25.
McGuckian, T. B., Beavan, A., Mayer, J., Chalkley, D., & Pepping, G. J. (­2020). The associa-
tion between visual exploration and passing performance in ­h igh-​­level U13 and U23 football
players. Science and Medicine in Football, 4(4), 278-284.
McGuckian, T. B., Cole, M. H., Jordet, G., Chalkley, D., & Pepping, G.-​­J. (­2018). Don’t
turn
blind! The relationship between exploration before ball possession and ­on-​­ball performance in
association football. Frontiers in Psychology, 9, ­1–​­13
McPherson, S. L., & Kernodle, M. W. (­2003). Tactics, the neglected attribute of expertise: prob-
lem representations and performance skills in tennis. In J. Starkes & K.A. Ericsson (­Eds.),
Expert Performance in Sport: Recent Advances in Research on Sport Expertise (­p­­p. ­137–​­168).
Champaign, IL: Human Kinetics.
138 A. Mark Williams et al.
McRobert, A. P., & Williams, A. M. (­2019). Integrating performance analysis and ­p erceptual-​­
cognitive training research. In A. M. Williams & R. C. Jackson (­Eds.) Anticipation and Deci-
sion Making in Sport. Abingdon, Oxon: Routledge.
Miles, H. C., Pop, S. R., Watt, S. J., Lawrence, G. P., & John, N. W. (­2012). A review of virtual
environments for training in ball sports. Computers and Graphics, 36(­6), ­714–​­726.
Navia, J. A., van der Kamp, J., & Ruiz, L. M. (­2013). On the use of situational and body in-
formation in goalkeeper actions during a soccer penalty kick. International Journal of Sport
Psychology, 44, ­234–​­251.
Neumann, D. L., Moffitt, R. L., Thomas, P., Loveday, K., Watling, D., Lombard, C. L.,
Antonova, S., & Tremeer, M. A. (­2017). A systematic review of the application of interactive
virtual reality to sport. Virtual Reality, 22, ­183–​­198.
Nimmerichter, A., Weber, N. J., Wirth, K., & Haller, A. (­2015). Effects of ­v ideo-​­based visual
training on ­decision-​­making and reactive agility in adolescent football players. Sports, 4(­1), 1.
North, J. S., Ward, P., Ericsson, K. A., & Williams, A. M. (­2011). Mechanisms underlying skilled
anticipation and recognition in a dynamic and temporally constrained domain. Memory, 19,
­155–​­168.
North, J. S., Williams, A. M., Ward, P., Hodges, N. J., & Ericsson, K. A. (­2009). Perceiving
patterns in dynamic action sequences: the relationship between anticipation and pattern rec-
ognition skill. Applied Cognitive Psychology, 23, ­1–​­17.
Piras, A., & Vickers, J. N. (­2011). The effect of fixation transitions on quiet eye duration and
performance in the soccer penalty kick: instep versus inside kicks. Cognitive Processing, 12,
­245–​­255
­Redwood-​­Brown A. J., O’Donoghue, P. G., Nevill, A. M., Saward, C., & Sunderland, C. (­2019).
Effects of playing position, pitch location, opposition ability and team ability on the tech-
nical performance of elite soccer players in different score line states. PLoS ONE, 14(­2),
e021170.
Reeves, M. J., & Roberts, S. J. (­2013) Perceptions of performance analysis in elite youth foot-
ball. International Journal of Performance Analysis in Sport, 13, ­200–​­211.
Reilly, T., Williams, A. M., Nevill, A., & Franks, A. (­2000). A multidisciplinary approach to
talent identification in soccer. Journal of Sports Sciences, 18, ­668–​­676.
Roca, A., Ford, P. R., McRobert, A., & Williams, A. M. (­2011). Identifying the processes un-
derpinning anticipation and ­decision-​­making in a dynamic ­time-​­constrained task. Cognitive
Processing, 12, ­301–​­310.
Roca, A., Ford, P. R., McRobert, A. P., & Williams, A. M. (­2013). ­Perceptual-​­cognitive skills
and their interaction as a function of task constraints in soccer. Journal of Sport & Exercise
Psychology, 35, ­144–​­155.
Roca, A., Williams, A. M., & Ford, P. R. (­2012). Developmental activities and the acquisition
of superior anticipation and decision making in soccer players. Journal of Sports Sciences,
30, ­1643–​­1652.
Rosalie, S. M., & Müller, S. (­2014). A model for the transfer of perceptual motor skill learning
in human behaviors. Research Quarterly for Exercise and Sport, 83, ­413– ​­421.
Runswick, O. R., Roca, A., Williams, A. M., Bezodis, N. E., & North, J. S. (­2018). The effects of
anxiety and ­situation-​­specific context on ­p erceptual-​­motor skill: a ­multi-​­level investigation.
Psychological Research, 82, ­708–​­719.
Ryu, D., Mann, D. L., Abernethy, B., & Poolton, J. M. (­2016). ­Gaze-​­contingent training en-
hances perceptual skill acquisition. Journal of Vision, 16, 2.
Ryu, D., Abernethy, B., Park, S. H., & Mann, D. L. (­2018). The perception of deceptive infor-
mation can be enhanced by training that removes superficial visual information. Frontiers in
Psychology, 9, 1132.
Savelsbergh, G. J. P., Van Gastel, P. J., & Van Kampen, P. M. (­2010). Anticipation of penalty
kicking direction can be improved by directing attention through perceptual learning. Inter-
national Journal of Sport Psychology, 41, ­24–​­41.
 Anticipation and ­decision-­making 139
Savelsbergh, G. J. P., Williams, A. M., van der Kamp, J., & Ward, P. (­2002). Visual search, an-
ticipation and expertise in soccer goalkeepers. J Sports Sci, 20, ­279–​­287.
Savelsbergh, G. J. P., van der Kamp, J. Williams, A.M., & Ward, P. (­2005). Anticipation and
visual search behaviour in expert soccer goalkeepers: a ­w ithin-​­group comparison. Ergonom-
ics, 48, ­11–​­14.
Serrano, J. S., Pizarro, A. P., ­García-​­González, L., Domínguez, A. M. & del Villar Álvarez,
F. (­2017). Evolution of tactical behavior of soccer players across their development. Interna-
tional Journal of Performance Analysis in Sport, 17, ­885–​­901.
Sigrist, R., Rauter, G., ­Marchal-​­Crespo, L., Riener, R., Wolf, P. (­2015). Sonification and haptic
feedback in addition to visual feedback enhances complex motor task learning. Experimental
Brain Research, 233, ­909–​­925.
Thatcher, B., Ivanov, G., Szerovay, M., & Mills, G. (­2020). Virtual reality technology in football
coaching: barriers and opportunities. International Sport Coaching Journal, (­­1–​­9), 8(2), 234-243.
Tyldesley, D. A., Bootsma, R. J., & Bomhoff, G. (­1982). Skill level and eye movement patterns
in a sport orientated reaction time task. In H. Rieder, K. Mechling, & K. Reischle (­Eds.),
Proceedings of an International Symposium on Motor Behaviour: Contribution to Learning in
Sport (­p­­p. ­290–​­296). Cologne: Hofmann.
Vaeyens, R., Lenoir, M., Williams, A. M., Mazyn, L., & Philippaerts, R. M. (­2007a). The effects
of task constraints on visual search behavior and d ­ ecision-​­making skill in youth soccer play-
ers. Journal of Sport & Exercise Psychology, 29, ­156–​­175.
Vaeyens, R., Lenoir, M., Williams, A. M., Mazyn, L., & Philippaerts, R. M. (­2007b) Visual
search behavior and d ­ ecision-​­making skill in soccer. Journal of Motor Behavior, 39 (­5),
­395–​­408.
Van Maarseveen, M., Oudejans, R., & Savelsbergh, G. (­2018). ­Self-​­controlled video feedback on
tactical skills for soccer teams results in more active involvement of players. Human Move-
ment Science, 57, ­194–​­204
Vickers, J. N., & Williams, A. M. (­2007). Why some choke and others don’t! Journal of Motor
Behavior, 39, ­381–​­394.
Ward, P., & Williams, A. M. (­2003). Perceptual and cognitive skill development in soccer: the
multidimensional nature of expert performance. Journal of Sport & Exercise Psychology, 25,
­93–​­111.
Ward, P., Hodges, N. J., Starkes, J., & Williams, A. M. (­2007). The road to excellence: deliberate
practice and the development of expertise. High Ability Studies, 18, ­119–​­153.
Whelan, J. (­2021). Decision making in soccer (­Doctoral dissertation, Liverpool John Moores
University, UK). Unpublished.
Williams, A. M. (­2000). Perceptual skill in soccer: implications for talent identification and
development. Journal of Sports Sciences, 18, ­737–​­740.
Williams, A. M., & Burwitz, K. (­1993). Advance cue utilization in soccer. In T. P. Reilly, J.
Clarys, & A. Stibbe (­Eds.), Science and Football II (­p­­p. ­239–​­244). London: E. & F.N. Spon.
Williams, A. M., & Davids, K. (­1998). Visual search strategy, selective attention, and expertise
in soccer. Research Quarterly for Exercise and Sport, 69, ­111–​­128.
Williams, A. M., & Ericsson, K. A. (­2005). Some considerations when applying the expert per-
formance approach in sport. Human Movement Science, 24, ­283–​­307.
Williams, A. M., & North, J. S. (­2009). Identifying the minimal essential information underly-
ing pattern recognition. In D. Arajuo, H. Ripoll, & M. Raab (­Eds), Perspectives on Cognition
and Action (­p­­p. ­95–​­107). New York: Nova Science Publishing Inc.
Williams, A. M., Ward, P., ­Bell-​­Walker, J., & Ford, P. R. (­2012). ­Perceptual-​­cognitive expertise,
practice history profiles and recall performance in soccer. British Journal of Psychology, 103,
­393–​­411.
Williams, A. M., Davids, K., Burwitz, L. & Williams, J. G. (­1994). Visual search strategies of
experienced and inexperienced soccer players. Research Quarterly for Exercise and Sport, 5,
­127–​­135.
140 A. Mark Williams et al.
Williams, A. M., Ford., P. R., Eccles, D., & Ward, P. (­2010) ­Perceptual-​­cognitive expertise in
sport and its acquisition: implications for applied cognitive psychology. Applied Cognitive
Psychology, 25, ­432–​­442.
Williams, A. M., Heron, K., Ward, P., & Smeeton, N. J. (­2005) Using situational probabilities
to train perceptual and cognitive skill in novice soccer players. In T. P. Reilly, J. Cabri, & D.
Araujo (­Eds.), Science and Football V (­p­­p. ­337–​­340). London: Taylor and Francis.
Williams, A. M., Hodges, N. J., North, J. S., & Barton, G. (­2006). Perceiving patterns of play in
dynamic sport tasks: identifying the essential information underlying skilled performance.
Perception, 35, ­317–​­332.
Williams, A. M., & Jackson, R. C. (­2020). Psychology of sport & exercise anticipation in sport:
fifty years on, what have we learned and what research still needs to be undertaken? Psychol-
ogy of Sport and Exercise, 42 (­August), ­16–​­24.
Williams, A. M., Ward, P., Smeeton, N. J., & Ward, J. (­2008). Task specificity, role, and antici-
pation skill in soccer. Research Quarterly for Exercise and Sport, 79, ­429–​­433.
Williams, A. M., Ward, P., Knowles, J. M., & Smeeton, N. J. (­2002). Anticipation skill in a
­real-​­world task: measurement, training, and transfer in tennis. Journal of Experimental Psy-
chology, 8, ­259–​­270.
Wilson, M. R., Wood, G., & Vine, S. J. (­2009). Anxiety, attentional control, and performance
impairment in penalty kicks. Journal of Sport and Exercise Psychology, 31, ­761–​­775.
Wood, G., & Wilson, M. R. (­2011). ­Quiet-​­eye training for soccer penalty kicks. Cognitive Pro-
cessing, 12(3), 257–266. doi:10.1007/­­s10339-­​­­011-­​­­0393-​­0.
Wood, G., Wright, D. J., Harris, D., Pal, A., Franklin, Z. C., & Vine, S. J. (­2020). Testing the
construct validity of a ­soccer-​­specific virtual reality simulator using novice, academy, and
professional soccer players. Virtual Reality, 25, 43–51.
Wright, C., Atkins, S., Jones, B., & Todd, J. (­2013). The role of an elite match analysts within
football. International Journal of Performance Analysis, 22, ­240–​­261.
Wulf, G., Raupach, M., & Pfeiffer, F. (­2005). ­Self-​­controlled observational practice enhances
learning. Research Quarterly for Exercise and Sport, 76, ­107–​­111.
9 Skill acquisition
Player pathways and effective practice
Paul R. Ford and A. Mark Williams

Introduction
Skill is an essential component of soccer at all levels of the game. A key challenge is
how best to develop skilled young players who can potentially become successful pro-
fessionals. While several factors must combine across an extended period for youths to
progress to professional status (­see Rees et al., 2016), the activities that they engage in
during development contribute significantly to the attainment of expertise. In this chap-
ter, we provide a review of the various types of sporting activities that players engage in
during development. We review research assessing the role of practice, play, and compe-
tition in soccer (­see ­Table 9.1). In soccer, ­coach-​­led team practice is the activity in which
players spend most time, so this activity will form the focus of the chapter. We separate
the chapter into sections based on three main areas of research and theory. First, we
review studies where researchers have had professional players retrospectively recall
the amount of time spent in practice and other developmental activities since starting in
the sport. Second, we synthesise studies in which researchers have conducted a system-
atic observation of ­coach-​­led practice sessions in soccer. Third, we review theoretical
accounts of how practice and other activities can be designed to optimally improve the
performances of players. We conclude by presenting future directions on this topic.

Developmental activcties and pathways

Most professional players start playing soccer in childhood, typically at around 5 or
6 years of age, with some variation (­Güllich, 2019; Hendry et al., 2019; Hornig et al.,
2016; Ford et al., 2020). Start age in formal c­ oach-​­led soccer practice often occurs 1
or 2 years after the initial start age in the sport, with relatively small variation across
most countries (­e.g., Ford et al., 2012). No researchers have longitudinally tracked the
activities of players from early childhood into adulthood and professional status. The
problem is identifying from the large playing population base those children who will
eventually progress to professional status. Consequently, researchers have assessed
developmental activities and pathways by asking adult professional players to retro-
spectively recall the activities they engaged in since starting the sport, usually using
questionnaires to collect the data (­Güllich, 2019; Hendry et al., 2019; Hornig et al.,
2016; Ford et al., 2020).
Hornig et al. (­2016) recorded the developmental activities of 52 Bundesliga and 50
­fourth-​­ to ­sixth-​­league male players in Germany. Players reported starting soccer
through ­peer-​­led play at an average age of 4­ –​­5 years, with their start in formal ­coach-​­led

DOI: 10.4324/9781003148418-11
142 Paul R. Ford and A. Mark Williams
Table 9.1 T
 he main soccer activities in which players participate.
Nb. The main intentions of a small set of individual
players within the activity might differ compared to the
main intention

Activity Main intention of participants Main setting

Practice To improve performance Formal

Play Fun and enjoyment Informal
Competition Winning Formal

soccer practice occurring 1 or 2 years later. The 52 Bundesliga players participated more
frequently in soccer ­peer-​­led play compared to ­coach-​­led practice up to the age of 10
years. The frequency of ­coach-​­led soccer practice increased as they aged, becoming sig-
nificantly greater than soccer ­peer-​­led play sometime in ­mid-​­to ­late-​­adolescence, with
­peer-​­led play decreasing across adolescence. The time spent in ­coach-​­led soccer practice
increased linearly from an approximate average of 2.5 h per week over a ­40-​­week season
up to 10 years of age to 13.5 h per week over a 4­ 0-​­week season in adulthood. Players
ended significant engagement in other sports at an average age of ­12–​­13 years and first
played for a representative team at 14 years of age. Players accumulated an average of
4,264 h (­SD = 1,631) in c­ oach-​­led soccer practice prior to making their debut in the first
Bundesliga at age 2­ 1–​­22 years. Half of the players engaged in one to two other sports
across their youth at a significantly lower frequency of sessions when compared to soc-
cer. The data are comparable to those reported for players in other nations (­e.g., Ford
et al., 2012).
The first Bundesliga players engaged in significantly greater amounts of soccer p ­ eer-​
l­ ed play up to 10 years of age when compared to f­ ourth-​­to ­sixth-​­league players, as well
as reporting a significantly earlier start age in junior representative teams (­approximate
average of 14 years of age vs. 16 years). The first Bundesliga players who subsequently
represented the national team ended their significant engagement in other sports later
(­approximate average of 14 years of age vs. 12 years) and made their first Bundesliga
debut earlier (­approximate average of 15 years of age vs. 16 years), when compared to
the other first Bundesliga players. Moreover, national team players differed from other
first Bundesliga players and ­fourth-​­to ­sixth-​­league players by engaging in significantly
more ­coach-​­led practice sessions in other sports during adolescence. However, the fre-
quency of these sessions was significantly lower than that reported for c­ oach-​­led soc-
cer practice. The first Bundesliga players engaged in a greater amount and frequency
of ­coach-​­led soccer practice in early adulthood (­­19–​­21 years of age) when compared
to the other two groups, but from 22 years of age onwards, there was no difference be-
tween national team and other first Bundesliga players. There were no other ­between-​
g­ roup differences reported. It is worth noting that relatively large variations existed
across many of the measured variables.
Professional female players have been participants in three studies. The develop-
mental activities of 29 female first Bundesliga players from one of the leading clubs in
Germany, half of whom were national team players, were assessed by Güllich (­2019).
Similarly, Hendry et al. (­2019) assessed the developmental activities of 21 national team
and 24 ­university-​­level female players in Canada. Finally, the developmental activities
of 86 players across the female national teams of Australia, Canada, England, Sweden,
and the United States of America were recorded by Ford et al. (­2020). The average
 Skill acquisition 143
start age in soccer in these studies was around 5 years of age, with start age in ­coach-​
l­ ed soccer practice occurring approximately a year later. Professional female players in
the three studies engaged in significantly more soccer activity than other sports during
childhood and adolescence. The relative amounts of play/­practice in soccer during
this period differed between the three studies. Güllich (­2019) reported that the first
Bundesliga players engaged in more sessions and amounts of ­p eer-​­led play in soccer
compared to c­ oach-​­led soccer practice during childhood and early adolescence (­see

a)
18
Play
16
Practice
14

12
Hours per week

10

0
-6 7 to 10 11 to 14 15 to 18 19 to 21 22+
Age category in years
b)
18
Play
16
Practice
14

12
Hours per week

10

0
-6 7 to 10 11 to 14 15 to 18 19 to 21 22+
Age category in years

­Figure 9.1 Hours per week in soccer practice and play across the development of (­a) 14
national team and (­b) 15 Bundesliga players in Germany.
144 Paul R. Ford and A. Mark Williams
­ igure 9.1), whereas in the other two studies there was either no difference in hours
F
accumulated between these two activities for this period (­Ford et al., 2020) or less play
than practice (­Hendry et al., 2019). Two studies report the start age for playing ­m ixed-​
­gender soccer as 6­ –​­7 years, whereas the end age for this activity was earlier for players
in Canada (­11 years of age, Hendry et al. 2019) compared to players in Germany (­17
years of age, Güllich, 2019). The engagement in other sports did not differ between
studies in childhood, albeit not all players engaged in other sports. The players who
participated accumulated around an average of 1,000 h in an average of four other
sports between 6 and 12 years of age in two of the studies (­Ford et al., 2020; Hendry
et al., 2019), which equates to around ­2–​­3 h week−1 over 7 × ­50-​­week years, similar
to that found for the players in Germany (­Güllich, 2019). Overall, these studies show
early engagement in soccer as the predominant approach with some diversification
into other sports during childhood and early adolescence.
Published reports suggest that professional soccer players should engage in mean-
ingful amounts of ­soccer-​­specific ­peer-​­led play during childhood (­Ford et al., 2020;
Güllich, 2019; Hornig et al., 2016). A concern is that children in some countries do
not engage in as much s­ occer-​­specific ­peer-​­led play activity compared to previous gen-
erations. Moreover, children in some countries may be engaging in too much formal
practice and competition at a young age, which might lead to negative consequences
later in life (­e.g., Baker et al., 2009). Therefore, there is a need for adults to provide
more opportunities for children to engage in meaningful amounts of ­soccer-​­specific
­p eer-​­led play. Some practical solutions include scheduling more ­soccer-​­specific play
in formal physical education classes and c­ oach-​­led practice sessions; designing and
creating school playgrounds, parks, and areas that enable children to safely engage
in this activity; encouraging child players to engage in this activity; and changing the
formal match or games programme so that it becomes more ­play-​­oriented (­e.g., Feno-
glio, 2003).
In all three studies (­Ford et al., 2020; Güllich, 2019; Hendry et al., 2019), the time
spent in ­coach-​­led soccer practice increased across adolescence when compared to
childhood, whereas time spent in p ­ eer-​­led soccer play and other sports decreased
from ­m id-​­adolescence. The average time spent in ­coach-​­led soccer practice during
adolescence was slightly higher in Canadian national team players (­g reater than 10
h week−1 across 7 × ­50-​­week years, Hendry et al., 2019) when compared to players
in the other two studies. The start age in senior professional soccer was 1­ 7–​­18 years
and with the national teams, it was 1­ 9–​­20 years (­Ford et al., 2020; Güllich, 2019). In
early adulthood, the time spent in c­ oach-​­led soccer practice was greater when com-
pared to adolescence, equating to around 1­ 2–​­13 h week−1 over 5­ 0-​­week years in the
two studies that reported this variable (­Ford et al., 2020; Güllich, 2019), plus at least
one match per week over a 4­ 0-​­week season (­Ford et al., 2020). The time spent in other
sports decreased to negligible amounts in adulthood compared to adolescence (­Ford
et al., 2020; Güllich, 2019). Overall, these three studies show specialisation in soccer
occurring in adolescence and an intensification of participation in the sport occurring
across this period and into adulthood, as evidenced by increasing amounts of c­ oach-​
­led soccer practice and promotions to ­h igher-​­level teams.
Two of the studies reported comparisons of national team players to other profes-
sional players (­Güllich, 2019) or ­university-​­level players (­Hendry et al., 2019). Güllich
(­2019) reported that national team players had an earlier start age in ­p eer-​­led soc-
cer play, more hours in ­peer-​­led play in soccer and ­coach-​­led practice in other sports
 Skill acquisition 145
through childhood and early adolescence, fewer hours in ­coach-​­led soccer practice
across that period, and a later start age in soccer competition and national youth
teams, when compared with the other professional players. Hendry et al. (­2019) re-
ported that national team players had a later start age in formal soccer activities and
in an academy, more hours in p ­ eer-​­led play in soccer through childhood and early ad-
olescence, and fewer other sports, when compared with u ­ niversity-​­level players. Some
differentiating variables were the same in the two studies (­Güllich, 2019; Hendry et al.,
2019). First, later start ages in some formal soccer activities and in joining ­h igher-​­level
teams were found in both studies for national team players. Second, more hours in
­soccer-​­specific p­ eer-​­led play compared to other activities through childhood and early
adolescence were found in both studies. Other researchers have found more hours in
­p eer-​­led soccer play through childhood for male youth players in English academies
who received a professional contract compared to those who did not (­Ford et al., 2009;
Ford & Williams, 2012) and in first Bundesliga male players compared to f­ourth-​­to
­sixth-​­league players (­Hornig et al., 2016).
In three out of the four studies, the authors explicitly noted that there was large
variability in their data (­Hendry et al., 2019; Hornig et al., 2016; Ford et al., 2020).
In other words, there were professional players in the studies whose developmental
activities notably differed to the reported averages for their group (­for detail, see Ford
et al., 2020). Moreover, there was no measure in these four studies of the effects on cur-
rent or future player performance of each different bout, block, or phase of activity.
Therefore, these studies do not show that any of the activities caused the attainment of
professional status and performance (­Ford & Williams, 2017). Furthermore, there is
no measurement of player soccer performance in these studies, so the relationship be-
tween activities engaged in and performance cannot be tested. Of course, it is obvious
that different bouts, blocks, or phases of activity could have very different effects on
improving current or future player performance. Finally, these studies assess practice,
play, and competition at a ­macro-​­level and provide no information on what the play-
ers did during those activities. In the next section, we review studies that assess the
microstructure of these soccer activities to reveal what players are doing.

Microstructure of practice
Researchers have filmed ­coach-​­led soccer practice sessions and analysed the micro-
structure of the activities engaged in by youth players. In two separate studies (­Ford
et al., 2010; Partington & Cushion, 2011) youth players engaged in ­drill-​­based activi-
ties for approximately ­two-​­thirds of ­coach-​­led team practice time, with the remaining
third of the time being spent in ­games-​­based activities. Coaches are thought to use
­drill-​­based activities to lessen the demands of the game for learners and because per-
formance appears to be successful during this type of activity (­Patterson & Lee, 2008).
Although the use of these types of activities is ­well-​­intended, and broadly speaking
repetition is an important part of practice, such widespread use has been questioned
(­Ford et al., 2010; Partington & Cushion, 2011). A suggestion is that d ­ rill-​­based ac-
tivities present a reduced opportunity for players to develop the ­perceptual-​­cognitive
skills that are important during m ­ atch-​­play at higher levels of the sport, particularly
visual search, anticipation, and d ­ ecision-​­making. It was suggested that g­ ames-​­based
activities present a better way to engage and develop the ­p erceptual-​­cognitive skills
required in ­match-​­play (­Ford et al., 2010; Partington & Cushion, 2011).
146 Paul R. Ford and A. Mark Williams
More recently, in three other studies (­Ford & Whelan, 2016; O’Connor et al., 2018;
Roca & Ford, 2020) researchers filmed ­coach-​­led youth soccer practice sessions and
analysed the microstructure of the activities. In these studies, youth players spent more
time in ­games-​­based practice activities compared with ­drill-​­based activities. Ford and
Whelan (­2016) analysed 108 coaching sessions involving child and adolescent teams
from the academies of three Premier League clubs, three Football League clubs, and
three amateur clubs in England. Three ­in-​­season sessions were filmed per team and
the video was analysed for the relative amounts of d ­ rill-​­or g­ ames-​­based activities. The
sessions contained 59% ­games-​­based activity, 20% ­drill-​­based activity, and 21% time
transitioning between activities. More time was spent in ­games-​­based activities for
the child compared with adolescent teams, but there were no differences between skill
levels. Most practice sessions were held in s­ mall-​­or ­medium-​­sized areas on artificial
grass. The increase in ­games-​­based activity in these later compared to earlier studies
may be due to recent changes to coach education and national guidelines (­e.g., The
Football Association). However, coaches should consider training more often than
currently on natural compared to artificial grass to increase realism, representative-
ness, variability, and specificity (­e.g., Andersson et al., 2008).
There are a few limitations with studies in which the microstructure of ­coach-​­led
soccer practice has been recorded and analysed. First, there is a lack of studies on
adult professional and female soccer teams. Second, some key contextual factors sur-
rounding the sessions are missing in that the intentions of the coaches have not been
recorded; we do not know why they used a particular activity at that specific time
point in player or team development. Third, soccer is a complex sport and there are
multiple aspects of performance that one can choose to practice with the ball in train-
ing or coaching sessions at any given time (­i.e., various technical skills and tactics or
strategies), but this has not been considered in this research. Fourth, although it is
assumed that ­p eer-​­led soccer play involves mostly g­ ames-​­based activities, there are no
studies published in which researchers have assessed what players do in this activity,
unlike for ­coach-​­led youth soccer practice. Finally, the binary differentiation between
­drill-​­and ­games-​­based activities was a heuristic used to ease understanding and help
change coach behaviour. In reality, common practice activities with the ball in soccer
lie on a continuum of representativeness when compared to ­match-​­play, as is shown in
­Figure 9.2. Moreover, the activity categories themselves in ­Figure 9.2 are continuous
and potentially mixable. For example, some phases of play activities in soccer can be
very similar to small-sided games and decision-making drills and others can be more
like the target context of ­match-​­play. Coaches are encouraged to work with special-
ists in skill acquisition to design these types of activity and practice environments
(­Williams & Ford, 2009). In the next section, we review the theory that details how to
optimise these practice activities.

Decision-making Unidirectional Small-sided Phases of play Match-play

Drills Drills Games Games (Target Context)

Usually increasing realism, representativeness, and specificity

­Figure 9.2 The continuum of representativeness for common practice activities with the
ball in soccer.
 Skill acquisition 147
Theoretical accounts

Deliberate practice
Deliberate practice theory has been outlined in detail in several publications by Erics-
son (­1996; 1998; 2003; 2006; 2007; 2013; 2017; 2020; Ericsson & Pool, 2016; Ericsson
et al., 1993; Ericsson & Towne, 2010) and there has been a debate between researchers
about its content, including in sport (­Macnamara et al., 2016a, b; Ericsson, 2016). The
activity of deliberate practice differs according to Ericsson (­2020; Ericsson & Pool,
2016) from other forms of practice, such as maintenance practice. Two recent publica-
tions have used acronyms to clarify the definition of deliberate practice (­Eccles et al.,
2020) and demonstrate how it can be administered in sport (­Ford & Coughlan, 2019).
Eccles et al. (­2020) forwarded the acronym EXPERTS to clarify the definition of
deliberate practice. They state that deliberate practice occurs in domains and for skills
where established (­E) and effective training techniques exist. Moreover, it involves
improving existing (­X) individual skills in a ­step-­​­­by-​­step process and attempts at skills
beyond the current ability level of the performer, termed ‘­pushing (­P) the envelope’.
Deliberate practice enhances (­E) mental representations making them more sophisti-
cated. Furthermore, improvement occurs by obtaining and responding (­R) to individ-
ualised feedback from instructors during the activity. It requires total (­T) application
from the performer in terms of giving their full attention and involves setting and
focusing on specific (­S) goals for improvement.
Second, Ford and Coughlan (­2019) use the acronym ASPIRE (­Analyse, Select, Prac-
tice, Individualise, Repetition, Evaluate) to detail how deliberate practice can be ad-
ministered in sport. First, player or team performance is analysed (­A) to select (­S)
the key aspect of performance requiring improvement at that time. Second, practice
(­P) bouts occur to improve the selected key aspect of performance involving individ-
ualisation (­I) of processes and feedback, along with repetition (­R) of the aspect in a
representative environment. Finally, player or team performance is evaluated (­E) to
determine the amount of improvement in the key aspect, with further practice bouts
required when there is no or little improvement or a new aspect of performance se-
lected from analysis if there is. Researchers have not assessed these hypotheses (­Eccles
et al., 2020; Ford & Coughlan, 2019) or those from deliberate practice theory in rela-
tion to their effect on performance improvement in soccer players.
The ‘­power law of practice’ holds that in the earlier stages of learning a new task
or domain, performance improvement is rapid, whereas later in the process the rate
begins to slow or plateau (­Newell & Rosenbloom, 1981). For many performers, the
plateau occurs because they are competent at the task and are satisfied to remain at
that level of performance. However, Ericsson (­2003, 2007) has termed this plateau in
performance ‘­arrested development’. He holds that expert performers are not satis-
fied with being merely competent, rather they begin to repetitively engage in bouts of
deliberate practice with the intention of improving performance beyond its current
level. Almost certainly, adolescent players desiring to be professionals should engage
in deliberate practice to avoid a plateau in performance and ‘­arrested development’. In
addition, deliberate practice can focus on aspects of performance for the team, unit,
and/­or player, focusing on enhancing strengths and improving weaknesses, but this
process should be individualised to each player. Therefore, the aspect of performance
that is chosen to practice very much depends on the current strengths and weaknesses
148 Paul R. Ford and A. Mark Williams
of the team, unit, or individual under consideration. Of course, there are multiple
physical, psychological, anthropometrical, skill, and social aspects of performance
that require improvement. In soccer, the difficulty comes when trying to individualise
this process to each player as is required in theory because there are usually too few
coaches available. We recommend the ASPIRE process (­Ford & Coughlan, 2019) is
used as the framework for these decisions and for the practice itself which should also
match the characteristics outlined in the EXPERTS acronym (­Eccles et al., 2020).
A key part of deliberate practice theory is that it is an effortful activity that can only
be maintained for short periods, such that rest and recovery are required (­Ericsson
et al., 1993). Therefore, rest and recovery processes should be optimised for adoles-
cents and adult players who not only engage in deliberate practice but also frequently
play in professional soccer matches. We would expect to see this activity occurring in
what we term a deliberate environment (­Ford et al., 2013; 2015; Ford & Coughlan, 2019).
A deliberate environment exists where the decisions, behaviours, and activities of the
players in their sporting and home life are optimally ­goal-​­directed toward improving
or maintaining their competitive performance (­Ford et al., 2015).

Challenge point hypothesis

The challenge point framework presented by Guadagnoli and Lee (­2004; see also
Hodges & Lohse, 2022) holds that practice activities present different levels of dif-
ficulty depending on the skill level of the performer and the practice conditions.
Nominal task difficulty is the constant difficulty of the task, irrespective of the person
performing the task. In contrast, functional task difficulty includes the task and how
challenging it is to the individual. The optimal challenge point occurs around the point
of functional task difficulty that a performer at a specific skill level would need to
optimise perceptual, cognitive, and motor learning. When a practice task is too easy
or too difficult for a performer either no or minimal learning may occur. A related
concept is task simplification (­Renshaw, Chow, Davids, & Hammond, 2010; Davids
et al., 2008) which involves lowering the difficulty of the task to an appropriate level
for the learner while maintaining the natural performance conditions of the task (­e.g.,
­small-​­sided games in soccer). There are several methods that coaches can use to reduce
the functional task difficulty of ­small-​­sided games for the skill level of the learners
participating (­e.g., ­Table 9.2).

­Table 9.2 Some examples of manipulations to the rules of ­small-​­sided games (­e.g., 3 vs. 3) that
may reduce the difficulty of the sport for learners

(­1) Increase the size of the pitches (­e.g, Clemente & Sarmento, 2020)
(­2) Reduce the number of players on each team (­e.g., Clemente & Sarmento, 2020)
(­3) Include extra players who play for whichever team is in possession of the ball during the
game (­e.g., Clemente & Sarmento, 2020)
(­4) Ban tackling only allowing blocks of passes and pressure
(­5) Ban tackling in the middle half of the pitch ­only – ​­only allowing blocks of passes and
pressure in that area
(­6) Use unidirectional games in which there are more teammates than opposition (­e.g., 2 vs.
1; 3 vs. 1; 4 vs. 2)
(­7) Have the coach join in the play
(­8) Ban ­r unning – ​­have the players walk only
 Skill acquisition 149
When an aspect of an activity is too demanding for learners, this is known as a
rate limiter. Rate limiters are most often thought of as an individual characteristic,
such as height or muscle strength, that is holding back the progression of learning
and development (­Haywood & Getchell, 2001; Horn & Williams, 2004). However,
rate limiters can exist within characteristics of the task or environment that can
hold back the progression of learning. For example, in soccer, opponents tackling
the player in possession of the ball and reducing time/­space make the game very
difficult for relatively novice players and acts as a key rate limiter reducing the
opportunity for them to learn how to manipulate the ball and move around op-
ponents. By identifying and changing the task or environmental rate limiters, the
difficulty of the task can be lowered to the optimal challenge point for the learners
(­s ee ­Table 9.2).

­Constraints-​­led approach
The ­constraints-​­led approach has been fully outlined in detail in several books (­e.g.,
Button et al., 2020; Chow et al., 2015; Davids et al., 2008; Renshaw et al., 2019) and re-
view articles (­e.g., Otte et al., 2021; Renshaw et al.; 2016; Renshaw & Chow, 2019). Con-
straints are defined as interacting boundaries that shape and bring order to behaviour
and its emergence in humans (­Newell, 1986). Three types of interacting constraints ex-
ist that operate at differing timescales: (­i) individual constraints, such as leg strength,
current ability, or aerobic capacity; (­ii) environment constraints, such as the ground
surface and light; and (­iii) task constraints, such as the rules, goals, and conditions
of soccer. The performer generates movement solutions through a ­self-​­organisation
process that is bound by these constraints in their current environment (­Newell, 1986).
Learning and acquisition occurs through the performer becoming better attuned to
key information and intentions in that environment (­Renshaw & Chow, 2019). Of
course, information in the ­match-​­play environment includes the movements, actions,
intentions, patterns, and tactics of teammates and opponents upon a pitch that has
its markings and a goal at either end. A key aspect of this approach is that infor-
mation, intentions, and actions from the target context should be represented during
practice so that performers can search, discover, and exploit its use (­Otte et al., 2021).
Furthermore, coaches can manipulate constraints during practice so that behaviour
emerges and learning occurs that is relevant for the later target context of ­match-​­play.
Task constraints are perhaps the easiest for coaches to manipulate and many coaches
already do this intuitively. For example, ­Table 9.3 shows practice activities in which
the rules of the game (­or task constraints) have been changed to bring about a greater
frequency of desired actions and learning in players. However, the ­constraints-​­led ap-
proach and related theories provide a framework for coaches that goes beyond their
intuitive processes when designing learning environments (­for reviews, see Chow et al.,
2015; Otte et al., 2021; O Sullivan et al., 2021).

­G ames-​­based approaches
A few ­games-​­based approaches (­GBAs) to skill acquisition in sport exist, particu-
larly those from the physical education field (­e.g., Teaching Games for Understanding
(­TGFU); Games Sense; and Play Practice; for a review, see Kinnerk et al., 2018), but
also more recently from outside of that field (­e.g., ­Video-​­game Design; for a review, see
150 Paul R. Ford and A. Mark Williams
­Table 9.3 Some examples of manipulations to the rules of ­small-​­sided games (­e.g., 4 vs. 4) so
that players practice specific ­p erceptual-​­motor skills more frequently than normal

Motor skill Game manipulations

Dribbling Remove goals and have players score by dribbling across their opposition’s
goal touch lines.
Passing All s­ mall-​­sided games contain a lot of passing, although to encourage one
and ­two-​­touch passing, the coach can limit touches (­e.g., “­­2-​­touch”).
Long passing Make the pitch very long but not too wide. Alternatively, have two very
small goals with no goalkeepers and a “­no go” penalty area.
Forward passing Remove goals and replace with two relatively large American Football
style “­end zones”. Players score by passing the ball into the path of a
teammate who runs into the opposition’s end zone. Use the touchline
that marks the start of the “­end zone” as an “­offside line”.
­Switch-​­play Make the pitch wide but short. Plus, remove goals and replace with two
passing smaller goals at each goal line, which are placed on the goal lines
extending in from both corners. Players must score by dribbling the ball
through one of the two small goals.
Turning Allow both teams to score at either end of the pitch.
Shooting Place large goal nets at either end of the pitch.
Crossing Place corridors along the touchlines from which players who play for
whichever team is in possession can cross the ball without opposition.
Perhaps limit the number of players allowed in the “­p enalty area”.

Price et al., 2018). There is a large volume of literature outlining and assessing GBA.
Kinnerk et al. (­2018) conducted one of several systematic reviews of GBA studies in
which researchers have evaluated outcomes in competitive team sport settings. They
located 23 studies that included 21 studies assessing invasion game sports, from which
eight studies were s­ occer-​­based. There were 13 studies with youth participants and 14
studies contained interventions of which six were ­longer-​­term. There were six studies
utilising systematic observation tools to assess p ­ ost-​­intervention improvements in par-
ticipant game performance. Altogether, five out of those six studies reported signifi-
cant improvements in various aspects of ­decision-​­making and tactical ability. There
were two out of six studies that found significant improvements in technical ability in
soccer, specifically passing (­four out of six studies found no improvement here). Trans-
fer to ­match-​­play was assessed in two out of six studies. Those two studies (­Pizarro
et al., 2017; Práxedes et al., 2016) contained the longest interventions (­12 weeks), with
most studies having shorter interventions (­­4–​­5 weeks) and no test of transfer to ­match-​
p­ lay. Moreover, the two studies (­Pizarro et al., 2017; Práxedes et al., 2016) contained
the same age players (­U11/­12) and skill level (­intermediate). Both studies found sig-
nificant ­post-​­intervention ­match-​­play performance improvement in ­decision-​­making
and technical ability. The use of questioning coaching behaviours varied between
the six studies, there was an overall lack of detail on the actual game activities, and
there was a lack of control groups, confounding findings. Overall, we consider there
to be ­medium-​­strength evidence for the use of GBA, particularly with younger play-
ers. Intervention studies contain limitations and mainly assess the TGFU approach,
as opposed to other GBA. It is likely the application of GBA and the activities in
­Figure 9.2 are c­ ontext-​­specific in that it will depend on several current contextual fac-
tors surrounding the bout of activity/­ies, such as the current age stage of the players
or their current strengths and weaknesses, etc. Coaches who work with specialists in
 Skill acquisition 151
skill acquisition may be best placed to optimally design practice activities for player
improvement within a specific context (­Williams & Ford, 2009).

Future directions and conclusions

There are two immediate priorities for researchers in this area that have been outlined
in detail by Williams et al. (­2020). First, there are several theoretical ideas on opti-
mal potential activities for players, many of which have been outlined in this chap-
ter. Researchers need to provide a rigorous ­quasi-​­experimental assessment of these
ideas, using robust study designs and methods more common to medicine, such as
randomised control trials (­for an example in soccer, see Roberts et al., 2020; see also
Miller et al., 2016). Second, a standardised method to measure player performance
in matches and ­small-​­sided games is required to assess the causal effects of potential
optimal activities and interventions in these research studies. Researchers need to val-
idate this reliable standard method to measure player performance in matches and
­small-​­sided games. Performance analysis may provide the best tools to achieve this
goal and some research has already been published on this topic (­e.g., van Maarseveen
et al., 2017).
The practice and other activities in which players engage influence their develop-
ment and attainment. In this chapter, we reviewed theory and research on this topic
and outlined implications for coaches and other interested persons involved in the
design of practice activities and environments for players. We recommend aspiring
soccer players to progress from mostly s­ occer-​­specific ­play-​­type activities in childhood
to mostly deliberate practice activities in adolescence and adulthood. We advocate
that specialists in skill acquisition are employed by clubs and national associations to
provide support with the design of practice environments. Regardless, the publication
of research and theory in this area will continue and we recommended it focuses on
robustly testing theoretical ideas using accepted experimental designs and creating a
standard method to measure player performance in matches that can be used to meas-
ure the effects of these ideas.

References
Andersson, H., Ekblom, B., & Krustrup, P. (­2008). Elite football on artificial turf versus natu-
ral grass: movement patterns technical standards, and player impressions. Journal of Sports
Sciences, 26, ­113–​­122.
Baker, J, Cobley, S., & Fraser-Thomas, J. (2009). What do we know about early sport speciali-
zation? Not much! High Ability Studies, 20, 77–89.
Button, C., Seifert, L., Chow, J. Y., Araújo, D., & Davids, K. (­2020). Dynamics of Skill Acquisi-
tion: An Ecological Dynamics rationale (­2nd Ed.). Champaignl: Human Kinetics.
Chow, J. Y., Davids, K., Button, C., & Renshaw, I. (­2015). Nonlinear Pedagogy in Skill Acquisi-
tion: An Introduction. London: Routledge.
Clemente, F. M. & Sarmento, H. (­2020). The effects of s­ mall-​­sided soccer games on technical
actions and skills: A systematic review. Human Movement, 21, ­100–​­119.
Davids, K., Button, C., & Bennett, S. (­2008). Dynamics of Skill Acquisition: A ­Constraints-​­led
Approach. Champaign, IL: Human Kinetics.
Eccles, D. W., Leone, E. J., & Williams, A. M. (­2020). Deliberate practice: What is it and how
can I use it? Journal of Sport Psychology in Action, 13, 16–26
152 Paul R. Ford and A. Mark Williams
Ericsson, K. A. (­Ed.) (­1996). The acquisition of expert performance: an introduction to some
of the issues. In K. A. Ericsson (­Ed.), The Road to Excellence: The Acquisition of Expert
Performance in the Arts and Sciences, Sports and Games (­p­­p. ­1–​­50). Hillsdale, NJ: Lawrence
Erlbaum.
Ericsson, K. A. (­1998). The scientific study of expert levels of performance: General implica-
tions for optimal learning and creativity. High Ability Studies, 9, ­75–​­100.
Ericsson, K. A. (­2003). Development of elite performance and deliberate practice: an update
from the perspective of the expert performance approach. In J. L. Starkes & K. A. Ericsson
(­Eds.), Expert Performance in Sports: Advances in Research on Sport Expertise (­p­­p. ­49–​­84).
Champaign: IL, Human Kinetics.
Ericsson, K. A. (­2006). The influence of experience and deliberate practice on the develop-
ment of superior expert performance. In K. A. Ericsson, N. Charness, P. Feltovich, & R. R.
Hoffman (­Eds.), Cambridge Handbook of Expertise and Expert Performance (­p­­p. ­683–​­703).
Cambridge, UK: Cambridge University Press.
Ericsson, K. A. (­2007). Deliberate practice and the modifiability of body and mind: toward a
science of the structure and acquisition of expert and elite performance. International Jour-
nal of Sport Psychology, 38, ­4 –​­34.
Ericsson, K. A. (­2013). Training history, deliberate practice and elite sports performance: an
analysis in response to Tucker and Collins r­ eview – what ​­ makes champions? British Journal
of Sports Medicine, 47, ­533–​­535.
Ericsson, K. A. (2016). Summing up hours of any type of practice versus identifying optimal
practice activities: Commentary on Macnamara, Moreau, & Hambrick (2016). Perspectives
on Psychological Science, 11, 351–354.
Ericsson, K. A. (­2017). Summing up hours of any type of practice versus identifying optimal
practice activities: commentary on Macnamara, Moreau, & Hambrick (­2016). Perspectives
on Psychological Science, 11, ­351–​­354.
Ericsson, K. A. (­2020). Towards a science of the acquisition of expert performance in sports:
Clarifying the differences between deliberate practice and other types of practice. Journal of
Sports Sciences, 38, ­159–​­176.
Ericsson, K. A., Krampe, R. T., & T ­ esch-​­Römer, C. (­1993). The role of deliberate practice in the
acquisition of expert performance. Psychological Review, 100, ­363–​­406.
Ericsson, K. A. & Towne, T. J. (­2010). Expertise. Wiley Interdisciplinary Reviews Cognitive Sci-
ence, 1, ­404–​­416.
Ericsson, K. A. & Pool, R. (­2016). Peak: Secrets From the New Science of Success. Boston, USA:
Houghton Mifflin Harcourt.
Fenoglio, R. (­2003). The Manchester United 4 v 4 pilot scheme for U9s. Insight: The FA Coaches
Association Journal, 6 (­3), ­18–​­19.
Ford, P. R., Carling, C., Garces, M., Marques, M., Miguel, C., Farrant, A., Stenling, A.,
Moreno, J., Le Gall, F., Holmström, S., Salmela, J. H., & Williams, A. M. (­2012). The devel-
opmental activities of elite soccer players aged u ­ nder-​­16 years from Brazil, England, France,
Ghana, Mexico, Portugal and Sweden. Journal of Sports Sciences, 30, ­1653–​­1663.
Ford, P. R. & Coughlan, E. (­2019). Operationalizing deliberate practice for performance im-
provement in sport. In A. M. Williams & N. J. Hodges (­Eds.), Skill Acquisition in Sport:
Research, Theory and Practice. 3rd Edn. London: Routledge.
Ford, P. R., Coughlan, E. K., Hodges, N. J., & Williams, A. M. (­2015). Deliberate practice in
sport. In J. Baker & D. Farrow (­Eds.), The Handbook of Sport Expertise (­p­­p. ­347–​­362). Lon-
don: Routledge.
Ford, P. R., Hodges, N. J., & Williams, A. M. (­2013). Creating champions: the development of
expertise in sports. In S. B. Kaufman (­Ed.), Beyond Talent: The Complexity of Greatness (­pp.­
391–​­414). Oxford: Oxford University Press.
Ford, P. R., Hodges, N. J., Broadbent, D., O’Connor, D., Scott, D., Datson, N., Andersson,
H. A., & Williams, A. M. (­2020). The developmental and professional activities of female
 Skill acquisition 153
international soccer players from five h ­ igh-​­performing nations. Journal of Sports Sciences,
38, ­1432–​­1440.
Ford, P. R., Ward, P., Hodges, N. J., & Williams, A. M. (­2009). The role of deliberate practice
and play in career progression in sport: the early engagement hypothesis. High Ability Stud-
ies, 20, ­65–​­75.
Ford, P. R. & Whelan, J. (­2016). Practice activities during coaching sessions in elite youth
football and their effect on skill acquisition. In W. Allison, A. Abraham, & A. Cale (­Eds.),
Advances in Coach Education and Development: From Research to Practice (­p­­p. ­112–​­123).
London: Routledge.
Ford P. R., & Williams A. M. (­2017). Sport activity in childhood: early specialisation and diver-
sification. In J. Baker, S. Cobley, J. Schorer, & N. Wattie (­Eds.), Handbook of Talent Identifi-
cation and Development (­p­­p. ­117–​­132). London: Routledge.
Ford, P. R., Yates, I. & Williams, A. M. (­2010). An analysis of practice activities and instruc-
tional behaviours used by youth soccer coaches during practice: exploring the link between
science and application. Journal of Sports Sciences, 28, ­483–​­495.
Guadagnoli, M. A, & Lee, T. D. (­2004). Challenge point: a framework for conceptualizing the ef-
fects of various practice conditions in motor learning. Journal of Motor Behavior, 36, ­212–​­224.
Güllich, A. (­2019). “­­Macro-​­structure” of developmental participation histories and “­­micro-​
­structure” of practice of German female ­world-​­class and ­national-​­class football players.
Journal of Sports Sciences, 37, ­1347–​­1355.
Haywood, K., & Getchell, N. (­2001). Life Span Motor Development. Champaign, IL: Human
Kinetics.
Hendry, D., Williams, A. M., Ford, P. R., & Hodges, N. J. (­2019). Developmental activities and
perceptions of challenge for national and varsity women soccer players in Canada. Psychol-
ogy of Sport and Exercise, 43, ­210–​­218.
Hodges, N. J. & Lohse, K. R. (­2022). An extended ­challenge-​­based framework for practice
design in sports coaching. Journal of Sports Sciences. Advance online publication. DOI:
10.1080/­02640414.2021.2015917
Horn, R., & Williams, A. M. (­2004). Rate limiters in the development of football skills. Insight:
The FA Coaches Association Journal, 7 (­1), ­59–​­62.
Hornig, M., Aust, F. & Güllich, A. (2016). Practice and play in the development of German top-
level professional football players. European Journal of Sport Science, 16, 96–105.
Kinnerk, P., Harvey, S., MacDonncha, C., & Lyons, M. (­2018). A review of the ­game-​­based
approaches to coaching literature in competitive team sport settings. Quest, 70, ­401–​­418.
Macnamara, B. N., Moreau, D., & Hambrick, D. Z. (­2016a). The relationship between deliber-
ate practice and performance in sports: a ­meta-​­analysis. Perspectives on Psychological Sci-
ence, 11, ­333–​­350.
Macnamara, B. N., Hambrick, D. Z., & Moreau, D. (­2016b). How important is deliberate prac-
tice? Reply to Ericsson (­2016b). Perspectives on Psychological Science, 11, ­355–​­358.
Miller, A., Harvey, S., Morley, D., Nemes, R., Janes, M., & Eather, N. (­2016). Exposing athletes
to playing form activity: outcomes of a randomised control trial among community netball
teams using a ­game-​­centred approach. Journal of Sports Sciences, 35, ­1846–​­1857.
Newell, A., & Rosenbloom, P. S. (­1981). Mechanisms of skill acquisition and the law of practice. In
J. R. Anderson (­Ed.), Cognitive Skills and Their Acquisition (­p­­p. ­1–​­55). Hillsdale, NJ: Erlbaum.
Newell, K. M. (1986). Coordination, control, and skill. In D. Goodman, R. B. Wilberg, & I. M.
Franks (Eds.), Differing Perspectives in Motor Learning, Memory and Control (pp. 295–317).
Amsterdam: Elsevier.
O’ Connor, D., Larkin, P., & Williams, A. (­2018). Observations of youth football training: how do
coaches structure training sessions for player development? Journal of Sports Sciences, 36, ­39–​­47
O’ Sullivan, M. O., Woods, C. T., Vaughan, J., & Davids, K. (­2021). Towards a contemporary
player learning in development framework for sports practitioners. International Journal of
Sports Science & Coaching, 16, ­1214–​­1222.
154 Paul R. Ford and A. Mark Williams
Otte, F. W., Davids, K., Millar, S. K., & Klatt, S. (­2021). Understanding how athletes learn: in-
tegrating skill training concepts, theory, and practice from an ecological perspective. Applied
Coaching Research Journal, 7. Retrieved January 12, 2022 from https://­w ww.ukcoaching.
org/­getattachment/­Resources/­Topics/­Research/­­Applied-­​­­Coaching-­​­­Research-­​­­Journal-­​­­April-​
­2021/­­Research-­​­­Journal-­​­­Vol-­​­­7-­​­­Understanding-­​­­How-­​­­Athletes-​­Learn.pdf?lang=­en-​­GB
Partington, M., & Cushion, C. (­2011). An investigation of the practice activities and coaching
behaviors of professional t­ op-​­level youth soccer coaches. Scandinavian Journal of Medicine
and Science in Sports, 23, 374, 382.
Patterson, J. T., & Lee, T. (­2008). Organizing practice: the interaction of repetition and cogni-
tive effort for skilled performance. In D. Farrow, J. Baker, & C. McMahon (­Eds.), Developing
Sports Expertise: Researchers and Coaches put Theory into Practice (­p­­p. ­119–​­134). London:
Routledge.
Pizarro, A. P., Domínguez, A. M., Serrano, J. S., G ­ arcía-​­González, L., & Del Villar Álvarez, F.
(­2017). The effects of a comprehensive teaching program on dribbling and passing d ­ ecision-​
­making and execution skills of young footballers. Kinesiology, 49, ­74–​­83.
Práxedes, A., Moreno, A., Sevil, J., ­García-​­González, L., & Del Villar, F. (­2016). A preliminary
study of the effects of a comprehensive teaching program, based on questioning, to improve
tactical actions in young footballers. Perceptual & Motor Skills, 122, ­742–​­756.
Price, A., Collins, D., Stoszkowski, J., & Pill, S. (­2018). Learning to play soccer: lessons on
­meta-​­cognition from video game design. Quest, 70, ­321–​­333.
Rees, T., Hardy, L., Güllich, A., Abernethy, B., Côté, J., Woodman, T., … Warr, C. (­2016). The
Great British Medalists Project: a review of current knowledge on the development of the
world’s best sporting talent. Sports Medicine, 46, ­1041–​­1058.
Renshaw, I., Araujo, D., Button, C., Chow, J., Davids, K., & Moy, B. (­2016). Why the ­constraints-​
­led approach is not teaching games for understanding: a clarification. Physical Education and
Sport Pedagogy, 21, ­459–​­480.
Renshaw, I. & Chow, J. (­2019). A c­ onstraint-​­led approach to sport and physical education ped-
agogy. Physical Education and Sport Pedagogy, 24, ­103–​­116.
Renshaw, I., Chow, J., Davids, K., & Hammond, J. (­2010). A c­ onstraints-​­led perspective to un-
derstanding skill acquisition and game play: a basis for integration of motor learning theory
and physical education praxis? Physical Education and Sport Pedagogy, 15, ­117–​­137.
Renshaw, I., Davids, K., Newcombe, D., & Roberts, W. (­2019). The ­Constraints-​­ Led Approach:
Principles for Sports Coaching and Practice Design London: Routledge.
Roberts, S. J., Rudd, J. R., & Reeves, M. J. (­2020). Efficacy of using ­non-​­linear pedagogy to sup-
port attacking players’ individual learning objectives in ­elite-​­youth football: a randomised
­cross-​­over trial. Journal of Sports Sciences, 38, 1454–1464.
Roca, A. & Ford, P. R. (­2020). ­Decision-​­making practice during coaching sessions in elite youth
football across European countries. Science and Medicine in Football, 4, ­263–​­268.
van Maarseveen, M. J., Oudejans, R. R., & Savelsbergh, G. J. (­2017). System for notational
analysis in ­small-​­sided soccer games. International Journal of Sports Science & Coaching, 12,
­194–​­206.
Williams, A. M. & Ford, P. R. (­2009). Promoting a ­skills-​­based agenda in Olympic sports: the
role of ­skill-​­acquisition specialists. Journal of Sports Sciences, 27, ­1381–​­1392.
Williams, A. M., Drust, B., & Ford, P. R. (­2020). Talent identification and development in soc-
cer since the millennium. Journal of Sports Sciences, 38, ­1199–​­1210.
10 Sociological influences on the
identification and development of
players
Matthew J. Reeves and Simon J. Roberts

Introduction
Soccer is the world’s most popular sport and subsequently an important sociocultural
driver. One of the key factors in the sport’s worldwide dominance has been the creation
of professional leagues and the emergence of teams as powerful commercial brands
and, for some (­i.e., investors/­owners), a substantive financial opportunity. The current
context is a far cry from the local, amateur activity that emerged from the middle of
the 19th century (­cf. Elliott, 2017). At the highest levels of soccer, the frenzied envi-
ronment is more akin to the entertainment business; whilst at the lowest levels of soc-
cer competition, the game is concerned with continued delivery of a quality product
that offers hope, aspiration, and expectation. Regardless of whether competing for the
highest international honours available (­e.g., the World Cup and the European Cham-
pions League), or to remain competitive within a national league structure, there is the
requirement for clubs to field a team that can perform.
Due to the ­ever-​­increasing costs associated with purchasing players from another
club, it is unsurprising that clubs prefer to look at their own talent identification and
development (­TID) processes and practices (­Reeves & Roberts, 2020). Alongside c­ lub-​
d
­ riven methodologies for talent identification and development, national and inter-
national federations have brought about rule changes. For over a decade, efforts have
been made with the broad intention of increasing the quality and quantity of players
developed by clubs to support their, and in some instances the national federation’s,
aspirations. Some examples of these changes include the Deutscher F ­ ußball-​­Bund
(­DFB) mandating that all German clubs in the top three tiers must operate an acad-
emy; the Fédération Française de Football (­FFF) and Ligue de Football Professionnel
(­LPF) implementing the ‘­Charte du Football Professionnel’; and the Premier Leagues
‘­Elite Player Performance Plan’ (­EPPP). There have, however, also been other, some-
what, controversial, and ­w ide-​­ranging rule changes, such as UEFAs ‘­Level Playing
Field’ initiative, more often referred to as Financial Fair Play (­FFP), which has polar-
ised clubs and fans and, seemingly, done little that it set out to achieve.
While there have been numerous influences on clubs and their talent identifica-
tion and development processes and practices, researchers continue to question the
productivity of academies in developing players who can transition to the first team
(­Morris, Todd & Oliver, 2015). The purpose and different structures of academies
across Europe have been w ­ ell-​­documented (­see Relvas et al., 2010). The range of spe-
cialist practitioners within these structures, that help guide player development, has
been expanded, though their individual and combined influence remains to be fully

DOI: 10.4324/9781003148418-12
156 Matthew J. Reeves and Simon J. Roberts
understood. As the breadth of influence (­i.e., specialist practitioners) on an individual,
from a club or academy environment increases, so too does the need to better under-
stand that influence. It is important to note that the impact of sociological factors on
talent identification and development in soccer has received less attention than other
disciplines/­areas of investigation (­Reeves et al., 2018b). However, seven sociological
factors have been proposed as potential predictors of future, adult, high performance
in soccer (­cf. Williams & Reilly, 2000; Williams, Ford & Drust, 2020). In this chapter,
we consider several of those factors and attempt to explain how practitioners and re-
searchers can, with an enhanced understanding of the issues explored, more effectively
manage processes and practices that ultimately lead to better outcomes in terms of
player identification, development, productivity, and club success.

The role of family

The role of the family unit, but particularly parents, has been of interest to re-
searchers from both participation and performance perspectives (­Hoyle & Leff,
1997; for a historical review, see Dorsch et al., 2021). Understandably, parents make
a significant contribution to their child’s (­non)­i nvolvement in any sport or activity
and there is a body of work that has sought to understand this issue across various
sports. Scientists have examined several broad issues including parents’ experi-
ences in youth soccer (­C larke & Harwood, 2014; Clarke, Harwood & Cushion,
2016; Newport, Knight & Love, 2020), children’s preferences for parental involve-
ment and enjoyment (­Furusa et al., 2020), and the role of siblings during talent
development (­Taylor, Carson & Collins, 2018), though the importance and role of
the family do not just concern young players. For example, findings from other
studies have highlighted the role of family support in dealing with issues of men-
tal ­ill-​­health amongst professional players (­Wood, Harrison & Kucharska, 2017),
and the impact of job relocation on families (­Molnar & Maguire, 2008; Roderick,
2012, 2013).
Scientists that have investigated parents’ experiences in youth soccer have reported
several common features, including increased sense of parental responsibility and an
embodied sense of closeness. An increased sense of parental responsibility has been
shown to occur due to enhanced parental identity, linked to their child’s role as an acad-
emy player (­Clarke & Harwood, 2014; Clarke, Harwood & Cushion, 2016). Parents feel
that their child being identified and labelled as a ­junior-​­elite soccer player reflects their
parenting ability and, thus, their identity as a parent. The proximity to parental iden-
tity and their child’s transition through different stages of development programmes
and environments has also been noted to affect parents’ identity (­Clarke & Harwood,
2014; Clarke, Harwood & Cushion, 2016). In addition to changes in identity, parents
must carefully navigate their position within the academy environment (­Reeves et al.,
2018b), seeking to understand the landscape and manage their exchanges with a range
of other actors within the environment. Furthermore, interactions between parents
have been suggested to require mediation of expectations regarding their child’s tran-
sition to becoming an elite athlete. The high attrition rate of j­ unior-​­elite soccer players
means that parents, like their child(­ren), require careful management of self within the
development environment.
Managing identity, expectations, and self within a talent development environment
has been closely linked to notions of socialisation and conforming to norms, practices,
 Sociological influences 157
and expectations within the established culture. These norms, it is suggested, are
heightened through parents’ interactions with coaches and other parents; meaning
that the quality of a parent’s relationship with their child’s coach, or other parents,
might affect the comments they make, the questions they pose, and the role they take
in coaching their own child (­Clarke & Harwood, 2014). Clarke and Harwood’s (­2014)
study found that parents had to adjust to the shift in power to, and increased involve-
ment from, their child’s coach(­es) while negotiating the expectations placed on them,
and how this all personally affected their identity. Parents suggested that they expe-
rienced difficulties controlling their behaviours while watching competitive games
from the ­side-​­line and ensuring that they adhered to the sociocultural norms of ‘­not
interfering’ despite competition being an emotionally loaded aspect of a parent’s role
(­Dorsch, Smith & McDonough, 2015) and one that can influence both the parent’s and
child’s experience (­K night et al., 2016).
In their study of parents’ experiences of the youth soccer journey, Newport, Knight,
and Love (­2020) sought to understand parental experiences at different transitions of
youngsters through an academy environment. Parents detailed an e­ ver-​­changing jour-
ney through the academy environment that included a dual relationship that ranged
from enjoyment and opportunity to sacrifice and consequences. Those dualistic expe-
riences coincided with an evolving experience of the implications of the environment,
which ranged from initial excitement and amazement to focusing on the future (­see
­Figure 10.1).
In addition, Newport and colleagues proposed several recommendations for acad-
emies that included creating a ­parent-​­supportive culture, facilitating an environment
that is welcoming for parents, respecting, and appreciating parents’ commitment, val-
uing input and feedback from parents, and delivering a programme of support for
parents. All these suggestions have resonance with the broader talent development
literature (­Furusa, Knight, & Hill, 2020), such as the need to support and educate
parents on multiple factors relating to their child’s involvement and development in the
academy environment. Parents blindly trust the academy to do what is best as ‘­they’re

Enjoyment, opportunity, and development

Excited Accepting Focusing

and Dawning and on the
Amazed of Reality Rationalising Future

Sacrifice, commitment, and consequences

­Figure 10.1 Parents’ experiences of the youth soccer academy parenting journey.

Source: Adapted from Newport et al. (­2020)
158 Matthew J. Reeves and Simon J. Roberts
the experts’, but acknowledge that they would like to know more to be able to engage
with their child in an understanding manner (­Reeves et al., 2018c).
While efforts to be more inclusive for parents are certainly warranted, we should not
assume that the role of family is only impacted by and through the academy systems
and environments. Families themselves have been shown to exercise influence in the
decision of whether a young player engages within a talent development programme
or not. In their study of young soccer players in Ghana, van der Meij and Darby (­2017)
found that players believed that being recruited to an academy1 was necessary to help
them to migrate as a professional soccer player to one of the more lucrative leagues,
often in Europe. Their ability to ­take-​­up the offer of a place at an academy, however,
was fraught with delicate negotiations with their families. These negotiations often
revolved around the perceived value of soccer and its role in facilitating international
mobility as it related to a broader, l­ onger-​­term livelihood strategy for the whole family.
Such studies offer a sort of balance to the standard thinking around engagement in
academies and professional soccer, particularly within developing nations.
The role of the family, as a focus of investigation in talent identification and devel-
opment in soccer, is of great importance. As key stakeholders in the lives of young
and established players, their potential influence on myriad factors that have direct
or ­k nock-​­on effects to other domains (­i.e., psychological) and ultimately performance
cannot be underestimated.

­Coach- ​­athlete relationship

There is a large body of work that underpins our knowledge of the ­coach-​­athlete rela-
tionship, though its importance was, for a long time, ignored (­Yang & Jowett, 2016).
Coaches spend a significant amount of time with their players, involved in ­on-​­and ­off-​
­field learning and development activities; this is coupled with the input of other spe-
cialist coaches and support staff (­e.g., strength and conditioning coaches, performance
analysts, and nutritionists). There are also other instances where coaches and players
spend long periods of time together, such as travelling to games, where relationships
can be affected. The ­coach-​­athlete relationship includes all situations where a coach’s
and athlete’s feelings, thoughts, and/­or behaviours are ­inter-​­related (­Jowett, 2007). The
relationship between a player and their coach is of great importance and can affect
multiple facets of a player’s life, including their happiness (­Lafrenière et al., 2011), abil-
ity to cope (­Nicholls et al., 2016), and performance (­Jowett & Cockerill, 2003; Murray
et al., 2020). However, much of the research in this area has been conducted with elite
players or athletes, and so our understanding of the c­ oach-​­athlete relationship within
talent development programmes is sparse.
In recent years, there have been efforts to better understand the c­ oach-​­athlete re-
lationship within ­junior-​­elite soccer. Nicholls and colleagues (­2017) sought to explore
whether the ­coach-​­athlete relationships were able to longitudinally predict the attain-
ment of mastery achievement goals. The study surveyed 104 male academy players
aged between 9 and 20 years old and using two measures, the C ­ oach-​­Athlete Rela-
tionship Questionnaire (­­CART-​­Q; Jowett & Ntoumanis, 2004) and the Attainment of
Sport Achievement Goal Scale (­­A-​­SAGS; Amiot, Gaudreau & Blanchard, 2004). The
­coach-​­athlete relationship did not change over a ­6 -​­month period and the quality of
the relationship remained relatively stable. Players who perceived a stronger relation-
ship with their coach were more likely to note higher perceived levels of mastery goal
 Sociological influences 159
­ chievement – goals
a ​­ that are aimed at attaining a level of competence defined by skill
development or s­ elf-­​­­improvement – 6​­ months later. Nicholls et al. (­2017) concluded
that the c­ oach-​­athlete relationship might be an important predictor of mastery goal
achievement and that academies might maximise its benefit by incorporating c­ oach-​
a­ thlete relationship training within coach development programmes.
A similar study examined the link between the transformational behaviours of par-
ents and coaches, and the impact of age (­Murray et al., 2020). Transformational be-
haviours of parents and coaches were assessed using the Transformational Parenting
Questionnaire (­TPQ; Morton et al., 2011) and the Differentiated Transformational
Leadership Inventory (­DTLI; Hardy et al., 2010), respectively; and players’ mental
toughness was measured using the Mental Toughness Index (­MTI; Gucciardi et al.,
2015), and their physical performance through seven ­field-​­based fitness tests commonly
used to assess physical performance in adolescent soccer players (­Paul & Nassis, 2015).
A total of 334 male players, aged ­10–​­17 years participated. ­Multi-​­level modelling ex-
amined the interaction between age and transformational leadership behaviours of
parents and coaches on players’ mental toughness and physical performance. The fa-
ther’s transformational leadership was positively associated with the mental toughness
of younger players, while the coach’s transformational leadership behaviours were
positively associated with the physical performance of older players. The influence
shifts from parent to coach at an older age, and so implications for the ­coach-​­athlete
relationship and how those dynamics change and, thus, require different behaviours.
There remains a need to understand the causal pathways for these shifts in influence
and to understand their potential impact on engagement and performance, particu-
larly as young players transition between different phases of player development (­i.e.,
training to train/­deliberate play through to training to compete/­deliberate practice;
Côté, 1999). The results of this study touch on the influence of family and how it might
further influence relationships and d ­ ecision-​­making between the three groups.
Such influence might also affect how relationships evolve and manifest. As such,
there has been an increased interest in the notion of ‘­care’, as a lens by which we can
understand relationships between players and coaches. Noddings’ (­1988) seminal work
in education drew on feminist theory to suggest that care should be the central tenet of
the t­ eacher-​­student relationship; an idea that has now been extended to c­ oach-​­athlete
relationships (­see Annerstedt & Lindgren, 2014; Jones, 2009). Care has been shown to
be an essential component of pedagogy (­Cronin, Knowles & Enright, 2019) and thus,
the development and maintenance of relationships. However, soccer environments are
typically characterised as harsh and uncaring, with myriad micropolitical factors for
individuals to contend with (­Potrac et al., 2012).
In their case study of an EPL soccer player’s relationship with a strength and condi-
tioning coach during a period of ­long-​­term injury, Cronin and colleagues (­2019) pro-
pose three important findings. First, that the coach ‘­cared for’ the player through a
­r ules-​­based approach that adopted elements of Noddings’ (­1988) pedagogical caring re-
lation but was largely driven by utilisation of scientific measures and logical rules in a
‘­­care-​­full’ manner. Second, both coach and player appeared to be engaged in a caring
relationship that was positioned in a broader milieu shaped by external and internal
pressures that included others’ employment status, financial pressures associated with
league position, and an aggressive blame culture. Thus, how the player was cared for
and how that care was received by the player was a complex interplay of factors that
reinforce the notion of care as an integrated, not isolated, activity. Finally, while care
160 Matthew J. Reeves and Simon J. Roberts
is suggested as being central to pedagogical endeavours, the care given can be defined,
limited, or enabled by other actors within their social context (­e.g., other coaches,
players, agents, etc.). Consequently, this study highlights that for coaches to care, there
needs to be a shared understanding with players.
Communication is suggested as a critical component of care with all involved need-
ing to embrace authentic dialogue that involves a genuine effort to listen to individ-
uals (­Noddings, 2005). In complex environments, like professional soccer clubs, it is
suggested that there is a need to genuinely listen and involve players in order that they
receive and accept an appropriate form of care (­Cronin, Knowles, & Enright, 2019).
Moreover, the involvement of medical staff, ­soccer-​­specific coaches, strength and con-
ditioning coaches, sports psychologists, nutritionists, data scientists, and o ­ thers – ​­all
of whom have a role in assessing, monitoring, supporting, and caring for ­players – ​­it
might be better to care through an integrated approach, creating a climate, or web, of
care that surrounds players with staff and teammates (­­Gano-​­Overway, 2014; Cronin,
Knowles, & Enright, 2019).

Cultural background
The process of globalisation in professional soccer has been driven by increased tele-
vision and media rights, sponsorship, and merchandise sales which has, in turn, man-
ifested in the global migration of players (­Magee & Sudgen, 2002; Poli, 2010; Relvas
et al., 2010). In recent years, there have been initiatives by some federations to increase
the numbers of indigenous players in club squads. UEFA introduced the ­home-​­grown
rule in 2006, with quota rules to be met by clubs for the start of the ­2008–​­2009 sea-
son. Evidence from the six major European leagues (­England, France, Germany, Hol-
land, Italy, and Spain) showed that opportunities for ­home-​­grown players (­i.e., minutes
played and appearances) between 1999 and 2015 were mixed. Only Germany saw sig-
nificant increases in playing opportunities for indigenous players when comparing be-
fore and after the introduction of the rule; England and Italy saw significant decreases,
and all other countries saw decreased, though not statistically significant, opportuni-
ties (­Bullough et al., 2016). During the 2­ 015–​­2016 season, approximately 50% of play-
ers from the top five European leagues (­as above but excluding Holland) were foreign
(­Gerhards & Mutz, 2017) compared to 20% in ­1995–​­1996, and 39% in ­2005–​­2006.
Cultural diversity in soccer teams around the world has increased over the last few
decades (­Poli, 2010), though research efforts to understand the impact have only rela-
tively recently begun to appear and the implications are broad. What can be recognised
already is that players from different countries, with different cultural backgrounds,
languages, social and behavioural norms, are frequently integrated into, and ex-
pected to perform effectively, as a team. It has been suggested that the differences
noted above increase the likelihood of misunderstandings and conflicts (­Lazear, 1999),
which might stem from an individual’s own or, indeed, his/her cultural prejudices that
inhibit willingness to cooperate with others.
When examining the ‘­big five’ leagues, Maderer, Holtbrügge, and Schuster (­2014),
found that culturally homogenous teams achieved higher average performances. They
concluded that managers of more culturally and ethnically diverse teams should con-
sider the potential costs associated with achieving integration and instead should strive
to embed young players from the club’s own academy. The effect of cultural heteroge-
neity, as observed in the Bundesliga, has been shown to negatively (­Haas & Nüesch,
 Sociological influences 161
2012) and positively (­Andresen & Altmann, 2006) affect team performance. Looking
beyond the ­macro-​­level m
­ ake-​­up of a team’s cultural diversity, Brandes and colleagues
(­2009) have suggested a more complex interaction of cultural influence on team per-
formance. When accounting for playing positions, more homogenous defensive forma-
tions performed better, whereas the opposite was true for striker formations. However,
when the performance of teams from the big five leagues in the European Champions
League games was examined, diverse and valuable teams tended to outperform less
diverse and less valuable ones (­Ingersoll et al., 2017), suggesting that the cost of players
acted as a mediator to performance outcome alongside cultural diversity.
As the results and findings surrounding cultural and ethnic diversity are inconclu-
sive and evidence is, at best, mixed, it is safe to say that we need to know more about
this issue. While it appears that a ­non-​­linear relationship exists between cultural and
ethnic diversity and team performance, with some teams benefitting from diversity
in their teams’ makeup, it is not clear where the tipping point between benefits and
disadvantages lie or what or how much other factors might be of influence (­e.g., team
value). While the impact of diversity on team performance has been examined across
the top 12 European leagues (­Gerhards & Mutz, 2017), a team’s market value might be
a stronger predictor of success, particularly in leagues with greater financial inequal-
ities amongst clubs. While market value and relative team salary have been shown to
have a positive effect on performance and squad size a negative effect, cultural diver-
sity has no significant correlation. These studies have been largely confined to elite
teams rather than development environments. While the latter has been examined in
relation to the impact of geographic location on talent identification and talent devel-
opment practices, there has been no attempt to understand the influence of cultural
background at this critical ­time-​­point in young soccer players’ development. There
are no studies that have sought to understand the implications of cultural background
on teams or individuals within academic environments. Such studies would be wel-
comed and would undoubtedly have value as soccer’s globalised state continues to
grow and interest, participation, and investment increases from countries that have,
previously, had little influence in soccer, such as China and the Arab States of the
Persian Gulf.

Socioeconomic background
The influence of socioeconomic background has been largely overlooked within soc-
cer talent identification and development research. While there is strong evidence re-
lating to engagement in, and drop out from, grassroots sport based on social class
(­Pabayo et al., 2014; Pabayo, Molnar et al., 2014; Lammle, Worth, & Bos, 2012; Van-
dendriessche et al., 2012), there is little examination of this issue from a talent devel-
opment or elite performance perspective. In other sports, scientists have reported that
sociodemographic markers, such as race and relative access to wealth, favour white,
privately educated athletes (­Lawrence, 2017; Winn et al., 2017). However, this change
within soccer has been slow to occur; since inception, soccer has been the quintes-
sential w
­ orking-​­class sport. Less than two decades ago, it was suggested that in Ire-
land, young soccer players tended to be targeted from ­working-​­class families (­Bourke,
2003), perhaps, due to soccer’s historical roots as one of the few sporting opportunities
available to those from lower socioeconomic backgrounds (­Hodkinson & Sparkes,
1997), though current evidence challenges that notion.
162 Matthew J. Reeves and Simon J. Roberts
In the United States, there have been material, geographic, and cultural changes
in soccer since the 1970s that have included the expansion of private leagues, pushing
competitive leagues into the suburbs and away from larger cities with obvious impli-
cations for the demographic of players participating (­Andrews, 1999; Andrews et al.,
1997; Reck & Bruce, 2015). A recent study of the socioeconomic, racial, and geographic
composition of professional female soccer players in the United States (­A llison & Bar-
ranco, 2021) found support for these claims. The study examined longitudinal data
including National Women’s Super League (­N WSL) rosters and combined these with
US Census data and concluded that those at the highest levels of women’s soccer in the
United States come from ‘­places (“­hometowns”) that are whiter, less black or Latino,
more suburban, and less socioeconomically disadvantaged than the national average,
with higher per capita, median household, and median family incomes’ (­­p. ­464–​­465).
Also, studies of academies within the United Kingdom indicate that youngsters enter-
ing soccer talent development programmes are perceived by scouts and recruitment
staff as being increasingly from ­m iddle-​­class backgrounds (­Reeves et al., 2018a).
There is only one study, of which we are aware, that has specifically focussed on
issues of socioeconomic status of academy soccer players from Europe (­Kelly et al., in
review). This study explored socioeconomic status and psychological characteristics
in academy players in England. Players’ home postcodes were used to determine so-
cioeconomic status and the Psychological Characteristics for Developing Excellence
Questionnaire (­PCDEQ) to explore psychological constructs of ­coach-​­rated ‘­h igh’ and
‘­low’ potential players. Players rated as having a higher potential were from families
with a significantly lower socioeconomic status (­P < 0.05) and scored higher on factor
three of the PCDEQ (­i.e., coping with performance and developmental pressures (­P <
0.05), compared to players considered to have lower potential. These results suggest a
possible causal link between socioeconomic status, psychological characteristics, and
perceived potential to become a professional player. Similar findings have recently
been reported in Brazil, where it was suggested that the poverty of young soccer play-
ers might help shape their level of skill and expertise (­Uehara et al., 2021). The au-
thors suggested that poverty created an ecosystem in which young players increased
the likelihood of participation in ­soccer-​­specific activities and, thus, their engagement
in deliberate practice and play (­e.g., Ford, Ward, Hodges, & Williams 2009; Hornig,
Aust, & Güllich, 2016), which have both been shown to facilitate the development of
expertise. Such situational factors might facilitate some psychological characteristics,
such as overcoming adversity, motivation, mental toughness, and resilience.
There are obvious differences between the socioeconomic status of players and their
families around the world, but it is imperative that those involved in academies and de-
velopment programmes recognise the influence that socioeconomic status might have
when designing, implementing, and evaluating talent development pathways (­Rees
et al., 2016).

Future directions and conclusions

In this chapter, we explored how sociological influences on talent identification and
talent development in soccer can have widespread implications. The range, breadth,
and interconnectedness of these factors can be a confounding factor and researchers
have only recently begun to explore some of these issues. Social factors do not occur
in isolation, and so neither can our efforts to examine these issues. We suggest that the
 Sociological influences 163
impact on the development and performance of individuals and teams can be greatly
influenced by sociological factors.
One of the largest contributory factors is the role of family in talent identification
and development. Family have been shown to be crucial in providing a range of re-
sources and support to youngsters. But they have also been identified as key in deter-
mining (­non)­engagement in academy/­development programme environments and, as
such, should be viewed as one of the most crucial stakeholders in their child’s talent
development pathway. Where players and their families do engage in academies, ev-
idence has indicated that there needs to be a better appreciation of how families are
welcomed, appreciated, and valued. Another critical relationship exists between player
and coach. This relationship has been shown to be significant in terms of the time spent
together, both on and off the ­pitch – ​­and in soccer, involving multiple coaches and sup-
port staff. The c­ oach-​­athlete relationship has been linked to player happiness, ability
to cope, and performance. Recently, the ability of coaches to show care to players has
been highlighted as an important factor in how the relationship can manifest but for
care to manifest, there must first be a shared understanding of what care is and what
it means between the coach and player. The effect of cultural factors in ­coach-​­athlete
relationships is yet to be explored; and due to the inconclusive and mixed nature of
findings from studies examining cultural diversity in soccer, we have a long way to go
before we can fully understand and appreciate the complexity of cultural heritage and
its impact on talent identification and talent development. Similarly, we have a limited
understanding of the role socioeconomic status plays in identification and development.
The limited, yet growing data, paints a picture of an increased number of m ­ iddle-​­class
participants, from less diverse backgrounds entering academies and development pro-
grammes in developed countries. However, it is noted that poverty in developing na-
tions, like Brazil, is suggested to be at least in part responsible for the development of
more skilful players, through promotion of an ecosystem that promotes deliberate play
and practice. That said, the causal relationship between poverty and skill development
in soccer has not been established, despite calls for such examinations in the literature.
We must recognise that not all academies and development programmes are created
equal and that the social determinants have a significant role to play in the identification
and development of soccer players. In order that we, as researchers and practitioners,
do not miss or prevent any individual from succeeding in soccer, we must continue to
enhance our understanding of the complexity and interconnectedness of social factors
with psychological, technical, tactical, and physical determinants of talent in soccer.

Note
1 It is important to distinguish between the ­European-​­style academies, typically owned and
operated by professional clubs with no associated costs to players and their families, from
the A­ frican-​­(­and ­other-​­) style academies, which are ­fee-​­paying private academies. This
highlights a clear distinction in the sport development models operated around the world
but is not for further discussion here.

References
Allison, R., & Barranco, R. (­2021). ‘­A rich white kid sport?’ Hometown socioeconomic, racial,
and geographic composition among U.S. women’s professional soccer players. Soccer & Soci-
ety, 22(­5), ­457– ​­469. https://­doi.org/­10.1080/­14660970.2020.1827231
164 Matthew J. Reeves and Simon J. Roberts
Amiot, C. E., Gaudreau, P., & Blanchard, C. M. (­2004). ­Self-​­Determination, coping, and goal
attainment in sport. Journal of Sport and Exercise Psychology, 26(­3), ­396–​­411. https://­doi.
org/­10.1123/­jsep.26.3.396
Andresen, M., & Altmann, T. (­2006). Diversity and success in professional football. Leadership
Organization Magazine, 75(­6), ­325–​­332.
Andrews, D. L. (­1999). Contextualizing suburban soccer: consumer culture, lifestyle differ-
entiation and suburban America. Cultural Sport Society, 2(­3), ­31–​­53. https://­doi.org/­10.1080/­
14610989908721846
Andrews, D. L., Pitter, R., Zwick, D., & Ambrose, D. (­1997). Soccer’s racial frontier: sport and
the suburbanization of contemporary America. In G. Armstrong & R. Giulianotti (­Eds.),
Entering the Field: New Perspectives on World Football (­p­­p. ­261–​­282). New York, NY: Berg.
Annerstedt, C., & Lindgren, E.-​­C. (­2014). Caring as an important foundation in coaching for
social sustainability: a case study of a successful Swedish coach in h ­ igh-​­performance sport.
Reflective Practice, 15(­1), ­27–​­39. https://­doi.org/­10.1080/­14623943.2013.869204
Bourke, A. (­2003). The dream of being a professional soccer player. Journal of Sport and Social
Issues, 27(­4), ­399– ​­419. https://­doi.org/­10.1177/­0193732503255478
Brandes, L., Franck, E. P., & Theiler, P. (­2009). The effect from national diversity on team
­production – ​­empirical evidence from the sports industry. Schmalenbach Business Review,
61(­­225–​­246).
Bullough, S., Moore, R., Goldsmith, S., & Edmondson, L. (­2016). Player migration and op-
portunity: examining the efficacy of the UEFA ­home-​­grown rule in six European football
leagues. International Journal of Sports Science & Coaching, 11(­5), ­662–​­672. https://­doi.
org/­10.1177/­1747954116667104
Clarke, N. J., & Harwood, C. G. (­2014). Parenting experiences in elite youth football: a phenom-
enological study. Psychology of Sport and Exercise, 15(­5), ­528–​­537. https://­doi.org/­10.1016/­j.
psychsport.2014.05.004
Clarke, N. J., Harwood, C. G., & Cushion, C. J. (­2016). A phenomenological interpretation of
the ­parent-​­child relationship in elite youth football. Sport, Exercise, and Performance Psy-
chology, 5(­2), ­125–​­143. https://­doi.org/­10.1037/­spy0000052
Côté, J. (1999). The Influence of the Family in the Development of Talent in Sport. The Sport
Psychologist, 13(4), 395–417. https://doi.org/10.1123/tsp.13.4.395
Cronin, C., Knowles, Z. R., & Enright, K. (­2019). The challenge to care in a premier league foot-
ball club. Sports Coaching Review, 9(­2), ­123–​­146. https://­doi.org/­10.1080/­21640629.2019.1578593
Dorsch, T. E., Smith, A. L., & McDonough, M. H. (­2015). Early socialization of parents through
organized youth sport. Sport, Exercise and Performance Psychology, 4(­1), ­3 –​­18. https://­doi.
org/­10.1037/­spy0000021
Dorsch, T. E., Wright, E., Eckardt, V. C., Elliott, S., Thrower, S. N., & Knight, C. J. (­2021). A
history of parent involvement in organized youth sport: a scoping review. Sport, Exercise and
Performance Psychology, 10(­4), ­536–​­557. https://­doi.org/­10.1037/­spy0000266
Elliott, R. (Ed.). (2017). The English Premier League: A socio-cultural analysis. Routledge: Oxon.
Ford, P. R., Ward, P., Hodges, N. J., & Williams, A. M. (2009). The role of deliberate practice
and play in career progression in sport: The early engagement hypothesis. High Ability Stud-
ies, 20(1), 65–75. https://doi.org/10.1080/13598130902860721
­Gano-​­Overway, L. A. (­2014). The caring climate: how sport environments can develop empa-
thy in young people. In K. Pavlovich & K. Krahnke (­Eds.), Organising Through Empathy
(­p­­p. ­166–​­183). New York, NY: Routledge.
Gerhards, J., & Mutz, M. (­2017). Who wins the championship? Market value and team compo-
sition as predictors of success in the top European football leagues. European Societies, 19(­3),
­223–​­242. https://­doi.org/­10.1080/­14616696.2016.1268704
Gucciardi, D. F., Hanton, S., Gordon, S., Mallett, C. J., & Temby, P. (­2015). The concept of
mental toughness: tests of dimensionality, nomological network, and traitness. Journal of
Personality, 83(­1), ­26–​­44. https://­doi.org/­10.1111/­jopy.12079
 Sociological influences 165
Haas, H., & Nüesch, S. (­2012). Are multinational teams more successful? The International
Journal of Human Resource Management, 23(­15), ­3105–​­3113. https://­doi.org/­10.1080/­09585192.
2011.610948
Hardy, L., Arthur, C. A., Jones, G., Shariff, A., Munnoch, K., Isaacs, I., & Allsopp, A. J. (­2010).
The relationship between transformational leadership behaviors, psychological, and train-
ing outcomes in elite military recruits. The Leadership Quarterly, 21(­1), ­20–​­32. https://­doi.
org/­10.1016/­j.leaqua.2009.10.002
Hodkinson, P., & Sparkes, A. C. (­ 1997). Careership: a sociological theory of career de-
cision making. British Journal of Sociology of Education, 18(­1), ­29–​­44. https://­doi.
org/­10.1080/­0142569970180102
Hornig, M., Aust, F., & Güllich, A. (2016). Practice and play in the development of German
top-level professional football players. European Journal of Sport Science, 16(1), 96 -105.
https://doi.org/10.1080/17461391.2014.982204
Hoyle, R. H., & Leff, S. S. (­1997). The role of parental involvement in youth sport participation
and performance. Adolescence, 32(­125), ­233–​­243.
Ingersoll, K., Malesky, E., & Saiegh, S. M. (­2017). Heterogeneity and team performance: eval-
uating the effect of cultural diversity in the world’s top soccer league. Journal of Sports Ana-
lytics, 3(­2), ­67–​­92. https://­doi.org/­10.3233/­­JSA-​­170052
Jones, R. L. (­2 009). Coaching as caring (­the smiling gallery): accessing hidden knowl-
edge. Physical Education & Sport Pedagogy, 14(­4), ­377–​­390. https://­doi.org/­10.1080/­
17408980801976551
Jowett, S. (­2007). Interdependence analysis and the 3+1Cs in the ­coach-​­athlete relationship. In
S. J. and D. Lavallee (­Ed.), Social Psychology in Sport (­p­­p. ­15–​­27). Champaign, IL: Human
Kinetics.
Jowett, S., & Cockerill, I. M. (­2003). Olympic medallists’ perspective of the a­ thlete–​­coach
relationship. Psychology of Sport and Exercise, 4(­4), ­313–​­331. https://­doi.org/­10.1016/­­
S1469-​­0292(­02)­­0 0011-​­0
Jowett, S., & Ntoumanis, N. (­2004). The ­coach-​­athlete relationship questionnaire (­­CART-​­Q):
development and initial validation. Scandinavian Journal of Medicine and Science in Sports,
14(­4), ­245–​­257. https://­doi.org/­10.1111/­j.­1600-​­0838.2003.00338.x
Kelly, A., Williams, C. A., Jackson, D. T., Turnnidge, J., Reeves, M. J., Dugdale, J., & Wilson,
M. R. (in press). Exploring the role of socioeconomic status and psychological characteristics
in talent development in an English soccer academy. Science & Medicine in Football.
Knight, C. J., Dorsch, T. E., Osai, K. V., Haderlie, K. L., & Sellars, P. A. (­2016). Influences on
parental involvement in youth sport. Sport, Exercise, and Performance Psychology, 5(­2), ­161–​
­178. https://­doi.org/­10.1037/­spy0000053
Lafrenière, M.-​­ A. K., Jowett, S., Vallerand, R. J., & Carbonneau, N. (­ 2011). Passion for
coaching and the quality of the c­ oach–​­athlete relationship: the mediating role of coach-
ing behaviors. Psychology of Sport and Exercise, 12(­2), ­144–​­152. https://­doi.org/­10.1016/­j.
psychsport.2010.08.002
Lammle, L., Worth, A., & Bos, K. (­2012). S ­ ocio-​­demographic correlates of physical activity
and physical fitness in German children and adolescents. The European Journal of Public
Health, 22(­6), ­880–​­884. https://­doi.org/­10.1093/­eurpub/­ckr191
Lawrence, D. W. (­2017). Sociodemographic profile of an Olympic team. Public Health, 148,
­149–​­158. https://­doi.org/­10.1016/­j.puhe.2017.03.011
Lazear, E. P. (­1999). Globalisation and the market for team‐mates. The Economic Journal, 109(­
454), ­15–​­40. https://­doi.org/­10.1111/­­1468-​­0297.00414
Maderer, D., Holtbrügge, D., & Schuster, T. (­2014). Professional football squads as multicul-
tural teams. International Journal of Cross Cultural Management, 14(­2), ­215–​­238. https://­doi.
org/­10.1177/­1470595813510710
Magee, J., & Sugden, J. (­2002). The world at their feet. Journal of Sport and Social Issues, 26(­4),
­421– ​­437. https://­doi.org/­10.1177/­0193732502238257
166 Matthew J. Reeves and Simon J. Roberts
Molnar, G., & Maguire, J. (­2008). Hungarian footballers on the move: Issues of and obser-
vations on the first migratory phase. Sport in Society, 11(­1), ­74– ​­89. https://­doi.org/­10.1080/
­17430430701717798
Morris, R., Tod, D., & Oliver, E. (­2015). An analysis of organizational structure and transition
outcomes in the ­youth-­​­­to-​­senior professional soccer transition. Journal of Applied Sport Psy-
chology, 27(­2), ­216–​­234. https://­doi.org/­10.1080/­10413200.2014.980015
Morton, K. L., Barling, J., Rhodes, R. E., Mâsse, L. C., Zumbo, B. D., & Beauchamp, M. R.
(­2011). The application of transformational leadership theory to parenting: questionnaire
development and implications for adolescent ­self-​­regulatory efficacy and life satisfaction.
Journal of Sport and Exercise Psychology, 33(­5), ­688–​­709. https://­doi.org/­10.1123/­jsep.33.5.688
Murray, R. M., Dugdale, J. H., Habeeb, C. M., & Arthur, C. A. (­2020). Transformational par-
enting and coaching on mental toughness and physical performance in adolescent soccer
players: the moderating effect of athlete age. European Journal of Sport Science, 21(­4), ­580–​
­589. https://­doi.org/­10.1080/­17461391.2020.1765027
Newport, R. A., Knight, C. J., & Love, T. D. (2021). The youth football journey: Parents’ experi-
ences and recommendations for support. Qualitative Research in Sport, Exercise and Health,
13(6), 1006 -1026. https://doi.org/10.1080/2159676X.2020.1833966
Nicholls, A. R., Levy, A. R., Jones, L., Meir, R., Radcliffe, J. N., & Perry, J. L. (­2016). Com-
mitted relationships and enhanced threat levels: perceptions of coach behavior, the ­coach–​
­athlete relationship, stress appraisals, and coping among athletes. International Journal of
Sports Science & Coaching, 11(­1), ­16–​­26. https://­doi.org/­10.1177/­1747954115624825
Nicholls, A. R., Earle, K., Earle, F., & Madigan, D. J. (2017). Perceptions of the Coach -Athlete
Relationship Predict the Attainment of Mastery Achievement Goals Six Months Later: A
Two-Wave Longitudinal Study among F. A. Premier League Academy Soccer Players. Fron-
tiers in Psychology, 8, 684. https://doi.org/10.3389/fpsyg.2017.00684
Noddings, N. (­2005). The Challenge to Care in Schools: An Alternative Approach to Education
(­2nd ed.). New Jersey, NY: Teachers College Press.
Noddings, N. (­1988). An ethic of caring and its implications for instructional arrangements.
American Journal of Education, 96(­2), ­215–​­230. https://­doi.org/­10.1086/­443894
Pabayo, R., Janosz, M., Bisset, S., & Kawachi, I. (­2014). School social fragmentation, economic
deprivation and social cohesion and adolescent physical inactivity: a longitudinal study.
PLoS ONE, 9(­6), e99154. https://­doi.org/­10.1371/­journal.pone.0099154
Pabayo, R., Molnar, B. E., Cradock, A., & Kawachi, I. (­2014). The relationship between neigh-
borhood socioeconomic characteristics and physical inactivity among adolescents living in
Boston, Massachusetts. American Journal of Public Health, 104(­11), ­e142–​­e149. https://­doi.
org/­10.2105/­AJPH.2014.302109
Paul, D. J., & Nassis, G. P. (­2015). Physical fitness testing in youth soccer: issues and considera-
tions regarding reliability, validity, and sensitivity. Pediatric Exercise Science, 27(­3), ­301–​­313.
https://­doi.org/­10.1123/­p es.­2014- ​­0 085
Poli, R. (­2010). Understanding globalization through football: the new international division
of labour, migratory channels and transnational trade circuits. International Review for the
Sociology of Sport, 45(­4), ­491–​­506. https://­doi.org/­10.1177/­1012690210370640
Potrac, P., Jones, R. L., Gilbourne, D., & Nelson, L. (­2012). ‘­Handshakes, BBQs, and bullets’:
­self-​­interest, shame and regret in football coaching. Sports Coaching Review, 1(­2), ­79–​­92.
https://­doi.org/­10.1080/­21640629.2013.768418
Reck, G. G., & Bruce, A. (­2015). American Soccer: History, Culture, Class. Jefferson, NC:
McFarland & Company, Inc.
Rees, T., Hardy, L., Güllich, A., Abernethy, B., Côté, J., Woodman, T., … Warr, C. (­2016). The
great British medalists project: a review of current knowledge on the development of the
world’s best sporting talent. Sports Medicine, 46(­8), ­1041–​­1058. https://­doi.org/­10.1007/­­s40279-
­​­­016-­​­­0476-​­2
 Sociological influences 167
Reeves, M. J., Enright, K. J., Dowling, J., & Roberts, S. J. (­2018a). Stakeholders’ understanding
and perceptions of ­bio-​­banding in j­ unior-​­elite football training. Soccer & Society, 19(­8), ­1–​­17.
https://­doi.org/­10.1080/­14660970.2018.1432384
Reeves, M. J., Littlewood, M. A., McRobert, A. P., & Roberts, S. J. (­2018b). The nature and
function of talent identification in ­junior-​­elite football in English category one academies.
Soccer & Society, 19(­8), ­1122–​­1134. https://­doi.org/­10.1080/­14660970.2018.1432385
Reeves, M. J., McRobert, A. P., Littlewood, M. A., & Roberts, S. J. (­2018c). A scoping review
of the potential sociological predictors of talent in ­junior-​­elite football: ­2000–​­2016. Soccer &
Society, 19(­8), ­1–​­21. https://­doi.org/­10.1080/­14660970.2018.1432386
Reeves, M. J., & Roberts, S. J. (­2020). A bioecological perspective on talent identification in
­junior-​­elite soccer: a ­Pan-​­European perspective. Journal of Sports Sciences, 38(­­11–​­12), ­1259–​
­1268. https://­doi.org/­10.1080/­02640414.2019.1702282
Relvas, H., Littlewood, M., Nesti, M., Gilbourne, D., & Richardson, D. (­2010). Organizational
structures and working practices in elite European professional football clubs: understand-
ing the relationship between youth and professional domains. European Sport Management
Quarterly, 10(­2), ­165–​­187. https://­doi.org/­10.1080/­16184740903559891
Roderick, M. (­2013). Domestic moves: an exploration of i­ntra-​­national labour mobility in the
working lives of professional footballers. International Review for the Sociology of Sport, 48(­
4), ­387–​­404. https://­doi.org/­10.1177/­1012690212442497
Roderick, M. J. (­2012). An unpaid labor of love. Journal of Sport and Social Issues, 36(­3), ­317–​
­338. https://­doi.org/­10.1177/­0193723512445283
Taylor, R. D., Carson, H. J., & Collins, D. (­2018). The impact of siblings during talent develop-
ment: a longitudinal examination in sport. Journal of Applied Sport Psychology, 30(­3), ­272–​
­287. https://­doi.org/­10.1080/­10413200.2017.1384938
van der Meij, N., & Darby, P. (2017). Getting in the game and getting on the move: Family, the
intergenerational contract and internal migration into football academies in Ghana. Sport in
Society, 20(11), 1580–1595. https://doi.org/10.1080/17430437.2017.1284807
Vandendriessche, J. B., Vandorpe, B. F. R., Vaeyens, R., Malina, R. M., Lefevre, J., Lenoir,
M., & Philippaerts, R. M. (­2012). Variation in sport participation, fitness and motor coordi-
nation with socioeconomic status among Flemish children. Pediatric Exercise Science, 24(­1),
­113–​­128. https://­doi.org/­10.1123/­p es.24.1.113
Williams, A. M., Ford, P. R., & Drust, B. (­2020). Talent identification and development in
soccer since the millennium. Journal of Sports Sciences, 38(­­11–​­12), ­1199–​­1210. https://­doi.
org/­10.1080/­02640414.2020.1766647
Williams, A. M., & Reilly, T. (­2000). Talent identification and development in soccer. Journal of
Sports Sciences, 18(­9), ­657– ​­667. https://­doi.org/­10.1080/­02640410050120041
Winn, C. O. N., Ford, P. R., McNarry, M. A., Lewis, J., & Stratton, G. (­2017). The effect of dep-
rivation on the developmental activities of adolescent rugby union players in Wales. Journal
of Sports Sciences, 35(­24), ­2390–​­2396. https://­doi.org/­10.1080/­02640414.2016.1271136
Wood, S., Harrison, L. K., & Kucharska, J. (­2017). Male professional footballers’ experiences
of mental health difficulties and ­help-​­seeking. The Physician and Sports Medicine, 45(­2), ­120–​
­128. https://­doi.org/­10.1080/­0 0913847.2017.1283209
Yang, S. X., & Jowett, S. (­2016). Understanding and enhancing c­ oach–​­athlete relationships
through the 3 + 1Cs model. In R. Thelwell, C. Harwood, & I. Greenlees (­Eds.), The Psychol-
ogy of Sports Coaching (­p­­p. ­54–​­67). Abingdon, OX: Routledge.
11 Player wellbeing and career
transitions
Carolina Lundqvist and David P. Schary

Introduction
In this chapter, we focus on wellbeing and wellbeing promotion among soccer players
from youth to the professional level. Organized sport, such as soccer, is a social phe-
nomenon, which when properly structured, can promote wellbeing, quality of life, and
develop protective psychosocial resources (­e.g., s­ elf-​­esteem, life skills, and social rela-
tionships) for mental health among young athletes (­Cronin & Allen, 2018; Eime et al.,
2013; Swann et al., 2018; Wold et al., 2013). When the level of competition increases and
the player becomes more committed to soccer, the psychosocial demands become more
complex, posing increased challenges for players to sustain their wellbeing over time
(­McKay et al., 2022; Reverberi et al., 2020). Scientists have shown that professional
soccer players ­self-​­report symptoms of psychological distress, anxiety, depression,
and insomnia (­Gouttebarge et al., 2015; Junge & ­Feddermann-​­Demont, 2016; Junge &
Prinz, 2019; Kilic et al., 2022). Moreover, deselection and early career termination are
associated with an increased risk of identity loss and distress among elite adolescent
soccer players (­Blakelock et al., 2016; Brown & Potrac, 2009; Wilkinson, 2021).
­Sport-​­related risk factors and situations that decrease wellbeing and are related to
elevated symptoms of, for example, psychological stress or depression, often occur
during challenging life or sport events (­e.g., sports injuries, transition phases, deselec-
tions, and performance barriers). These challenging events require life or sports adjust-
ment beyond the usual changes normally expected (­Appaneal et al., 2009; Blakelock
et al., 2016; Roiger et al., 2015). Certain factors can protect a player’s wellbeing during
these challenges, like fulfilled basic needs and career satisfaction, resilience, social
support, positive relationships, and mental health literacy (­MHL) (­K ilic et al., 2021;
Kuettel et al., 2021; Lundqvist & Sandin, 2014; Madsen et al., 2021). In addition, the
dynamic interplay and relationships between various participants in the environment
(­e.g., players, coaches, staff, family members, and school) pose an impact on player
wellbeing (­Larsen et al., 2013). Thus, wellbeing variations and outcomes found among
athletes may not only be linked to individual factors but also to structural and social
elements in the players’ sport and/­or general life.
Regardless of age or skill level, players’ health and performance will benefit when
given opportunities to improve or sustain their wellbeing. Mental health promotion
involves support to increase players’ psychosocial resources and competencies to cope
with the demands, obstacles, and challenges naturally occurring in sports and life
(­Barry, 2001). Efforts are already underway to raise awareness of mental health in
soccer at the global level. For example, supported by the World Health Organization
(­WHO), FIFA, and FIFPRO launched the campaigns “#ReachOut” (­FIFA, 2021) and

DOI: 10.4324/9781003148418-13
 Player wellbeing and career transitions 169
“­Are you ready to talk” (­FIFPRO, 2021a). Given this level of international attention,
in this chapter, we aim to help researchers and practitioners understand mental health
and wellbeing, focusing on strategies and interventions to promote wellbeing, particu-
larly during times of transition. We begin by defining wellbeing, then provide a brief
overview of the literature on wellbeing promotion and transitions in soccer. We finish
with some suggestions for future research and applied implications.

­Wellbeing – ​­the positive side of mental health

Wellbeing has been associated with a variety of positive outcomes like improved
health, recovery, and longevity (­Diener et al., 2017; Iasiello et al., 2019; Keyes, 2017;
­Schotanus-​­Dijkstra et al., 2019). Moreover, improvements in wellbeing are linked to
a reduced risk of developing mental illness in n ­ on-​­clinical populations (­Keyes et al.,
2010; Wood & Joseph, 2010). Within the general psychology literature, wellbeing is
conceptualized as independent from, but related to, mental illness. As a result, psy-
chological interventions can act to change levels of wellbeing, illbeing, or both (­Iasiello
et al., 2019; van Agteren et al., 2021). The study of wellbeing is nevertheless complex.
Several biopsychosocial factors interact, like genetic vulnerability, stress reactivity, at-
titudes, cognitions, moods/­affects, health behaviors, coping skills, family background,
social support, and environments (­Diener et al., 2017; Lundqvist, 2021).
Progress on the topic of wellbeing was initially hampered because of inconsistent
and ambiguous definitions, combined with atheoretical approaches and varied as-
sessments (­Lundqvist, 2011). Although definitions and assessments still vary, current
research is becoming more intentional in the operationalization and assessment of
wellbeing as a defined construct in sports (­Giles et al., 2020; Kuettel et al., 2021). Within
sport psychology, wellbeing is generally seen as a subdimension of mental health, re-
flecting a positive and desirable state where the player is functional in life and sports,
copes successfully with daily challenges, and subsequently experiences happiness and
life satisfaction on a regular basis (­Keyes, 2007; Lundqvist & Andersson, 2021). Any
deviations from this functional state of wellbeing could be regarded as the negative
subdimension of mental health, varying from ­non-​­clinical mental health concerns to
diagnosed mental disorders (­for various theoretical perspectives on mental health, see
Lundqvist & Andersson, 2021) (­­Figure 11.1).

Hedonic and eudaimonic wellbeing

Two different philosophical perspectives on wellbeing dominate the literature, the he-
donic and eudaimonic orientation views. The hedonic view adopts the label subjec-
tive or emotional wellbeing and considers it synonymously with pleasure and comfort
(­Diener, 2009; Huta & Ryan, 2010). The central components of subjective wellbeing
are life satisfaction and happiness (­Diener, 2009; Diener et al., 2009; Huta & Ryan,
2010). Life satisfaction refers to the cognitive evaluation or judgment of the perceived
discrepancies between one’s actual and desired life. Happiness refers to the presence
of positive affect in the relative absence of negative affect (­Diener et al., 2009; Huta &
Ryan, 2010). Thus, hedonic wellbeing is generally treated as an emotional outcome
and measured by how a player subjectively feels. Scholars have nevertheless cautioned
that momentary responses assessed in relation to specific activities (­i.e., episodic hap-
piness) may not endure l­ ong-​­term, or even be representative of what a person perceives
as a meaningful life (­Raibley, 2012). Moreover, it is known that a multitude of variables
170 Carolina Lundqvist and David P. Schary

Mental health
Wellbeing Illbeing
Hedonic (happiness, life-satisfaction) Mental health concerns (non-clinical)
Eudaimonic (positive functionality) Psychiatric conditions (DSM-5, ICD-11)

­Figure 11.1 An overview of mental health as an umbrella term for both wellbeing and
illbeing.

(­e.g., context, physiology, and health behaviors) mediate the association between sub-
jective wellbeing and health outcomes (­Diener et al., 2017).
The eudaimonic perspective focuses on positive functionality and ­self-​­realization of in-
dividual talents. Since life inherently involves adversity, the eudaimonic perspective con-
siders how people create meaning during times of difficulty (­Keyes & Annas, 2009; Ryff
et al., 2004; Ryff, 2014). Personal growth and development are essential components of
wellbeing, regardless of their association with positive or negative affect (­Huta & Water-
man, 2014). Psychological and social wellbeing are common conceptualizations of the eu-
daimonic orientation. Psychological wellbeing refers to Ryff’s (­2014) six dimensions of a
person’s positive functioning: autonomy; environmental mastery; personal growth; posi-
tive relations with others; purpose in life; and ­self-​­acceptance. Social wellbeing refers to
functionality and flourishing in social life, conceptualized by Keyes (­1998) as social accept-
ance, social actualization, social contribution, social coherence, and social integration.
Although distinct, hedonic, and eudaimonic wellbeing are overlapping constructs
(­Keyes et al., 2002). Eudaimonia is often regarded as a predictor (­i.e., how the person
lives or behaves) and hedonia as an outcome (­i.e., happiness and ­life-​­satisfaction) associ-
ated with living a ­well-​­functioning life (­Ryan et al., 2008). Moreover, hedonic wellbeing
might provide more immediate benefits to an individual, whereas eudaimonic wellbeing
might develop more l­ong-​­term benefits, suggesting their combination has the greatest
effect on an individual’s overall wellbeing (­Huta & Ryan, 2010). In sport, Lundqvist and
Andersson (­2021) suggest that hedonic and eudaimonic perspectives together could be
regarded as “­the athlete’s psychosocial functionality and ability to nurture individual
talents in the lived elite sports environment, subsequently also increasing the probability
of the elite athlete regularly experiencing positive affect and l­ife-​­satisfaction” (­­p. 3). We
briefly summarize subdimensions of hedonic and eudaimonic wellbeing in ­Table 11.1.

Strengthening wellbeing: mental health promotion and prevention

Organized sports, and particularly team sports, is an avenue where wellbeing among
youths can be strengthened by use of mental health interventions (­Swann et al., 2018).
Until recently, s­port-​­specific approaches that attempted to build wellbeing and in-
crease protective factors among sports populations received little attention (­Breslin
­Table 11.1 A summary of various subdimensions of hedonic and eudaimonic perspectives on wellbeing (­based on Diener, 2009; Keyes, 1998; Ryff, 2014)

Hedonic wellbeing (­emotional Eudaimonic Wellbeing (positive functionality)

outcome)

Subjective (­emotional) wellbeing Psychological wellbeing Social wellbeing

Happiness Perceives that Autonomy Is ­self-​­determined and Social Has a positive view of human kindness.
positive affect independent with ­self-​ acceptance Feels comfortable with and trusts
outweighs ­referenced standards for other people.
negative affect behavioral regulation and
­self-​­evaluation. Can withstand
social pressure.
Life A cognitive overall Environmental Manages the environment Social Is hopeful about future social evolution
satisfaction evaluation of mastery effectively and can use or actualization and think it has potential. Perceives
the lived life and create opportunities in the citizens as assets for the societal
the perceived external environment to satisfy progress.
discrepancy and realize personal needs and
between the goals.
desired and the
existent life
Personal Perceives development and Social Has a perception of being valuable
growth growth as a person. Is open to contribution to the society with important
new experiences and perceives contributions to the world.
continued improvements
in ­self-​­k nowledge and
effectiveness.
Positive Cares about others’ welfare. Social Has an ambition to understand and make
relations Has trusting, empathetic, and coherence sense of what is happening in the world
with others sincere relationships with although it may not always be perfect.
others. Sees the world as organized and
possible to understand.
Purpose in life Perceives that life has a meaning Social Perceives being part of a social reality,
and purpose with directedness integration with quality in relationships with
and goals. society and community and things in
common with others.
Player wellbeing and career transitions

­Self-​­acceptance Accepts and has a positive view

of own qualities and various
171

aspects of the self. Has a

positive view of past life.
172 Carolina Lundqvist and David P. Schary
et al., 2017; Kuettel & Larsen, 2020; Rice et al., 2016). As seen in F ­ igure 11.2, interven-
tions targeting wellbeing and mental health can focus on mental health promotion by
strengthening competencies and resources that act to increase positive mental health
and flourishing (­e.g., necessary support, life skills, social and emotional learning, and
resources to overcome adversity and fulfill their potential in sports and life (­Barry,
2001; Barry et al., 2013). Interventions can also focus on the prevention and reduction
of a risk factor for mental health concerns, for example, decreasing the risk for depres-
sion, anxiety, substance abuse, and behavioral problems (­Barry, 2001; Jacobsson &
Timpka, 2015). Prevention is further classified as: (­a) primary prevention before pa-
thology is established; (­b) secondary prevention focused on reducing the duration of
diagnosed pathology; and (­c) tertiary prevention used to reduce ­long-​­term impair-
ment of clinical disorders (­Barry, 2001; Jacobsson & Timpka, 2015). Moreover, uni-
versal prevention is recommended for everyone. Selective prevention targets certain
subgroups of athletes who at group level are identified by various risk indicators (­e.g.,
age, sex, s­ ocio-​­demographic variables, and sport type), and indicated prevention is de-
livered to those individuals which have a ­h igher-­​­­than-​­average risk to develop clinical
issues (­Jacobsson & Timpka, 2015).
­Evidence-​­based recommendations for supporting wellbeing are limited for athletes
in general, and soccer players specifically, because there are few rigorous interventions
(­i.e., randomized controlled trials) evaluating the efficacy and feasibility of these well-
being strategies and therapies (­Breslin et al., 2017). Yet, despite these limitations, we
provide a brief, ­non-​­comprehensive overview of the current wellbeing strategies for
soccer players in the next section.

­Self-​­care and health behaviors

The World Health Organization (WHO, 2022) suggests s­ elf-​­care strategies as critical
for enhancing mental health across all populations and sleep, diet, and exercise are de-
scribed as the big three health behaviors for mental health (­Wickham et al., 2020). Un-
fortunately, professional soccer players may engage in adverse health behaviors that
diminish their wellbeing over time like alcohol misuse, smoking, and poor nutrition

Classification
Classification of intervention
on risk-factors

Universal:
Mental Health Mental Health All athletes
Promotion Prevention regardless of
risk
Increasing wellbeing (positive mental health) Decreasing the risk of mental health symptoms
and disorders Selective:
Subgroups of
Psychosocial resources and capacities to Primary prevention: Before pathology is athletes at
enhance wellbeing and flourishing established higher risk

E.g., resilience, life-style, supporting a healthy Secondary prevention: Reduction of duration

environment of diagnosed pathology Indicated:
Individual
Tertiary prevention: Reduction of long-term athletes at
impairment of clinical disorders higher risk

­Figure 11.2 Classifications of interventions based on their overall target and risk factors
(­based on Barry, 2001; Jacobsson & Timpka, 2015).
 Player wellbeing and career transitions 173
(­Gouttebarge et al., 2015). Prioritizing healthy habits and behaviors is essential in
building and sustaining wellbeing. Good sleep (­i.e., both sleep duration and qual-
ity) has, for example, been associated with wellbeing and performance optimization
(­Walsh et al., 2021). Proper sleep habits and regular sleep routines among elite soccer
players may nevertheless be challenged by several s­ port-​­specific factors (­e.g., travels,
inconsistency in match schedules, ­hyper-​­arousal after matches, early and late training
sessions, and high training load), as well as common cultural factors such as smart-
phones and social media (­Fullagar et al., 2016; Nédélec et al., 2015; Walsh et al., 2021).
Scientists have indicated that sleep dysfunction and subsequently insufficient recovery
and symptoms of negative mental health are prevalent among both male and female pro-
fessional and collegiate soccer players (­Abbott et al., 2022; Benjamin et al., 2020; Kilic
et al., 2021). For clinical and n
­ on-​­clinical populations suffering from sleep problems, cog-
nitive behavioral therapy (­CBT) sleep interventions have strong evidence and are com-
monly recommended (­Friedrich & Schlarb, 2018; Rios et al., 2019). ­Sport-​­specific sleep
interventions for athletes are nascent, but so far include strategies like improving sleep hy-
giene, sleep education, sleep screening, and managing jetlag (­see review Walsh et al., 2021).

Mental health literacy

MHL evolved as an extension of health literacy primarily used within health care, refer-
ring to an individual’s ability to understand and effectively use medical information and
adhere to medication treatments (­Kutcher et al., 2016). Early MHL definitions focused
on pathological mental health conditions; for example, Jorm et al. (­1997) described it as
the “­knowledge and beliefs about mental disorders which aid their recognition, manage-
ment or prevention” (­­p. 182). However, a ­one-​­sided approach focused on relieving symp-
toms of illbeing or mental disorders is inadequate and does not consider people who do
not struggle with illbeing but still experience suboptimal mental health (­van Agteren
et al., 2021). MHL includes mental health promotion and emphasizes: (­a) how positive
mental health can be derived and maintained; (­b) reduction of stigma of mental health;
and (­c) knowledge of h ­ elp-​­seeking (­e.g., when and where), s­ elf-​­management skills, and
other competences needed to sustain or improve mental health (­Kutcher et al., 2016).
Researchers have evaluated MHL programs and intervention among adolescent soccer
players. Liddle et al. (­2021) found support for a brief ­45-​­min MHL intervention (“­Help Out
a Mate”) delivered to community male soccer players in Australia. In comparison to the
control group, participants significantly improved their knowledge of mental illness, in-
creased intentions, or attitudes towards ­help-​­provision to friends with mental health prob-
lems, and their ­help-​­seeking and problem recognition. Similarly, Vella et al. (­2021a) found
support for the effectiveness of a multicomponent MHL sports program called “­The Ahead
of the Game”, which included a coach and a parent education program. The program was
developed to promote early intervention, resilience, and h ­ elp-​­seeking among adolescent
males from various sports, including soccer, and the results showed ­improved outcomes
in depression and anxiety literacy, ­help-​­seeking intentions from formal but not informal
sources, and confidence in seeking mental health information, resilience, and wellbeing.

Miscellaneous wellbeing interventions

Wellbeing interventions vary greatly in content, goals, and theoretical underpinnings.
Interventions found in the literature may include, for example, exercises or wellbeing
174 Carolina Lundqvist and David P. Schary
therapies which originate in positive psychology (­e.g., character strengths, gratitude,
and optimism), clinical or general psychology (­ e.g., ­
self-​­
compassion, ­ acceptance-­​
c­­ ommitment-​­therapy, ­m indfulness-​­based interventions, CBT, and relaxation), or
sports psychology (­e.g., psychological skills training; see reviews by Galante et al., 2021;
van Agteren et al., 2021). C ­ BT-​­based approaches and m ­ indfulness-​­based interventions
may support young and professional players by giving them psychological skills to
cope with stress and improve wellbeing (­Miçooğullari & Ekmekci, 2017; Olmedilla
et al., 2019; Shannon et al., 2019). Other researchers have argued for the benefits of re-
silience interventions and s­ tress-​­exposure training or ­pressure-​­training interventions
for both performance and wellbeing purposes (­Low et al., 2021; Madsen et al., 2021).

Career transitions and wellbeing

Within sport psychology, the field of career transitions is a ­well-​­researched area (­for
a more thorough review of the literature, see Stambulova et al., 2021). Over the years,
researchers have found that athletes face two general types of ­transitions – ​­normative
and ­non-​­normative (­Petitpas et al., 2013; Stambulova, 2010; Wylleman & Lavallee,
2004). Normative transitions are more predictable and expected, occurring within
sport (­e.g., moving from junior to senior level) and outside of sport (­e.g., moving from
college/­university to the workplace). In contrast, n ­ on-​­normative transitions are less
predictable and usually unexpected, but occur within (­e.g., deselection from a team)
and outside of sport (­e.g., moving to a new country).
Both types of career transitions can affect performance and wellbeing, regardless of
whether they are inside or outside of sport. Much of the research focuses on the nega-
tive effects of transitions and challenges. It is ­well-​­documented that during career tran-
sitions, athletes can struggle with a variety of challenges like identity loss, adjustment
difficulties, social/­relationship issues, and financial hardship (­Stambulova et al., 2021).
To protect wellbeing, athletes need the right resources and support to effectively cope
with a major transition (Lundqvist et al., 2022; Samuel & Tenenbaum, 2011; Schloss-
berg, 1981). Individual athletes vary, however, in how they experience and react to the
same career transitions, producing intraindividual variation of coping skills, needed
resources, and outcomes for mental health (­Wilkinson, 2021).

Common career transitions in soccer

Most of the career transition research in soccer focuses on career termination, primar-
ily at the elite or professional level (­Barth et al., 2021). Due to the highly competitive
nature of the sport, and the diminishing opportunities for players at each subsequent
level, career termination is inevitable for even the most talented players. Since career
transitions like termination can pose a serious threat to wellbeing, soccer players need
to prepare early for this critical transition especially because most players will not
become a professional. Almost all players in the United Kingdom who receive a schol-
arship to play at a soccer academy believe they will become a professional (­Platts &
Smith, 2010), but 85% of them will not receive a contract, and of those that do, only
a fraction will play for a top professional team (­Brown & Potrac, 2009). In addition,
FIFPRO (­2021b) found that out of 89 former soccer players from around the world,
close to half retired unexpectedly from professional soccer. Given the competitive and
unexpected nature of soccer, players of all ages need to prepare and cultivate a life
outside of soccer.
 Player wellbeing and career transitions 175
Psychological consequences of forced retirement
Having an identity and life outside of soccer is important because many players will end
their careers through deselection or injury. These forced retirements can be a traumatic
experience because most players are unprepared and/­or receive little support from their
clubs (­Fortunato & Marchant, 1999). Although players who had the opportunity to vol-
untarily retire after long and successful careers have a less traumatic experience (­Gervis
et al., 2019), over 80% have no ­post-​­career plan (­Barth et al., 2021). Similarly, FIFPRO
(­2021b) found that 50% of current professional players had not started to prepare for the
transition out of soccer. The respondents’ primary reasons for not preparing for a p ­ ost-​
p
­ laying career were the wish to focus on their current playing career and the perception
that their transition to a different career is too far away (­FIFPRO, 2021b).
This type of thinking is dangerous because whether forced or voluntary, experienc-
ing career termination without a plan or support can lead to higher levels of psycho-
logical distress and lower levels of wellbeing. Blakelock et al. (­2016) found that 55% of
elite adolescent soccer players (­ages ­15–​­18) experienced clinical levels of psychological
distress 21 days after being released, with many requiring psychosocial treatments
from a mental health professional. The most common mental health issues were loss
of confidence, social dysfunction, anxiety, and depression.
Similarly, Brown and Potrac (­2009) found that four players that joined their soccer
club between the ages of 10 and 13 struggled with the loss of identity following their
deselection after years of participation. Their identity had become ­one-​­dimensional,
centered on their athletic skills and team performances. Suddenly removing this sole
identity during their formative adolescent years, without developing the psychosocial
skills to overcome the challenges, likely led to the players experiencing feelings of loss,
uncertainty, and failure.
Soccer clubs are now putting systems in place to prevent and treat mental health
issues. This includes making an independent mental health professional available to
meet with players in a confidential space. Unfortunately, the mental health resources
are for those still associated with the club or team, there is still little support for de-
selected players (Wilkinson, 2021). For elite players, most received support from a
player’s association (­FIFPRO, 2021b), but that option may not be available for younger
players. In addition, the resources are reactionary, trying to improve negative mental
health outcomes, instead of proactive like wellbeing promotion. Calvin (­2017) stated
that since players and their families sacrifice a significant part of their lives and re-
sources pursuing their soccer careers, clubs and academies have a duty of care for
all their players, particularly supporting them before and after career transitions like
deselection and injury. Historically, clubs have been unwilling to provide clarification
to parents after releasing a player, let alone provide professional support or wellbeing
promotion (e.g., Wilkinson, 2021).

Psychological benefits of ­dual-​­career programs

­ ual-​­career programs, where athletes combine their sports career with another do-
D
main specific to the athletes’ life phase (­e.g., education, employment, and family), can
protect players from negative outcomes by providing them opportunities to build a
more robust identity, broader repertoire of life skills, balanced lifestyle, and greater
social networks. As a result, these programs can, if properly structured, help to im-
prove wellbeing by providing players with psychosocial resources and safety to handle
career termination and positively adapt to life after sports (­Breslin et al., 2019; Storm
176 Carolina Lundqvist and David P. Schary
et al., 2021). Many soccer players are involved in another career (­academic or employ-
ment). FIFPRO (­2021b) reported that 46% of active player respondents were engaged
in a dual career (­27% in education and 19% in employment). As a result, clubs and
academies need a culture that supports this reality and concentrates on developing
wellbeing. Larsen et al. (­2013) found that young soccer players in Denmark thrived in a
holistic environment that went beyond winning to prioritize things like healthy ­coach-​
­athlete relationships, overall development, and academic responsibilities. Building a
supportive culture is important, but these Danish programs established an interven-
tion program to intentionally assist their younger players with the challenges of ca-
reer transitions by strengthening the ties between elite and youth players, as well as
facilitating a workshop series to introduce and train psychosocial skills (­Larsen et al.,
2014). This program helped younger players understand the demands and expectations
involved in transitioning to the more elite levels.
Although programs that emphasize realistic expectations prepare young players for
the harsh realities of ­elite-​­level soccer, it does not help them develop or balance an-
other career. These types of programs should also help players manage dual careers,
teaching skills like time management, study skills, and financial literacy. Mentorship,
advising, and presentations from retired players with successful ­non-​­athletic careers
can also help players of all ages understand the challenges and rewards that await them
after their soccer careers. Finally, coaches and club officials can promote and encour-
age ­non-​­athletic activities like academics and/­or outside employment.

Future directions and conclusions

Wellbeing promotion and preventative strategies for mental health issues are increas-
ingly getting attention both in applied sports psychology services to athletes and in
sports research. Undoubtedly, protecting soccer players’ mental health and stimu-
lating wellbeing should be prioritized in sports. Psychosocial factors, exemplified in
­Figure 11.3, have the potential to protect and increase soccer players’ wellbeing re-
gardless of age, skill, or competitive level but are still relatively unexplored in the re-
search literature. Similarly, ­evidence-​­based interventions developed for athletes, and
soccer players specifically, are presently sparse. Researchers are, therefore, encour-
aged to focus on increasing the empirical knowledge of essential psychosocial factors
for athletes’ wellbeing and to increase the availability of tailored and e­ vidence-​­based
wellbeing interventions that can be implemented in soccer from the g­ rass-​­root level to
the professional level.
In addition, mental health is a complex construct. Cultural and social factors in
sports and society, which change over time, influence what gets characterized as men-
tal health (­Bolton & Bhugra, 2021; Lundqvist & Andersson, 2021). There is also a lack
of consensus among governing organizations on the definition and theoretical per-
spectives of mental health and wellbeing in sports (Vella et al., 2021b), making it diffi-
cult for practitioners to provide correct interventions or recommendations. Bringing
clarity to this area will help soccer professionals (­e.g., coaches, managers, and support
personnel) and organizations (­e.g., clubs, unions, and schools) know the best strate-
gies for helping their players improve wellbeing and prevent psychological distress.
In the future, researchers need to explore more diverse populations. Currently, most
of the research on mental health focuses on European and North American males
playing at the professional or elite levels. It would be helpful for the knowledge de-
velopment within this research field to include more youth, amateur, recreational,
 Player wellbeing and career transitions 177

Healthy and supporting environment Regular experiences of

(e.g., social support, functional happiness, life-satisfaction,
relationships) personal growth and
purpose in life

Resources to cope
Resiliency, stress reactivity, with critical
attitudes, cognitions, life- and sports situations
moods/affects (e.g., career transitions)

Fulfillment of basic needs

(autonomy, competence, relatedness) Mental health literacy

Health behaviors and self-care

(e.g., sleep, recovery, diet, exercise)

­Figure 11.3 Overview of essential factors for players’ wellbeing.

women, and n ­ on-​­European/­North American populations (­e.g., African, Asian, and

South American) in studies and investigate wellbeing related to sociocultural factors.
In addition, more r­ esearcher-​­practitioner collaboration could improve the applicabil-
ity and effectiveness of wellbeing interventions across all competitive levels.
In conclusion, wellbeing reflects an athlete’s positive psychosocial functionality and
life satisfaction within the lived life circumstances. While soccer players face many
challenges across their careers, times of transition are especially demanding on their
mental health, particularly forced or unexpected retirement. These players are at
higher risk for developing psychological distress and lower wellbeing, especially if they
have no plan or access to mental health resources. While more research and consensus
are still needed, there are several interventions and resources that can provide athletes
with the tools necessary to overcome and thrive amidst the challenges inherent in
soccer. For soccer players’ wellbeing to become a priority for all ages and abilities,
commitment and action from all stakeholders are required.

References
Abbott, W., Brett, A., Watson, A. W., Brooker, H., & Clifford, T. (2022). Sleep restriction in elite
soccer players: Effects on explosive power, wellbeing, and cognitive function. Research Quar-
terly for Exercise and Sport, 93(2), 325 -332. https://doi.org/10.1080/02701367.2020.1834071
Appaneal, R. N., Levine, B. R., Perna, F. M., & Roh, J. L. (­2009). Measuring postinjury depres-
sion among male and female competitive athletes. Journal of Sport and Exercise Psychology,
31(­1), ­60–​­76. https://­doi.org/­10.1123/­jsep.31.1.60
Barry, Margaret M. (2001). Promoting positive mental health: theoretical frameworks for prac-
tice. International Journal of Mental Health Promotion, 3(1), 25–34.
Barry, M. M., Clarke, A. M., Jenkins, R., & Patel, V. (­2013). A systematic review of the effective-
ness of mental health promotion interventions for young people in low and middle income
countries. BMC Public Health, 13(­1), 835. https://­doi.org/­10.1186/­­1471-­​­­2458-­​­­13-​­835
Barth, M., Güllich, A., Forstinger, C. A., Schlesinger, T., Schröder, F., & Emrich, E. (­2021).
Retirement of professional soccer players: a systematic review from social sciences perspec-
tives. Journal of Sports Sciences, 39(­8), ­903–​­914. https://­doi.org/­10.1080/­02640414.2020.1851449
178 Carolina Lundqvist and David P. Schary
Benjamin, C. L., Curtis, R. M., Huggins, R. A., Sekiguchi, Y., Jain, R. K., McFadden, B. A., &
Casa, D. J. (­2020). Sleep dysfunction and mood in collegiate soccer athletes. Sports Health,
12(­3), ­234–​­240. https://­doi.org/­10.1177/­1941738120916735
Blakelock, D. J., Chen, M. A., & Prescott, T. (­2016). Psychological distress in elite adolescent
soccer players following deselection. Journal of Clinical Sport Psychology, 10(­1), ­59–​­77.
https://­doi.org/­10.1123/­jcsp.­2015- ​­0 010
Bolton, D., & Bhugra, D. (­2021). Changes in society and young people’s mental health. Interna-
tional Review of Psychiatry, 33(­­1–​­2), ­154–​­161. https://­doi.org/­10.1080/­09540261.2020.1753968
Breslin, G., Shannon, S., Haughey, T., Donnelly, P., & Leavey, G. (­2017). A systematic review of
interventions to increase awareness of mental health and ­well-​­being in athletes, coaches and
officials. Systematic Reviews, 6(­1), 177. https://­doi.org/­10.1186/­­s13643- ­​­­017- ­​­­0568- ​­6
Breslin, G., Smith, A., Donohue, B., Donnelly, P., Shannon, S., Haughey, T. J., Vella, S. A.,
Swann, C., Cotterill, S., Macintyre, T., Rogers, T., & Leavey, G. (­2019). International con-
sensus statement on the psychosocial and ­policy-​­related approaches to mental health aware-
ness programmes in sport. BMJ Open Sport & Exercise Medicine, 5(­1), e000585. https://­doi.
org/­10.1136/­­bmjsem-­​­­2019-​­0 00585
Brown, G., & Potrac, P. (­2009). ‘­You’ve not made the grade, son’: de‐selection and iden-
tity disruption in elite level youth football. Soccer & Society, 10(­2), ­143–​­159. https://­doi.
org/­10.1080/­14660970802601613
Calvin, M. (2017). No hunger in paradise. The players. The journey. The dream. London: Arrow Books.
Cronin, L. D., & Allen, J. (­2018). Examining the relationships among the coaching climate, life
skills development and ­well-​­being in sport. International Journal of Sports Science & Coach-
ing, 13(­6), ­815–​­827. https://­doi.org/­10.1177/­1747954118787949
Diener, E. (2009). Introduction – The science of well-being: Reviews and theoretical articles by
Ed Diener. In: Diener, E. (Ed.). The Science of Well-Being. Social Indicators Research Series,
vol 37. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2350-6_1
Diener, E., Oishi, S., & Lucas, R. E. (­2009). Subjective ­well-​­being: the science of happiness and
life satisfaction. In Oxford Handbook of Positive Psychology (­2nd ed.) (­p­­p. ­187–​­194). Oxford
University Press.
Diener, E., Pressman, S. D., Hunter, J., & ­Delgadillo-​­Chase, D. (­2017). If, why, and when sub-
jective w ­ ell-​­being influences health, and future needed research. Applied Psychology: Health
and ­Well-​­B eing, 9(­2), ­133–​­167. https://­doi.org/­10.1111/­aphw.12090
Eime, R. M., Young, J. A., Harvey, J. T., Charity, M. J., & Payne, W. R. (­2013). A systematic review
of the psychological and social benefits of participation in sport for children and adolescents:
Informing development of a conceptual model of health through sport. International Journal
of Behavioral Nutrition and Physical Activity, 10(­1), 98. https://­doi.org/­10.1186/­­1479-­​­­5868-­​­­10-​­98
FIFA. (August, 2, 2021). FIFA launches #ReachOut campaign for better mental health. https://www.
fifa.com/about-fifa/medical/news/fifa-launches-reach-out-campaign-for-better-mental-health
FIFPRO. (June 1, 2021). FIFPRO video about mental health: Are you ready to talk? https://
fifpro.org/en/supporting-players/health-and-performance/mental-health/fifpro-video-
about-mental-health-are-you-ready-to-talk/
FIFPRO (2021b). Mind the gap. https://fifpro.org/en/supporting-players/development-­b eyond-
football/project-mind-the-gap/mind-the-gap-67-percent-of-footballers-unsure-of-second-
career-path-fifpro-survey-finds/
Fortunato, V., & Marchant, D. (­ 1999). Forced retirement from elite football in Aus-
tralia. Journal of Personal and Interpersonal Loss, 4(­3), ­269–​­280. https://­doi.org/­10.1080/­
10811449908409735
Friedrich, A., & Schlarb, A. A. (­2018). Let’s talk about sleep: a systematic review of psycholog-
ical interventions to improve sleep in college students. Journal of Sleep Research, 27(­1), ­4 –​­22.
https://­doi.org/­10.1111/­jsr.12568
Fullagar, H. H. K., Skorski, S., Duffield, R., Julian, R., Bartlett, J., & Meyer, T. (­2016). Impaired
sleep and recovery after night matches in elite football players. Journal of Sports Sciences,
34(­14), ­1333–​­1339. https://­doi.org/­10.1080/­02640414.2015.1135249
 Player wellbeing and career transitions 179
Galante, J., Friedrich, C., Dawson, A. F., Modrego-Alarcón, M., Gebbing, P., Delgado-Suárez,
I., Gupta, R., Dean, L., Dalgleish, T., White, I. R., & Jones, P. B. (2021). Mindfulness-based
programmes for mental health promotion in adults in nonclinical settings: A systematic
review and meta-analysis of randomised controlled trials. PLoS Medicine, 18(1), e1003481.
https://doi.org/10.1371/journal.pmed.1003481
Gervis, M., Pickford, H. C., & Hau, T. (­2019). Professional footballer: association counselor
perceptions of the role ­long-​­term injury plays in mental health issues presented by current and
former players. Journal of Clinical Sport Psychology, 13(3), 451–468. https://doi.org/10.1123/
jcsp.2018-0049.
Giles, S., Fletcher, D., Arnold, R., Ashfield, A., & Harrison, J. (­2020). Measuring ­well-​­being in
sport performers: where are we now and how do we progress? Sports Medicine, 50(­7), ­1255–​
­1270. https://­doi.org/­10.1007/­­s40279-­​­­020-­​­­01274-​­z
Gouttebarge, V., Backx, F. J. G., Aoki, H., & Kerkhoffs, G. M. M. J. (­2015). Symptoms of
common mental disorders in professional football (­Soccer) across five European countries.
Journal of Sports Science & Medicine, 14(­4), ­811–​­818.
Huta, V., & Ryan, R. M. (­2010). Pursuing pleasure or virtue: the differential and overlapping
­well-​­being benefits of hedonic and eudaimonic motives. Journal of Happiness Studies, 11(­6),
­735–​­762. https://­doi.org/­10.1007/­­s10902-­​­­0 09-­​­­9171-​­4
Huta, V., & Waterman, A. S. (­2 014). Eudaimonia and its distinction from hedonia: devel-
oping a classification and terminology for understanding conceptual and operational
definitions. Journal of Happiness Studies, 15(­6 ), ­1425–​­1456. https://­doi.org/­10.1007/­­s10902-
­​­­013-­​­­9485-​­0
Iasiello, M., Agteren, J. van, Keyes, C. L. M., & Cochrane, E. M. (­2019). Positive mental health
as a predictor of recovery from mental illness. Journal of Affective Disorders, 251, ­227–​­230.
https://­doi.org/­10.1016/­j.jad.2019.03.065
Jacobsson, J., & Timpka, T. (­2015). Classification of prevention in sports medicine and epidemi-
ology. Sports Medicine, 45(­11), ­1483–​­1487. https://­doi.org/­10.1007/­­s40279-­​­­015-­​­­0368-​­x
Jorm, A. F., Korten, A. E., Jacomb, P. A., Christensen, H., Rodgers, B., & Pollitt, P. (1997).
“Mental health literacy”: a survey of the public’s ability to recognise mental disorders and
their beliefs about the effectiveness of treatment. The Medical Journal of Australia, 166(4),
182–186. https://doi.org/10.5694/j.1326-5377.1997.tb140071.x
Junge, A., & ­Feddermann-​­Demont, N. (­2016). Prevalence of depression and anxiety in t­ op-​­level
male and female football players. BMJ Open Sport & Exercise Medicine, 2(­1), e000087. https://­
doi.org/­10.1136/­­bmjsem-­​­­2015- ​­0 00087
Junge, A., & Prinz, B. (­2019). Depression and anxiety symptoms in 17 teams of female football
players including 10 German first league teams. British Journal of Sports Medicine, 53(­8), 471.
https://­doi.org/­10.1136/­­bjsports-­​­­2017- ​­098033
Keyes, C. L. M. (­1998). Social ­well-​­being. Social Psychology Quarterly, 61(­2), 121–140. https://­
doi.org/­10.2307/­2787065
Keyes, C. L. M. (­2007). Promoting and protecting mental health as flourishing: a complemen-
tary strategy for improving national mental health. American Psychologist, 62(­2), ­95–​­108.
https://­doi.org/­10.1037/­­0003- ​­066X.62.2.95
Keyes, C. L. M., & Annas, J. (­2009). Feeling good and functioning well: distinctive concepts
in ancient philosophy and contemporary science. The Journal of Positive Psychology, 4(­3),
­197–​­201. https://­doi.org/­10.1080/­17439760902844228
Keyes, C. L. M., Dhingra, S. S., & Simoes, E. J. (­2010). Change in level of positive mental health
as a predictor of future risk of mental illness. American Journal of Public Health, 100(­12),
­2366–​­2371. https://­doi.org/­10.2105/­AJPH.2010.192245
Keyes, C. L. M., Shmotkin, D., & Ryff, C. D. (­2002). Optimizing ­well-​­being: the empirical
encounter of two traditions. Journal of Personality and Social Psychology, 82(­6), ­1007–​­1022.
https://­doi.org/­10.1037/­­0022-​­3514.82.6.1007
Kilic, Ö., Carmody, S., Upmeijer, J., Kerkhoffs, G. M. M. J., Purcell, R., Rice, S., & Goutte-
barge, V. (­2021). Prevalence of mental health symptoms among male and female Australian
180 Carolina Lundqvist and David P. Schary
professional footballers. BMJ Open Sport & Exercise Medicine, 7(­3), e001043. https://­doi.
org/­10.1136/­­bmjsem-­​­­2021-​­0 01043
Kuettel, A., & Larsen, C. H. (­2020). Risk and protective factors for mental health in elite ath-
letes: A scoping review. International Review of Sport and Exercise Psychology, 13(­1), ­231–​­265.
https://­doi.org/­10.1080/­1750984X.2019.1689574
Kuettel, A., Pedersen, A. K., & Larsen, C. H. (­2021). To flourish or languish, that is the ques-
tion: exploring the mental health profiles of Danish elite athletes. Psychology of Sport and
Exercise, 52, 101837. https://­doi.org/­10.1016/­j.psychsport.2020.101837
Kutcher, S., Wei, Y., & Coniglio, C. (­2016). Mental health literacy: past, present, and future.
The Canadian Journal of Psychiatry, 61(­3), ­154–​­158. https://­doi.org/­10.1177/­0706743715616609
Larsen, C. H., Alfermann, D., Henriksen, K., & Christensen, M. K. (­2013). Successful talent
development in soccer: the characteristics of the environment. Sport, Exercise, and Perfor-
mance Psychology, 2(­3), ­190–​­206. https://­doi.org/­10.1037/­a0031958
Larsen, C. H., Alfermann, D., Henriksen, K., & Christensen, M. K. (­2014). Preparing foot-
ballers for the next step: an intervention program from an ecological perspective. The Sport
Psychologist, 28(­1), ­91–​­102. https://­doi.org/­10.1123/­tsp.­2013-​­0 015
Liddle, S.K., Deane, F.P., Batterham, M. & Vella S.A. (2021). A brief sports-based mental
health literacy program for male adolescents: A cluster-randomized controlled trial. Journal
of Applied Sport Psychology, 33(1), 20–44. https://doi.org/10.1080/10413200.2019.1653404
Low, W. R., Sandercock, G. R. H., Freeman, P., Winter, M. E., Butt, J., & Maynard, I. (2021).
Pressure training for performance domains: A meta-analysis. Sport, Exercise, and Perfor-
mance Psychology, 10(1), 149–163. https://doi.org/10.1037/spy0000202
Lundqvist, C. (2011). Well-being in competitive sports—The feel-good factor? A review of con-
ceptual considerations of well-being. International Review of Sport and Exercise Psychol-
ogy, 4(2), 109–127. https://doi.org/10.1080/1750984X.2011.584067
Lundqvist, C. (­2021). W ­ ell-​­being and quality of life. In R. Arnold & D. Fletcher (­Eds.), Stress,
­Well-​­being and Performance in Sport (­p­­p. ­131–​­147). New York: Routledge.
Lundqvist, C., & Andersson, G. (­2021). Let’s talk about mental health and mental disorders in
elite sports: a narrative review of theoretical perspectives. Frontiers in Psychology, 12, 700829.
https://­doi.org/­10.3389/­fpsyg.2021.700829
Lundqvist, C., Sandin, F., (2014), Well-being in elite sport: Dimensions of hedonic and eudai-
monic well-being among elite orienteers at a global and sport specific level, The Sport psy-
chologist, 28(3), 245–254. https://doi.org/10.1123/tsp.2013-0024
Madsen, E. E., Krustrup, P., Larsen, C. H., Elbe, A. M., Wikman, J. M., Ivarsson, A., & Lauten-
bach, F. (2021). Resilience as a protective factor for well-being and emotional stability in elite-
level football players during the first wave of the COVID-19 pandemic. Science & Medicine in
Football, 5 (sup1), 62–69. https://doi.org/10.1080/24733938.2021.1959047
McKay, A., Cropley, B., Mullen, R., Shearer D., & Hanton, S. (2022) Psychosocial demands and
situational properties of the club-to-international transition in male youth football, Journal
of Applied Sport Psychology, 34 (6), 1272-1294. https://doi.org/10.1080/10413200.2021.1972495
Miçooğullari, B. O., & Ekmekci, R. (­2017). Evaluation of a psychological skill training program
on mental toughness and psychological wellbeing for professional soccer players. Universal
Journal of Educational Research, 5, ­2312–​­2319.
Nédélec, M., Halson, S., Abaidia, A.-​­E., Ahmaidi, S., & Dupont, G. (­2015). Stress, sleep and
recovery in elite soccer: a critical review of the literature. Sports Medicine, 45(­10), ­1387–​­1400.
https://­doi.org/­10.1007/­­s40279- ­​­­015- ­​­­0358-​­z
Lundqvist, C., Sandin, F., (2014), Well-being in elite sport: Dimensions of hedonic and eudai-
monic well-being among elite orienteers at a global and sport specific level, The Sport psy-
chologist, 28(3), 245–254. https://doi.org/10.1123/tsp.2013-0024
Olmedilla, A., M ­ oreno-​­Fernández, I. M., ­Gómez-​­Espejo, V., R ­ obles-​­Palazón, F. J., Verdú, I., &
Ortega, E. (­2019). Psychological intervention program to control stress in youth soccer ­players.
Frontiers in Psychology, 10, 2260. https://­doi.org/­10.3389/­fpsyg.2019.02260
 Player wellbeing and career transitions 181
Petitpas, A., Van Raalte, J. L., & Brewer, B. W. (2013). Athletes’ careers in the United States: De-
velopmental programming for athletes in transition. In N. B. Stambulova & T. V. Ryba (Eds.),
Athletes’ careers across cultures (pp. 222–234). New York: Routledge/Taylor & Francis Group.
Platts, C., & Smith, A. (­2010). ‘­Money, money, money?’ The development of financial in-
equalities in English professional football. Soccer & Society, 11(­5), ­643–​­658. https://­doi.
org/­10.1080/­14660970.2010.497365
Raibley, J. R. (­2012). Happiness is not ­well-​­b eing. Journal of Happiness Studies: An Interdisciplinary
Forum on Subjective ­Well-​­B eing, 13(­6), ­1105–​­1129. https://­doi.org/­10.1007/­­s10902-­​­­011-­​­­9309-​­z
Reverberi, E., D’Angelo, C., Littlewood, M. A., & Gozzoli, C. F. (­2020). Youth football players’
psychological ­well-​­being: the key role of relationships. Frontiers in Psychology, 11, 567776.
https://­doi.org/­10.3389/­fpsyg.2020.567776
Rice, S. M., Purcell, R., De Silva, S., Mawren, D., McGorry, P. D., & Parker, A. G. (­2016). The
mental health of elite athletes: a narrative systematic review. Sports Medicine, 46(­9), ­1333–​
­1353. https://­doi.org/­10.1007/­­s40279- ­​­­016- ­​­­0492-​­2
Rios, P., Cardoso, R., Morra, D., Nincic, V., Goodarzi, Z., Farah, B., Harricharan, S., Morin,
C. M., Leech, J., Straus, S. E., & Tricco, A. C. (­2019). Comparative effectiveness and safety
of pharmacological and ­non-​­pharmacological interventions for insomnia: an overview of
reviews. Systematic Reviews, 8(­1), 281. https://­doi.org/­10.1186/­­s13643- ­​­­019-­​­­1163-​­9
Roiger, T., Weidauer, L., & Kern, B. (­2015). A longitudinal pilot study of depressive symp-
toms in concussed and injured/­nonconcussed national collegiate athletic association divi-
sion i ­student-​­athletes. Journal of Athletic Training, 50(­3), ­256–​­261. https://­doi.org/­10.4085/­­
1062-­​­­6050-​­49.3.83
Ryan, R. M., Huta, V., & Deci, E. L. (­2008). Living well: a ­self-​­determination theory perspective
on eudaimonia. Journal of Happiness Studies, 9(­1), ­139–​­170. https://­doi.org/­10.1007/­­s10902-
­​­­0 06-­​­­9023-​­4
Ryff, C. D. (­2014). Psychological ­well-​­being revisited: advances in the science and practice of
Eudaimonia. Psychotherapy and Psychosomatics, 83(­1), ­10–​­28. https://­doi.org/­10.1159/­000353263
Ryff, C. D., Singer, B. H., & Dienberg Love, G. (­2004). Positive health: connecting ­well–​­being
with biology. Philosophical Transactions of the Royal Society of London. Series B: Biological
Sciences, 359(­1449), ­1383–​­1394. https://­doi.org/­10.1098/­rstb.2004.1521
Samuel, R. D., & Tenenbaum, G. (­2011). The role of change in athletes’ careers: a scheme of
change for sport psychology practice. The Sport Psychologist, 25(­2), ­233–​­252. https://­doi.
org/­10.1123/­tsp.25.2.233
Schotanus-Dijkstra, M., Keyes, C. L. M., de Graaf, R., & Ten Have, M. (2019). Recovery from
mood and anxiety disorders: The influence of positive mental health. Journal of Affective
Disorders, 252, 107–113. https://doi.org/10.1016/j.jad.2019.04.051
Shannon, S., Hanna, D., Haughey, T., Leavey, G., McGeown, C., & Breslin, G. (­2019). Effects
of a mental health intervention in athletes: applying s­ elf-​­determination theory. Frontiers in
Psychology, 10, 1875. https://­doi.org/­10.3389/­fpsyg.2019.01875
Stambulova, N. (­ 2010). Professional culture of career assistance to athletes: a look
through contrasting lenses of career metaphors. In Tatiana V. Ryba, Robert J. Schinke,
Gershon Tenenbaum (­ Eds.), The Cultural Turn in Sport Psychology (­p­­p. ­285–​­312).
Morgantown,WV: Fitness Information Technology.http://­urn.kb.se/­resolve?urn=urn:nbn:se:hh:­
diva- ​­4882
Stambulova, N. B., Ryba, T. V., & Henriksen, K. (­ 2021). Career development and tran-
sitions of athletes: the international society of sport psychology position stand revis-
ited. International Journal of Sport and Exercise Psychology, 19(­4), ­524–​­550. https://­doi.
org/­10.1080/­1612197X.2020.1737836
Storm, L. K., Henriksen, K., Stambulova, N. B., Cartigny, E., Ryba, T. V., De Brandt, K.,
Ramis, Y., & Cecić Erpič, S. (­2021). Ten essential features of European dual career devel-
opment environments: a multiple case study. Psychology of Sport and Exercise, 54, 101918.
https://­doi.org/­10.1016/­j.psychsport.2021.101918
182 Carolina Lundqvist and David P. Schary
Swann, C., Telenta, J., Draper, G., Liddle, S., Fogarty, A., Hurley, D., & Vella, S. (­2018). Youth
sport as a context for supporting mental health: adolescent male perspectives. Psychology of
Sport and Exercise, 35, ­55–​­64. https://­doi.org/­10.1016/­j.psychsport.2017.11.008
van Agteren, J., Iasiello, M., Lo, L., Bartholomaeus, J., Kopsaftis, Z., Carey, M., & Kyrios, M.
(­2021). A systematic review and m ­ eta-​­analysis of psychological interventions to improve mental
wellbeing. Nature Human Behaviour, 5(­5), ­631–​­652. https://­doi.org/­10.1038/­­s41562-­​­­021-­​­­01093-​­w
Vella, S. A., Swann, C., Batterham, M., Boydell, K. M., Eckermann, S., Ferguson, H., Fogarty,
A., Hurley, D., Liddle, S. K., Lonsdale, C., Miller, A., Noetel, M., Okely, A. D., Sanders, T.,
Schweickle, M. J., Telenta, J., & Deane, F. P. (2021a). An intervention for mental health liter-
acy and resilience in organized sports. Medicine and Science in Sports and Exercise, 53(1),
139–149. https://doi.org/10.1249/MSS.0000000000002433
Vella, S.A., Schweickle, M.J., Sutcliffe, J.T., Swann, C. (2021b). A systematic review and meta-­
synthesis of mental health position statements in sport: Scope, quality and future directions.
Psychology of Sport Exercise,55:101946. https://doi.org/10.1016/j.psychsport.2021.101946
Walsh, N. P., Halson, S. L., Sargent, C., Roach, G. D., Nédélec, M., Gupta, L., Leeder, J.,
Fullagar, H. H., Coutts, A. J., Edwards, B. J., Pullinger, S. A., Robertson, C. M., Burnis-
ton, J. G., Lastella, M., Le Meur, Y., Hausswirth, C., Bender, A. M., Grandner, M. A., &
Samuels, C. H. (­2021). Sleep and the athlete: narrative review and 2021 expert consensus
recommendations. British Journal of Sports Medicine, 55(­7), ­356–​­368. https://­doi.org/­10.1136/
­­bjsports-­​­­2020-​­102025
Wickham, S.-​­R., Amarasekara, N. A., Bartonicek, A., & Conner, T. S. (­2020). The big three
health behaviors and mental health and w ­ ell-​­being among young adults: a c­ ross-​­sectional
investigation of sleep, exercise, and diet. Frontiers in Psychology, 11, 579205. https://­doi.
org/­10.3389/­fpsyg.2020.579205
Wilkinson, R. J. (­2021). A literature review exploring the mental health issues in academy foot-
ball players following career termination due to deselection or injury and how counselling
could support future players. Counselling and Psychotherapy Research, 21, 859-868. https://­
doi.org/­10.1002/­capr.12417
Wold, B., Duda, J. L., Balaguer, I., Smith, O. R. F., Ommundsen, Y., Hall, H. K., Samdal, O.,
Heuzé, J.-​­P., Haug, E., Bracey, S., Castillo, I., Ramis, Y., Quested, E., & Krommidas, C. (­2013).
Comparing ­self-​­reported ­leisure-​­time physical activity, subjective health, and life satisfaction
among youth soccer players and adolescents in a reference sample. International Journal of
Sport and Exercise Psychology, 11(­4), ­328–​­340. https://­doi.org/­10.1080/­1612197X.2013.830433
Wood, A. M., & Joseph, S. (­2010). The absence of positive psychological (­eudemonic) ­well-​­being
as a risk factor for depression: a ten year cohort study. Journal of Affective Disorders, 122(­3),
­213–​­217. https://­doi.org/­10.1016/­j.jad.2009.06.032
World Health Organization (2022). WHO guideline on self-care interventions for health and
well-being, 2022 revision. Geneva: World Health Organization.
Wylleman, P., & Lavallee, D. (­2004). A developmental perspective on transitions faced by ath-
letes. In Developmental Sport and Exercise Psychology: A Lifespan Perspective. (­p­­p. ­503–​­523).
Morgantown, WV: Fitness Information Technology.
12 Developing (­adaptive) coaching
expertise
Christopher J. Cushion and Anna Stodter

Introduction
The study of coach development pathways is of interest to those seeking understand
how expert coaches develop their skills and knowledge. Knowing and understand-
ing what the journey to coaching expertise looks like enables coach educators to help
coaches transition from novice to expert status, thus raising the quality of coaching
practice across all areas of the game (­g rassroots, academy, and professional) and in
different coaching domains (­participation, development, and performance). That said,
recent years have seen developments in coach education, with its evaluation and effec-
tiveness supported by rapid growth in research on coach learning, creating a ‘­hotbed’
of scholarly activity (­Lyle & Cushion, 2017). This growth has occurred alongside a
gradual paradigm shift whereby coach education based on ‘­k nowledge transfer’ from
experienced, ‘­expert’ coaches to novices, has moved towards attempts to provide fa-
cilitation of more participatory ‘­­learner-​­centred’ approaches to coach development.
In this chapter, we explore coach learning alongside a contemporary understanding of
expertise as it applies to coaching in soccer. We consider how findings about current
coach development may, or may not, contribute to the development of coaching exper-
tise. We then present ­evidence-​­informed guidance for coach development focusing on
developing adaptive coaching expertise.

Expertise in coaching
Governing bodies in soccer, through hierarchical accreditation systems, appear to view
expertise in part as a function of experience and coaching competencies. Coaching ex-
pertise can be conceptualised in this ­outcome-​­focused way, or as Berry (­2020) suggests,
as a process, reflecting definitional challenges in the expertise literature (­­Farrington-​
­Darby & Wilson, 2006). An outcome conceptualisation is consistent with the defini-
tion of expertise as ‘­reproducible superior performance’ (­Ericsson & Charness, 1994,
­p. 726). This concept of routine expertise is referred to as the ability to master ­domain-​
s­ pecific skills without error (­Carbonell et al., 2016). In this regard, routine expertise
can be considered analogous to the l­evel-​­or ­stage-​­based competency frameworks em-
bedded within soccer’s formal accreditation systems. This approach has largely been
adopted in coaching research where it is well established that ‘­reproducible superior
performance’ in coaching is not innate, but instead is developed through learning from
idiosyncratic combinations of experiences over time (­Schempp & McCullick, 2010). In
other words, for those striving to advance in coaching and transition from novice to

DOI: 10.4324/9781003148418-14
184 Christopher J. Cushion and Anna Stodter
expert status, the past twenty or so years of scholarly activity have suggested that
coaches can become ‘­more expert’ through learning effectively from their experiences.
Deliberate practice has been found to be a mediating factor in the development of
expertise in sport. It is a specific form of practice designed to improve performance
through a cyclical process involving the repetition of skills at the edge of one’s abil-
ity, refined by feedback (­Berry, 2020). Critiques of formal coach education provide a
persuasive argument that the factors necessary for deliberate practice are currently
absent. Not least, the amount of time spent engaged in coach education renders it ‘­low
impact’, and within coach education itself the time spent practising coaching and re-
ceiving appropriate feedback is limited (­Stodter & Cushion, 2017, 2019a). Moreover, as
Cushion et al. (­2021) argue, coaches’ experiences show that courses exhibit a number
of common features: a single style or formula for coaching; ‘­sacred texts’ prescribing
what and how to coach; ‘­r ites of passage’ from one level to the next; ‘­instrumental
design’ driven by passing of assessments; and on course ‘­­time-​­crunch’ limiting space
for spontaneous discussion, challenge, or meaningful feedback to facilitate improve-
ment (­Downham & Cushion, 2020; Piggott, 2012; Williams & Bush, 2019; Dempsey
et al., 2020; ­inter- ​­alia). Townsend et al. (­2021) contend that while research on coach
education has significantly increased over the last decade, much of this work reiter-
ates that coach education remains a ­low-​­impact endeavour perceived to lack relevance
for coaches. As a result, coaching knowledge and practices are still being derived
overwhelmingly from experiential, informal, and ­non-​­formal sources, with this effect
magnified in marginalised coaching spaces such as disability (­Townsend et al., 2021).
It is unclear if the current conceptions of coach education can legitimately claim to
constitute deliberate practice, and the applicability of the deliberate practice model to
develop expertise in coaching may currently be questioned.
Coaching in soccer is an impactful and complex activity requiring the flexible bal-
ance of numerous changeable tasks, interactions, and relationships (­Jones, Bailey, &
Thompson, 2013), and applying knowledge appropriate to the context often under
competitive pressure. The ‘­art’ of coaching appears instinctive, yet researchers have
suggested the use of tacit knowledge to reliably plan, predict outcomes, solve prob-
lems, communicate, ­self-​­monitor, and make intuitive decisions (­Lyle & Cushion, 2017;
Nash & Collins, 2006). Superior knowledge, a key characteristic of expert coaching,
developed through learning from years of experience, seems to underpin these quali-
ties in consistently bringing about positive outcomes for players.
Given this understanding of the nature of coaching, and useful for coaching an in-
teractive team game like soccer, is a shift in thinking about expertise towards a more
­process-​­oriented view (­Berry, 2020; Turner, Nelson & Potrac, 2012). In this view, ex-
pertise is less a personal characteristic than the product of an interaction between the
person and the environment (­Turner et al., 2012). From this perspective, experts have
been shown to distinguish themselves in their ability to perceive meaningful patterns
in their coaching environments that novices cannot (­Cushion et al., 2010; ­Farrington-​
D
­ arby & Wilson, 2006; Schempp & McCullick, 2010). In essence, a different defini-
tion of expertise has different implications for its relevance and application within
coaching and coach education. A process view is supportive of the ability of coaches
to develop adaptive expertise, the ability to master novel tasks and transfer skills to
different and unknown contexts (­Barnett & Koslowski, 2002; Sonnentage et al., 2006).
As Mees, Sinfield, Collins, and Collins (­2020) explain, adaptive expertise builds on,
yet contrasts, with routine expertise (­Hatano & Inagaki, 1986; Hatano & Oura, 2003).
 Developing (­adaptive) coaching expertise 185
Both notions of expertise demand the capacity to perform standard tasks and routine
functions without error (­Mees et al., 2020). Adaptive expertise is less about repeat-
ing standardised tasks to a high standard, and more concerned with developing more
nuanced planning, situational awareness, reflection, metacognition, and ­problem-​
s­olving skills characterised by efficiency and innovation in applying knowledge to
new situations and challenges (­Berry, 2020, Bransford et al., 2005; Hutton et al., 2017;
Mees et al., 2020). This approach seems relevant to soccer coaching, where coaching
is increasingly seen as the orchestration of dynamic problems to be solved rather than
simply imparting skills.
Fundamental to an adaptive expertise framework is the need to analyse and develop
practitioner d ­ ecision-​­making; that of the player and the coach, understanding ‘­why
they do what they do’ (­Bachkirova & Smith, 2015, ­p. 135). Adaptive expertise is built
on routine expertise, yet individuals with adaptive expertise do not rely solely on r­ ule-​
b
­ ased d­ ecision-​­making and know when not to rely on automatic processes like intui-
tion (­Berry, 2020; Carbonell et al., 2016). This notion is consistent with Bachkirova and
Smith’s (­2015) argument that competency models oversimplify the demands placed on
a coach and fail to account for the complexity of thinking. Complexity within the
coaching context underpins the need to focus on process (­i.e., reasoning) rather than
outcome (­Owen & Lindley, 2010). Expertise then becomes about developing cogni-
tive skills, managing complexity, and adapting to new contexts (­cf. Cruickshank et al.,
2018; Martindale & Collins, 2013; Turner et al., 2012).

Exploring coach development pathways

Like the broader expertise literature, most researchers have centred on the general
characteristics of expertise and knowledge, with less focus on the detail or processes
of their acquisition, development, and/­or construction over time. What needs to be
developed is identified, but not how or whether it is an endpoint that can be achieved,
meaning it is often difficult to extrapolate informative guidance for coach learning.
In considering how coach development pathways develop expertise, coaching as an
academic area of study has been characterised by a concern for the description and
classification of experiences into the situations or contexts in which coaches’ learning,
and the development of expertise, supposedly occurs. Scholars have typically echoed
Trudel and Gilbert’s (­2006) use of Sfard’s (­1998) dichotomous learning framework,
exploring the acquisition of knowledge through formal (­institutionalised) and ­non-​
­formal education programmes (­occurring outside of broader initiatives), or focusing
on learning through participation in informal daily experiences and interacting with
the environment and others.

Informal learning/­apprenticeship
Coaches frequently report that informal learning grounded in everyday experiences
has much more influence on their development in comparison to the impact of formal-
ised coach education (­e.g., Blackett et al., 2019; Mallett, Trudel, Lyle & Rynne, 2009;
Stodter & Cushion, 2014; ­inter- ​­alia). Informal learning encapsulates the aggregated
effect of the conscious and subconscious knowledge acquired through experiences
(­Blackett et al., 2019; Cushion et al., 2010; Trudel, Culver & Werthner, 2013). Research-
ers repeatedly illustrate that much of the knowledge acquired by coaches is picked
186 Christopher J. Cushion and Anna Stodter
up through ‘­apprenticeships of observation’ as players, and subsequent experiential
learning and mentoring as coaches (­Cushion, 2019). Findings over time reinforce the
view that coaches mainly learn on the job. Embedded within context and responsive to
the everyday realities of practice, coaches spend much more time accumulating these
experiences than engaging in formal coach education.
This accumulated coaching knowledge has been considered to be incidental, un-
guided, unstructured, and uncritical (­ Cushion et al., 2003; Blackett et al., 2019;
Lemyre, Trudel & ­Durand-​­Bush, 2007; Mallett et al., 2009; ­inter- ​­alia), occurring
within particular ­socio-​­cultural contexts. Blackett et al. (­2019) argue that coach learn-
ing and therefore the development of expertise is bound to the informal s­ ocio-​­cultural
norms of the sport’s (­or club’s) ­sub-​­culture (­Townsend & Cushion, 2017; B ­ arker-​­Ruchti
et al., 2016; Lemyre et al., 2007). The implications are that learning through observa-
tion and experience can promote and reinforce certain ideological interpretations of
knowledge and practice, resulting in behaviour guided by uncritical inertia, with po-
tentially outdated knowledge and behaviours passed on and reproduced. In addition,
the importance placed on informal or ‘­embodied learning’ (­Blackett et al., 2019) can
create ‘­­one-​­dimensional’ (­Brown & Potrac, 2009, p ­ . 155) coach identities. This latter
notion has implications for coach development, where coaches may not fully engage
in purposeful reflection or critical t­ hinking – both
​­ of which are significant aspects of
adaptive expertise and its development (­Mees, et al., 2020). At the same time, such
experience does substantially contribute to the development of ­sport-​­specific coaching
content knowledge (­Blackett et al., 2019; Cushion et al., 2003; Mallett, et al., 2009).
This factor then acts in developing tacit knowledge of the sport and coaching practices
(­Nash & Collins, 2006).
Often, these learning processes connect to a ‘­default’ coaching role, and the be-
haviours and knowledge that coaches engage with are linked to the issues surround-
ing ‘­traditional’ coaching, the espoused club culture and socialisation experiences
(­Cushion, 2019). This issue is problematic for soccer coaching, resulting in an extraor-
dinary sameness in coaching practice with findings of contemporary research tending
to mirror work conducted over the last 35 years (­e.g., Potrac, Jones & Cushion, 2007;
Ford et al., 2010; Lacy & Darst, 1985; O’Connor et al., 2017, 2018). It appears that
‘­traditional’ coaching in soccer is unchangeable, ‘­what is expected’ within the coach-
ing role by coaches, players, parents, and clubs (­Cushion, 2013, 2019; Potrac et al.,
2007). Potrac et al. (­2007, ­p. 40) claim “­the consequence of such action is that athletes
are increasingly socialised into expecting instructional behaviours from coaches, and
thus resist other coaching methods”. As a result, coaching becomes a historical and
traditional thread where experiences are powerful, l­ong-​­lasting, and have a continual
influence over pedagogical perspectives, practices, beliefs, and behaviours (­Cushion,
2019, 2013; Cushion et al., 2003; Potrac et al., 2007). Therefore, coach socialisation
needs to be examined before drawing conclusions about what might constitute good
coaching knowledge and practice (­Cushion, 2010, 2019).

Formal learning
Although they are often treated as conceptually distinct, regulated formal coach
certification and education programmes occur in combination with informal learn-
ing (­Werthner & Trudel, 2009) and against a similarly influential cultural backdrop
(­Stodter & Cushion, 2014). Typically, programmes entail certain prerequisites, are
 Developing (­adaptive) coaching expertise 187
built around compartmentalised, standardised curricula over short blocks of time and
result in certification, but in soccer, there is huge variation in their extent and duration.
Researchers have tended to report coaches’ perceptions of formal learning oppor-
tunities, with much criticism directed at the use of prescriptive teaching strategies
aligned to a simplistic ‘­instruction’ paradigm, decontextualised delivery, and limited
relevancy or influence on the ‘­­real-​­world’ dynamic demands of coaching. Chapman
et al. (­2020) described soccer coach education courses as decontextualised (­i.e., di-
vorced from the coaches’ own coaching context), inadequate (­i.e., failing to meet learn-
ers’ needs) and bureaucratic (­Mallett et al., 2009; Sawiuk, Taylor, & Groom, 2016). In
other words, not providing the conditions to develop adaptive expertise or its cognitive
facets such as flexible planning, nuanced situational awareness, i­n-​­action reflection,
and metacognition allow for deep ­self-​­awareness (­Mees et al., 2020). Coaches may
merely abide by strict rules on courses to gain certification (­cf. Chesterfield, Potrac, &
Jones, 2010), missing out on ‘­deliberate practice’. In contrast, a recent review found
that coaches report positive perceptions of more participatory, interactive, and re-
flective teaching strategies and contextualised assessment processes in line with a
‘­learning’ paradigm (­Ciampolini et al., 2019). Such approaches would appear to align
with what Mees et al. (­2020) outline as valued by adaptive experts, namely, learning
and applying knowledge that is motivated to solving novel ­situation-​­specific problems
(­Bransford et al., 2005).
In recent years, there has been a trend towards more ‘­­learner-​­centred’ perspectives
(­Dempsey et al., 2020) tending to promote a more ­constructivist-​­informed epistemol-
ogy. Knowledge is assumed to be socially constructed in interaction and must be ex-
perienced rather than acquired, with the coach positioned more as a n ­ on-​­directive
facilitator and, within certain constraints, the player (­learner) largely controls their
own development. This emphasises the coach’s facilitative behaviours, not instruct-
ing per se but constructing experiences for players. In this case, coaches would pro-
vide limited amounts of instructional feedback but engage in helping the learner solve
problems and construct knowledge experientially through, for example, questioning,
summarising, reflecting, and ­listening – ​­methods more aligned with developing adap-
tive expertise. Paquette and Trudel (­2018) described coach education approaches in-
formed by constructivist epistemology as those that involve facilitation, group work,
localised p­ roblem-​­solving, and the sharing of ideas (­Dempsey et al., 2020), and these
learning principles have become more established in the recent history of coach edu-
cation (­Ciampolini et al., 2019). Moreover, in England, the Football Association has
continued a clear move towards coach education being informed by social construc-
tivism (­Chapman et al., 2020; Dempsey et al., 2020).
However, as Dempsey et al. (­2020) and Cushion (­2013) demonstrate, understanding
of learning strategy(­s) and the theory that informs it varies. Constructivist approaches
are not prescriptions for methods or strategies of teaching and a focus on methods
rather than underlying philosophical positions can result in a naïve constructivism,
placing an inordinate faith in the ability of the learner to structure their own learn-
ing (­Cushion, 2013, 2019). This notion equates learning exclusively with activity and
involvement alone as a sufficient and necessary condition for learning (­K irschner,
Sweller & Clark, 2006). Coach development and the education of coach developers
themselves rely on assumed learning through such ‘­active learning opportunities’, in
line with preferences for experiential learning involving interaction with other coaches
(­Stodter & Cushion, 2019b).
188 Christopher J. Cushion and Anna Stodter
Meaningful learning occurs when the learner is able to connect to, and make sense
of, what is to be learned, identify relevant knowledge and information, organise it into
a coherent structure, and integrating it with existing knowledge (­Mayer, 2004). Experts
progress through levels of knowledge acquisition, but for information to become
knowledge, the learner must share some context and meaning with those imparting the
knowledge (­Cushion et al., 2010; Swap et al., 2001). Therefore, providing meaningful
learning experiences is crucial in developing expertise. Learning requires skilful and
progressive instruction that assists metacognition and s­ elf-​­monitoring, helping each
learner to reflect on answers, and giving feedback that focuses learners on the task.
However, a ‘­­one-­​­­size-­​­­fits-​­all’ approach to learning regardless of individual differences,
with very little variation in practice, remains prevalent in soccer (­Stodter & Cushion,
2019b). Not all learners are the same, nor are circumstances and contexts, and advo-
cating a singular approach seems to contradict l­ earner-​­centeredness, conflict with the
characteristics of adaptive expertise, and deny or minimise difference (­Cushion, 2010,
2013). Engagement with ‘­naïve constructivism as method’ may inadvertently impose
arbitrary ideology and values through practice, rather than providing that which will
best meet the learner’s needs. Importantly, despite the popularity of, and prescrip-
tions for, outwardly ‘­­learner-​­centred’ approaches, the evidence of increased impact on
learning, knowledge, practice, or the development of expertise is not clear (­Paquette &
Trudel, 2018).
Cope, Cushion, Harvey, and Partingon (­2021) argue that only a handful of studies
spread over 20 years have attempted to show how formal coach education has changed
knowledge and practice. Stodter and Cushion (­2019a) looked at a level three soccer
course and reported changes in the use of knowledge around tactics, and engaging
with individual players, reflected in an altered proportion of technical to tactically
related questions, and more behaviours directed at individual players. Course partici-
pants also had changed knowledge of practice structures, challenges and questioning,
learning principles and reflection, although corresponding behaviours and practice
activities generally remained consistent. The minimal impact of learning on observed
coaching behaviour, alongside interview data, revealed some disconnect between
knowledge and situated action, suggesting a lack of deep learning. Coaches were able
to adopt and reinforce knowledge without challenging deeply held assumptions, re-
flecting common criticisms of coach education in generating meaningful change. This
process is not supportive of developing adaptive expertise which fosters a willingness
to challenge and replace prior assumptions and recognise gaps in knowledge, drawing
on the individual’s reflective and metacognitive capacities (­Mees et al., 2020; Bransford
et al., 2005). ‘­­Deep-​­seated’ practices can be resistant to change, and changing behav-
iour is particularly challenging using short, formal coach education courses. While
some impact was evidenced, the findings pose questions to the duration, design, and
­follow-​­up of educational episodes.
Behavioural research reports a continued disconnect between coaches’ intentions
and their practice suggesting low s­ elf-​­awareness, and illustrates soccer coaches as di-
rective, instructional, or prescriptive, with the coach deciding when and how players
should perform specified skills or movements (­cf. O’Connor et al., 2017, 2018). Further-
more, analysis by Cope et al. (­2016) showed that coaches engage in limited dialogic
behaviour and ask few questions, typically between 2% and 5% of overall reported
coaching behaviours. Studies also demonstrate that coaches predominantly ask con-
vergent rather than divergent questions (­e.g., Harvey et al., 2011; Partington & Cushion,
 Developing (­adaptive) coaching expertise 189
2013) with the latter seen as pivotal in learning to develop h
­ igher-​­order thinking and
the application of adaptive expertise.

Developing coaching practice and adaptive expertise

Clearly, how coaches are educated in soccer has a direct influence on the nature of
their practice of adaptive expertise (­Mees et al., 2020). Developing adaptive coaching
expertise requires building, then moving beyond, proceduralised practice and compe-
tency toward ­in-​­context practices that are more flexible, ­decision-​­based, and reflective.
This change includes developing a range of practices that avoid promoting one ap-
proach to coaching as superior to another, as different approaches will be appropriate
in different situations. A balance is required between impacting the development of
­decision-​­making, ­problem-​­solving, and creative skills (­Potrac & Cassidy, 2006) with
acquiring levels of knowledge and understanding that are immature, incorrect, and
may lead to the neglect of key skills (­Cushion, 2019; Cushion et al., 2012a; Potrac &
Cassidy, 2006).
Potrac and Cassidy (­2006) argue that to develop ­self-​­regulating and autonomous
learners requires “­more than either the o ­ ne-​­directional transmission of knowledge …
or the total ownership by learners of their own development” (­­p. 40). Thus, being
highly adaptive and ­context-​­specific, means there is no single ­all-​­encompassing ap-
proach. Coaches need to be free to interact and behave in a variety of ways and in at-
tempting to adhere to a particular way of coaching, may lose sight of the fact that they
need to act to create optimal conditions for learning. In other words, there is a need to
be responsive to individual differences where the most valuable coaching practices cor-
respond with developmental needs and individual particularities, requiring a diverse
range of approaches (­Cushion, 2010, 2019). Adaptive expert, ­learner-​­centred coaches
should be continuously engaged with ­evidence-​­informed approaches and reflection as
to how their players learn effectively, being primarily concerned about whether their
coaching impairs or facilitates learning (­Cushion, 2019; Cushion et al., 2012a).
At the very least, a starting point to a discussion around recommendations/­
guidelines for developing coach expertise is a need to emphasise that coaches should
be aware of their actual behaviour and the assumptions about learning underpinning
their practice (­Cushion, 2019). Crucial in raising coach ­self-​­awareness, this aspect is a
feature of adaptive experts who demonstrate the capacity to ­self-​­assess their expertise,
knowledge, learning, and ­problem-​­solving ability (­Mees et al., 2020). While evidence
suggests this quality is lacking in soccer, it seems essential if coaches are to grasp the
implications of their coaching (­good or bad). Coaches can develop a better concep-
tual understanding by reflecting on why they coach as they do and related underlying
assumptions. Alongside critical reflection on their socialisation experiences and the
culturally accepted coaching behaviours of soccer, this puts coaches in a strong po-
sition to transcend ‘­traditional’ behaviour and develop their own informed approach
to expertise. All of which require high cognitive flexibility, deep thinking skills, and
metacognitive ability (­Mees et al., 2020).
However, established practices in coaching are difficult to change because many
coaches “­find it difficult to reflect upon, and possibly critique, taken for granted prac-
tices that have become integral to their sense of self” (­Cassidy, 2010, ­p. 143). The pro-
cess of relying solely on one’s ­self-​­perception of what works closes conversations, blunts
knowledge and stifles creativity, which, if left unchallenged, produces stagnation and
190 Christopher J. Cushion and Anna Stodter
a climate of s­ elf-​­referential, ­self-​­justifying knowledge structures (­Cushion, 2019; Abra-
ham et al., 2006). There is a need to use more objective methods that allow coaches
to reflect on their practice; robust changes to coaching practice rely on reflection.
Systematic observation is a means of analysing what behaviours coaches employ and
these data can be used to support reflection through discussions about practice. Par-
tington et al. (­2015) tracked five elite soccer coaches over three seasons (­approximately
30 months) using the Coach Analysis Intervention System (­Cushion et al., 2012b) and
video feedback. The study reported significant differences over time in four behav-
iours: instruction; feedback; silence; and questioning. Objective data and video feed-
back provided a structure for reflective conversations, improved s­ elf-​­awareness, and
triggered behaviour change. There are further examples of coaches developing and
changing their coaching behaviour and practice structures when accessing behav-
ioural data combined with reflective practice (­e.g., Harvey et al., 2010, 2011). However,
changes in practice and behaviour were not totally adopted, with customary practices
resisting change. Cope et al. (­2021) worked with coaches to develop a learning pro-
gramme, where the participants perceived changes in their way of thinking about de-
veloping as coaches and reported changes in their coaching practice, substantiated by
observational data. These studies show that by providing coaches with an opportunity
to discuss issues specific to their practice and supporting them to think more critically
about their coaching (­e.g. through reflective conversations), changes can and do occur
(­Cope et al., 2021).
Reflective practice is important in developing expertise as well as being a feature of
adaptive expertise. There are many types of reflection (­e.g., descriptive and creative),
but the key type in coach development is critical reflection (­Cushion et al., 2012a).
Critical reflection necessitates that coaches question and challenge current practices,
habits, routines, values, and beliefs. Ghaye (­2001, ­p. 10) calls this “­asking the ‘­­why-​
t­ype’ question: ‘­why do I/­we coach in this way?’” Critical reflection enables coaches
to integrate various sources of knowledge they encounter into their repertoire, a pro-
cess necessary to transform behaviours. For coaches with ­well-​­developed beliefs, in-
formation acquired may contradict their current practice, presenting the dilemma of
revising their thinking through ‘­conceptual change’ (­Cushion et al., 2012a; Schraw,
Crippen, & Hartley, 2006). The ability to engage in critical reflection (­i.e., questioning
and challenging current practices, habits, routines, values, and beliefs) is therefore a
fundamental process for a coach.
Coaches, therefore, require the ‘­tools’ (­i.e., reflection, ­self-​­regulation, and aligned
epistemological beliefs) to deal with the many different and evolving situations that they
come across, with coaches appearing to develop and refine strategies through cycles
of experimentation and evaluation (­Gilbert & Trudel, 2001; Stodter & Cushion, 2017).
Expert coaches learn more from events because they critically reflect rather than sim-
ply accumulating experience. Such reflection enables a comparison of p ­ roblem-​­solving
processes with those who are deemed ‘­more expert’ and provides a conceptualisation
of adaptive expertise (­Hatano & Inagaki, 1986; Nash, Martindale, Collins, & Mar-
tindale, 2012) that allows a comparison towards the behaviour of an adaptive expert
(­Mees et al., 2020). Coaches can become “­more expert” by mastering the skill of learn-
ing from their experiences through reflective practice (­Schempp & McCullick, 2010,
­p. 230). To develop adaptive expertise, coach education should provide an environ-
ment where practice, and the practice of others, can be interrogated and assumptions
made explicit, providing the skills and resources to enable reflection and to critically
 Developing (­adaptive) coaching expertise 191
examine the inadequacies of different conceptions of practice (­cf. Lyle & Cushion,
2017). However, learning in this way is beyond existing conceptions of soccer coach
education which is largely an additive r­ e-​­tooling (­g rafting new ‘­skills’/­k nowledge onto
an existing repertoire) rather than critically transformative (­deconstructing t­ aken-­​­­for-​
g­ ranted beliefs, assumptions, knowledge and habits, and rebuilding practice; Cushion,
2013, 2019).

Conclusions and future directions

Ericsson and Charness (­1994) argue that expertise is developed by learning through doing
and is characterised by pattern recognition based on experience. Coaches can develop
expert skills, behaviours, and practices based on highly interconnected knowledge struc-
tures, through conscious investment in, and refinement of, experiences. However, these
suppositions remain largely untested in the coaching literature (­Cushion, 2019). Taking
a more ­process-​­oriented view, adaptive experts possess extensive, integrated knowledge
differentiating them from routine experts (­Hatano & Inagaki, 1986). Adaptive experts
appear to focus on acquiring new domain knowledge and skills to apply across changing
contexts as opposed to learning procedures; suggesting their training and development
require a ­non-​­routine approach (­Mees et al., 2020). Currently, in soccer, coach socialisa-
tion is the dominant means of sharing experiences and creating tacit knowledge, largely
through informal processes. In recognition of this fact, linear, functionalist, and unprob-
lematic coaching pathway models do not accurately reflect coaching reality, which is
‘­messy’, ‘­fragmented’, and ­situation-​­specific (­Jones, Armour & Potrac, 2004, ­p. 1; Black-
ett et al., 2019). Currently, then, within coach education structures, it is unclear how
coaches can engage in targeted ‘­deliberate’ coaching practice to develop specific, c­ ontext-​
r­ elevant knowledge and skills and progress towards adaptive expertise.
Research into coach learning has suggested that rather than try to classify the best
learning situation or source of coaching knowledge, it is more important to under-
stand the complementarity of different learning situations in contributing to the de-
velopment of expertise (­Trudel et al., 2010). This blending rather than separation is key
(­Cushion et al., 2010). Contested processes of coach socialisation currently contour
coach development by significantly influencing which information is initially acquired
and then contextualised into useable knowledge (­Blackett et al., 2019). These cir-
cumstances greatly influence the nature and likelihood of expertise being developed.
Importantly for coaches, time constrains the amount and intensity of formal develop-
ment that could enable the transfer of knowledge, yet acquiring experience is equally
important. There remains, therefore, a requirement to disaggregate experience as a
coach from coach education to help understand how coaches may develop requisite
levels of expertise.
A need for more thorough, integrated, practical, and conceptually informed ap-
proaches to investigating how coaches develop and use their knowledge and skills in
context is also apparent. What is clear is that the critical skills of adaptive expertise,
including deep knowledge of the content domain, metacognitive skills and ­problem-​
s­ olving across differing environments, require formal learning approaches that more
accurately resemble continuous deliberate practice, employing explicit and unambig-
uous means of communication and feedback for coaches. More evidence is needed to
say much with certainty about the most appropriate feedback to support coaches’ de-
veloping adaptive expertise, but reflective c­ onversations – ​­repeated cycles of problem
192 Christopher J. Cushion and Anna Stodter
(­re)­appreciation, strategy generation, experimentation, and ­evaluation – based
​­ on spe-
cific practice issues and grounded in everyday experiences, appear to offer the poten-
tial for structuring feedback and learning in coaching. Reflective conversations can be
embedded into coach development opportunities, notably supported by skilled coach
developers to help coaches connect to and make sense of what is to be learned in their
own changing environments, thereby facilitating more individually meaningful learn-
ing opportunities (­Stodter, Cope & Townsend, 2021).
Video recordings of practice and systematic observation of coaching behaviour can
also be built into the above process as a powerful catalyst to enhance coaches’ s­ elf-​
­awareness and metacognitive skills, ultimately working towards changing behaviour
and practice in line with adaptive expertise. The significance of helping coaches to un-
derstand their own practice, their view of learning, and deliberately ‘­learning to learn’
as part of ­learner-​­centred coach education has been noted (­e.g., Paquette & Trudel,
2018) and this could be a fruitful but as yet ­under-​­evidenced area to develop adaptive
expertise in coaching. Overall, rather than a rigid l­ evel-​­and ­competency-​­based formal
coach education system reflecting the concept of expertise as an outcome, a shift in
focus towards the processes of adaptive expertise and varied situations that facilitate
learning of these in combination suggests a need for more aligned pedagogic agility in
coach development (­Mees et al., 2020).

References
Abraham, A., Collins, D., & Martindale, R. (­2006). The coaching schematic: validation through
expert coach consensus. Journal of Sports Sciences, 24, ­549–​­564.
Bachkirova, T., & Smith, C. (­2015). From competencies to capabilities in the assessment and ac-
creditation of coaches. International Journal of Evidence Based Coaching and Mentoring, 13(­2),
­123–​­140. https://­radar.brookes.ac.uk/­radar/­items/­­a7515cd5-­​­­e58f- ­​­­4aa6-­​­­b504-​­a1f9c6b92268/­1/
­Barker-​­Ruchti, N., Barker, D., Rynne, S. B., & Lee, J. (­2016). Learning cultures and cultural
learning in ­h igh-​­performance sport: opportunities for sport pedagogues. Physical Education
and Sport Pedagogy, 21, ­1–​­9.
Barnett, S., & Koslowski, B. (­2002). Adaptive expertise: effects of type of experience and the
level of theoretical understanding it generates. Thinking & Reasoning, 8(­4), ­237–​­267. https://­
doi.org/­10.1080/­13546780244000088
Berry, P. (­2020). An alternative conceptualisation of coach expertise. Coaching: An International
Journal of Theory, Research and Practice, 14(2), 202-213. DOI: 10.1080/­17521882.2020.1853189
Blackett, A. D., Evans, A. B., & Piggott, D. (­2019). “­They have to toe the line”: a Foucauld-
ian analysis of the socialisation of former elite athletes into academy coaching roles. Sports
Coaching Review, 8(­1), ­83–​­102, DOI: 10.1080/­21640629.2018.1436502
Bransford, J., Derry, S., Berliner, D., Hammerness, K., & Beckett. K. L. (­2005). Theories of
learning and their roles in teaching. In L. ­Darling-​­Hammond & J. Bransford (­Eds.). Prepar-
ing Teachers for a Changing World: What Teachers Should Learn and Be Able to Do (­p­­p. ­40–​
­87). San Francisco: ­Jossey-​­Bass.
Brown, G., & Potrac, P. (­2009). “­You’ve not made the grade, son”: d ­ e-​­selection and identity
disruption in elite level youth football. Soccer & Society, 10, ­143–​­159.
Carbonell, K., Könings, K., Segers, M., & van Merriënboer, J. (­2016). Measuring adaptive ex-
pertise: development and validation of an instrument. European Journal of Work and Organ-
izational Psychology, 25(­2), ­167–​­180. https://­doi.org/­10.1080/­1359432X.2015.1036858
Cassidy, T. (­2010). Understanding athlete learning and caching practice: utilising ‘­practice the-
ories’ and ‘­theories of practice’. In J. Lyle & C. Cushion (­Eds.), Sports Coaching Professional-
ization and Practice (­p­­p. ­177–​­192). London: Churchill Livingstone Elsevier.
 Developing (­adaptive) coaching expertise 193
Chapman, R., Richardson, D., Cope, E., & Cronin, C. (­2020). Learning from the past; a Frierean
analysis of FA coach education since 1967. Sport, Education and Society, 25 (­6),­618–​­697.
Chesterfield, G., Potrac, P., & Jones, R. L. (­2010). ‘­Studentship’ and ‘­i mpression management’:
coaches’ experiences of an advanced soccer coach education award. Sport, Education and
Society, 15, ­299–​­314.
Ciampolini, V., Milistetd, M., Rynne, S. B., Brasil, V. Z., & do Nascimento, J. V. (­2019). Research
review on coaches’ perceptions regarding the teaching strategies experienced in coach educa-
tion programs. International Journal of Sports, Science and Coaching, 14(­2), ­216–​­228. https://­
doi.org/­10.1177/­1747954119833597
Cope, E., Cushion, C. J., Harvey, S., & Partington, M. (­2021). Investigating the impact of a
Freirean informed coach education programme. Physical Education and Sport Pedagogy,
26(­1), ­65–​­78. DOI: 10.1080/­17408989.2020.1800619
Cope, E., Partington, M., Cushion, C. J., & Harvey, S. (­2016). An investigation of professional
­top-​­level youth football coaches’ questioning practice. Qualitative Research in Sport, Exer-
cise and Health, 8(4), 380–393. DOI: 10.1080/­2159676X.2016.1157829
Cruickshank, A., Martindale, A., & Collins, D. (­2018). Raising our game: the necessity and
progression of ­expertise-​­based training in applied sport psychology. Journal of Applied Sport
Psychology­, 32(3), 237–255. https://­doi.org/­10.1080/­10413200.2018.1492471
Cushion. C. J. (­2019). Observing coach behaviours: developing coaching practice and coach
education? In Thelwell R., & Dicks M., (­Eds). Professional Advances in Sports Coaching:
Research and Practice (­p­­p. ­358–​­376). London: Routledge.
Cushion, C. J. (­2013). Applying game centered approaches to coaching: a critical analysis of the
‘­dilemmas’ of practice impacting change. Sports Coaching Review, 2(­1), ­61–​­76
Cushion, C. J., (­2010). Coach behaviour. In. J. Lyle, & C. J. Cushion (­Eds.), Sports Coaching
Professionalization and Practice (­p­­p. ­43–​­62). London: Elsevier.
Cushion, C. J., Armour, K. M., & Jones, R. L. (­2003). Coach education and continuing profes-
sional development: experience and learning to coach. Quest, 55(­3), ­215–​­230.
Cushion, C. J., Ford, P. R., & Williams, A. M. (­2012a). Coach behaviours and practice struc-
tures in youth soccer: implications for talent development. Journal of Sports Sciences, 30(­15),
­1631–​­164.
Cushion, C. J., Harvey, S., Muir, B., & Nelson, L. (­2012b). Developing the coach analysis and
intervention system (­CAIS): establishing validity and reliability of a computerised systematic
observation instrument. Journal of Sports Sciences, 30(­2), ­203–​­218.
Cushion, C. J., Nelson, L., Armour, K., Lyle, J., Jones R. L., Sandford, R., & O’Callaghan, C.
(­2010). Coach Learning and Development: A Review of Literature. Leeds: Sports Coach.
Cushion, C. J., Stodter, A. & Clarke, N. J. (­2021). ‘­It’s an experiential thing’: the discursive
construction of learning in ­h igh-​­performance coach education. Sport Education and Society,
27(7), 844–861. DOI: 10.1080/­13573322.2021.1924143
Dempsey, N. M., Richardson, D. J., Cope, E., & Cronin, C. J. (­2020). Creating and disseminat-
ing coach education policy: a case of formal coach education in grassroots football. Sport,
Education and Society, 26(8), 917–930. DOI:10.1080/­13573322.2020.1802711
Downham, L., & Cushion, C. J., (­2020). Reflection in a ­h igh-​­performance sport coach educa-
tion programme: a Foucauldian analysis of coach developers. International Sport Coaching
Journal, 7(3), 347–359. https://­doi.org/­10.1123/­iscj.­2018- ​­0 093
Ericsson, K., & Charness, N. (­1994). Expert performance: its structure and acquisition. Ameri-
can Psychologist, 49(­8), ­725–​­747. https://­doi.org/­10.1037/­­0 003-​­066X.49.8.725
­Farrington-​­Darby, T., & Wilson, J. (­2006). The nature of expertise: a review. Applied Ergonom-
ics, 37(­1), ­17–​­32. https://­doi.org/­10.1016/­j.apergo.2005.09.001
Ford, P. R., Yates, I., & Williams, A. M. (­2010). An analysis of practice activities and instruc-
tional behaviours used by youth soccer coaches during practice: exploring the link between
science and application. Journal of Sports Sciences, 28, ­483–​­495.
Ghaye, T. (­2001). Reflective practice. Faster, Higher, Stronger, 10, ­9 –​­12.
194 Christopher J. Cushion and Anna Stodter
Gilbert, W. D. & Trudel, P. (­2001). Learning to coach through experience: reflection in model
youth sport coaches. Journal of Teaching in Physical Education, 21, ­16–​­34.
Harvey, S., Cushion, C. J., Wegis, H. M., & ­Massa-​­Gonzalez, A. N. (­2010). Teaching games for
understanding in American h ­ igh-​­school soccer: a quantitative data analysis using the game
performance assessment instrument. Physical Education and Sport Pedagogy, 15, ­29–​­54.
Harvey, S., Cushion, C. J., & M ­ assa-​­Gonzalez, A. N. (­2011). Learning a new method: teaching
games for understanding in the coaches’ eyes. Physical Education and Sport Pedagogy, 15,
­361–​­382.
Hatano, G., & Inagaki, K. (­1986). Two courses of expertise. In H. Stevenson, H. Azuma, & K.
Hakuta (­Eds.), Child Development and Education in Japan (­p­­p. ­262–​­272). New York: Free-
man. doi:10.1002/­c cd.10470.
Hatano, G., & Oura, Y. (­2003). Commentary: reconceptualizing school learning. Educational
Researcher, 32(­8), ­26–​­29. doi:10.3102/­0 013189X032008026.
Hutton, R., Ward, P., Gore, J., Turner, P., Hoffman, R., & Conway, G. (­2017). Developing adap-
tive expertise: a synthesis of literature and implications for training. In 13th International
Conference on Naturalistic Decision Making (­p­­p. ­81–​­86). Bath, UK.
Jones, R. L., Armour, K. M., & Potrac, P. (­2004). Constructing expert knowledge: a case study
of a ­top-​­level professional soccer coach. Sport, Education and Society, 8, ­213–​­229.
Jones, R. L., Bailey, J., & Thompson, A. (­2013). Ambiguity, noticing and orchestration: further
thoughts on managing the complex coaching context. In P. Potrac, W. Gilbert & J. Denison
(­Eds.), Routledge Handbook of Sports Coaching (­p­­p. ­271–​­283). Abingdon, UK: Routledge.
Kirschner, P. A., Sweller J., & Clark, R. E. (­2006). Why minimal guidance during instruction
does not work: an analysis of the failure of constructivist, problem based, experiential and
­i nquiry-​­based teaching. Educational Psychologist, 41(­2), ­75–​­86.
Lacy, A. C., & Darst, P. W. (­1985). Systematic observation of behaviours of winning high school
head football coaches. Journal of Teaching in Physical Education, 4, ­256–​­270.
Lemyre, F., Trudel, P., & ­Durand-​­Bush, N. (­2007). How ­youth-​­sport coaches learn to coach.
The Sport Psychologist, 21, ­191–​­209.
Lyle, J., & Cushion, C. J. (­2017). Sports Coaching Concepts: A Framework for Coaching Practice
(­2nd ed). London: Routledge.
Mallett, C., Trudel, P., Lyle, J., & Rynne, S. (­2009). Formal vs. informal coach education. Inter-
national Journal of Sports Science & Coaching, 4(­3), ­325–​­364. doi:10.1260/­174795409789623883
Martindale, A., & Collins, D. (­2013). The development of professional judgment and ­decision-​
­making expertise in applied sport psychology. The Sport Psychologist, 27(­4), ­390–​­399. https://­
doi.org/­10.1123/­tsp.27.4.390
Mayer, R. E. (­2004). Should there be a three strikes rule against pure discovery learning? Amer-
ican Psychologist, 59(­1), ­14–​­19.
Mees, A., Sinfield, D., Collins, D., & Collins, L., (­2020). Adaptive expertise: a characteristic
of expertise in outdoor instructors? Physical Education and Sport Pedagogy, 25(­4), ­423–​­438.
Nash, C., & Collins, D. (­2006). Tacit knowledge in expert coaching: science or art? Quest, 58,
­465–​­477.
Nash, C., Martindale, R., Collins, D., & Martindale. A. (­2012). Parameterising expertise in
coaching: past, present and future. Journal of Sports Sciences, 30(­10), ­985–​­994. doi:10.108
0/­02640414.2012.682079.
O’Connor, D., Larkin, P., & Williams, M. (­2017). Observations of youth football training. How
do coaches structure training sessions for player development? Journal of Sport Sciences,
36(­1), ­39–​­47.
O’Connor, D., Larkin, P., & Williams, M. (­2018). What earning environments help improve
­decision-​­making? Physical Education and Sport Pedagogy, 22(­6), ­647–​­660.
Owen, J., & Lindley, L. (­2010). Therapists’ cognitive complexity: review of theoretical models
and development of an integrated approach for training. Training and Education in Profes-
sional Psychology, 4(­2), ­128–​­137. https://­doi.org/­10.1037/­a0017697
 Developing (­adaptive) coaching expertise 195
Paquette, K., & Trudel, P. (­2018). ­Learner-​­centered coach education: practical recommen-
dations for coach development administrators. International Sport Coaching Journal, 5(­1),
­169–​­175.
Partington, M., & Cushion, C. (­2013). An investigation of the practice activities and coaching
behaviors of professional t­ op-​­level youth soccer coaches. Scandinavian Journal of Medicine &
Science in Sports, 13, ­1–​­9.
Partington, M., Cushion, C. J., Cope, E., & Harvey, S. (­2015). The impact of video feedback on
professional youth football coaches’ reflection and practice behaviour: a longitudinal investi-
gation of behaviour change. Reflective Practice: International and Multidisciplinary Perspec-
tives, 16(5), 700–716. DOI: 10.1080/­14623943.2015.1071707.
Piggott, D. (­2012). Coaches’ experiences of formal coach education: a critical sociological in-
vestigation. Sport, Education and Society, 17(­4), ­535–​­554.
Potrac P., & Cassidy, T. (­2006). The coach as ‘­more capable other’. In R. L. Jones (­ed.), The Sports
Coach as Educator R ­ e-​­conceptualising Sports Coaching (­pp ­39–​­50). London: Routledge.
Potrac, P., Jones, R. L., & Cushion, C. J., (­2007). Understanding power and the coach’s role
in professional English soccer: a preliminary investigation of coach behaviour. Soccer and
Society, 8, ­33–​­49.
Sawiuk, R., Taylor, W., & Groom, R. (­ 2016). Exploring formalized elite coach mentor-
ing programmes in the UK. Sport, Education and Society, 23(­6), ­619–​­631. doi:10.108
0/­13573322.2016.1248386
Schempp, P. G., & McCullick, B. (­2010). Coaches’ expertise. In J. Lyle & C. Cushion (­Eds.),
Sports Coaching: Professionalisation and Practice (­p­­p. ­221–​­231). China: Elsevier.
Schraw, G. S., Crippen, K. J., & Hartley, K. (­2006). Promoting s­ elf-​­regulation in science ed-
ucation: metacognition as part of a broader perspective on learning. Research in Science
Education, 36, ­111–​­139.
Sfard, A. (­1998). On two metaphors for learning and the dangers of choosing just one. Educa-
tional Researcher, 27, ­4 –​­13.
Sonnentage, S., Niessen, C., & Volmer, J. (­2006). Expertise in software design. In A. Ericsson,
N. Charness, P. Feltovich, & R. Hoffman (­Eds.), The Cambridge Handbook of Expertise and
Expert Performance (­p­­p. ­373–​­389). Cambridge University Press, Cambridge, UK.
Stodter, A., & Cushion, C. J. (­2014). Coaches’ learning and education: a case study of cultures
in conflict. Sports Coaching Review, 3(­1), ­63–​­79.
Stodter, A., & Cushion, C. J. (­2017). What works in coach learning, how, and for whom? A
grounded process of soccer coaches’ professional learning. Qualitative Research in Sport,
Exercise and Health, 9(­3), ­321–​­338.
Stodter, A., & Cushion, C. J. (­2019a). Evidencing the impact of coaches’ learning: changes in
coaching knowledge and practice over time. Journal of Sports Sciences, 37(­18), ­2086–​­2093.
Stodter, A., & Cushion. C. J. (­2019b). Layers of learning in coach developers’ practice theories,
preparation and delivery. International Sport Coaching Journal, 6(­3), ­307–​­316.
Anna Stodter, Ed Cope & Robert C. Townsend (2021) Reflective conversations as a basis for
sport coaches’ learning: a theory-informed pedagogic design for educating reflective practi-
tioners, Professional Development in Education, DOI: 10.1080/19415257.2021.1902836
Swap, D., Leonard, D., Shields, M., & Abrams, A. (­2001) Using mentoring and storytelling
to transfer knowledge in the workplace. Journal of Management Information Systems, 18(­1),
­95–​­114.
Townsend, R. C., & Cushion, C. (­2017). Elite cricket coach education: a Bourdieusian analysis.
Sport, Education and Society, 4, ­528–​­546.
Townsend, R. C., Huntley, T. D., Cushion, C. J., & Culver, D. (­2021). Infusing disability into
coach education and development: a critical review and agenda for change. Physical Educa-
tion and Sport Pedagogy, 27(3), 247–260. DOI: 10.1080/­17408989.2021.1873932
Trudel, P., Culver, D., & Werthner, P. (­2013). Looking at coach development from the c­ oach-​
­learner’s perspective: considerations for coach development administrators. In P. Potrac, W.
196 Christopher J. Cushion and Anna Stodter
Gilbert & J. Denison (­Eds.), Routledge Handbook of Sports Coaching (­p­­p. ­375–​­387). London:
Routledge.
Trudel, P., & Gilbert, W. (­2006). Coaching and coach education. In D. Kirk, D. Macdonald &
M. O’Sullivan (­Eds.), The Handbook of Physical Education. London: Sage.
Trudel, P., Gilbert, W., & Werthner, P. (­2010). Coach education effectiveness. In J. Lyle &
C. Cushion (­Eds.) Sports Coaching: Professionalisation and Practice (­p­­p. ­135–​­152). China:
Elsevier.
Turner, D., Nelson, L., & Potrac, P. (­2012). The journey is the destination: reconsidering the
expert sports coach. Quest, 64, ­313–​­325.
Werthner, P., & Trudel, P. (­2009). Investigating the idiosyncratic learning paths of elite Cana-
dian coaches. International Journal of Sports Science & Coaching, 4, ­433–​­449.
Williams, S., & Bush, A. J. (­2019). Connecting knowledge(­s) to practice: a Bernsteinian theo-
rising of a collaborative coach learning community project. Sport, Education and Society,
24(­4), ­375–​­389.
Section C

Sports Medicine and

Biomechanics
13 Injury epidemiology, monitoring, and
prevention
Ian Beasley

Introduction
Soccer is a contact sport, involving running, jumping, and changing direction suddenly
(­known as ‘­cutting’), whereas for goalkeepers it involves diving with unprotected land-
ing. It follows, therefore, that injury is part of playing the sport, and this can be related
to any of the above activities or by way of contact with other players, or ­on-​­pitch/­­off-​
p
­ itch hardware, such as goalposts or advertising hoardings. Professional players train
for up to 3 h daily and play competitive matches (­at least) twice a week, placing upon
them what might be considered unreasonable physiological and psychological stress.
Most practitioners working in professional soccer can identify players that seem
to be more susceptible to injury than others, and some who seem to take longer than
others to recover from injury. Suffice to say that like the general population, players
are a ‘­m ixed bag’ and idiosyncratically respond to the demands of the sport, both in
performance and susceptibility to, and recuperation from, injury. The mechanism of
injury may be of use when trying to assess severity, and in the modern game, there are
video recordings of incidents that can be evaluated ‘­live’ by staff on the team bench
and help guide management of injuries via radio link with the practitioners attending
the injury. Concussion is often best observed from the stand, and ‘­spotters’ are now
deployed with video replay facilities, as well as a better vantage point to view the field
of play, enabling them to deliver ­real-​­time information to those delivering emergency
aid to the injured player on the field, for instance, regarding whether the player con-
cerned lost consciousness.

Epidemiology of injury
The largest body of work in this field is the UEFA Champions League (­UCL) studies
(­Ekstrand et al., 2020), which have been running since 2001. These studies include data
from professional clubs in European Leagues that are involved in the ­pan-​­European
competitions run by UEFA. The findings have highlighted the most common injury
patterns in soccer (­Ekstrand et al., 2016), as well as injury trends (­Ekstrand et al., 2016),
and average time loss from injury. From a practitioner’s point of view, this information
is valuable when predicting r­ e-​­availability/­return to play (­RTP) (­Ekstrand et al., 2020,
Lubberts et al., 2019). Availability of players within a squad has been shown to con-
tribute to success of a team (­Ekstrand, 2013).
There are now many epidemiological studies from different leagues and compe-
titions across the globe revealing underlying injury patterns (­Ekstrand et al., 2020;

DOI: 10.4324/9781003148418-16
200 Ian Beasley
Mosler et al., 2018; Tabben et al., 2021). It is useful also, within a league, to understand
what the ‘­normal’ (­in a Gaussian distribution sense) injury rates are. Any research
into injury patterns within a league should be shared between clubs/­teams, so that
any glaring differences can be examined, and acted upon so that players are protected
from injury.
Within clubs, epidemiological studies are useful in understanding which injuries
are more common, when injury risk is highest (­e.g., with higher match frequency),
and which player positions are most susceptible to injury. Planning and preparation
within a medical and sports science m ­ ulti-​­disciplinary team (­MDT) on where the
‘­pinch points’ are in a season, and which injuries are more common, helps in advising
coaching staff when players might be at greater risk.

Screening/­profiling and injury mitigation

There have been endless discussions about screening/­periodic health evaluation and
whether it prevents injury (­Bahr, 2016; Boles et al., 2015), and whether we profile or
screen. Wilson and Jungner (­1968) described the criteria in Public Health circles for
mass screening programmes (­e.g., cervical cancer screening) and some of their prin-
ciples apply when screening in this context, and this is where profiling, rather than
screening comes into the picture. For instance, one of Wilson and Jungners’ criteria
states, ‘­The natural history of the disease or condition should be adequately understood,
the disease or condition well defined, and there should be a detectable ­pre-​­clinical phase’.
This is clearly often not the case in musculoskeletal injury. This has ramifications, in
explaining why a condition was not picked up in a ­pre-​­signing medical, or a p ­ re-​­season
screening session, despite investigating things to the full. The use of the term profiling/­
screening is probably more appropriate, with the emphasis on the stroke. There may
be some things that are detectable, but certainly not all. We can measure quite well but
are unable to always predict. It is fair to say that screening can identify some suscepti-
bilities (­e.g., hypermobility, Paccy et al., 2010); cardiac risk (­Malhotra et al., 2017), but
soccer is an unpredictable sport, and injuries and other issues will occur, hence the use
of ‘­injury and illness mitigation’ rather than injury prevention.
Most professional clubs will carry out profiling/­screening activity, which may con-
sist only of statutory cardiac screening, or may consist of cardiac, medical, muscu-
loskeletal, nutritional, and ­psycho-​­social components. Screening/profiling resources
and is usually carried out during the ­pre-​­season conditioning period. This process
can coincide with times when coaches require players to be available for training,
hence planning the screening/­profiling with coaching staff is important so that it can
take place without the pressure of players having to be available for other activities.
A proper and honest assessment of the time needed for adequate profiling/­screening
should be agreed upon within the medical and science MDT, and presented to team
management, and a timetable agreed.
The epidemiological literature will outline what the most common injuries are
(­Ekstrand et al., 2016; Tabben et al., 2021) whereas other research findings will indi-
cate what susceptibilities might be implicated. As more publications appear, possible
causations as well as treatments change or are refined, so a constant surveillance of
current knowledge is important. The published evidence will guide screening practice,
so that any prevention/­m itigation of injury can be achieved by acting on findings dur-
ing the screening session.
 Injury epidemiology, monitoring, and prevention 201
At the end of the session, all the information gathered should be collated and re-
viewed. For instance, a certain player may be weak or lack flexibility in an area where
they have (­p erhaps) sustained an injury in the past. The issue(­s) can be explained to
the player, and an agreed programme to address weaknesses can be made. A set pe-
riod is given before a reassessment of the issue to review progress, and further action/­
maintenance plan.

Muscle injury
Muscle injuries are common in soccer (Ekstrand et al., 2012), and mostly non-contact
in origin, with the hamstring being the most frequently injured (see Figure 13.1; Ek-
strand et al., 2012)
Muscle injury occurs when the muscle is stretched beyond its capacity to resist the
excessive stretching force applied to it, causing tearing and disruption of the muscle fi-
bres, the connective tissue, and the tendons associated with the muscle. Some tendons
are intramuscular, that is, within the muscle itself (­e.g., in the soleus muscle). When a
muscle injury occurs, the player will often describe hearing or feeling something ‘­go’.
This should not be taken as necessarily indicating a more severe injury, but is an im-
portant issue for the player, as they perceive it as such. The extent of muscle injury, as
one might expect, has a bearing on when a player might RTP. The amount of damage is
graded so that prognostication is more accessible. The first question asked by players,
coaches, and fans alike ­is – how
​­ long will it be before RTP!
There have been many grading systems described and Grassi et al. (2016) gives a com-
prehensive overview of the evolution of the grading systems, and how imaging modal-
ities and research findings (­e.g., of tendon involvement influencing the time of RTP)
have necessitated modifications and additions to each system, leading to the creation
of new categories and gradings. As mentioned, with grading, a more accurate predic-
tion of RTP (­Ardern et al., 2016) can be made, and this is of psychological benefit to the

­Figure 13.1 Hamstring injury.

202 Ian Beasley
athlete and of practical worth to the coaching staff, who may need to plan to recruit
a replacement.
Imaging is undoubtedly useful in the management of muscle injuries. Armed with
the extent of muscle damage, c­ ross-​­referencing this with which grade the injury can be
assigned to help not only to prognosticate RTP but also to guide practitioners in the
rehabilitation process. When treating muscle injuries, the aim is to return the player
to full activity while avoiding a recurrence of the injury. Recurrence is a ­well-​­known
hazard of muscle injury, often taking longer to recover than the initial injury (­Donmez
et al., 2020). As radiological imaging techniques have improved, it is now possible to
grade the extent of a muscle injury using MRI or ultrasonography (­Pollock et al., 2014;
Hamilton et al., 2015; Lee & Healy, 2004). Muscle damage, as with any healing tissue,
results in some scarring. Scar tissue is ­non-​­contractile and is at risk of being torn dur-
ing normal muscle action during the RTP process or when the player has returned to
play. While this is not usually a significant problem, repeated injury at or near the site
of an original injury is worrisome and can interrupt successful RTP.
Myositis ossificans is a ­well-​­known complication of muscle injury, often resulting
from direct trauma to the muscle in a tackle, or with collision with p ­ itch-​­side apparatus.
The trauma prompts the formation of ectopic bone in the muscle. It takes 2­ –​­3 weeks to
establish itself and can take up to a year to resolve spontaneously (­https://­orthobullets.
com/­pathology/­8042/­myositis ossificans). The calcification can be seen on plain radio-
graphs, but often the manual examination findings are more impressive than the x­ -​­ray
appearance. Ultrasound examination is a much more sensitive way to view this injury
and following progress of resolution can be better monitored using this modality, as
well as avoiding repeated radiation exposure (­Lacout et al., 2012).

Treatment
Treatment of muscle injuries is w­ ell-​­established. The acronyms POLICE (­Bleakley
et al., 2012) or PRICE (­Brooks et al., 1981) give a guide to initial/­first aid treatment
regimens (­see ­Table 13.1).

­Table 13.1 The POLICE/­PRICE guidelines to initial/­­fi rst-​­aid treatment

P= Protection from further injury, which usually means withdrawing the player from performing
is standard in all fi
­ rst-​­aid advice.
OL/­R = Optimal Loading, or Rest. This amounts to the same thing. A player can weight bear if
they are not going to injure the part more.
I = Ice, to reduce inflammation and pain.
C = Compression to reduce bleeding at the site of injury.
E = Elevation, to help drain any accumulating inflammatory oedema causing congestion around
the injury that potentially inhibits early local biochemical activity that leads to efficient
healing.
P = Protection from further injury, which usually means withdrawing the player from performing
is standard in all fi
­ rst-​­aid advice.
OL/­R = Optimal Loading, or Rest. This amounts to the same thing. A player can weight bear if
they are not going to injure the part more.
I = Ice, to reduce inflammation and pain.
C = Compression to reduce bleeding at the site of injury.
E = Elevation, to help drain any accumulating inflammatory oedema causing congestion around
the injury that potentially inhibits early local biochemical activity that leads to efficient healing.
 Injury epidemiology, monitoring, and prevention 203
After being withdrawn from the field of play, and first aid treatment administered,
and the diagnosis confirmed by investigation, the next steps in management of the
injury are made by the medical and sports science MDT, and a plan formulated with a
prediction of RTP. Early predictions, as in any branch of medicine, are not definitive.
Communication to team management staff of the possible deviations from a prospec-
tive timeline should be explained so that there are no surprises when things, as is often
the case, do not progress in the desired linear fashion.
The next phase in managing an injured player is where the MDT planning becomes
most important. Physiotherapy treatment in the early stages forms the basis of physi-
cal treatment. To make sure that healing and adapting tissues have the right environ-
ment to optimally recover, performance nutrition is an important tool to use. Early
deployment is essential so that the different phases of inflammation, through to the
healing of an injury are supported by appropriate supplementation of the normal diet.
Psychological support is warranted, as the player will inevitably have concerns
about recovery, any threat an injury might have to their career, and whether an injury
may impact income. Following mood and sleep patterns and addressing any ‘­bumps
in the road’ is important in helping the player cope with the evolution of an injury
towards RTP. As implied above, recovery from injury does not follow straight lines,
and there will be times when the rate of progress is slower than the athlete wishes.
For ­long-​­term injuries, such as anterior cruciate ligament (­ACL) reconstruction or se-
vere fracture, there is evidence that psychological support is important, despite not all
clubs having resources to offer this support (­Gervis et al., 2020). A more thorough un-
derstanding of players’ fears and anxieties is valuable in the holistic/­MDT approach to
care. This is oft best obtained using a psychologist, who may have b ­ etter-​­interviewing
skills and more time to use them. Sharing knowledge obtained can be invaluable when
planning the varying care pathway. Once the player is ‘­off the couch’ the sports science
and fitness coach teams become more heavily involved, the pathway to RTP is usually
clearer, but, of course, beware the ups and downs of rehabilitation.

Joint injury
In soccer, ankle and knee joints are the commonest injury (­­Lopez-​­Valenciano et al.,
2020) with shoulder, elbow, and hand/­wrist more common in goalkeepers (­Ekstrand
et al., 2013). Joint injuries can result in damage that causes problems in later life with
knee and hip osteoarthritis being more common in e­ x-​­players as is the need for arthro-
plasty for these two joints in retired professional population (­Fernandes et al., 2018;
Van den Noort et al., 2021). Each joint is different, but there are some commonalities.
Joints are enclosed in a joint capsule, and mostly with a synovial membrane within the
capsule producing synovial fluid, which helps nourish the joint. Joint surfaces are cov-
ered in hyaline (­articular) cartilage, which is a g­ lass-​­like substance consisting of type II
collagen and chondromucoprotein (­w ww.medcell.med.yale.edu/­h istology/­connective_
tissue_lab/­hyaline_cartilage.php) which when under compression ‘­evens out’ the ef-
fects of pressure by moving water within the substance of the hyaline cartilage away
from the point of pressure. After the pressure is removed during the completion of a
movement, the water returns to the area, which helps prevent wearing at those areas of
the joint surface experiencing most use.
The bones forming the joint are held together by ligaments which attach to the
bones on each side. These stabilising ligaments are usually called collateral ligaments.
204 Ian Beasley
In general, the bigger the joint, the more complex the ligaments. The bones forming
the knee joint, for instance, the biggest joint in the body, must weight bear and the lig-
aments must manage ­multi-​­directional forces. It has collateral ligaments and cruciate
ligaments, as well as some accessory ligaments to ensure that during ambulation, and
sometimes at speed, the knee retains its integrity.
Joint injuries cause inflammation, which is usually associated with joint swelling
due to fluid collection within the joint caused when the synovial membrane o ­ ver-​
­produces ­fluid – ​­this inflammation is its normal response to injury. Bleeding into the
joint (­called a haemarthrosis) caused by tearing of tissues within the joint also causes
swelling. Taking an accurate history from the player about the injury is important.
Immediate (­or within an hour or so) swelling indicates a haemarthrosis and indicates
significant damage to the joint. Quite apart from the injury that has caused bleeding
into the joint, blood in the joint is damaging to the joint surfaces. For this reason, it
may be reasonable to attempt to aspirate the joint to minimise the irritation.
Examination of joints should be approached with a routine in mind that is repro-
ducible. The examiner should have an idea of what normal function is, and if possible,
the contralateral joint should be assessed as a ‘­normal’ control. It is helpful to first
make sure that you, as the examiner, are not going to cause so much discomfort to the
player that they are unable to comply with the examination and are guarding so much
that no useful information can be o ­ btained – ​­despite the accurate history that you will
have already obtained.

Knee injury

Meniscus injuries
There are two menisci (­medial and lateral) in the knee. They are made of fibrocarti-
lage. The lateral is smaller than the medial. They sit on top of the tibia, and act as a
cushion, as well as making the relatively flat top of the tibia a better fit with the more
rounded condyles of the femur. They are susceptible to injury when the femur rotates
on a fixed tibia, for instance, when the foot is planted on the turf (­and stuck because
of boot studs) and cannot rotate. Characteristically, the knee swells within 12 h, often
the player wakes with swelling the next day, describing it as ‘­it looked like a grapefruit’.
There are many types of meniscal injuries, or tears (­see ­Figures 13.2 and 13.3;
Nguyen et al., 2014), and the ongoing management of this injury can depend on the
type of tear. The meniscus has a blood supply, richer in the periphery, which declines
with age. It follows that it may be possible to repair/­suture together a meniscal tear if
it is in a zone where there is a blood supply; named, for obvious reasons, the ‘­red zone’.
Resection of significant amounts of a meniscus, or total meniscectomy results in the
knee becoming more susceptible to degenerative change, and earlier onset of osteoar-
thritis (­see ­Figure 13.4; Ardern, 2013).

Cruciate ligament injuries

There are two cruciate ligaments, anterior and posterior. The ‘­anterior’ and ‘­posterior’
refer to where the respective ligaments are attached to the tibial spine; this the
prominence/­line on the tibial plateau which bisects the medial and lateral parts (­or
condyles) of the tibial plateau. The ACL is injured more often than the posterior
 Injury epidemiology, monitoring, and prevention 205

­Figure 13.2 Meniscal tear.

­Figure 13.3 Meniscal cyst.

cruciate ligament (­PCL), and results in a haemarthrosis (­see F­ igure 13.5). The inci-
dence of A ­ CL-​­related knee injuries has been quoted to be as high as 50% (­Joseph
et al., 2013). The mechanism of injury is by an external tibial rotational force with
knee valgus strain, usually ­non-​­contact, and often when ‘­cutting’. The player often
hears a ‘­pop’ in the knee at the time of injury. An ACL rupture is almost invariably
managed with surgery. There is some research evidence that shows that players can
RTP without surgery (­Ardern, 2013), but rehabilitation without surgical intervention
206 Ian Beasley

­Figure 13.4 Degenerative change after meniscectomy.

­Figure 13.5 ACL rupture, with bone bruising, and medial collateral ligament injury
 Injury epidemiology, monitoring, and prevention 207
from this injury can take 3 months or more, and if rehabilitation fails and surgery is
required, the RTP time is much longer. The longer time span from the advent of the
injury to RTP is undesirable in the professional game, but may be more acceptable in
the recreational player.
ACL injury is often combined with other damage to ­intra-​­articular structures.
O’Donoghue (­1950) described an ‘­u nhappy triad’ of ACL rupture, medial collateral
ligament (­MCL) tear, and medial meniscus disruption (­s ee F ­ igure 13.6). It is essen-
tial that any management considers the condition of the whole joint when planning
treatment. At professional level, 83% return to the same level as prior to injury (­Lai
et al., 2018). Median time to RTP in professional sport is ­6 –​­13 months (­Lai et al.,
2018), but it should be borne in mind that players in this situation have physiotherapy
and rehabilitation daily, something that may not be available to all at the recrea-
tional level.
PCL injuries are uncommon, with an incidence of 0.­65–​­3% of all s­ports-​­related
knee injuries (­Longo et al., 2021) usually caused by a direct blow to the front of the
tibia, and around the tibial tuberosity, on a flexed knee forcing the tibia backwards,
and tearing the PCL (­described as a ‘­dashboard injury’ from the days before seat
belts). Isolated PCL injuries are often managed without surgery, but this injury can
be associated with damage to other stabilising structures at the ­postero-​­lateral corner
(­PLC) of the joint. Proper assessment of the joint needs to be carried out to ascertain
if this is the case. Surgery may be needed with complex injuries of this type, or at least
bracing, depending on the severity. It can be confusing to hear that a player has a
PCL/­PLC injury!

­Figure 13.6 ACL rupture sagittal.

208 Ian Beasley
Medial collateral ligament (­MCL)
The MCL is a large ligament that originates at the superior part of the medial femoral
condyle and extends to a hand’s width below the joint line of the knee to an attachment
on the tibia. It journeys slightly forwards to its attachment, resisting lateral tibial rota-
tion as well as the valgus strain of the knee. Injury to this ligament is usually because
of a forced valgus strain, with external rotation of the tibia often involved. This causes
the ligament to tear and become laxer, and the extent of the laxity directs the grading
of the tear. The injury is graded ­I–​­III, with treatment driven by the grading, although
recently a novel grading has been reported with five grades of tear, with the aim of
refining treatment regimens (­Makhmalbaf et al., 2018). Treatment includes bracing to
prevent extension of the injury and on occasion surgery, but physiotherapy with reha-
bilitation is the mainstay of treatment.

Ankle
The ankle is held together by a complex array of ligaments. The tibia and fibula are
bound together near the joint by strong ligaments at the front and back (­the anterior
and posterior inferior tibiofibular l­igaments – AITFL​­ and PITFL) with the interosseus
membrane in between the two bones, as its name suggests. These three elements are
known as ankle syndesmosis. The MCL of the ankle joint is a strong band of tissue con-
sisting of two layers. The superficial layer consists of the tibionavicular, tibiospring, tibi-
ocalcaneal, and superficial posterior tibiotalar ligaments. The deep layer consists of the
anterior tibiotalar ligament and the deep posterior tibiotalar ligament. The lateral liga-
ment complex comprises three parts; the anterior talofibular ligament (­ATFL), the cal-
caneofibular ligament (­CFL), and the posterior talofibular ligament (­PTFL). The lateral
ligament complex, particularly the ATFL, is the most injured, and the usual mechanism
is a forced inversion of the ankle, often when landing after jumping (­see ­Figure 13.7).
Complete rupture of the ATFL can lead to anteroposterior instability of the ankle,
and place extra strain on the other structures around the ankle, causing recurrent
swelling and p ­ ain – ​­the ‘­chronic ankle’. Rehabilitation is the key to mitigating the ef-
fect of the ATFL deficiency and continued topping up of the rehabilitation process is
­necessary – ​­even when the player has returned to playing and training fully.
The three elements of rehabilitation are stretch, strength, and proprioception. Pro-
prioception is an ability of the tissues around the joint to avoid damage by acting on
a spinal reflex initiated by stretch receptors that are present in all tissues. If it appears
that the joint is in a position where it may be injured, the stretch receptors prompt a
change in body posture to avoid damage. Think of the situation where, on occasion,
you may have tripped and almost injured on your ankle whilst walking along on an
uneven surface, but somehow, and without conscious effort, you manage to ­re-​­gain
balance before falling and injuring yourself. This is a system that is damaged when
the joint itself is damaged, but it is something that can be trained back so that further
harm to the joint is prevented. Any player who has twisted their ankle will be seen on
various pieces of apparatus in the rehabilitation gym trying to maintain balance on
the injured ankle (­see ­Figure 13.8). This encourages the neural pathways to r­ e-​­engage
with the aim of keeping the patient upright, as well as preventing further damage to
the ankle. Occasionally, if an A ­ TFL-​­deficient ankle persists in swelling and with dys-
function, surgical intervention may be necessary to try and stabilise the joint.
 Injury epidemiology, monitoring, and prevention 209

­Figure 13.7 Ankle injury.

­Figure 13.8 Wobble (balance) board to improve proprioception

210 Ian Beasley
‘­High ankle sprains’ is a term used to describe injury to the AITFL, PITFL, and the
interosseus m­ embrane-​­the ankle syndesmosis. The mechanism for this injury is often a
forced external rotation of the joint, often combined with dorsiflexion. The three parts
of the ligament complex tend to get damaged in sequence, AITFL, then interosseus
membrane, and then PITFL. The MCL complex is usually damaged to some extent at
the same time. These injuries are best assessed, after taking a history and examining
the joint, by imaging with MRI scanning. The full extent of the damage can be difficult
to assess clinically, certainly in the acute phase, and usually, management is driven by
MRI appearances. In general, if all three of the syndesmosis elements are markedly
injured, surgery may be opted for; a loose syndesmosis leads to joint instability. Stabi-
lising and immobilising the joint while the ligaments have healed is the aim of surgery.

Tendon injury
Tendons are made of type 1 collagen (­­65–​­80%) and elastin (­­1–​­2%) embedded in a
­proteoglycan-​­water matrix (­Kannus, 2000). The tendon has a microstructure of c­ ross-​
l­ inkage and bundling to form the whole tendon, which is surrounded by a sheath called
the paratenon. Tendons are structures that attach a muscle to a bone. When a muscle
contracts, it pulls on the bone via the tendon and the limb/­part concerned moves.
Tendon injuries are not uncommon in soccer with varying degrees of damage from
strains to tears, to complete rupture, and often in conjunction with muscle injury, for
instance, the intramuscular tendon of the rectus femoris. Some tendons, such as the
Achilles and patellar tendons are prone to overuse causing degenerative change within
the tendon substance.
The issue with tendon disruption of any kind is that blood supply is low and so
healing is slow. Even though not commonplace, tendon ruptures, such as those of the
Achilles (­Tarantino et al., 2020), require surgical intervention, at least in professional
and academy players. Achilles tendon rupture in the recreational player is often treated
conservatively with the ankle in equinus (­toes pointing ­down-​­full plantar flexion) in-
itially, and gradually reducing back to a normal position (­Holm et al., 2015). This is
achieved using a heel wedge (­or wedges) in a boot plastic boot. The size or number of
wedges is gradually reduced until the neutral position is reached.
Tendinopathy is an overuse condition of a tendon, where, in response to overload,
the tendon tries to adapt, and produces more tenocytes and supportive matrix to cope
with the excess load (Sharma & Maffulli, 2006). This results in a tendon less able to
withstand this extra burden, which leads to pain and dysfunction. In soccer, Achilles
and patellar tendon (­see F ­ igure 13.9) involvement are the most common, but goalkeep-
ers may suffer the same issues with rotator cuff tendons of the shoulder, and wrist
extensor or flexor tendons at the elbow.
Although MRI imaging will help exclude other diagnoses in the region of pain (­e.g.,
­co-​­existing fat pad syndrome or bursitis in the case of patellar tendinopathy), ultra-
sound is the investigation of choice for tendons, and the feature in tendinopathy that
is best seen with ultrasound is neovascularisation. This is visualised with the use of
Doppler software and can show dramatic changes within the tendon. The neovascular
changes represent the endeavours of the tendon to heal, with the new vessels growing
in to aid the process (­see ­Figure 13.10).
Ultrasound tissue characterisation (­UTC) scanning is another technique using ul-
trasound, but shows the damaged/­degenerative areas of the tendon involved in more
 Injury epidemiology, monitoring, and prevention 211

­Figure 13.9 Patellar tendinopathy.

­Figure 13.10 Patellar tendinopathy with Doppler© 2022 Christoph Spang, Lorenzo Masci
and Håkan Alfredson. https://­w ww.mdpi.com/­­1648-​­9144/­58/­5/­601/­htm
212 Ian Beasley
detail than the standard ‘­­grey-​­scale’ ultrasound used regularly in clinical practice
(­Winter Bee et al., 2017). Following progress using UTC gives a better idea of the res-
toration of normalised anatomy, helping to guide the rehabilitation process towards
normal function.
Treatment revolves around physiotherapy. When seeing patients in the clinic, they
will often give a long history with periods of enforced rest due to pain, thinking that rest
will help heal the issue. This is one of the situations where (­graded) exercise is curative,
but rest is not. Disused tendons show similar histological changes as overuse tendinop-
athic ones (­Cook & Purdam, 2018). The physiotherapist will initiate the graded exercise
programme, often starting with isometric ‘­holds’, where the player resists a weight, but
holds (­in the case of Achilles tendinopathy) the ankle joint in neutral, with the muscle
not lengthening or shortening. Weight and time of holding are incremental and done so
whilst monitoring symptoms and reaction to each session. The exercise that most will
know is then brought in, which is ‘­eccentric exercises’. This produces load for the ten-
don, which hopefully will promote healing (­Rees et al., 2008; Grigg et al., 2009). Eccen-
tric exercise is a muscle contraction while the muscle/­tendon unit l­engthens – ​­think of
putting something heavy down on the ground after lifting. Lengthening your muscles
to do this equates to an eccentric contraction. Other treatments involve e­ xtra-​­corporeal
shockwave therapy (­Abdelkader et al., 2021), and injection therapy using differing
chemical (­e.g., corticosteroid and hyaluronic acid) and biochemical (­e.g., ­platelet-​­rich
plasma and other orthobiologics) agents (­Madhi et al., 2020; Jiang et al., 2020; Nuhm-
ani, 2020; ­Lopez-​­Royo et al., 2020; Saif Azmy et al., 2021).

Bone injury
Bone injury falls into two categories, acute and overuse. Professional teams can expect
one to two fractures per season (­Larsson et al., 2016). Most are traumatic in nature
due to contact with another player or an object on the field (­e.g., goal post) or near
the field (­e.g., advertising hoardings), but can be due to falling or landing awkwardly
when jumping. The commonest bones injured are lower limb in outfield players and
upper limb in goalkeepers (­study of Qatar Super League players: personal communi-
cation). Bones bleed when fractured, and localised swelling is an early indication that
the injury may be a fracture. The investigation of choice if a fracture is suspected is
plain ­x-​­ray, although often an MRI is ordered as the diagnosis is not clear from ei-
ther mechanism or history and examination. If a fracture is reported then appropriate
further imaging may be required, which may be plain ­x-​­ray or CT scan. As with any
other type of injury, once a definitive diagnosis and grading/­extent of the fracture (­e.g.,
displacement/­comminuted or not) is made, further management can be planned.
The reported time loss for this type of injury depends, as one might expect, on the
bone injured, and the type of fracture, open or closed (­an open fracture is one where
the skin is breached), comminuted or not (­a comminuted fracture is one where the
bone is in many pieces), or displaced or not. All these factors are considered when
planning further management and whether the player may need surgery. Decisions
should be made in a shared and m ­ ulti-​­disciplinary environment. These injuries can be
­career-​­threatening, and all those concerned in player care, which includes coaching
staff, should be involved in the process and be aware of the issues. In general, although
the absence after fracture is quoted as 32 days (­median), the range is much greater,
between 1 and 278 days (­Larsson et al., 2016).
 Injury epidemiology, monitoring, and prevention 213

­Figure 13.11 Jones fracture.

Overuse bony injuries are stress fractures and occur at approximately ­one-​­tenth
the incidence of traumatic fractures, although appear to take longer before the player
returns to action (­Larsson et al., 2016). The initial investigation of choice once again
will be x­ -​­ray but will often not yield a diagnosis. MRI will demonstrate the subtle signs
of a stress injury or stress fracture to bone and is quoted as the ‘­gold standard’ in diag-
nosis (­Saunier & Chapurlat, 2018). Stress injuries and fractures to bone have a grading
system which helps to prognosticate when managing this type of injury (­Fredericson
et al., 1995; Kijowski et al., 2012).
Conservative treatment is the cornerstone of fracture management of any kind, with
immobilisation in a cast or other device mandatory while the bones heal. However,
there are instances where surgical intervention is required, and fixation of the bones
in a position where healing can take place. Surgical intervention can be necessary in
either traumatic fractures (­e.g., tibia and fibula fracture) or overuse fractures (­e.g.,
navicular stress fracture). For most stress injuries, however, a period of relative rest is
often enough to allow the bone to heal without intervention. This can entail a period
of n­ on-​­weight bearing (­e.g., pelvic stress fracture) or immobilisation (­e.g., metatarsal
stress fracture).
One w­ ell-​­known type of stress fracture is that of the fifth metatarsal, the eponymous
‘­Jones fracture’. After some h ­ igh-​­profile players sustained this injury, it gained some
renown (figure 13.11).
At the time, there were some changes in boot design that seemed to p ­ re-​­dispose to
sustaining this injury (­K ijowski et al., 2012). Biomechanics, boot design, and nutri-
tion status must all be considered when planning a prevention, or mitigation strategy.
214 Ian Beasley
Professional players have highly lucrative contracts with boot companies, and it is
sometimes necessary to liaise with these companies to make sure there the player will
not fall foul of a new boot design which may not suit their biomechanical makeup.

Women’s soccer
The injuries are the same, but female soccer warrants a separate section because of
a slightly different pattern of injury (­Larruskain. et al., 2018), and an explanation
regarding some of the reasons why, and the prevention strategies that might be em-
ployed. It is ­well-​­documented now that differing levels of oestrogen during the men-
strual cycle influence injury incidence (­­Chidi-​­Ogbolu et al., 2019; Martin et al., 2021).
It is w­ ell-​­established that ACL rupture is more common in women (Larruskain. et al.,
2018), and in part this is due to the ACL becoming laxer, with anteroposterior trans-
lation increasing incrementally until the ­pre-​­ovulatory phase (­Belanger et al., 2013;
Shultz et al., 2005), making the ligament more prone to stretch and rupture. Another
factor in the increased incidence of ACL rupture in women is that an increase in hip
varus and knee valgus when cutting and landing exposes the ligament to increased
stress. Preventative measures with ­re-​­training of core neuromechanics have reduced
the incidence (­Mandelbaum et al., 2005; Steffen et al 2013).
Oestrogen inhibits an enzyme called lysyl oxidase, which facilitates collagen ­cross-​
l­ inkages which normally help stiffen a ligament. Inhibition of this enzyme, especially
in the p ­ re-​­ovulatory phase of the menstrual cycle, when oestrogen levels approach
their zenith, reduces the stiffness and resilience of tendons and ligaments (­Cassandra
et al., 2015). There has been some research showing that women using the oral contra-
ceptive were less likely to undergo ACL surgery (­­Rahr-​­Wagner et al., 2014), which may
mean conferring protection, although the research was undertaken surveying a group
of women who underwent surgery, so it is not prospective in nature.
In a study carried out in track and field athletics, men were found to have twice the
risk of muscle injuries (­Edouard et al., 2016). This may be due to tendon compliance
being higher (­i.e., less stiff) due to the limitations of ­cross-​­linkage as described above.
Achilles rupture is less common in ­pre-​­menopausal women, compared with men and
their ­post-​­menopausal counterparts. ­Post-​­menopausal women and men share similar
incidences. Muscle and tendon injuries occur twice as often in the days before ovula-
tion (­Martin et al., 2021).
Although treatments for injuries have no gender differences, the risk of injury
seems to differ with the phase of the menstrual cycle. There are some individual and
genetic differences in the way tissues respond to their hormonal milieu but having
knowledge of the stage each player is at may be able to help plan training sessions, and
guide more closely rehabilitation sessions (­e.g., the first twist and turn session with
the ball for, say, an ankle sprain may be best carried out ­post-​­ovulation). Although
it may seem intrusive, there may be some merit in tracking individual risk profiles to
avoid injury.

­Age-​­specific soccer
The advent of soccer as a route to general fitness and better health outcomes for women
(­K rustrup et al., 2018) and men (­Bangsbo et al., 2015), with reviews hailing recrea-
tional soccer at any age to be ‘­medicine against n
­ on-​­communicable disease’ (­Sarmento
 Injury epidemiology, monitoring, and prevention 215
et al., 2020), has meant greater involvement in soccer in advancing years, with walking
soccer now ­well-​­established.
The physical sequelae from playing soccer are poorly understood in the recrea-
tional arena, but are becoming more appreciated in the ­ex-​­professional. In males,
­ex-​­players experience twice as much knee pain and degenerative changes on ­x-​­ray
as the general population. They also experience knee symptoms ­10–​­15 years before
those in the general population and require three times as many knee replacements
(­Fernandes et al., 2018). Hip arthritis is of a similar incidence range as in the gen-
eral population (­0.­3 –​­8% general population vs. ­2 –​­8.3% in e­ x-​­players), but it has been
noted that quality of life is affected more in e­ x-​­players with hip degenerative disease
(­Van den Noort et al., 2021).
Runacres et al. (­2021) reviewed over 38,000 articles on longevity and concluded that
­m ixed-​­event athletes such as soccer players lived longer, by virtue of a reduction in car-
diovascular disease and cancer. Mental health has been a focus in e­ x-​­soccer players,
and Van Ramele (­2017) noted that the incidence of common mental health disorders
was high when compared with the general population. Overall, it appears that soccer
is an appropriate source of exercise throughout life and fulfils WHO recommendations
(­http://­w ww.who.int/­dietphysicalactivity/­factsheet).

Concussion
A concussion is an injury to the brain, which can occur because of a blow to the head,
or trauma to any part of the body that might cause a perturbing force to be transmit-
ted to the brain within the skull. Most s­ ports-​­related concussions resolve within ­7–​­10
days, but recovery can take longer. On occasion, the trauma is severe enough to cause
bleeding around the brain or its coverings (­called the meninges), causing an increase
in pressure within the skull. This constitutes a medical emergency and may require
surgical intervention to remove any collection of blood.
The brain sits inside the skull, and when injured, cannot be directly examined in
the same way joints and soft tissue can. The clinician assesses neurological (­i.e., brain)
function, and this gives them an indirect view of how the brain is doing. An Interna-
tional Conference on Concussion in Sport has been held since 2001, the first being in
Vienna, with ­multi-​­sport collaboration producing guidelines on ­sports-​­related con-
cussion management from injury to RTP (­Aubry et al., 2002). Since then, similar con-
ferences have been held with the latest being in Berlin in 2016 (­McCrory et al., 2017).
The consensus of concussion recognition and management from these conferences
has become the cornerstone of concussion guidelines issued by federations and inter-
national bodies.
­Pitch-​­side management of concussion is based around the mantra ‘­if in doubt, sit
them out’. Clinicians entering the field of play for a suspected concussion will assess
the various brain/­neurological functions that will demonstrate whether there has been
a concussion and should remove the player if there is any doubt about their ability to
continue to take part in the match/­session. The player will not be allowed to take part
in any activity from that point, until cleared to do so by a clinician.
Knowing the player and understanding the player’s usual demeanour are important
in this situation. The effects of concussion can cause mood changes, and these can be
difficult to pick up unless the clinician knows what a player is usually like. An under-
standing of the mechanism of the injury will be helpful and may be available from a
216 Ian Beasley
­Table 13.2 Summary of information on ­CRT-​­5 form

Step ­1-​­Red flags: These are indications that the injury is a serious one, and the player needs
urgent transfer to hospital
Step ­2-​­Observable signs (­e.g., Gait disturbance, slow to get up)
Step ­3-​­Symptoms (­e.g., What is the player feeling? Dazed? Headache?)
Step ­4 -​­Memory assessment (­e.g., Maddocks questions; Maddocks et al., 1995)
Step ­1-​­Red flags: These are indications that the injury is a serious one, and the player needs
urgent transfer to hospital
Step ­2-​­Observable signs: e.g. Gait disturbance, slow to get up
Step ­3-​­Symptoms: e.g., What is the player feeling? Dazed? Headache?
Step ­4 -​­Memory assessment: e.g., Maddocks questions (­Maddocks et al., 1995)

player or the referee (­e.g., ‘­he was knocked out’ and ‘­he got a real bang on his head’). A
reliable history, even though s­ econd-​­hand, will help the clinician come to a decision.
A systematic approach to the examination is always advisable, and aide memoires are
helpful here. The Concussion Recognition Tool 5 (­­CRT-​­5) (­BJSM, 2017) (­­Table 13.2)
should be in every ‘­­run-​­on’ bag to aid assessment.
Once the player has been removed from the field of play, they should be taken to a
quiet location to undergo a more thorough examination which in the acute stage is
done by using the SCAT5 (­Sports Concussion Assessment Tool 5) which covers similar
areas to the ­CRT-​­5, but in more detail. Players should undergo a SCAT5 examination
at the beginning of the season as a baseline, so comparisons can be made.
If a concussion is diagnosed, the player must enter a graduated RTP process.
This begins with a period of rest, followed by a graduated exercise programme un-
til back in full training and eligible for selection. The English Football Association
(­http://­uptonjfc.org/­­w p- ​­c ontent/­uploads/­2021/­05/­­the-­​­­fa- ­​­­c oncussion-­​­­g uidelines-­​­­2019-­​
changes-​­
­­ highlighed.pdf) has published guidelines which include an RTP protocol,
which differs for junior and senior players, as junior players are more susceptible to
the effects of concussion, as are women (­Gomez et al., 2013). The player must be signed
off as fit to RTP by the team physician, or a physician experienced in the management
of sports concussion. Although RTP decisions can be made purely using serial SCAT 5
examinations until there is a return to baseline, there are a­ udio-​­visual tools that allow
assessment of players’ neurocognitive functions that are used in professional soccer
(­Schatz et al., 2006). These can be helpful if there are language barriers or observer
bias.
If a player suffers more than one concussion in a season, they should be reviewed in
a specialist ­multi-​­disciplinary clinic, with a comprehensive examination to include ves-
tibular function as well as imaging and neurological assessment. The player with mul-
tiple concussions should be counselled as to the possible ­long-​­term effects of (­repeated)
brain injury. There are many cases of e­ x-​­soccer players suffering from dementia that
have been reported in the national press. Ling et al. (­2017) described the ­post-​­mortem
appearances of e­ x-​­professional soccer players who had been suffering from dementia.
They found a greater incidence of chronic traumatic encephalopathy in t­wo-​­thirds,
where the normal amount would have been o ­ ne-​­eighth approximately. Their conclu-
sion was that this difference was due to heading the ball. This study comprised of low
numbers, however. A large study in Scotland found that there was a ­three-​­fold increase
in death from neurodegenerative diseases in ­ex-​­soccer players, compared with normal,
matched, and controls.
 Injury epidemiology, monitoring, and prevention 217

­Figure 13.12 Pocket Concussion recognition tool-5.

The debate rages on whether heading the ball in soccer is too much of a risk, with
the accumulative effects of ­sub-​­concussive events leading to damage to the brain, re-
sulting eventually in an increased incidence of neurological disease. Lipton et al. (­2013)
counted headers in a group of amateur soccer players and followed them with MRI
scanning and memory testing. They demonstrated that there was white matter damage
and neurocognitive effects for those having headed the ball more than 1,800 times in a
218 Ian Beasley
year. There is, however, no doubt that not every soccer player suffers in this way, and
there seems to be a genetic susceptibility to concussion (­Antrobus et al., 2021). Until
there is a clearer understanding of the risks, and who might be more prone to the ­long-​
­lasting effects of a career in soccer, it would seem prudent to give advice based on our
current level of knowledge.

Future directions and conclusions

The increase in sports science input into soccer is remarkable, and the advent of
GPS has meant that it is now possible to monitor physical load much more accu-
rately and predict when a player might be reaching a point where they are liable
to get injured. It seems apparent that undertrained players are more likely to get
injured, they reach a breaking point in matches much easier. It is also apparent
that overtrained players get injured more often. This group is ‘­nearer the edge’. It
follows that there is a ‘­sweet spot’, which is individual of course. This is the classic
‘­­J-​­shaped curve of risk’ (­G abbett, 2016). GPS helps science and medical staff under-
stand where each player is on this continuum, and its refined use will aid injury pre-
vention in the future, enabling coaches to train players more efficiently and safely.
At present, soccer players are not counselled regarding the possible effects of a
career playing the game professionally. Degenerative joint disease (­Fernandes et al.,
2018; Van den Noort et al., 2021) is more common, with symptoms earlier in life than
normal, and there is the spectre of repeated brain trauma leading to dementia or other
neurodegenerative diseases. While the players performing in the top teams in their
respective countries may enjoy a good standard of living, most players are not in this
category and have less choice when it comes to weighing the pros and cons of giv-
ing up their livelihood without the certain knowledge that playing soccer might be
detrimental to their health later in life. However, we are not at a point where we can
easily predict and advise prospective players. Gouttebarge et al. (­2019) have begun a
prospective study looking at all these aspects so that we can advise players, as well as
governing bodies and national and international federations on how we might support
players in retirement. We have a duty of care to players who have entertained us all
(­Carmody et al., 2019).

References
Abdelkader NA, Helmy MNK, Fayaz NA, Saweeres ESB. S ­ hort-​­and ­i ntermediate-​­term results
of extracorporeal shockwave therapy for noninsertional achilles tendinopathy. Foot Ankle
Int. 2021;42(­6):­788–​­797.
Antrobus MR, Brazier J, Stebbings GK, Day SH, Heffernan SM, Kilduff LP, Erskine RM,
Williams AG. Genetic factors that could affect concussion risk in elite rugby. Sports (­B asel).
2021 Jan 22;9(­2):19.
Ardern C. Reconstruction surgery is not always necessary for active young people who rupture
their anterior cruciate ligament. J Physiother. 2013 Sep;59(­3):209.
Ardern CL, Glasgow P, Schneiders A, et al. Consensus statement on return to sport from the
first world congress in sports physical therapy, Bern. Br J Sports Med. 2016;50:­853–​­864.
Aubry M, Cantu R, Dvorak J, et al. Summary and agreement statement of the first interna-
tional conference on concussion in Sport, Vienna 2001. Br J Sports Med. 2002;36:­6 –​­7.
Bahr R. Why screening tests to predict injury do not ­work—​­and probably never will …: a crit-
ical review. Br J Sports Med. 2016;50:­776–​­780.
 Injury epidemiology, monitoring, and prevention 219
Bangsbo J, Hansen PR, Dvorak J, et al. Recreational football for disease prevention and ­treatment
in untrained men: a narrative review examining cardiovascular health, lipid profile, body com-
position, muscle strength and functional capacity. Br J Sports Med. 2015;49:­568–​­576.
Belanger L, Burt D, Callaghan J, Clifton S, Gleberzon BJ. Anterior cruciate ligament laxity
related to the menstrual cycle: an updated systematic review of the literature. J Can Chiropr
Assoc. 2013;57(­1):76.
Bentley JA, Ramanathan AK, Arnold GP, Wang W, Abboud RJ. Harmful cleats of football
boots: a biomechanical evaluation. Foot Ankle Surg. 2011 Sep;17(­3):­140–​­144.
Bleakley CM, Glasgow P, MacAuley DC. PRICE needs updating, should we call the POLICE?
Br J Sports Med. 2012;46:­220–​­221.
Boles, Andrew & Potts, Alex & Hodgson, Lisa. The functional movement screening tool does
not predict injury in football. Progr Orthop Sci. 2015;1:1.
Brooks SC, Potter BT, Rainey JB. Treatment for partial tears of the lateral ligament of the an-
kle: a prospective trial. Br Med J (­Clin Res Ed). 1981;21282(­6264):606.
Carmody S, Jones C, Malhotra A, et al. Put out to pasture: what is our duty of care to the re-
tiring professional footballer? Promoting the concept of the ‘­exit health examination’ (­EHE).
Br J Sports Med. 2019;53:­788–​­789.
Cassandra A. Lee, Ann L ­ ee-​­Barthel, Louise Marquino, Natalie Sandoval, George R. Mar-
cotte, Keith Baar. Estrogen inhibits lysyl oxidase and decreases mechanical function in engi-
neered ligaments. J Appl Physiol. 2015 March;118:­1250–​­1257.
­Chidi-​­Ogbolu Nkechinyere, Baar Keith. Effect of estrogen on musculoskeletal performance
and injury. Risk Front Physiol. 2019; 9:1834.
Cook JL, Purdam CR. Is tendon pathology a continuum? A pathology model to explain the
clinical presentation of ­load-​­induced tendinopathy. Br J Sports Med. 2018;43:­409–​­416.
Dönmez G, Kudaş S, Yörübulut M, Yıldırım M, Babayeva N, Torgutalp SS. Evaluation of mus-
cle injuries in professional football players: does coach replacement affect the injury rate?
Clin J Sport Med. 2020 Sep;30(­5):­478– ​­483.
Edouard P, Branco P, Alonso J. Muscle injury is the principal injury type and hamstring mus-
cle injury is the first injury diagnosis during ­top-​­level international athletics championships
between 2007 and 2015. Br J Sports Med. 2016;50:­619–​­630.
Ekstrand J. Keeping your top players on the pitch: the key to football medicine at a professional
level. Br J Sports Med. 2013;47:­723–​­724.
Ekstrand J, Hägglund M, Törnqvist H, et al. Upper extremity injuries in male elite football
players. Knee Surg Sports Traumatol Arthrosc. 2013;21:­1626–​­1632.
Ekstrand J, Hägglund M, Waldén M. Epidemiology of muscle injuries in professional football
(­soccer). Am J Sports Med. 2012;39(­6):­1226–​­1232
Ekstrand J, Krutsch W, Spreco A, et al. Time before return to play for the most common in-
juries in professional football: a ­16-​­year ­follow-​­up of the UEFA elite club injury study. Br J
Sports Med. 2020;54:­421–​­426.
Ekstrand J, Waldén M, Hägglund M. Hamstring injuries have increased by 4% annually in
men’s professional football, since 2001: a ­13-​­year longitudinal analysis of the UEFA elite club
injury study. Br J Sports Med. 2016;50:­731-​­737.
Fernandes GS, et al. Prevalence of knee pain, radiographic osteoarthritis and arthroplasty
in retired professional footballers compared with men in the general population: a ­cross-​
­sectional study. Br J Sports Med. 2018;52:­678–​­683.
Fredericson M, Bergman AG, Hoffman KL, Dillingham MS. Tibial stress reaction in runners.
Correlation of clinical symptoms and scintigraphy with a new magnetic resonance imaging
grading system. Am J Sports Med. 1995;23(­4):­472–​­81.
Gabbett TJ. The ­training—​­injury prevention paradox: should athletes be training smarter and
harder? Br J Sports Med. 2016;50:­273–​­280.
Gervis M, Helen Pickford, Thomas Hau, Meghan Fruth. A review of the psychological support
mechanisms available for l­ong-​­term injured footballers in the UK throughout their rehabili-
tation. Sci Med Footb. 2020;4(­1):­22–​­29.
220 Ian Beasley
Gómez JE, Hergenroeder AC, et al. New guidelines for management of concussion in sport:
special concern for youth. J Adol Health. 2013;53(­3):­311–​­313.
Gouttebarge V, et al Monitoring the health of transitioning professional footballers: proto-
col of an observational prospective cohort study BMJ Open Sport & Exercise Medicine
2019;5:e000680. doi: 10.1136/bmjsem-2019-000680
Grassi A, Quaglia A, Canata GL, Zaffagnini S. An update on the grading of muscle injuries: a
narrative review from clinical to comprehensive systems. Joints. 2016;4(­1):­39–​­46.
Grigg NL, Wearing SC, Smeathers JE. Eccentric calf muscle exercise produces a greater
acute reduction in Achilles tendon thickness than concentric exercise. Br J Sports Med.
2009;43:­280–​­283.
Hamilton B, Valle X, Rodas G, et al. Classification and grading of muscle injuries: a narrative
review. Br J Sports Med. 2015;49:306.
Holm C, Kjaer M, Eliasson P. Treatment of achilles tendon ruptures. Scand J Med Sci Sports.
2015;25:­e1– ​­e10. https://­w ww.orthobullets.com/­pathology/­8042/­­myositis-​­ossificans
Jiang G, Wu Y, Meng J, et al. Comparison of ­leukocyte-​­rich ­platelet-​­rich plasma and ­leukocyte-​
­poor p
­ latelet-​­rich plasma on achilles tendinopathy at an early stage in a rabbit model. Am J
Sports Med. 2020;48(­5):­1189–​­1199.
Joseph AM, Collins CL, Henke NM, Yard EE, Fields SK, Comstock RD. A multisport epide-
miologic comparison of anterior cruciate ligament injuries in high school athletics. J Athl
Train. 2013;48(­6):­810–​­817. doi:10.4085/­­1062–­​­­6050-​­48.6.03
Kannus, P. Structure of tendon and connective tissue. Scan J Med Sci Sports. 2000
Dec;10(­6):­312–​­320.
Kijowski R, Choi J, Shinki K, Del Rio AM, De Smet A. Validation of MRI classification sys-
tem for tibial stress injuries. AJR Am J Roentgenol. 2012;198(­4):­878–​­884.
Krustrup P, Helge EW, Hansen PR, et al. Effects of recreational football on women’s fitness and
health: adaptations and mechanisms. Eur J Appl Physiol. 2018;118:­11–​­32.
Lacout Alexis, et al. Myositis ossificans imaging: keys to successful diagnosis. Ind J Radiol
Imag. 2012;22(­1):­35–​­39.
Lai CCH, Ardern CL, Feller JA, et al. E ­ ighty-​­three per cent of elite athletes return to preinjury
sport after anterior cruciate ligament reconstruction: a systematic review with ­meta-​­analysis
of return to sport rates, graft rupture rates and performance outcomes. Br J Sports Med.
2018;52:­128–​­138.
Larruskian J, Lekue JA, Diaz N, Odriozola A, Gil SM. A comparison of injuries in elite
male and female football players: a fi ­ ve-​­season prospective study. Scand J Med Sci Sports.
2018;28:­237–​­245.
Larsson D, Ekstrand J, Karlsson MK. Fracture epidemiology in male elite football players
from 2001 to 2013: how long will this fracture keep me out?. Br J Sports Med. 2016;50:­759–​­763.
Lee JC, Healy J. Sonography of lower limb muscle injury. Am J Roentgenol. 2004;182(­2):­341–​­351.
Ling H, et al. Mixed pathologies including chronic traumatic encephalopathy account for de-
mentia in retired association football (­soccer) players. Acta Neuropathol. 2017;133:­337–​­352.
Lipton ML, Kim N, Zimmerman ME, Kim M, Stewart WF, Branch CA, Lipton RB. Soccer
heading is associated with white matter microstructural and cognitive abnormalities. Radi-
ology. 2013 Sep;268(3):850-7.
Longo UG, Viganò M, Candela V, de Girolamo L, Cella E, Thiebat G, Salvatore G, Ciccozzi
M, Denaro V. Epidemiology of posterior cruciate ligament reconstructions in Italy: a 1­ 5-​­year
study. J Clin Med. 2021;10(­3):499.
López-Royo MP, Ortiz-Lucas M, Gómez-Trullén EM, Herrero P. The Effectiveness of Mini-
mally Invasive Techniques in the Treatment of Patellar Tendinopathy: A Systematic Review
and Meta-Analysis of Randomized Controlled Trials. Evid Based Complement Alternat
Med. 2020 Sep 5;2020
­López-​­Valenciano A, ­Ruiz-​­Pérez I, ­Garcia-​­Gómez A, et al. Epidemiology of injuries in pro-
fessional football: a systematic review and ­meta-​­analysis. Br J Sports Med. 2020;54:­711–​­771.
 Injury epidemiology, monitoring, and prevention 221
Lubberts B, D’Hooghe P, Bengtsson H, et al. Epidemiology and return to play following iso-
lated syndesmotic injuries of the ankle: a prospective cohort study of 3677 male professional
footballers in the UEFA elite club injury study. Br J Sports Med. 2019;53:­959–​­964.
Maddocks DL, Dicker GD, Saling MM. The assessment of orientation following concussion in
athletes. Clin J Sport Med. 1995;5(­1):­32–​­35.
Madhi I, et al. The use of PRP in treatment of achilles tendinopathy: a systematic review of
literature. Study design: systematic review of literature. Ann Med Surg. 2020;55:­320–​­326.
Makhmalbaf H, Shahpari O, et al. medial collateral ligament injury; a new classification based
on MRI and clinical findings: a guide for patient selection and early surgical intervention.
Arch Bone Jt Surg. 2018;6(­1):­3 –​­7.
Malhotra A, Sharma S, et al. Hypertrophic cardiomyopathy in athletes. Eur Cardiol.
2017;12(­2):­80–​­82.
Mandelbaum BR, Silvers HJ, Watanabe DS, et al. Effectiveness of a neuromuscular and pro-
prioceptive training program in preventing anterior cruciate ligament injuries in female ath-
letes: ­2-​­year ­follow-​­up. Am J Sports Med. 2005;33(­7):­1003–​­1010.
Martin Dan, Timmins Kate, Cowie Charlotte, Alty Jon, Mehta Ritan, Tang Alicia, Varley Ian.
Injury incidence across the menstrual cycle in international footballers. Front Sports Act Liv.
2021;3:17.
McCrory P, Meeuwisse WH, Dvořák J, et al. 5th International conference on concussion in
sport (­Berlin). Br J Sports Med. 2017;51:837.
Mosler AB, Weir A, Eirale C, et al. Epidemiology of time loss groin injuries in a men’s pro-
fessional football league: a ­2-​­year prospective study of 17 clubs and 606 players. Br J Sports
Med. 2018;52:­292–​­297.
Nguyen JC, Arthur A De Smet, Ben K Graf, Humberto G Rosas. MR ­i maging–​­based diagnosis
and classification of meniscal tears. Radio Graph. 2014;34(­4):­981–​­999.
Nuhmani S. Injection therapies for patellar tendinopathy. Phys Sportsmed. 2020;48(­2):­125–​­130.
O’Donoghue D. Surgical treatment of fresh injuries to the major ligaments of the knee. J Bone
Joint Surg Am. 1950;32(­A4):­721–​­738.
Paccy V, Nicholson LL, Adams RD, Munn J, Munns CF. Generalized joint hypermobility and
risk of lower limb joint injury during sport: a systematic review with ­meta-​­analysis. Am J
Sports Med. 2010;38(­7):­1487–​­1497.
Pollock N, James SLJ, Lee JC, et al. British athletics muscle injury classification: a new grading
system. Br J Sports Med. 2014;48:­1347–​­1351.
­Rahr-​­Wagner L, Thillemann TM, Mehnert F, Pedersen AB, Lind M. Is the use of oral con-
traceptives associated with operatively treated anterior cruciate ligament injury?: a ­case-​
­control study from the Danish knee ligament reconstruction registry. Am J Sports Med.
2014;42(­12):­2897–​­2905.
Rees JD, Lichtwark GA, Wolman RL, Wilson AM. The mechanism for efficacy of eccen-
tric loading in achilles tendon injury; an in vivo study in humans. Rheumatology. 2008
Oct;47(­10):­1493–​­1497.
Runacres A, Mackintosh KA, McNarry MA. Health consequences of an elite sporting career:
­long-​­term detriment or l­ong-​­term gain? a m ­ eta-​­analysis of 165,000 former athletes. Sports
Med. 2021 Feb;51(­2):­289–​­301.
Saif Azmy M, Ibtesam K Ali, Ahmed R Radwan, Mohammed Ali Ismail. Efficacy of hyalu-
ronic acid injections versus steroid injections on painful tendinopathies. Egyptian J Hosp
Med. 2021 Autumn;85(­2):3551–​­3556.
Sarmento H, Manuel Clemente F, Marques A, Milanovic Z, David Harper L, Figueiredo A.
Recreational football is medicine against n ­ on-​­communicable diseases: a systematic review.
Scand J Med Sci Sports. 2020;30:­618–​­637.
Saunier J, Roland Chapurlat R. Stress fracture in athletes. Joint Bone Spine. 2018;85(­3):­307–​­310.
Schatz P, et al. Sensitivity and specificity of the impact test battery for concussion in athletes.
Arch Clin Neuropsychol. 2006 Jan;21(­1):­91–​­99.
222 Ian Beasley
Sharma P, Nicola Maffulli. Understanding and managing achilles tendinopathy. Br J Hosp
Med. 2006;67(­2):­64–​­67.
Shultz SJ, Sander TC, Kirk SE, Perrin DH. Sex differences in knee joint laxity change across
the female menstrual cycle. J Sports Med Phys Fitness. 2005 Dec;45(­4):­594–​­603.
Steffen K, Emery CA, Romiti M, et al. High adherence to a neuromuscular injury prevention
programme (­FIFA 11+) improves functional balance and reduces injury risk in Canadian
youth female football players: a cluster randomised trial. Br J Sports Med. 2013;47:­794–​­802.
Tabben M, Eirale C, Singh G, et al. Injury and illness epidemiology in professional Asian foot-
ball: lower general incidence and burden but higher ACL and hamstring injury burden com-
pared with Europe. Br J Sports Med. 2021 Jan; Published Online First.
Tarantino D, Palermi S, Sirico F, Corrado B. Achilles tendon rupture: mechanisms of injury,
principles of rehabilitation and return to play. J Funct Morphol Kinesiol. 2020;5(­4):95.
Van den Noort D, et al. Clinical hip osteoarthritis in current and former professional football-
ers and its effect on hip function and quality of life. J Sports Science Med. 2021;20:­284–​­290.
Van Ramele S, et al. Mental health in retired professional football players: ­12-​­month incidence,
adverse life events and support. Psychol Sport Exer. 2017 Jan;28:­85–​­90.
Wilson JMG, Jungner G. Principles and practice of screening for disease. Geneva: WHO; 1968.
Winter Bee W, Ubhi J, Kumar B. Subcategories of tendinopathy using ultrasound tissue char-
acterization (­utc): dorsal ­m id-​­portion achilles tendinopathy is more severe than ventral achil-
les tendinopathy. Br J Sports Med. 2017 May;Published Online First.
14 Infectious diseases
Monica Duarte Muñoz and Tim Meyer

Introduction
At first sight, players may be considered at high risk of acquiring and spreading infec-
tious diseases considering the typical circumstances of their training and competition.
The most relevant aspects seem to be the proximity to teammates and opponents,
travel requirements, and possibly some detrimental effects on the immune system from
intense sport. However, there is little research available on this topic, which might be
due to the predominant presence of t­raumatology-​­oriented members of the medical
staff around teams. The importance of infections can be underestimated due to their
lower incidence compared to that of injuries (­Bjørneboe et al., 2016). Nevertheless, in-
fectious diseases have the potential to interfere with training and match performance
and produce time loss. While a mild cold may seem trivial for a w ­ hite-​­collar worker,
this will hardly be the case for elite athletes, where even mild symptoms can impair
performance. Infections may even have potentially l­ife-​­threatening complications
without adequate treatment. Finally, infections may lead to an increased number of
injuries in the following weeks. Therefore, timely identification and proper manage-
ment of infectious diseases are of high relevance in soccer.

Epidemiology and clinical presentation of infections in players

As with the rest of the general p
­ opulation – ​­and other a­ thletes – ​­the most common in-
fections among soccer players are those of the upper respiratory tract (­URTI), ranging
from 40% to 74% of all illnesses in professional players (­Orhant et al., 2010; Bjørneboe
et al., 2016; Dvorak et al., 2011). The same is true in other codes of football, such as
American football, rugby, and Australian Rules football (­Chesson et al., 2020). It is
noteworthy that epidemiological data about infections in soccer are scarce, and the
available information from the UEFA Champions League and FIFA World Cups
(­Bjørneboe et al., 2016; Dvorak et al., 2011) reflects the highest level of play only (­and,
thus, a high level of medical care).
URTI symptoms include runny nose, nasal congestion, cough, sore throat, malaise,
and fever. In most cases, these are caused by viral agents. In professional players, the
average incidence of URTI episodes has been found to be 1.5 per 1,000 player days,
leading to an average training absence of 3 days per episode (­Bjørneboe et al., 2016).
As a result, such infections are not considered a major cause of time loss. However, a
single URTI may mean the loss of an important match and performance impairment
after infectious episodes remain uninvestigated. On the other hand, a player might not

DOI: 10.4324/9781003148418-17
224 Monica Duarte Muñoz and Tim Meyer
report mild symptoms or may go undiagnosed. The absence of diagnosis should be
avoided given that training or playing during an acute infection has the potential to
cause severe consequences.
The second most common infection in soccer ­players – ​­as well as in the rest of the
­population – ​­is gastrointestinal illness (­GI) (­Orhant et al., 2010; Bjørneboe et al., 2016;
Dvorak et al., 2011). It is often caused by bacteria like Escherichia coli types, but some-
times by viruses (­e.g., norovirus) and other agents. Symptoms of GI include diarrhea,
stomachache, and malaise. GI account for approximately ­13–​­28% of all infectious ep-
isodes in professional soccer (­Orhant et al., 2010; Bjørneboe et al., 2016; Dvorak et al.,
2011). Less than one episode per 1,000 player days is reported with an absence of 1 day
per 1,000 p ­ layer-​­days (­Bjørneboe et al., 2016). Malaise is more frequent in GI than in
URTI, and it is generally easier for players to accept the need for adequate rest. Fluids
lost due to fever, vomiting, or diarrhea, need to be replaced before safely returning to
play. Therefore, weight control is among the important measures of GI management.
Players must be weighed as soon as possible after the onset of symptoms and before re-
turning to play to ensure that fluid loss has been sufficiently replaced. Adequate hand
hygiene is critical in preventing the occurrence and spread of GI.
Skin infections are much less common, but they are the main source of “­outbreaks”
in sport settings (­Fontanilla et al., 2010; Turbeville et al., 2006). Their relevance for
soccer players is mainly dependent on their location and severity (­i.e., acuteness and
degree of inflammation). Skin lesions, such as infected blisters, at the players’ feet can
represent a very serious problem because of their interference with wearing proper
shoes and possibly because of the resulting pain during training and match play.
Skin infections are often caused by Streptococcus pyogenes (­e.g., erysipela) and Staph-
ylococcus aureus, including ­methicillin-​­resistant S. aureus (­MRSA) (­Romano et al.,
2006; Shaban et al., 2020). S. aureus is often harbored in asymptomatic athletes in the
nares, oropharynx, axilla, and groin. This ­so-​­called “­asymptomatic colonization” is
more common in contact sports athletes than in n ­ on-​­contact sports athletes (­­Jimenez-​
­Truque et al., 2017). Other skin infections such as onychomycosis, tinea pedis, and
pityriasis versicolor are more common in professional soccer players than in the gen-
eral population (­Buder et al., 2018).

Less common infections (­­vector-​­borne, ­blood-​­borne)

Less common infectious diseases that occur in soccer players include dental, eye, and
sexually transmitted infections, among others. These rarely cause severe complica-
tions, at least not immediately, but they do interfere with overall wellbeing and, there-
fore, with performance. Thus, as is the case with the a­ bove-​­mentioned diseases, they
require medical evaluation and treatment which may exceed the protocols typically
employed for such infections.
There are no specific considerations for ­vector-​­borne infectious diseases like malaria
or yellow fever besides the ones in place for all persons traveling to countries where
they are endemic (­see ­Table 14.1). Some infections can be prevented via vaccination.
Possibly a bit more surprisingly, infections that can be transmitted via body fluids
(­usually excluding sweat) and, therefore, also by blood, do not warrant specific precau-
tions in addition to the ones usually taken by medical staff. The reason is the very low
transmission rate under ­soccer-​­specific conditions. This is not only true for HIV but
also for the much more contagious hepatitis B.
 Infectious diseases 225
­Table 14.1 Prevention of v­ ector-​­borne infectious diseases (­Tickborne Encephalitis, 2022; Yellow
Fever, 2022)

Prevent mosquito bites Use insect repellent (­DEET, picaridin/­icaridin, etc.)

Minimize skin exposure (­­long-​­sleeve shirts, long pants, closed
shoes, tucking clothes in, etc.)
Use bed nets
Treat clothes with permethrin
Control mosquitoes Use screens on windows and doors
Stop mosquitoes from laying eggs (­empty and clean items that can
hold water)
Use air conditioning
Insecticides and spatial repellents
Check for ticks Inspect body and clothing after visiting a ­tick-​­infested area

Prevention of infectious diseases

The most “­ definite” approach for prevention of infectious diseases is vaccina-
tion. Little is s­port-​­specific about vaccinations, but statements can be made about
performance-​­
­ oriented athletes. The “­
disadvantage” of vaccinations is that they
only prevent one specific infectious disease and do not provide a broader protection
(­although this is sometimes purported). Therefore, they must be supplemented by
­other – ­​­­less-­​­­specific – ​­measures.

Vaccination
Guidelines available in most countries provide a vaccination scheme to be followed
by the general population, including elite athletes. However, some cases require spe-
cific recommendations according to exposure circumstances, such as travel or living
conditions. A few specific considerations apply to elite athletes as a group (­Gärtner &
Meyer, 2014). Planning vaccinations early enough before travel is critical in soccer
players, as there are diseases that are endemic in certain areas and countries may re-
quire vaccinations to be applied prior to travel (­see ­Table 14.2).
With each vaccine, there are risks of side effects. However, certain circumstances in
soccer players require special attention. For example, pain in the site of inoculation,
which is one of the most common side effects of vaccines, may interfere with training
or playing. Therefore, whenever possible, a vaccine should be applied in a region that
does not hinder training or playing; for example, the deltoid might be preferred over
the ­intra-​­gluteal route (­except for goalkeepers), plus, the vaccine should be applied on
the ­non-​­dominant extremity. An adequate application technique is also fundamental
to minimize pain afterwards. These considerations also apply in lower levels of play.
Severe side effects can occur, albeit infrequently. For example, ­vaccine-​­specific
symptoms may appear with live vaccines. Anaphylactic reactions or syncopes can
have serious consequences and require advanced medical attention, although athletes
are not at higher risk of presenting with these side effects than the rest of the popula-
tion. However, as with infectious illnesses, the consequences of such side effects may
appear more disabling in athletes. An ideal time for vaccination is during or shortly
prior to the winter and summer breaks (­Gärtner & Meyer, 2014). This timing ensures
that, should a complication or ­side-​­effects arise, it will not interfere with the players’
schedules. When this is not feasible, no specific interruptions or adjustments of the
226 Monica Duarte Muñoz and Tim Meyer
­Table 14.2 Preventive measures

Adequate hand hygiene Isolation of sick players

Avoid sharing personal objects Use of antibacterial gel
Adequate coughing and sneezing etiquette Bottled water when water quality is unknown
Load monitoring Ensure food is not contaminated

training schedule are required. Training sessions or matches do not relevantly affect
induction of the immune response to vaccination in elite athletes or modify the oc-
currence of side effects (­Stenger et al., 2020). The optimal time point for a vaccination
during ongoing training seems to be the day after a match.

Other preventive measures

Other measures can and should be taken to prevent the occurrence and spread of
infectious diseases (­­Table 14.2). Ensuring adequate hand hygiene might be the most
obvious measure, yet it is not always respected. Players should also be reminded not to
share their personal objects, such as towels, water bottles, and cutlery. One of the main
ways in which certain pathogens spread is through respiratory droplets and aerosols,
therefore, athletes should follow an adequate coughing and sneezing etiquette. It will
also be important to monitor load, as there may be periods of high match and training
load (­e.g., during ­pre-​­season), which may make players prone to infections (­Schwellnus
et al., 2016; Piggot et al., 2009; Jones et al., 2017). Finally, sick players should usually
be isolated. Many of these measures are common sense although their efficacy has
not been scientifically proven. Evidence only comes from a few papers in other sports
(­Schwellnus et al., 2016; Hanstad et al., 2011).
The ­above-​­mentioned measures can be applied under any circumstances. There are
certain additional actions that can be taken during traveling. The use of antibacterial
and hand disinfectants has been widely promoted (­K ratzel et al., 2020; Tamimi et al.,
2015; Henriey et al., 2014) given that it is a simple and effective measure. In countries
with warm climates and inadequate hygiene, where tournaments and training camps
frequently take place, it is recommended to drink only bottled water and be cautious
with food preparation.
Certain ­improper – ​­yet ­common – ​­practices in soccer may contribute to spread-
ing infections and other pathogens. Some examples are sharing personal objects (­e.g.,
drinking bottles and towels) and use of a single towel for several players (­by medi-
cal personnel and physiotherapists) (­Shaban et al., 2020). Correctly managing open
wounds (­which may occur frequently) is also crucial, and in such cases, players must
refrain from using communal baths. In addition to this, following the recommenda-
tions from the Centers for Disease Control and Prevention (­CDC) is strongly sug-
gested (­­Table 14.3).

Drugs to prevent infectious diseases

Most approaches to reduce the number of infectious diseases by intake of drugs claim
to boost or improve the immune response. Candidates for such pharmaceutical ac-
tions include echinacea (­Wang et al., 2006; ­Karsch-​­Völk et al., 2015), umckaloabo
(­Timmer et al., 2013; Roth et al., 2019; Jekabsone et al., 2019), and several other plant
 Infectious diseases 227
­Table 14.3 CDC recommendations for athletes for prevention of spread of MRSA (­MRSA, 2019)

Wash hands often with soap and water or Cover skin cuts and wounds
use ­alcohol-​­based sanitizer
• With clean, dry bandages or other dressings
• Before and after playing sports recommended by healthcare provider until
• After using shared ­weight-​­training healed.
equipment • Follow healthcare provider’s instructions on
• After caring for wounds change of bandages and dressings.
• After using the toilet
Shower immediately after exercise Wear protective clothing or gear designed to prevent
• Avoid sharing bar soap or towels skin abrasions or cuts.
Wash your uniform and clothing after Do not share items that come into contact with
each use your skin
• Dry clothes completely (­i n a dryer) • Personal items
• Ointments applied by placing your hand in the
container
• Use a barrier (­e.g., a towel) between your skin and
shared equipment (­e.g., sauna, ­weight-​­training)
Risk of URTI

Level of physical activity

­Figure 14.1 The risk of URTI is lower with moderate levels of physical activity when com-
pared to more sedentary people. The risk of URTI increases progressively
with higher levels of physical activity Adapted from Nieman, 1994.

compounds as well as probiotics (­Pyne et al., 2015) and zinc (­Hojyo & Fukada, 2016;
Wessels et al., 2017). Little evidence is available, and many researchers do not utilize
appropriate control conditions or prefer target parameters from the blood to the “­real
currency”, that is the incidence of infectious diseases. Moreover, most of these studies
are sponsored by companies, which creates the potential for publication bias.

­Soccer-​­specific influences on the likelihood of infectious diseases

Certain factors may make players more prone to infectious diseases than the general
population. These include high training loads, close interaction with teammates and
228 Monica Duarte Muñoz and Tim Meyer
opponents, and frequent travel. However, these negative factors must be weighed against
the fact that most players are healthy and young, which gives them a potentially robust
immune system. First, we address the high training and match loads to which players are
subjected and the impact they may have on the immune response. There are indications
that an acquisition of infections is more likely in the immediate aftermath of intense ex-
ercise (­like matches and hard training sessions). This factor is summarized in the “­open
window theory”. The theory states that there is a decreased immune response in athletes
during the first hours after exercise (­Pedersen & Ullum, 1994) and refers to the concen-
trations of some lymphocyte ­subpopulations – ​­like natural killer cells (­Kakanis et al.,
2010; Shek et al., 1995) – ​­as well as salivary immunoglobin A (­sIgA) (­Fahlman & Engels,
2005) (­a mucosal defense mechanism) which fall below p ­ re-​­exercise baseline values. It
follows from such considerations that players who frequently undergo strenuous exercise
have multiple “­windows” through which infectious agents might enter their bodies.
There is an accompanying theory about the l­ong-​­term (“­chronic”) consequences of re-
peated exercise bouts. The ­J-​­shaped curve (­Nieman, 1994) states that moderate exercisers
are at a lower risk of URTI when compared to athletes who exercise at high intensities
(­Pedersen & Bruunsgaard, 1995). It would seem, therefore, that elite players are prone to
infectious illness both acutely and chronically. sIgA, which is part of the initial (­or acute)
immune response to pathogens entering the body via the mucosae, decreases progres-
sively in soccer players when matches are scheduled too close to each other (­Morgans
et al., 2014). This factor might suggest a chronically increased susceptibility to infectious
diseases. However, there is currently no consensus about the significance of both theories
for soccer. It is of relevance whether training and competition stimuli as they typically
occur in professional soccer are of sufficient intensity, duration, and frequency to com-
promise the immune response. At least at the ­semi-​­professional and recreational level, it
is unlikely that proneness to infections exceeds that of the general population.
A second inherent risk is the close interaction that occurs between teammates and
­opponents – ​­particularly when combined with periods of impaired immunity like during
an “­open window”. Players come into close contact with their opponents during matches.
Tackling, yelling, heavy breathing, and touching one’s face may contribute to increasing
the risk of pathogen transmission through airborne particles. However, during a match,
players were found within 1.5 m or less of both, teammates, and opponents, for an aver-
age total time of 1 min and a half (­87.8 s) (­Knudsen et al., in press), with most interactions
lasting less than 3 s (­Egger, in press). This exposure may not be sufficient time to spread
pathogens through close contact, at least not the less contagious ones. Another publica-
tion from the Netherlands documented those other interactions on the pitch such as goal
celebrations and corner kicks contributed the most to the risk (Knudsen, et al., 2022).
Third, traveling may increase the risk of infections in professional players. Naturally,
some areas of the world pose risks (­­Table 14.4). Therefore, it is essential to be informed be-
fore travel to prepare accordingly. For example, vaccination can be required in certain ar-
eas with endemic diseases. This applies to competition as well as to training camps, which
often take place in developing/­warm countries. In such countries, there may be a higher
risk of GI due to lower hygiene standards. Thus, adequate hand hygiene and ensuring
food and water safety are of considerable importance. Another risk in such countries is
­vector-​­transmitted diseases, such as malaria, for which mosquito repellents (­among other
measures) can be useful (­see ­Table 14.1). However, there is an additional inherent risk in
traveling itself. L
­ ong-​­haul air travel for tournaments and competition poses an increased
risk, although responsible mechanisms remain speculative at this moment. Among the
 Infectious diseases 229
­Table 14.4 Infectious diseases to consider in traveling athletes

Disease Cause Where?

­Tick-​­borne Tick bite (­Ixodes ricinus, I. Eastern, Central, and Northern

encephalitis (­TBE) persulcatus) Europe
(­Tickborne TBEV (­F laviviridae) Europe, Northern China, Mongolia,
Encephalitis, 2022) and the Russian Federation
Hepatitis A Ingesting contaminated food ­Low-​­ and ­m iddle-​­i ncome countries
(­Hepatitis A, 2022) or water, direct contact. with poor sanitary conditions and
HAV hygiene practices
Yellow fever Mosquito bite (­Aedes or Africa and some tropical parts of
(­Yellow Fever, 2022) Haemagogus) South America
Flavivirus
Typhoid fever Poor hygiene Asian regions of Russia and
(­Typhoid Fever, 2022) Salmonella typhi neighboring countries, parts of
South and ­South-​­East Asia, Africa,
and South America
Dengue Dengue virus, mosquito bite Caribbean, Mexico, Central and
(­Dengue, 2023) (­Aedes aegypti or Aedes South America, Southeast Asia,
albopictus) and Pacific Islands
Zika Zika virus, mosquito bite North, Central and South America,
(­Zika, 2019, 2022) (­Aedes aegypti or Aedes France, Africa, and Asia
albopictus)
Helminthes ­Soil-​­transmitted parasites Tropical and subtropical areas, ­sub-​
(­Helminth infections, (­Ascaris lumbricoides, S
­ aharan Africa, the Americas,
2023) Trichuris trichiura, Necator China, and East Asia
americanus, etc.)
Chagas Bite, urine, or feces of Mexico, Central and South America
(­Chagas, n.d.) triatomines (­Trypanosoma (­currently widespread)
cruzi)

candidate factors are proximity to fellow passengers in an enclosed environment (­cabin

of the plane), stress, and possibly lack of sleep. Moreover, crossing a high number of time
zones seems to contribute to the risk of infections (­Schwellnus et al., 2012) with a direction
away from home being another aggravating factor. Finally, differing spectrums of infec-
tious agents between countries may challenge an immune system further.
Finally, inadequate nutrition and difficult ­intra-​­and ­inter-​­personal or family sit-
uations can likewise contribute to a decreased function of the immune system and
increase the risk of infections. Therefore, it is important that medical and other staff
keep track of the general wellbeing of players.

Diagnosis of infectious diseases

Usually, diagnosis is initiated and guided by symptoms of infection. It does not make
sense to screen for infectious diseases without any suspicious complaints (­possibly
except for pandemic situations like C ­ OVID-​­19). It is well possible that a diagnosis can
be made based on history and physical findings alone. At least in professional players,
it is advisable to consider taking a venous blood sample to determine blood count and
­C-​­reactive protein (­CRP; possibly additionally liver enzymes and other ­organ-​­targeted
parameters). This procedure may help assess the severity of the condition and be val-
uable for later decisions about the ­return-­​­­to-​­play when the question arises whether the
course of the disease has reached its climax (­Scharhag & Meyer, 2014).
230 Monica Duarte Muñoz and Tim Meyer
A major focus of initial diagnosis is always to determine if the infection is local or
generalized. Also, an assessment must be made about contagiousness (­to allow for
proper management in a team setting). This is usually only possible by a summarizing
view on all available findings and has to be carried out by a trained physician. The
presence of generalized symptoms (­fever, malaise, and swollen lymph nodes) speaks in
favor of n
­ on-​­eligibility for any kind of physical activity. When contagiousness must be
assumed, an isolation of the affected player is usually wise or at least strict advice on
how tosss behave towards teammates.

Consequences of infectious diseases

Infectious symptoms have the potential to interfere with training, competition, and in
general with the performance of players. In contrast to a w ­ hite-​­collar worker, a player
will likely notice even minor symptoms and perceive them as inconvenient. This is not
only true for upper respiratory symptoms but also for symptoms in other organs. It
follows that players should be thoroughly examined and questioned to safely determine
whether they are eligible again for training and match play. Also, symptomatic treatment
is still important even when medical constraints for ­return-­​­­to-​­play have disappeared.
After URTI or any other infection has been diagnosed, proper treatment and recov-
ery are fundamental. A recovery and resting period of a few days will be required in
many cases (­Scharhag & Meyer, 2014). This process can have important consequences
for the affected player as well as for his/­her teammates. Even during short recovery
periods, this may mean the absence of a player for an important match. Furthermore,
when a longer resting period is required, the outcome for the affected player can be a
decrease in physical condition and skill. The extent of this temporary loss in perfor-
mance will naturally be different depending on the time of the season. Notwithstand-
ing, return to play and training should take place gradually and only after the player
is s­ ymptom-​­free (­Börjesson et al., 2018). Sufficient recovery is of utmost importance
given the possible and severe consequences that can come from training and compet-
ing during a viral infection (­i.e., the affection of other organs).
One of the most feared complications is ­myocarditis – ​­an inflammation of the heart
muscle. Infectious ­agents – ​­such as viruses (­influenza, coxsackie, adeno, and her-
pes), bacteria (­meningococcus and streptococcus), and fungus (­aspergillosis) among
­others – ​­are the most common causes of myocarditis (­Basso et al., 2007). Physical
activity during viral replication may cause myocardial necrosis and death. Although
this has only been experimentally shown in mice (­Gatmaitan et al., 1970), we should
assume the same effect in humans.
Some illnesses require a prolonged recovery period. One such case is infectious mon-
onucleosis, which has a higher incidence in athletes from 15 to 25 years of age (­Becker &
Smith, 2014). Athletes who have suffered from this disease may have an enlarged spleen
for weeks after the initial infection, with an increased risk of splenic rupture, which can
happen with minor trauma or even spontaneously. Other diseases, such as glandular
fever (­­Epstein–​­Barr virus), Lyme disease (­Borrelia burgdorferi), or Q fever (­Coxiella bur-
netii), have been linked to chronic ­post-​­infective fatigue states (­Hickie et al., 2006). A
player should have full resolution of fatigue and other associated symptoms (­Becker &
Smith, 2014) before returning to full training load and competition. It is recommended
that physical activity progresses gradually to prevent complications. Close ­follow-​­up of
players who have presented an infectious illness is therefore imperative.
 Infectious diseases 231
Treatment of infectious diseases
There is a plethora of drugs utilized for the treatment of infectious diseases. Most of
them do not interfere with training or match activity. It is the severity of each infec-
tious disease that must be assessed to conclude about medical eligibility (­Scharhag &
Meyer, 2014). This is true for antibiotic treatment as well. The application of antibi-
otics alone does not preclude participation in training or competition. However, the
severity of an illness is usually high when antibiotic treatment is considered. Although
these drugs are only effective against bacteria, they are sometimes used to prevent
bacterial superinfections or because uncertainty exists about the infectious agent.
Another medication class that is often used to alleviate infection symptoms is ­non-​
s­ teroidal ­anti-​­inflammatory drugs (­NSAIDs). They are available as ­over-­​­­the-​­counter
drugs in most countries and, therefore, much less controlled by medical staff. It needs to
be considered that frequent intake of NSAIDs may lead to gastroduodenal ulcers and
renal damage, which means that players and staff members with medical conditions at
these organs should employ particular care. Another consideration is that NSAIDs can
cover infectious symptoms and lead to a falsely positive reception of one’s clinical status.

­Return-­​­­to-​­training and ­return-­​­­to-​­play after infectious diseases

Naturally, the question arises of how to determine whether a player can continue to
train and compete. There exists a thumb rule that may be of use: the s­ o-​­called “­neck
check” (­Eichner, 1993; Primos, 1996). This rule simply states that if a player has symp-
toms “­above the neck” (­i.e., sore throat and runny nose) they can be, in general, allowed
to train and compete; whereas when “­below the neck” symptoms are present (­i.e., fever
and muscle ache) it is advisable to restrict the player (­Primos, 1996). This is, as stated
before, only a rule of thumb. It is merely to be used as an initial reference and by no
means should substitute an adequate medical examination (­Scharhag & Meyer, 2014).
Like with injuries, there is a ­trade-​­off between a quick return to training and com-
petition and medical safety. A few recommendations have been published (­Scharhag &
Meyer, 2014) and many considerations are ­sport – ​­rather than ­soccer-​­specific. A return
too early imposes the risk of underperformance as well as complicated and lengthy
courses of the infection. In the worst case, organ affections like hepatitis or even my-
ocarditis can arise. The most reliable indicators of sufficient recovery are cessation
of symptoms and normalization of laboratory values, the latter being the more ob-
jective ones, of course. These may be of importance particularly in professional soc-
cer because there is some financial attractiveness in participating in the next match
which may lead to dissimulation. CRP can be considered the most reliable indicator
(­Scharhag & Meyer, 2014), particularly when it has been determined repeatedly.

Specific considerations for ­COVID-​­19

Professional leagues have been able to restart their competitions with costly hygiene
protocols, including repeated PCR testing and elaborate measures to allow for dis-
tancing and to avoid virus transmission within a team and its staff (­Meyer et al., 2021;
Schumacher et al., 2021). However, for all leagues which are unable to afford such
protocols, a major question arose around the likelihood of S ­ ARS-­​­­CoV-​­2 transmis-
sion under “­normal” conditions on a pitch. Early studies investigated the distance
232 Monica Duarte Muñoz and Tim Meyer
between players during a match and found that ­player-​­player contacts at less than 2
m mostly have a duration below 1 min, some of them even lower (­K nudsen et al., in
press; Van Duivenbode & Goes, 2020). This finding was later complemented by more
detailed analyses of the players’ behavior including mucosae contacts and direction
of the face during contacts (­Egger, in press). S ­ ARS-­​­­CoV-​­2 transmissions during foot-
ball play are unlikely, whereas simulations or commentaries partly concluded the
opposite. ­Corner kicks and goal celebrations were the activities with the longest close
contact.
Of course, the experimental ­approach – ​­letting infected persons play soccer and
assess the degree of transmission ­directly – ​­is unethical. Therefore, the only way of ad-
dressing real transmissions is to analyze retrospectively cases where contagious play-
ers have participated in matches unintentionally (­e.g., in error about testing results
or due to failure of the information chain). Such a study was carried out by Egger (­in
press). Their thorough ­follow-​­up revealed not a single transmission case on the pitch,
confirming the match analysis data. The study has been mirrored in English rugby
players (­Jones et al., in press). The fact that they did not find transmissions in a dis-
cipline with very close body contact makes a strong point in favor of soccer being a
­low-​­risk sport for acquiring respiratory infections on the pitch.

Conditions that may appear to be of infectious origin

While it is important not to miss a diagnosis of a URTI, it is equally important to not to
“­­over-​­diagnose” upper respiratory symptoms (­URS) as URTI in players. An increase
in minute ventilation during exercise can produce significant stress on the respiratory
tract (­Hull et al., 2017). This factor can cause certain typically ­URTI-​­associated symp-
toms, such as cough. Extreme conditions, such as cold air and ­h igh-​­intensity exercise,
may promote airway ­hyper-​­responsiveness (­Hull et al., 2017).
Increased airflow also increases exposure to allergens present in the air, which
can trigger an allergic response. It has also been suggested that a reactivation of the
­Epstein–​­Barr virus (­EBV) may cause transient symptoms. We do not agree with the
assumption that such reactivations which may be seen in immunocompromised pa-
tients occur in healthy soccer players. However, allergic conditions may mimic in-
fectious diseases and may partly account for a relatively short duration of symptoms
(­Gleeson & Pyne, 2016).

Future directions and conclusions

Some research has been done pertaining to infectious diseases and soccer. However,
much of the information that is currently available about the topic of infectious dis-
eases and sport comes from disciplines other than soccer (­e.g., cycling, running, and
skiing). Therefore, there is a need for more studies conducted specifically in soccer,
and more importantly, in female and male players at different levels of play, as well as
different age groups. Moreover, the ­SARS-­​­­CoV-​­2 pandemic, although it has already
fueled much research in the immunology of exercise, will demand even further investi-
gations as the situation progresses and when it finally comes to an end.
In conclusion, the most common infections in soccer players are URTI, followed
by GI. Other endemic diseases (­such as v­ ector-​­borne diseases) should be thought of
before traveling to competitions or training camps. Preventive measures include vac-
cinations, hand hygiene, and ensuring food and water quality. Certain factors increase
 Infectious diseases 233
the risk of infectious diseases, for example, proximity to teammates and opponents.
However, it seems that match play does not pose an increased risk for URTI. Labora-
tory parameters (­such as leukocytes and CRP), as well as signs and symptoms, aid in
the diagnosis of infectious diseases. Players with generalized symptoms should refrain
from physical activity. An infectious episode might lead to a loss of the sick player for
important trainings or matches. However, the consequences of an inadequate period
of rest and recovery are potentially far worse. Common drugs used as part of a treat-
ment include antibiotics and NSAIDs. Most of the drugs used do not impede training
or playing per se. After an infectious episode, ­return-­​­­to-​­play and ­return-­​­­to-​­training
should take place when the player is s­ ymptom-​­free and should be gradual depending
on the circumstances of each individual case. There seems to be very little risk of
­SARS-­​­­CoV-​­2 spread during a match. Avoiding ­under-​­diagnosing is as important as
avoiding ­over-​­diagnosing. Some URS may occur after strenuous exercise, it is impor-
tant that these are not mistaken for URTI.

References
Basso, C., Carturan, E., Corrado, D., & Thiene, G. (2007). Myocarditis and dilated cardiomy-
opathy in athletes: diagnosis, management, and recommendations for sport activity. Cardiol
Clin, 25(3), 423–429, vi. https://doi.org/10.1016/j.ccl.2007.08.008
Becker, J. A., & Smith, J. A. (2014). Return to play after infectious mononucleosis. Sports
Health, 6(3), 232–238. https://doi.org/10.1177/1941738114521984
Bjørneboe, J., Kristenson, K., Waldén, M., Bengtsson, H., Ekstrand, J., Hägglund, M., Rønsen, O., &
Andersen, T. E. (2016). Role of illness in male professional football: not a major contributor
to time loss. Br J Sports Med, 50(11), 699–702. https://doi.org/10.1136/bjsports-2015-095921
Börjesson M., Arvidsson D., Rensburg C.J.V., Schwellnus M. (2018). Return to Play After Infec-
tious Disease. In: Musahl V., Karlsson J., Krutsch W., Mandelbaum B., Espregueira-Mendes
J., d’Hooghe P. (Eds), Return to Play in Football: An Evidence-Based Approach (755–769).
Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-55713-6_56
Buder, V., Augustin, M., Schäfer, I., Welsch, G., Catala-Lehnen, P., & Herberger, K. (2018).
[Prevalence of dermatomycoses in professional football players: A study based on data of
German Bundesliga fitness check-ups (2013–2015) compared to data of the general popula-
tion]. Hautarzt, 69(5), 401–407. https://doi.org/10.1007/s00105-017-4120-3
Bury, T., Marechal, R., Mahieu, P., & Pirnay, F. (1998). Immunological status of competitive
football players during the training season. Int J Sports Med, 19(5), 364–368. https://doi.
org/10.1055/s-2007-971931
Centers for Disease Control and Prevention. (2019, May 20). About Zika. Centers for Disease
Control and Prevention. Retrieved February 27, 2023, from https://www.cdc.gov/zika/about/
index.html
Centers for Disease Control and Prevention. (2023, February 9). Dengue. Centers for Disease
Control and Prevention. Retrieved February 27, 2023, from https://www.cdc.gov/dengue/in-
dex.html#print
Centers for Disease Control and Prevention. (2019, January 31). Methicillin-resistant Staph-
ylococcus aureus (MRSA). For Athletes. Centers for Disease Control and Prevention. Re-
trieved February 27, 2023, from https://www.cdc.gov/mrsa/community/team-hc-providers/
advice-for-athletes.html#
Centers for Disease Control and Prevention. (2022, November 14). Prevention of yellow fever.
Centers for Disease Control and Prevention. Retrieved February 27, 2023, from https://www.
cdc.gov/yellowfever/prevention/index.html
Centers for Disease Control and Prevention. (2020, July 1). Ticks. Preventing tick bites. Centers
for Disease Control and Prevention. Retrieved February 28, 2023, from https://www.cdc.gov/
ticks/avoid/on_people.html
234 Monica Duarte Muñoz and Tim Meyer
Centers for Disease Control and Prevention. (2022, September 16). Traveler’s Health. Hepatitis
A. Centers for Disease Control and Prevention. Retrieved February 27, 2023, from https://
wwwnc.cdc.gov/travel/diseases/hepatitis-a
Centers for Disease Control and Prevention. (2022, May 6). Traveler’s Health. Tick-borne en-
cephalitis. Centers for Disease Control and Prevention. Retrieved February 27, 2023, from
https://wwwnc.cdc.gov/travel/diseases/tickborne-encephalitis
Centers for Disease Control and Prevention. (2022, September 16). Traveler’s Health. Typhoid
fever. Centers for Disease Control and Prevention. Retrieved February 27, 2023, from https://
wwwnc.cdc.gov/travel/diseases/typhoid
Centers for Disease Control and Prevention. (2022, September 22). Traveler’s Health. Yellow
Fever. Centers for Disease Control and Prevention. Retrieved February 27, 2023, from https://
wwwnc.cdc.gov/travel/diseases/yellow-fever
Chesson, L., Whitehead, S., Flanagan, K., Deighton, K., Matu, J., Backhouse, S. H., &
Jones, B. (2021). Illness and infection in elite full-contact football-code sports: A system-
atic review. Journal of science and medicine in sport, 24(5), 435–440. https://doi.org/10.1016/j.
jsams.2020.11.001
Dvorak, J., Junge, A., Derman, W., & Schwellnus, M. (2011). Injuries and illnesses of foot-
ball players during the 2010 FIFA World Cup. Br J Sports Med, 45(8), 626–630. https://doi.
org/10.1136/bjsm.2010.079905
Egger, F., Faude, O., Schreiber, S., Gärtner, B. C., & Meyer, T. (2021). Does playing football
(soccer) lead to SARS-CoV-2 transmission? - A case study of 3 matches with 18 infected
football players. Science & medicine in football, 5(sup1), 2–7. https://doi.org/10.1080/24733938.
2021.1895442
Eichner, E. R. (1993). Infection, Immunity, and Exercise. Phys Sportsmed, 21(1), 125–135. https://
doi.org/10.1080/00913847.1993.11710319
Fahlman, M. M., & Engels, H. J. (2005). Mucosal IgA and URTI in American college foot-
ball players: a year longitudinal study. Med Sci Sports Exerc, 37(3), 374–380. https://doi.
org/10.1249/01.mss.0000155432.67020.88
Figueiredo, P., Nassis, G. P., & Brito, J. (2019). Within-Subject Correlation Between Salivary
IgA and Measures of Training Load in Elite Football Players. International journal of sports
physiology and performance, 14(6), 847–849. https://doi.org/10.1123/ijspp.2018-0455
Fontanilla, J. M., Kirkland, K. B., Talbot, E. A., Powell, K. E., Schwartzman, J. D., Goering,
R. V., & Parsonnet, J. (2010). Outbreak of skin infections in college football team members
due to an unusual strain of community-acquired methicillin-susceptible Staphylococcus au-
reus. J Clin Microbiol, 48(2), 609-611. https://doi.org/10.1128/JCM.02297-09
Gatmaitan, B. G., Chason, J. L., & Lerner, A. M. (1970). Augmentation of the virulence of mu-
rine coxsackie-virus B-3 myocardiopathy by exercise. J Exp Med, 131(6), 1121–1136. https://
doi.org/10.1084/jem.131.6.1121
Gleeson, M., & Pyne, D. B. (2016). Respiratory inflammation and infections in high-­performance
athletes. Immunol Cell Biol, 94(2), 124–131. https://doi.org/10.1038/icb.2015.100
Gärtner, B. C., & Meyer, T. (2014). Vaccination in elite athletes. Sports Med, 44(10), 1361–1376.
https://doi.org/10.1007/s40279-014-0217-3
Hanstad, D. V., Rønsen, O., Andersen, S. S., Steffen, K., & Engebretsen, L. (2011). Fit for the
fight? Illnesses in the Norwegian team in the Vancouver Olympic Games. Br J Sports Med,
45(7), 571–575. https://doi.org/10.1136/bjsm.2010.081364
Henriey, D., Delmont, J., & Gautret, P. (2014). Does the use of alcohol-based hand gel sanitizer
reduce travelers’ diarrhea and gastrointestinal upset?: A preliminary survey. Travel Med In-
fect Dis, 12(5), 494–498. https://doi.org/10.1016/j.tmaid.2014.07.002
Hickie, I., Davenport, T., Wakefield, D., Vollmer-Conna, U., Cameron, B., Vernon, S. D.,
Reeves, W. C., Lloyd, A., & Group, D. I. O. S. (2006). Post-infective and chronic fatigue
syndromes precipitated by viral and non-viral pathogens: prospective cohort study. BMJ,
333(7568), 575. https://doi.org/10.1136/bmj.38933.585764.AE
 Infectious diseases 235
Hojyo, S., & Fukada, T. (2016). Roles of Zinc Signaling in the Immune System. J Immunol Res,
2016, 6762343. https://doi.org/10.1155/2016/6762343
Hull, J. H., Dickinson, J. W., & Jackson, A. R. (2017). Cough in exercise and athletes. Pulm
Pharmacol Ther, 47, 49–55. https://doi.org/10.1016/j.pupt.2017.04.005
Jekabsone, A., Sile, I., Cochis, A., Makrecka-Kuka, M., Laucaityte, G., Makarova, E., Ri-
mondini, L., Bernotiene, R., Raudone, L., Vedlugaite, E., Baniene, R., Smalinskiene, A.,
Savickiene, N., & Dambrova, M. (2019). Investigation of Antibacterial and Antiinflamma-
tory Activities of Proanthocyanidins from Pelargonium sidoides DC Root Extract. Nutrients,
11(11), 2829. https://doi.org/10.3390/nu11112829
Jiménez-Truque, N., Saye, E. J., Soper, N., Saville, B. R., Thomsen, I., Edwards, K. M., &
Creech, C. B. (2017). Association Between Contact Sports and Colonization with Staphylo-
coccus aureus in a Prospective Cohort of Collegiate Athletes. Sports Med, 47(5), 1011–1019.
https://doi.org/10.1007/s40279-016-0618-6
Jones, C. M., Griffiths, P. C., & Mellalieu, S. D. (2017). Training Load and Fatigue Marker
Associations with Injury and Illness: A Systematic Review of Longitudinal Studies. Sports
Med, 47(5), 943-974. https://doi.org/10.1007/s40279-016-0619-5
Jones, B., Phillips, G., Kemp, S., Payne, B., Hart, B., Cross, M., & Stokes, K. A. (2021). SARS-
CoV-2 transmission during rugby league matches: do players become infected after partici-
pating with SARS-CoV-2 positive players?. British journal of sports medicine, 55(14), 807–813.
https://doi.org/10.1136/bjsports-2020-103714
Kakanis, M. W., Peake, J., Brenu, E. W., Simmonds, M., Gray, B., Hooper, S. L., &
­Marshall-Gradisnik, S. M. (2010). The open window of susceptibility to infection after acute
exercise in healthy young male elite athletes. Exerc Immunol Rev, 16, 119–137.
Karsch-Völk, M., Barrett, B., & Linde, K. (2015). Echinacea for preventing and treating the
common cold. JAMA, 313(6), 618-619. https://doi.org/10.1001/jama.2014.17145
Knudsen, N. S., Thomasen, M. M. D., & Andersen, T. B. (2022). Modelling the potential spread
of virus during soccer matches. BMJ open sport & exercise medicine, 8(2), e001268. https://doi.
org/10.1136/bmjsem-2021-001268
Kratzel, A., Todt, D., V’kovski, P., Steiner, S., Gultom, M., Thao, T. T. N., Ebert, N., Holwerda,
M., Steinmann, J., Niemeyer, D., Dijkman, R., Kampf, G., Drosten, C., Steinmann, E., Thiel,
V., & Pfaender, S. (2020). Inactivation of Severe Acute Respiratory Syndrome Coronavirus
2 by WHO-Recommended Hand Rub Formulations and Alcohols. Emerg Infect Dis, 26(7),
1592–1595. https://doi.org/10.3201/eid2607.200915
Maya, J., Marquez, P., Peñailillo, L., Contreras-Ferrat, A., Deldicque, L., & Zbinden-Foncea,
H. (2016). Salivary Biomarker Responses to Two Final Matches in Women’s Professional
Football. Journal of sports science & medicine, 15(2), 365–371.
Meyer, T., Mack, D., Donde, K., Harzer, O., Krutsch, W., Rössler, A., Kimpel, J., von Laer, D., &
Gärtner, B. C. (2021). Successful return to professional men’s football (soccer) competition
after the COVID-19 shutdown: a cohort study in the German Bundesliga. Br J Sports Med,
55(1), 62-66. https://doi.org/10.1136/bjsports-2020-103150
Moreira, A., Bradley, P., Carling, C., Arruda, A. F., Spigolon, L. M., Franciscon, C., & Aoki,
M. S. (2016). Effect of a congested match schedule on immune-endocrine responses, techni-
cal performance and session-RPE in elite youth soccer players. Journal of sports sciences,
34(24), 2255–2261. https://doi.org/10.1080/02640414.2016.1205753
Morgans, R., Orme, P., Anderson, L., Drust, B., & Morton, J. P. (2014). An intensive Winter
fixture schedule induces a transient fall in salivary IgA in English premier league soccer
players. Research in sports medicine (Print), 22(4), 346–354. https://doi.org/10.1080/15438627.
2014.944641
Mutebi, J. P., & Gimnig, J. E. (2020). Mosquitoes, Ticks & Other Arthropods. In Brunette,
G. W. and Nemhauser, J. B. (Eds.), CDC Yellow Book 2020: Health Information for Inter-
national Travel. New York: Oxford University Press; 2017. https://wwwnc.cdc.gov/travel/
yellowbook/2020/noninfectious-health-risks/mosquitoes-ticks-and-other-arthropods
236 Monica Duarte Muñoz and Tim Meyer
Nieman, D. C. (1994). Exercise, infection, and immunity. Int J Sports Med, 15 Suppl 3, S131–141.
https://doi.org/10.1055/s-2007-1021128
Orhant, E., Carling, C., & Cox, A. (2010). A three-year prospective study of illness in profes-
sional soccer players. Res Sports Med, 18(3), 199–204. https://doi.org/10.1080/15438627.2010.
490462
Pedersen, B. K., & Bruunsgaard, H. (1995). How physical exercise influences the establishment
of infections. Sports Med, 19(6), 393–400. https://doi.org/10.2165/00007256-199519060-00003
Pedersen, B. K., & Ullum, H. (1994). NK cell response to physical activity: possible mechanisms of
action. Med Sci Sports Exerc, 26(2), 140–146. https://doi.org/10.1249/00005768-199402000-00003
Piggott, B., Newton, M., McGuigan, M. (2009). The relationship between training load and
incidence of injury and illness over a pre-season at an Australian Football League Club.
JASC, 17(3), 4–17.
Primos, W. A. (1996). Sports and Exercise During Acute Illness. Phys Sportsmed, 24(1), 44–54.
https://doi.org/10.1080/00913847.1996.11947895
Pyne, D. B., West, N. P., Cox, A. J., & Cripps, A. W. (2015). Probiotics supplementation for
athletes - clinical and physiological effects. Eur J Sport Sci, 15(1), 63–72. https://doi.org/10.1
080/17461391.2014.971879
Romano, R., Lu, D., & Holtom, P. (2006). Outbreak of community-acquired methicillin-­
resistant Staphylococcus aureus skin infections among a collegiate football team. J Athl
Train, 41(2), 141–145.
Roth, M., Fang, L., Stolz, D., & Tamm, M. (2019). Pelargonium sidoides radix extract EPs 7630
reduces rhinovirus infection through modulation of viral binding proteins on human bron-
chial epithelial cells. PLoS One, 14(2), e0210702. https://doi.org/10.1371/journal.pone.0210702
Scharhag, J., & Meyer, T. (2014). Return to play after acute infectious disease in football play-
ers. J Sports Sci, 32(13), 1237–1242. https://doi.org/10.1080/02640414.2014.898861
Schlagheck, M. L., Walzik, D., Joisten, N., Koliamitra, C., Hardt, L., Metcalfe, A. J., Wahl,
P., Bloch, W., Schenk, A., & Zimmer, P. (2020). Cellular immune response to acute exercise:
Comparison of endurance and resistance exercise. European journal of haematology, 105(1),
75–84. https://doi.org/10.1111/ejh.13412
Schumacher, Y. O., Tabben, M., Hassoun, K., Al Marwani, A., Al Hussein, I., Coyle, P., Ab-
bassi, A. K., Ballan, H. T., Al-Kuwari, A., Chamari, K., & Bahr, R. (2021). Resuming pro-
fessional football (soccer) during the COVID-19 pandemic in a country with high infection
rates: a prospective cohort study. British journal of sports medicine, 55(19), 1092–1098. https://
doi.org/10.1136/bjsports-2020-103724
Schwellnus, M., Soligard, T., Alonso, J. M., Bahr, R., Clarsen, B., Dijkstra, H. P., Gabbett,
T. J., Gleeson, M., Hägglund, M., Hutchinson, M. R., Janse Van Rensburg, C., Meeusen,
R., Orchard, J. W., Pluim, B. M., Raftery, M., Budgett, R., & Engebretsen, L. (2016). How
much is too much? (Part 2) International Olympic Committee consensus statement on load
in sport and risk of illness. Br J Sports Med, 50(17), 1043–1052. https://doi.org/10.1136/
bjsports-2016-096572
Schwellnus, M. P., Derman, W. E., Jordaan, E., Page, T., Lambert, M. I., Readhead, C., R­ oberts, C.,
Kohler, R., Collins, R., Kara, S., Morris, M. I., Strauss, O., & Webb, S. (2012). Elite athletes
travelling to international destinations >5 time zone differences from their home country have
a 2-3-fold increased risk of illness. Br J Sports Med, 46(11), 816–821. https://doi.org/10.1136/
bjsports-2012-091395
Shaban, R. Z., Li, C., O’Sullivan, M. V. N., Kok, J., Dempsey, K., Ramsperger, M., Brown, M.,
Nahidi, S., & Sotomayor-Castillo, C. (2021). Outbreak of community-acquired Staphylococ-
cus aureus skin infections in an Australian professional football team. Journal of science and
medicine in sport, 24(6), 520–525. https://doi.org/10.1016/j.jsams.2020.11.006
Shek, P. N., Sabiston, B. H., Buguet, A., & Radomski, M. W. (1995). Strenuous exercise and
immunological changes: a multiple-time-point analysis of leukocyte subsets, CD4/CD8 ratio,
immunoglobulin production and NK cell response. Int J Sports Med, 16(7), 466–474. https://
doi.org/10.1055/s-2007-973039
 Infectious diseases 237
Springham, M., Williams, S., Waldron, M., Strudwick, A. J., Mclellan, C., & Newton, R. U.
(2021). Salivary Immunoendocrine and Self-report Monitoring Profiles across an Elite-Level
Professional Football Season. Medicine and science in sports and exercise, 53(5), 918–927.
https://doi.org/10.1249/MSS.0000000000002553
Stenger, T., Ledo, A., Ziller, C., Schub, D., Schmidt, T., Enders, M., GÄrtner, B. C., Ses-
ter, M., & Meyer, T. (2020). Timing of Vaccination after Training: Immune Response and
Side Effects in Athletes. Med Sci Sports Exerc, 52(7), 1603–1609. https://doi.org/10.1249/
MSS.0000000000002278
Tamimi, A. H., Maxwell, S., Edmonds, S. L., & Gerba, C. P. (2015). Impact of the use of an
alcohol-based hand sanitizer in the home on reduction in probability of infection by res-
piratory and enteric viruses. Epidemiol Infect, 143(15), 3335–3341. https://doi.org/10.1017/
S0950268815000035
Timmer, A., Günther, J., Motschall, E., Rücker, G., Antes, G., & Kern, W. V. (2013). Pelargo-
nium sidoides extract for treating acute respiratory tract infections. The Cochrane database
of systematic reviews 2013, Issue 10. Art. No.: CD006323. https://doi.org/10.1002/14651858.
CD006323.pub3
Turbeville, S. D., Cowan, L. D., & Greenfield, R. A. (2006). Infectious disease outbreaks in
competitive sports: a review of the literature. Am J Sports Med, 34(11), 1860–1865. https://doi.
org/10.1177/0363546505285385
Van Duivenbode, V; Goes, F. (2020). “Social Distancing” in Football (Powerpoint slides). Kon-
inklijke Nederlandse Voetbal Bond: https://www.mayouthsoccer.org/assets/61/6/knvb_re-
search_social_distancing.pdf
Wang, C. Y., Chiao, M. T., Yen, P. J., Huang, W. C., Hou, C. C., Chien, S. C., Yeh, K. C., Yang,
W. C., Shyur, L. F., & Yang, N. S. (2006). Modulatory effects of Echinacea purpurea extracts
on human dendritic cells: a cell- and gene-based study. Genomics, 88(6), 801-808. https://doi.
org/10.1016/j.ygeno.2006.08.011
Wentz, L. M., Nieman, D. C., McBride, J. E., Gillitt, N. D., Williams, L. L., & Warin, R. F.
(2018). Carbohydrate Intake Does Not Counter the Post-Exercise Decrease in Natural Killer
Cell Cytotoxicity. Nutrients, 10(11), 1658. https://doi.org/10.3390/nu10111658
Wessels, I., Maywald, M., & Rink, L. (2017). Zinc as a Gatekeeper of Immune Function. Nutri-
ents, 9(12), 1286. https://doi.org/10.3390/nu9121286
World Health Organization. (n.d.). Chagas disease (American trypanosomiasis). World Health
Organization. Retrieved February 27, 2023, from https://www.who.int/health-topics/
chagas-disease
World Health Organization. (2023, January 18). Soil-transmitted helminth infections. World
Health Organization. Retrieved February 27, 2023, from https://www.who.int/news-room/
fact-sheets/detail/soil-transmitted-helminth-infections
World Health Organization. (2022, December 8). Zika virus. World Health Organization. Re-
trieved February 27, 2023, from https://www.who.int/news-room/fact-sheets/detail/zika-virus
15 Biomechanical assessments
Mark A. Robinson, Katherine A.J. Daniels and
Jos Vanrenterghem

Introduction
Biomechanics is the study of the effect of forces on the body. In soccer, a player expe-
riences or generates many types of forces. The external forces come from outside of
the body and include reaction forces from contact with the ground, ball, or opponents.
The internal forces are generated inside the body through muscular contractions which
cause movement and prepare the body to cope with external forces. Soccer match play
is highly dynamic with activities such as jumping, landing, sprinting, and turning re-
quiring players to generate and dissipate high forces. Biomechanics has two broad
applications for soccer. First, to maximise performance during these tasks. Second,
to reduce injury/­­re-​­injury risk. Several comprehensive reviews exist that have covered
these applications in depth both holistically (­Lees & Nolan, 1998; Nunome et al., 2017),
and specifically, for example, related to kicking (­Kellis & Katis, 2007; Lees et al., 2010),
heading (­Caccese & Kaminski, 2016), surfaces, and equipment (­Lees & Lake, 2003). In
this chapter, we focus on practical tests and measurements that are used in soccer and
are interpreted in a biomechanical context. A suite of measurement tools and tech-
niques exists to provide detailed, objective, and quantitative data to understand and
evaluate the physical status and biomechanical effectiveness of players. Specifically,
we consider four areas based on assessments that could be performed by a sports sci-
entist with equipment that would typically be available in a professional and academy
club setting. Where ­low-​­cost alternatives exist, these will be considered.

Evaluating jump performance

The evaluation of jump performance has traditionally been part of p ­ re-​­season screen-
ing. While typically this is done as part of the assessment of players’ physical fitness,
the truth is that for many teams the recorded jump heights are perhaps not much more
than a stimulus for players to compete for the team record. Nonetheless, the trainer,
coach, and possibly physiotherapist, often have their own ideas on why screening for
jump performance may be relevant. They may, for example, have an interest in a­ ge-​
­dependent performance changes in the context of talent identification, seasonal varia-
tions in performance, or obtaining a baseline performance against which to compare
future evaluations (­e.g., during rehabilitation). What is certain is that in all cases, prac-
titioners who have worked out why they wish to evaluate jump performance will have
asked the following questions: which type of jump should I test? Which technology
should I use? How will I use the test outcomes to change my training/­rehabilitation

DOI: 10.4324/9781003148418-18
 Biomechanical assessments 239
approach? In this section, we provide a brief overview of some supportive evidence to
help answer those questions.

Considerations for data collection

Decisions about which type of jump to test are typically interlinked with the availa-
ble time and technology. An overview of common jump test approaches is provided
in ­Table 15.1. While the Sargent ‘­jump and reach test’ is the cheapest, the flight time
method has arguably been the most popularly used test in soccer. In the 1980s, Car-
melo Bosco described a simple procedure with the calculation of flight height (­Hflight)
from measured flight time (­tflight), derived from the motion equations related to para-
bolic flight (­Bosco et al., 1983).
2
1  tflight 
H flight =
2  2 

A schematic overview of commonly used jump evaluation approaches

­Table 15.1 

Method Equipment Outcome Main pro Main con

Sargent vertical Chalk on Distance between Cheapest Need to have

jump wall with reach height vertical a good arm
(­reach distance measuring marked at peak jump test coordination
method) tape; of flight relative during jumping
vertecTM with to standing
horizontally reach height
rotating vanes
Vertical jump Jump mat (­e.g., Flight height; Quick setup Need to land
height based just jump); ­Stretch-​ and accurate the jump in
on flight time opto jumpTM; ­shortening if recorded a controlled
recording my jumpTM cycle index; at a high fashion
(­fl ight time phone app repetitive jump enough
method) performance frame rate
(­avg contact (>100 Hz)
time and flight
height)
Jump height Any ­floor-​ Same as flight ­In-​­depth Expensive
based on ­mounted force time methods; data on equipment and
ground platform, ­push-​­off mechanical need for tightly
reaction force some mechanics (­e.g., quality of standardised
recording portable force rate of force the ­push-​­off procedures
(­i mpulse platforms development, to have valid
method) counter results
movement
depth); broad
jump horizontal
­take-​­off velocity
Standing broad ­Tape-​­measure Jump distance Relevance Landing
jump on ­non-​­slip based on foot for ­sprint-​ coordination
(­fl ight distance surface contact ­related can interfere
method) performance with ­push-​­off
indicators performance
240 Mark A. Robinson et al.
Practically, the flight time method is most applied using a ‘­jump mat’ which measures
flight time from contact switches. The main constraint with this method is that body
configuration at the instant of landing needs to be the same as at the instant of ­take-​­off.
Practitioners may sometimes confuse a ‘­jump mat’ with a force platform (­which meas-
ures forces). While a force platform could be used to measure flight time directly, the
main advantage is that it allows t­ ake-​­off velocity (­Vtakeoff ) to be calculated. To achieve
this aim, force signals are integrated over time to calculate the impulse, which is propor-
tional to the change in velocity of the body centre of mass (­hence referred to as the im-
pulse method). Using the same motion equations related to parabolic flight, flight height
can be calculated independent of whether the athlete returns onto the force platform.
2
V 
H flight =  takeoff  with g = 9.81 ms −2
 2g 
The impulse method allows for many other variables related to the ­push-​­off to be cal-
culated. Rate of force development metrics are likely to be the most relevant perfor-
mance determinants; peak power has been suggested to be highly relevant, but this
is a misconception stemming from commonly used terminology (‘­explosive power’)
(­Ruddock & Winter, 2016). However, the impulse method does come with some con-
cerns, requiring stricter data collection procedures and more advanced data processing
routines to counter undesirable measurement artefacts (­Vanrenterghem et al., 2001).
In terms of the type of jump, endless variations exist concerning starting configu-
ration (­from standing, from deep squat, following ­pre-​­hop, and after b ­ ox-​­drop), use
of the arms (­w ith arm swing, holding arms in front of chest or akimbo, holding a
bar across the shoulders, and holding added handheld weights), direction of the jump
(­vertical, broad, and lateral), single versus double legged p
­ ush-​­off, or jump repetitions
(­reactive strength, reactive strength endurance, and agility ladder jumps). The target
population often determines one’s choices. For example, evaluating the differences in
jump performance with and without the use of the arms may be relevant in goalkeep-
ers more so than in field players. Also, in soccer players unilateral jumps in horizontal
directions may be more relevant than the commonly used t­ wo-​­legged vertical jump to
assess explosive muscular capacity (­Murtagh et al., 2018).

Considerations for data interpretation

Whether or not a test outcome should trigger a change in training plan depends on two
interlinked questions. First, how confident can I be that my test result is valid (­against
a gold standard test), reliable (­variation within a session), and repeatable (­variation
between sessions)? This provides me with an overall noise estimate on my measure
(­standard deviation), allowing me to estimate the sensitivity of the test outcome for de-
tecting a meaningful change, that is, the Minimal Detectable Change. Second, I must
decide which criterion value (­e.g., normative data and a player’s own reference data) to
use to detect the change against. Whilst it is impossible to accurately summarise the
existing evidence related to these questions (­and its scientific quality), some practical
advice may be in place.

• An application with more outcome measures does not make it better, rather, it
often promotes ­cherry-​­picking to confirm ­pre-​­existing beliefs rather than truly
supporting the practitioner.
 Biomechanical assessments 241
• A player’s own historical test results are more valuable than the comparison
against peers or a normative dataset (­except perhaps when evaluating the rela-
tionship between physical growth and functional development as part of health
screening in young players).
• Routinely incorporating an easy but trusted jump evaluation in the training pro-
cess has greater chances of generating relevant information about player fitness
and/­or fatigue than running a fully comprehensive jump evaluation with dozens
of test outcome measures once in the season.
• The added value of jump tests as part of regular screening may not only lie in as-
sessing a player’s fitness, but in the biopsychosocial facets of player management
(­Bahr, 2016), none the least that it can promote ­good-​­natured banter between play-
ers and staff.

Muscle activity assessment with electromyography

Electromyography (­EMG) is used to measure and evaluate the electrical activity of a
muscle. It provides a way of understanding the behaviour of a muscle during a given
task. Observing muscle contraction and relaxation provides an insight into the dy-
namic function of the muscle. Muscular contraction is the product of action potentials
moving along muscle fibres. The change in electrical activity of a muscle fibre can
be detected by electrodes. The EMG signal, therefore, describes the recruitment and
firing pattern detected within a muscle (­Konrad, 2006). Different types of electrodes
can be used to detect muscular activity. Finewire electrodes are invasively placed into
the muscle (­inserted with a needle) and require specialist training to use but are some-
times needed for the detailed clinical assessment of individual muscles, particularly
if these muscles are not near the skin surface. H ­ igh-​­density electrodes are an array of
electrodes placed on the skin, covering a large surface of the muscle, and can provide a
detailed insight into motor unit firing and progression of the action potentials through
the muscle. The m ­ ost-​­used electrodes are surface electrodes. These electrodes by com-
parison are n ­ on-​­invasive and simply require two electrodes to be placed on the skin
above the muscle belly.
Within soccer, surface EMG has been applied in injury prevention and rehabilita-
tion contexts, for example, to investigate muscular fatigue, neuromuscular character-
isation, and training, or hamstring injury risk. While electromyography is primarily a
research tool, EMG is becoming increasingly more accessible to soccer clubs. Wireless
signal transmission directly from the muscle belly has become the norm, and even elec-
trodes embedded in clothing allow for more applied applications (­Finni et al., 2007).
Nonetheless, the implementation of EMG in an applied context remains complex be-
cause of the large number of considerations for data collection and treatment.

Considerations for data collection

We can draw many different questions and conclusions from EMG analysis. Practical
questions can allow comparisons within and between individuals, as well as within
and between muscles (­Vigotsky et al., 2018). All of which need careful consideration of
the data collection and interpretation.
The primary constraint of surface EMG is that it is not suitable for all muscles. Care-
ful palpation of the central portion of the muscle belly located closest to the surface of
242 Mark A. Robinson et al.
the skin is needed to avoid ‘­­cross-​­talk’ from other muscles nearby. Skin preparation is
required to reduce the electrical resistance of the skin and maximise the quality of the
EMG signal. Typically, this process will involve shaving areas on the muscle belly that
have excess hair and wiping with an alcohol swab. A good skin preparation will have
a resistance of <5 Ohms between the electrodes.
The most evident application in the practical setting is to provide r­ eal-​­time feedback
on whether and how a muscle is functioning during activities, typically in a rehabil-
itation context. If the intention is to compare the magnitude of activation between
muscles (­e.g., medial and lateral hamstring muscles) or between sessions (­before and
after a therapeutic intervention) it is necessary to first ‘­calibrate’ the raw EMG signals.
A common calibration method is to express the magnitude of the EMG signal against
the muscle’s maximal activation level, for which a maximum voluntary contraction
(­MVC) is recorded. Obtaining a reliable MVC can be challenging, as it depends on the
ability of the individual to do a maximal effort muscle contraction which they are not
used to. It is advised to collect multiple attempts to verify the data are representative.
Also, the calibration process typically needs to be done in ­post-​­processing, so cali-
brated data are not available ­real-​­time.
Another application is the identification of muscles that are being activated too late
or too early in a movement, for example, around the time of impact with the ground.
To identify the timings of activation with respect to key movement phases, it will be
necessary to synchronise the EMG equipment with other devices such as motion cap-
ture systems, force platforms, or wearable inertial measurement systems. Prior to
purchasing an EMG system, check that your intended system is compatible with the
relevant devices.

Considerations for data interpretation

The raw (­unprocessed) EMG signal is generally not used for any quantitative data
analysis as the h ­ igher-​­frequency components of the signal are not reproducible. It is
common to focus on the general shape of the EMG signal with ­h igh-​­frequency signals
removed. This type of analysis focuses on the time domain of the signal and is used to
address questions relating to the magnitude and timing of the signal. The second type
of analysis focuses on the frequency domain of the signal, basically identifying how
fast spikes follow one another. This measure is used to address questions relating the
signal ‘­drive’ to the muscle, for example, revealing the impact of fatigue on the ability
to fully recruit one’s muscles.

How do I process the EMG signal?

For time domain analysis, you will typically need to use three processes: bandpass
filter your signal (­­10–​­500 Hz) to remove ­h igh-​­frequency (­for example, coming from
electronic devices) and l­ow-​­frequency (­for example, movement artefacts) signals that
are not related to muscle activation; ­full-​­wave rectification to convert negatives to pos-
itives; then create a linear envelope (­a smooth outline of the signal). The root mean
square is a common choice to create this linear envelope, with a time window of 20 ms
for very rapid movements such as jumping, landing, or running, or up to 100 ms for
slower movements such as walking (­­Figure 15.1). For a frequency domain analysis, the
unfiltered signal should be used.
 Biomechanical assessments 243

­Figure 15.1 The processing stages of a raw EMG signal.

How should I calibrate the EMG signal?

By expressing the processed EMG as a percentage of the ­above-​­mentioned MVC value
for a time domain analysis is a common fourth step. This is not always easily obtained
in a practical setting, and expressing the signal relative to the activation level of a
standard activity such as walking or a maximal vertical jump may be preferred, de-
pending somewhat on the goal of the analysis (­Burden, 2010). It is not uncommon for
dynamic contractions to exceed the 100% value of an MVC recording.

What metrics can I use?

Typical metrics for a ­time-​­domain analysis are the mean or maximal signal, the
­t ime-­​­­to-​­peak activation, time between onset and offset, or the area under the curve
(­integrated EMG). For the frequency domain, the median frequency is often used
to represent changes in EMG due to fatigue. It is worthwhile identifying which of
these can be readily extracted from the software that comes with commercially
available EMG systems, potentially saving a lot of time and headaches. It may also
be possible to extract the raw data for your own processing in Microsoft Excel, for
example, using the Biomechanics Toolbar, a freely available ­p ost-​­processing ­a dd-​­in
(­w ww.biomechanicstoolbar.org).
An excellent general guide for all aspects of EMG is ‘­The ABC of EMG’ (­Konrad,
2006).
The SENIAM project http://­w ww.seniam.org/ has sensor location recommenda-
tions for 30 individual muscles.
The International Society of Electrophysiology and Kinesiology (­ISEK) is a multi-
disciplinary organisation interested in EMG https://­isek.org/. Their reports are a
­must-​­read for reporting EMG data in scientific publications: https://isek.org/-wp-
content/­uploads/­2015/­05/­Standards-for-Reporting-EMG­Data.pdf

Muscle strength assessment

Muscular strength is a key component of physical performance and injury preven-
tion. An isokinetic dynamometer (­IKD) is a sophisticated tool used to assess muscle
strength under controlled circumstances, most commonly at a constant (­isokinetic)
velocity of joint angular rotation (­­Figure 15.2). Within soccer, it would be used by a
244 Mark A. Robinson et al.

­Figure 15.2 An isokinetic dynamometer s­ et-​­up for right knee testing.

sports scientist, physiotherapist, or strength and conditioning coach either for gen-
eral health screening purposes, evaluation of training progress, or as part of return
to sport d ­ ecision-​­making (­e.g., establishing interlimb asymmetry). The most assessed
muscle groups are the quadriceps and hamstrings. Other devices are also popular for
strength assessment, but these are generally limited to a (­quasi) isometric evaluation
(­e.g., handheld dynamometer), assessment of one muscle group only (­e.g., NordBord),
or ­closed-​­chain actions (­e.g., portable force platform in combination with a Smith ma-
chine). The IKD by comparison is large and heavy, but nonetheless often available in
professional environments. We highlight some practical considerations for data col-
lection, treatment, and interpretation, which aim to complement other more detailed
resources (­e.g., Baltzopoulos, 2008).

Considerations for data collection

For simplicity, we focus on the assessment of knee ­flexion-​­extension as depicted in
­Figure 15.2, though many other actions in the lower and upper limbs can be evaluated.

Preparation
The collection of accurate IKD data is reliant on the correct s­ et-​­up of the player prior
to testing. The three key requirements are: (­1) the fixed body segments (­i.e., thigh and
 Biomechanical assessments 245
upper body) must be firmly fixated to avoid unwanted movements of the k ­ nee-​­joint
axis or confounding actions of biarticular muscles crossing both hip and knee (­i.e.,
rectus femoris and hamstrings); (­2) the rotating axle of the crank arm must be aligned
with the ­k nee-​­joint axis; and (­3) the end of the lower leg must be strapped firmly to the
crank to maximise the forces transferred to the torque sensor in the IKD. Allowing
the player multiple attempts at ­sub-​­maximal intensity after preparation would be good
practice.

Protocol selection and settings

An IKD will typically allow the practitioner to select the isokinetic contraction mode,
angular range, and angular velocity to be tested. The most common contraction modes
used for player assessment are concentric (­muscle fibres shortening), eccentric (­muscle
fibres lengthening), and isometric (­zero joint rotation speed and hence no change in
the length of the ­muscle-​­tendon unit). Angular range for isokinetic modes is typically
set to encompass the ­full-​­joint active range of motion, while isometric testing can be
done at several different joint angles to test different regions of the muscle f­ orce-​­length
relationship. The chosen angular velocity of the crank will influence the maximum
forces the player can generate based on the ­force-​­velocity relationship of muscle. Typi-
cal angular velocities reported in the literature include 60, 180, and 300 deg s-​­1. For the
higher angular velocities, it should be verified that the player generates the required
angular velocity within the permitted range of motion. Alternative options can be
available, such as protocols in which the crank arm produces a ­pre-​­determined resist-
ance rather than speed (­isotonic), but these are more commonly used for exercising
than for assessment.

Considerations for data interpretation

As the player’s effort is measured through a torque sensor in the crank arm axle,
the main measured variable is the joint moment reported in ­Newton-​­metres (­Nm) –​
n­ ot muscle force. The key outcome measure of an isokinetic assessment tends to be
the peak joint moment. A visual verification that the peak moment occurred when
the angular velocity was at the ­pre-​­determined speed is important for concentric
mode testing, particularly for higher angular velocities (­Baltzopoulos, 2008). The
software should permit the profiles of joint moment, angle of the crank, and angu-
lar velocity of the crank to be reported alongside each other (­s ee ­Figure 15.3 left
panel).
Besides peak joint moment, the IKD can provide detailed insight into the ­moment-​
­angle profile, that is, how the agonists are able to produce force throughout the joint
range of motion. For example, one can look at the joint angle at which the peak joint
moment is reached, but also at the general rise and fall of the joint moment because
of the ­force-​­length characteristics of muscle contraction. For this type of analysis,
one needs to present the moment data against joint angular displacement (­­Figure 15.3
right panel) rather than against time (­­Figure 15.3 left panel). Some device software has
this as a reporting option, but the user does not always have full control over what is
and is not included in the report. If practitioners wish to gain more control over this,
for example, in the context of applied research, then the use of an application such as
IKD1D (­w ww.ikd1d.org) may be preferred.
246 Mark A. Robinson et al.

­Figure 15.3 (­Left) Visualisation of the joint moment, angle, and angular velocity profiles
for a c­ oncentric-​­concentric Q
­ uadriceps-​­Hamstrings protocol with the isoki-
netic phase highlighted. (­Right) Calculation of a 1­0-​­point moving average
joint ­moment-​­angle profile for the multiple trials.

Finally, some practical advice:

• When reporting a joint moment, the moment should be ascribed to the muscle
group around the joint (­e.g., the quadriceps or triceps surae joint moment, rather
than a specific muscle such as the vastus or gastrocnemius moment). Also, while
reduced joint moments are typically interpreted as reduced agonist contractile
capacity, one should keep in mind that this can sometimes be linked to agonist
inhibition (­e.g., arthrogenic muscle inhibition immediately in the weeks following
ACL reconstruction) or increased antagonist ­co-​­contractions as a subconscious
protective mechanism following injury to the agonist.
• Joint moments are often expressed as a ratio against the antagonist moment to infer
‘­balance’ about the joint (­e.g., the Hamstrings: Quadriceps ratio evaluates the capacity
of the hamstring muscle strength against its antagonist the quadriceps). For maximal
clarity, it is useful to include the contraction type in the description of such ratio (­e.g.,
Hamcon:Quadcon). For example in soccer, the s­ o-​­called functional H:Q ratio (­Hecc:Qcon
ratio) is often reported to represent the perceived function of the hamstrings muscle
group in stabilising the knee during locomotion. As a safety precaution, the joint an-
gular velocity of the eccentric hamstring evaluation in such Hecc:Qcon ratio is typically
lower than the concentric quadriceps evaluation (­e.g., 30 deg s-​­1 versus 120 deg s-​­1).
• Caution is needed in interpreting maximum joint moments as indicative of dy-
namic muscle function during athletic tasks. The ­single-​­joint action during an
IKD assessment eliminates important ­multi-​­muscle actions such as the transfer
of muscle forces between joints and the capacity to return stored energy very ef-
fectively from tendon elastic forces during adequately coordinated m ­ ulti-​­joint ac-
tions (­i.e., ­stretch-​­shortening action).

Injury prevention screening and return to play testing

Systematic physical testing of athletes is increasingly incorporated into training struc-
tures within competitive sport, with the aim of minimising overall playing time lost
 Biomechanical assessments 247
to musculoskeletal injuries. Many of these tests incorporate observations and/­or tech-
nologies that would typically be used by biomechanists (­e.g., timing sensors, force sen-
sors, and video analysis). Testing can be carried out routinely on uninjured athletes to
identify individuals presenting with modifiable risk factors for injury (­injury prevention
screening) or can be used to monitor recovery from musculoskeletal injury and inform
the timing of an individual athlete’s return to competitive play (­return to sport testing).
Athletes identified as ‘­at risk’ through injury prevention screening programmes are
often targeted with interventions focused on reducing the likelihood of future injury,
while return to sport testing is used to guide ­decision-​­making when evaluating the
optimum route back to competition after injury or ‘­clearing’ athletes for full partici-
pation in sport.

Considerations for data collection

As it is often desirable to quantify multiple physical qualities, and no single isolated test
appears to provide adequate discriminative ability, testing batteries commonly comprise
the evaluation of several tasks that can be considered as independent ‘­pass/­fail’ compo-
nents of the assessment or can be used to derive an overall summed score. Some examples
of physical tests and testing batteries that have been utilised in soccer for these purposes
are listed below (­in approximate ascending order of time and equipment demands).

­Single-​­limb hop for distance testing

A series of ­single-​­limb hopping tasks commonly used for return to sport testing after
l­ower-​­limb injury. Routine tests include the single hop (­landing on the same foot), the
triple hop (­three consecutive hops), and the ­cross-​­over hop (­three consecutive hops
with a mediolateral component). For all of these tasks, the aim is to maximise the total
distance covered. Timed tests can also be included, for which the athlete is required to
hop a given distance in the shortest possible time.

The star excursion balance test / Y balance test

A dynamic balance test in which the participant stands on one leg and attempts to
extend the contralateral leg as far as possible in multiple directions. All distances are
comprised into a composite reach score which is used to identify athletes that may be
at risk of injury, and ­inter-​­limb asymmetries can be used to monitor rehabilitation.

The functional movement screen (­FMS)

A ­whole-​­body testing battery incorporating multiple movement tasks that require sta-
bility and controlled movement, such as the ­straight-​­leg raise and the deep squat. Each
component is rated visually on a f­our-​­point scale and the resultant score is used to
identify asymmetries and deficits that could indicate an increased risk of future injury.

The athletic shoulder (­ASH) test

An ­upper-​­limb isometric testing protocol involving the use of a single force platform
to measure isometric shoulder strength at multiple orientations. Test results are used
248 Mark A. Robinson et al.
to guide return to sport ­decision-​­making for overhead and contact sport athletes, such
as soccer goalkeepers.

Considerations for data interpretation

There are two key concepts to understand when interpreting the results of injury pre-
vention screening tests: sensitivity and specificity. Sensitivity describes the ability of a
test to identify a player who will obtain an injury (­a ‘­true positive’), while specificity
describes the ability of a test to correctly report a negative result for those who will not
obtain an injury (‘­true negative’). In practice, sensitivity and specificity usually ­trade-​
­ ff against each ­other – ​­high sensitivity is associated with lower specificity, and vice
o
versa. The multifactorial nature of many sports injuries means that physical screening
tests tend to have relatively low sensitivity and specificity, limiting their predictive
value (­Bahr, 2016). Practitioners may, therefore, choose to offer injury prevention pro-
grammes to the entire team rather than only to those athletes identified as presenting
an elevated individual ­injury-​­risk profile.
When physical testing is intended to inform return to sport d ­ ecision-​­making after re-
covery from injury, the injured athlete’s test results are commonly compared to ‘­reference’
values to estimate rehabilitation status. The choice of reference data can influence the
conclusions drawn and decisions made, so is an important consideration for practition-
ers. The preferred approach in most circumstances is to compare the athlete’s p ­ ost-​­injury
performance and/­or mechanics to their own ­pre-​­injury baseline measures. However, this
option relies on the existence and availability of appropriate baseline data (­hence why
clubs may hold ­team-​­based ­pre-​­season screenings). Alternative approaches are:

(­i) to compare the athlete’s p

­ ost-​­injury data to reference data collected from an unin-
jured control group; and
(­ii) in the case of unilateral injury, to use the athlete’s uninjured contralateral limb
data as the reference.

Both approaches have limitations. The range of ‘­normal’ values in many strength,
biomechanical and performance metrics is large, so it is only possible to compare to
a broad ‘­normal’ or ‘­healthy’ control group range. In addition, the choice of control
group should be carefully considered as differences in age, training history, and skill
level are known to affect many ­commonly-​­used assessment metrics. Comparing the
injured limb to the athlete’s own uninjured limb can circumvent these difficulties, but
­de-​­training adaptations experienced by both limbs following injury can lead to overes-
timation of rehabilitation status. For example, improvements in symmetry metrics can
often be partially ascribed to p ­ ost-​­injury deterioration of the uninjured limb rather
than solely to improvements in the injured limb (­Wellsandt et al., 2018).
Finally, some practical advice:

• ­Performance-​­based metrics such as task completion time or distance have the

advantage of efficiency, as many players can be s­creened – ​­or testing repeated
­frequently – ​­without extensive time and staffing requirements but can fail to high-
light movement patterns and compensations indicating incomplete rehabilitation
or ‘­­high-​­risk’ movement. The increased risk of ­re-​­injury from incomplete rehabil-
itation may justify the cost and time invested in a detailed functional movement
 Biomechanical assessments 249
assessment (­in the same way as MRI is used to obtain a h ­ igh-​­resolution structural
assessment).
• With the advent of ­h igh-​­resolution ­h igh-​­speed video cameras in smartphones
and tablets, there is also a surge of apps to undertake video analysis. Some of
these apps claim to measure ­force-​­related movement characteristics based on es-
timations of acceleration. Verifying how these parameters are being calculated/­
estimated, and what they exactly represent, is paramount to avoiding unfounded
(­and likely invalid) interpretations.

Future directions and conclusions

We considered biomechanical assessments that might be undertaken in a profes-
sional and academy soccer setting. Many assessments conducted within soccer are
underpinned by biomechanics and biomechanical principles. Consideration of these
principles alongside the practical considerations within this chapter will allow the
sports scientist to be ­well-​­informed and critical about how these assessments can
help answer ­soccer-​­related questions. We, therefore, advise practitioners to be cau-
tious in ensuring: (­1) the validity of biomechanical measurements in both the lab and
field; (­2) that the assessments and measurements undertaken are measuring what you
wish to measure and not an unrelated surrogate measure; and (­3) that the assessment
used is sufficiently reliable to allow changes in performance or rehabilitation to be
detected.
Over time, the role of biomechanical assessments within soccer has shifted from
primarily technique evaluation to underpinning medical and rehabilitation monitor-
ing. The last decade has seen an increased availability of portable and l­ ow-​­cost biome-
chanical assessments which will continue. New approaches likely to be applied within
soccer include ­multi-​­sensor biomechanical assessment and ­data-​­fusion for personal-
ised approaches, and novel techniques utilising neural networks for markerless mo-
tion capture to measure player movements and estimate forces in ­field-​­based settings
(­Verheul et al., 2020). Recently, a growing interest in biomechanical perspectives on
injury prevention and performance enhancement within the general context of player
load monitoring has led to increased research efforts to keep up with technological de-
velopments (­Vanrenterghem et al., 2017). Extensive ongoing efforts between scientists
and product developers are expected to continue to make the role of biomechanical
assessments in soccer more prominent in the coming decades.

References
Bahr, R. (­2016). Why screening tests to predict injury do not ­work—​­and probably never will: a
critical review. Br J Sports Med, 50(­13), ­776–​­780. https://­doi.org/­10.1136/­­bjsports-­​­­2016-​­096256
Baltzopoulos, V. (­2008). Biomechanical evaluation of movement in sport and exercise. In C.
J. Payton & R. Bartlett (­Eds.), The British Association of Sport and Exercise Sciences Guide-
lines. Oxfordshire, UK.
Bosco, C., Luhtanen, P., & Komi, P. V. (­1983). A simple method for measurement of me-
chanical power in jumping. Eur J Appl Physiol Occup Physiol, 50(­2), ­273–​­282. https://­doi.
org/­10.1007/­BF00422166
Burden, A. (­2010). How should we normalize electromyograms obtained from healthy partic-
ipants? What we have learned from over 25years of research. J Electromyog Kinesiol, 20(­6),
­1023–​­1035. https://­doi.org/­10.1016/­j.jelekin.2010.07.004
250 Mark A. Robinson et al.
Caccese, J. B., & Kaminski, T. W. (­2016). Minimizing head acceleration in soccer: a review of
the literature. Sports Med, 46(­11), ­1591–​­1604. https://­doi.org/­10.1007/­­s40279-­​­­016-­​­­0544-​­7
Finni, T., Hu, M., Kettunen, P., Vilavuo, T., & Cheng, S. (­2007). Measurement of EMG activ-
ity with textile electrodes embedded into clothing. Physiol Measure, 28(­11), 1405. https://­doi.
org/­10.1088/­­0967-​­3334/­28/­11/­0 07
Kellis, E., & Katis, A. (­2007). Biomechanical characteristics and determinants of instep soccer
kick. J Sports Sci Med, 6(­2), ­154–​­165.
Konrad, P. (­2006). The ABC of EMG: A Practical Introduction to Kinesiological Electromyogra-
phy. Arizona: Noraxon U.S.A. Inc., Scottsdale, U.S.A.
Lees, A., Asai, T., Andersen, T. B., Nunome, H., & Sterzing, T. (­2010). The biomechanics of kicking
in soccer: a review. J Sports Sci, 28(­8), ­805– ​­817. https://­doi.org/­10.1080/­02640414.2010.481305
Lees, A., & Lake, M. (­2003). The biomechanics of soccer surfaces and equipment. In T. Reilly
(­Ed.), Science and Soccer. Oxfordshire: Routledge.
Lees, A., & Nolan, L. (­1998). The biomechanics of soccer: a review. J Sports Sci, 16(­3), ­211–​­234.
https://­doi.org/­10.1080/­026404198366740
Murtagh, C. F., Nulty, C., Vanrenterghem, J., O’Boyle, A., Morgans, R., Drust, B., & Erskine,
R. M. (­2018). The neuromuscular determinants of unilateral jump performance in soc-
cer players are ­direction-​­specific. Int J Sports Physiol Perform, 13(­5), ­604–​­611. https://­doi.
org/­10.1123/­ijspp.­2017-​­0589
Nunome, H., Hennig, E., & Smith, N. (­2017). Football Biomechanics. Oxfordshire: Routledge.
Ruddock, A. D., & Winter, E. M. (­2016). Jumping depends on impulse not power. J Sports Sci,
34(­6), ­584–​­585. https://­doi.org/­10.1080/­02640414.2015.1064157
Vanrenterghem, J., Clercq, D. D., & Cleven, P. V. (­2001). Necessary precautions in measuring
correct vertical jumping height by means of force plate measurements. Ergonomics, 44(­8),
­814–​­818. https://­doi.org/­10.1080/­0 0140130118100
Vanrenterghem, J., Nedergaard, N. J., Robinson, M. A., & Drust, B. (­2017). Training load mon-
itoring in team sports: a novel framework separating physiological and biomechanical l­oad-​
­adaptation pathways. Sports Med, 47(­11), ­2135–​­2142. https://­doi.org/­10.1007/­­s40279- ­​­­017- ­​­­0714-​­2
Verheul, J., Nedergaard, N. J., Vanrenterghem, J., & Robinson, M. A. (­2020). Measuring bio-
mechanical loads in team ­sports – ​­from lab to field. Sci Med Footb, 4(­3), ­246–​­252. https://­doi.
org/­10.1080/­24733938.2019.1709654
Vigotsky, A. D., Halperin, I., Lehman, G. J., Trajano, G. S., & Vieira, T. M. (2018). Interpreting
signal amplitudes in surface electromyography studies in sport and rehabilitation sciences.
Frontiers in physiology, 8: 985.
Wellsandt, E., Failla, M., & S ­ nyder-​­Mackler, L. (­2018). Limb symmetry indexes can overesti-
mate knee function after ACL injury. J Orthop Sports Phys Therap, 47(­5), ­334–​­338. https://­doi.
org/­10.2519/­jospt.2017.7285.Limb
Section D

Analysing and Monitoring

Performances
16 Analysis of physical performance in
­match-​­play
Christopher Carling and Naomi Datson

Introduction
Quantifying physical match performance allows practitioners to use objective infor-
mation to develop systematic approaches to training prescriptions and create future
tactics (­Reilly, 2005). Time motion analysis is the predominant method for collecting
physical match performance data. Over the last five decades, scientists have progressed
from manual ­video-​­based coding to sophisticated systems that are commonplace
within professional soccer settings (­Bradley et al., 2013). These systems include ­semi-​
­automated ­multiple-​­camera systems, ­radio-​­based local positioning systems (­LPS), and
global positioning systems (­GPS).
­Semi-​­automated multiple camera systems became popularised in the late 1990s and
at the time provided a transformation in approach, with benefits such as m ­ ulti-​­player
tracking and integration of technical and tactical variables. Pioneers of this technol-
ogy included AMISCO (­Sport Universal Process, Nice, France) and Prozone (­Prozone
Sports Ltd., Leeds, UK). Subsequently, technological advancements have continued
and ­multi-​­camera systems such as TRACAB (­Chyron Hego, New York, USA) and
SportVU (­Stats Perform, Chicago, USA) provide r­eal-​­time analysis. These systems
allow practitioners to access ­in-​­match objective ­performance-​­related data that can
help inform ­decision-​­making.
Technological innovations have facilitated analysis by enabling players to wear
miniaturised sensors during m ­ atch-​­play. LPS and GPS allow metabolically taxing
activities such as accelerations, decelerations, and changes of direction to be ac-
counted for, thus allowing a more comprehensive understanding of the physiological,
metabolic, and mechanical demands of m ­ atch-​­play (­Bradley et al., 2018). There are
practical advantages and disadvantages to LPS and GPS, with LPS such as Inmotio
(­Inmotio Object Tracking BV, Amsterdam, Netherlands) and Kinexon (­K inexon Pre-
cision Technologies, Munich, Germany) offering high sampling rates but requiring a
­semi-​­fixed installation, whereas GPS such as Catapult (­Catapult Sports, Melbourne,
Australia) and STATSports (­STATSports Group Limited, Newry, Northern Ireland)
do not require any specific installation but may be subject to reduced measurement
accuracy inside stadia (­Malone et al., 2017).
Due to the inherent practicalities of each system, practitioners often use a combi-
nation of systems to gather physical performance data for an individual player. In
practice, GPS or LPS sensors are often worn during training, whereas s­ emi-​­automated
­multiple-​­camera systems are routinely used during matches (­Buchheit & Simpson,
2017). However, practitioners should be cautious of differences between systems and

DOI: 10.4324/9781003148418-20
254 Christopher Carling and Naomi Datson
are recommended to apply calibration equations to enable data integration (­Buchheit
et al., 2014; Taberner et al., 2020). In 2015, FIFA permitted the use of electronic per-
formance and tracking systems in competitive matches that may support practitioners
moving towards a single system for quantifying player physical performance in both
training and ­match-​­play.
Regardless of the system(­s) used, collecting objective physical performance data
from training and matches is of benefit when prescribing training and recovery strat-
egies. Such data can assist practitioners as they attempt to maximise player perfor-
mance and minimise susceptibility to injury or illness. In this chapter, we consider
general and ­position-​­specific characteristics of match physical performance with ex-
amples of published data across multiple forms of soccer. Moreover, we address those
factors affecting match physical performance and practical implications of the data.

General match demands

Total distance covered during a match is perhaps the ­most-​­cited metric when consid-
ering the physical performance of players. Total distance is indicative of the volume of
activity completed by players, providing a global representation of the overall match
physical demands. Typically, professional male outfield players cover a total match
distance of 1­ 1–​­12 km (­Bradley et al., 2013), whereas their elite female counterparts
cover ­9 –​­11 km (­Scott et al., 2020). Total distances covered have been described for
other forms of the game including youth, futsal, amputee, and beach soccer. Youth
players (­­U10–​­U18) cover ­5 –​­7 km during 60 min of ­match-​­play (­Saward et al., 2016),
futsal players cover ~4 km during 40 min of ­match-​­play (­Ribeiro et al., 2020), and
amputee players cover ~6 km during 50 min of m ­ atch-​­play (­Simim et al., 2018). As
beach soccer involves unlimited substitutions, players often have a reduced playing
time with research showing players cover ~1 km during 12 min of active playing time
(­Castellano & Casamichana, 2010).
The differences in match duration for various formats of the game make it chal-
lenging to draw meaningful conclusions from total distance data. Consequently, the
use of relative distance, that is, distance covered relative to match duration, allows
more appropriate comparisons between game formats. Approximate relative total dis-
tances for each of the above game formats are as follows: elite male (­­120–​­130 m min-​­1)
(­Bradley et al., 2013); elite female (­­100–​­120 m min-​­1) (­Scott et al., 2020); youth (­­80–​­120
m min-​­1) (­Saward et al., 2016); futsal (­­90–​­100 m min-​­1) (­Ribeiro et al., 2020); amputee
(­110 m min-​­1) (­Simim et al., 2018); and beach soccer players (­100 m min-​­1) (­Castellano &
Casamichana, 2010).
Although total distance provides a broad indication of the overall movement de-
mands, it does not provide a comprehensive understanding of physical match perfor-
mance. To gain a better understanding of exercise intensity, total distance covered is
generally ­sub-​­divided into activity categories or “­zones” that are determined by speed
of movement. Common qualitative descriptors for such activity categories include
walking, jogging, running, ­h igh-​­speed running, and sprinting. There are generally
two approaches for assigning speed thresholds to each activity category: (­1) the use of
absolute (­or arbitrary) thresholds; or (­2) the use of individualised (­or ­player-​­specific)
thresholds. While using arbitrary zones may facilitate ­between-​­study comparisons if
the same thresholds are applied, there remains no consensus within the literature for
the definition of movement categories according to running speed. For example, two
 Analysis of physical performance in match-play 255
recent studies involving male players (­Curtis et al., 2020; Fereday et al., 2020) classified
­h igh-​­speed running activity as 14.4 km h-​­1 and 19.8 km h-​­1, respectively. In addition,
if applying arbitrary zones to youth or female cohorts, then due consideration of po-
tentially adapted speed thresholds is warranted (­Malone et al., 2017). P ­ layer-​­specific
zones, based on individual fitness attributes have previously been suggested to offer a
more specific evaluation of external load in c­ ase-​­study scenarios (­Hunter et al., 2015;
Lovell & Abt, 2013). However, recent evidence suggests the practice of individualis-
ing speed thresholds might not add value in determining the dose response of soccer
activity in professional female players (­Scott & Lovell, 2018). If p ­ layer-​­specific zones
are to be used, then numerous challenges exist when considering an individualised
approach. For example, the physical performance test(­s) that should be used to assist
threshold determination and the frequency with which such tests can be administered
around the training and competition schedule (­Malone et al., 2017). While a definitive
consensus remains absent, researchers and practitioners are advised to consider the
cohort or individual being assessed when selecting thresholds for activity categories.
­Low-​­speed activity accounts for most of the distance covered in ­match-​­play, empha-
sising the predominantly aerobic nature of the game. English Premier League players
and i­nternational-​­level female players have been shown to cover ~75% and ~76%, re-
spectively, of the total distance covered in a match in l­ow-​­speed activity categories
(­i.e., walking and jogging) (­Bradley et al., 2013; Datson et al., 2017, see F ­ igure 16.1).
Values are comparable in youth soccer, with players covering approximately 71% and
76% of total distance in ­lower-​­speed categories in male (­Saward et al., 2016) and fe-
male ­match-​­play, respectively (­­Harkness-​­Armstrong et al., 2020). Similar values have
been demonstrated in both beach soccer (~70%) (­Castellano & Casamichana, 2010)
and futsal (~79%) (­Ribeiro et al., 2020).

6000

5000

4000
Distance (m)

3000

2000

1000

0
Walking Jogging Running High-Speed Running Sprinting
(<7.1 km/h) (7.2-14.3 km/h) (14.4-19.7 km/h) (19.8-25.1 km/h) (>25.2 km/h)

Male Female

­Figure 16.1 Physical match performance in professional male and female soccer players
(­adapted from Bradley et al., 2013; Datson et al., 2017).
256 Christopher Carling and Naomi Datson
Although ­low-​­speed activities dominate performance profiles in all forms of the
game, it is ­high-​­speed activities which are often considered critical to the match out-
come. These actions frequently precede crucial moments within ­match-​­play, such as the
movement required to evade the opposition and capitalise on g­ oal-​­scoring opportunities
(­Di Salvo et al., 2009). ­Figure 16.1 shows for professional male and female m ­ atch-​­play,
approximately 25% of total match performance is spent above 14.4 km h-​­1 (­i.e., running,
and above) and 9% is spent above 19.8 km h-​­1 (­i.e., ­high-​­speed running, and above).
Sprints generally occur over short distances with research showing 76% and 95%
of all match sprints occur over 5 m and 10 m, respectively, in female players (­Datson
et al., 2017). Di Salvo and colleagues reported similar findings in male players partici-
pating in European Cup competitions with most sprints occurring over short distances
(­­0–​­10 m) (­Di Salvo et al., 2010). ­Longer-​­distance sprints (>20 m) do occur, albeit infre-
quently, as demonstrated by an average sprint distance of 15.1 ± 9.4 m in female players
(­Vescovi, 2012). Professional male players complete more explosive (­characterised by
a fast acceleration) than leading (­characterised by a gradual acceleration) sprints (­Di
Salvo et al., 2010), whereas female players perform an even number of both types of
sprints (­Datson et al., 2017).
Soccer is inherently intermittent in nature as players are required to complete ­h igh-​
s­ peed or sprinting actions with variable recovery periods throughout the match. Sci-
entists have reported that these ­h igh-​­speed actions occur on average every ~70 s in
professional male players (­Bradley et al., 2010) and every ~40 s in professional female
players (­Datson et al., 2019). Slight methodological differences exist between these
studies which likely account for the differences between sexes, however, both stud-
ies emphasise the stochastic nature of ­match-​­play. While average data provide valu-
able information for estimating w ­ ork-­​­­to-​­rest ratios, practitioners should be mindful
of minimum and maximum recovery periods as well as b ­ etween-​­position differences
(­Carling et al., 2012). The ability to produce and recover from h ­ igh-​­speed actions in
a limited time frame is termed repeated sprint ability (­RSA). RSA is broadly defined
as multiple ­h igh-​­speed running and/­or sprinting bouts within a given ­time-​­period.
Published reports indicate that, when employing a sprinting threshold, the frequency
of RSA is relatively low (­one to two bouts per match) (­Datson et al., 2019; Schimpchen
et al., 2016). However, these data represent the average demands for RSA and may not
be reflective of the ­worst-​­case scenario that players may encounter. Nevertheless, the
low occurrence of RSA bouts suggests this particular fitness component might not be
as crucial to success as previously suggested (­Carling et al., 2012).
Profiling match performance based on locomotion will underestimate the true
workload for a player by neglecting the energy expenditure of ­sport-​­specific move-
ments (­e.g., accelerations, decelerations, and changes of direction) and actions (­e.g.,
heading, tackling, and running with the ball). For example, a maximum acceleration
commencing from a low speed is a ­h igh-​­intensity activity with a high metabolic load
(­Osgnach et al., 2010). However, this activity would be discounted from traditional
definitions that only consider ­h igh-​­intensity movements to be those occurring at high
speed. Researchers have shown that accelerations and decelerations occur frequently
(~850 per match, at a threshold of >2 m s-​­2) and that players generally perform more
­h igh-​­intensity decelerations compared to accelerations (­Harper et al., 2019; Mara
et al., 2017b). The energy cost of ­soccer-​­specific actions such as running with the ball
is not quantifiable when using ­locomotor-​­based analyses. However, running with a
ball on a pitch at a standard speed of 10 km h-​­1 requires an additional energy cost of
 Analysis of physical performance in match-play 257
­Table 16.1 Influence of playing position on match physical activity profile in elite female soccer
players (­data adapted from Datson et al., 2017, 2019)

Central Wide Central Wide

Attackers
defenders defenders midfielders midfielders

Total distance (­k m) 9.5 ± 0.6 10.3 ± 0.7 11.0 ± 0.7 10.6 ± 0.7 10.3 ± 0.8
­High-​­speed running (­m) 423 ± 79 634 ± 168 683 ± 170 700 ± 167 651 ± 135
Sprinting (­m) 111 ± 42 163 ± 79 170 ± 69 220 ± 116 221 ± 53
Recovery between ­h igh-​ 54 ± 9 40 ± 9 36 ± 9 35 ± 8 38 ± 8
s­ peed efforts (­s)

approximately 10% (­Piras et al., 2017). Such findings emphasise the importance of an
integrated approach to match analysis in soccer (­Bradley & Ade, 2018).

­Position-​­specific match demands

Physical match performance profiles differ distinctly across playing positions in senior
male (­Aquino et al., 2020b), senior female (­Datson et al., 2017), youth male (­Abbott
et al., 2018), youth female (­­Harkness-​­Armstrong et al., 2020), and futsal (­Ohmuro et al.,
2020) players. Scientists have routinely considered five key outfield playing positions in
the 11 vs. 11 format: defenders (­c entral and wide); midfielders (­c entral and wide); and
attackers. However, further s­ ub-​­divisions such as central defensive midfielders, central
attacking midfielders (­Dellal et al., 2011), and “­second” strikers (­Buchheit et al., 2010)
have been included in the literature. In futsal, the different playing positions com-
monly studied are pivots, wingers, and defenders.
Published reports frequently highlight that central defenders complete less total,
­h igh-​­speed, and sprinting activity per match compared to other playing positions
(­Abbott et al., 2018; Datson et al., 2017). Central midfielders often produce the highest
total distances (­Abbott et al., 2018; H
­ arkness-​­Armstrong et al., 2020) and wide attack-
ers the greatest h­ igh-​­speed running and sprinting distances (­Ingebrigtsen et al., 2015;
Mara et al., 2017a). The recovery duration between isolated and repeated h ­ igh-​­speed
actions varies with playing position, with longer recovery durations more common in
central defenders and shorter recovery durations more common in central and wide
midfield players (­Carling et al., 2012; Datson et al., 2019). An overview of the physical
match performance for different outfield playing positions is shown in ­Table 16.1. The
physical match profile of goalkeepers is less well studied, but recent reports show that
English Premier League goalkeepers cover a total distance of ~5.5 km with ~120 m at
high speed (>15 km h-​­1) (­W hite et al., 2020). These positional differences in activity
profiles are to be expected due to differing tactical roles. For example, central mid-
fielders link attack and defence and are often required to participate in both phases
of play. Meanwhile, wide attackers play in less congested areas of the pitch and have a
greater opportunity to achieve ­h igh-​­speeds unopposed (­Abbott et al., 2018).

Fatigue and variations in performance

Total match physical performance is often ­sub-​­divided into discrete time periods such
as ­45-​­m in (­i.e., ­between-​­half), ­15-​­m in, and ­5-​­m in intervals. Data are then analysed to
examine variability in work rate profiles between each time for individuals and teams.
258 Christopher Carling and Naomi Datson
­Table 16.2 T
 otal distance covered (­m) by soccer players during first and second halves of
competitive ­match-​­play

Reference Total 1st Half 2nd Half Difference Game format Statistical
distance (­m) (­m) (­m) conclusion
(­m)

Aquino et al., 6,249 3,086 3,163 +77 U16 Male No change

2016
Atan et al., 5,434 2,997 2,437 –​­560 U14 Male Reduction
2016
Bradley et al., 10,753 5,486 5,267 –​­219 Pro female Reduction
2014
Di Salvo et al., 11,393 5,709 5,684 –​­25 Pro male No change
2007
Russell et al., 9,457 4,891 4,566 –​­325 U21 Elite male Reduction
2016
Simim et al., 5,660 2,920 2,740 –​­180 Amputee male No change
2018

­Between-​­half match performance

The evidence of b ­ etween-​­half changes in total distance covered remains unclear with
some researchers observing reductions in s­ econd-​­half running performance, whereas
others report no change (­see ­Table 16.2). Similarly, contradictory findings exist for
­between-​­half differences in ­h igh-​­speed running distance, with some evidence of sig-
nificant ­second-​­half reductions (­Di Salvo et al., 2009) and others observing no changes
(­Russell et al., 2016).

Performance towards the end of each half

While ­between-​­half differences in match physical performance provide a broad appre-
ciation of work rate profiles, consideration of shorter time periods, such as 1­ 5-​­min in-
tervals, afford a more comprehensive understanding. Analysis of international female
­match-​­play observed a 35% reduction in ­h igh-​­speed running distance from the first to
the last 15 min. Furthermore, players completed less h ­ igh-​­speed running during the
final 15 min of each half compared with the previous 15 min (­Datson et al., 2017). Simi-
larly, in male ­match-​­play ­h igh-​­speed running distance as well as the number of sprints,
accelerations and decelerations were significantly lower in the last 15 min compared to
the first 15 min of ­match-​­play (­Russell et al., 2016).

Transient fatigue
Variability in match physical performance across ­5 -​­m in intervals has been shown in
elite male and female players, with players completing 40% less h ­ igh-​­speed running
distance in the ­5 -​­min period which follows the peak ­5 -​­min period for ­h igh-​­speed
running (­C arling & Dupont, 2011; Datson et al., 2017). The following 5­ -​­min period
has been shown to be 6­ –​­8% lower than the average 5­ -​­min period in Premier League
players (­Bradley et al., 2009). These ­5 -​­min periods were based on ­pre-​­defined inter-
vals within analysis software, such as 0­ –​­5 min and 5­ –​­10 min. However, researchers
have shown that there are even larger decrements when using rolling ­5 -​­min periods
 Analysis of physical performance in match-play 259
(­i.e., distance covered from every time point for the next ­5 -​­min period) (­Varley
et al., 2012).

Reasons for variations in performance

The decreases in physical match performance observed in the latter stages of ­match-​
p
­ lay may be a result of glycogen depletion of individual muscle fibres (­K rustrup et al.,
2006), whereas transient changes after periods of high intensity may be due to in-
tramuscular acidosis or changes in the concentration of potassium in the muscle in-
terstitium (­Mohr et al., 2005). There are suggestions that declines in match running
performance may be related to mental fatigue (­Paul et al., 2015) or the conscious or
subconscious employment of pacing strategies to ensure physical readiness for the
most challenging periods of a game (­Drust et al., 2007).
While variations in player physical performance at different time points within
a match may represent fatigue, caution must be exhibited when analysing physical
performance without due consideration of technical and tactical indices. Basing
fatigue purely on match running performances is likely too simplistic, particularly
due to our limited understanding of physiological responses to match demands
(­Paul et al., 2015). Such a reductionist approach is likely to impede the development
of a comprehensive and holistic understanding of m ­ atch-​­play demands (­Bradley &
Ade, 2018). For example, while a reduced physical performance is observed in the
final 15 min of m ­ atch-​­play compared to the first 15 min, it should be considered that
teams will try to establish tactical superiority at the start of a match which may lead
to artificially increased values for ­h igh-​­intensity activities during the first 15 min
(­Weston et al., 2011). Recently, researchers have reported that approximately 58% of
the decline in match running performance in matches in the Bundesliga is caused by
an increase in game interruptions and cannot be related to physical fatigue (­Linke
et al., 2018).
Match performance data are generally “­noisy” in nature and demonstrate high lev-
els of natural variability in match as well as from one match to the next. The interpre-
tation of findings from ­time-​­motion studies can be hampered by the large variability
in performance (­typically reported as a % coefficient of variation or % CV) within and
between players. Gregson et al. (­2010) investigating a large sample of Premier League
players demonstrated that ­h igh-​­intensity activities varied by ~­15–​­30% from match to
match and that the variability was higher for central defenders and midfielders than
for wide midfielders and attackers. In a French Ligue 1 team, high collective CV values
were found for h ­ igh-​­intensity distances of ~32%, ~26%, ~60%, and 24%, respectively
when the team was in and out of ball possession, in individual ball possession, and
during the peak ­5-​­min activity period. In the same study, individual values for ­h igh-​
i­ ntensity distance ranged from 11% in a full back to 26% in a central defender (­Carling
et al., 2016).
The variability in physical performance is mediated through the inherent demands
of the game that are influenced by a myriad of contextual factors (­Bush, Archer,
Hogg & Bradley, 2015) (­­Figure 16.2). A large body of research relating to the effects of
situational and environmental factors on ­match-​­running currently exists. In addition
to playing position, the influence of situational factors such as playing formation and
tactics, time spent in ball possession, opposition ranking, standard of play, location
(­home or away match), effective ­ball-­​­­in-​­play time, pacing strategy, and score status
260 Christopher Carling and Naomi Datson

Scoreline
Result

Fitness
Physical &
Standard of
physiological
play &
status
opposition
Age
Maturity

MATCH RUNNING
PERFORMANCE

Positional
role Team Ball
formation possession
Substitutes Ball in play
Cautions time
Pacing
Location
Environment
Fixture
congestion

­Figure 16.2 A summary of the numerous factors influencing soccer m

­ atch-​­play running
performance.

have been comprehensively investigated (­see Bush et al., 2015; Trewin et al., 2018). The
evidence of a deleterious effect on m ­ atch-­​­­to-​­match performance when players are ex-
posed to fixture congestion, where multiple matches are played over short and long
periods, has not been conclusive (­Julian et al., 2020). Environmental factors such as
altitude and temperature (­both heat and cold) can affect m ­ atch-​­running due to physi-
ological limitations and possible subconscious pacing while performing in these envi-
ronments (­Trewin et al., 2018). A recent review synthesises the relationships between
match running performance and player anthropometric, maturity, and physical fitness
characteristics (­Aquino et al., 2020a).
Finally, it is important to mention that studies reporting the influence of situational
and environmental factors have generally examined these in an isolated manner.
While no single study can comprehensively measure and control all these factors, it is
useful to try to verify the relative contribution of the independent variables to the var-
iance in match running performance before making inferences. Recently, researchers
have integrated and examined the influence of several contextual factors notably in
professional female (­Trewin et al., 2018) and youth male players (­Aquino et al., 2020b).
Moreover, a novel study focusing on the role of substitutes investigated the impact on
performance of substitution timing, score line, and match location, helping coaches
assess the efficacy of their substitution strategies (­Hills et al., 2020b).
 Analysis of physical performance in match-play 261
Practical implications of t­ ime-​­motion analyses

Physical conditioning strategies

As part of the contemporary coaching process, empirical information derived from
­time–​­motion analyses of physical performance in competition are essential to provide
a platform for making objective decisions relating to fitness training and match prepa-
ration. The aim of a soccer physical conditioning programme is to prepare players to
cope with the i­ ntermittent-​­endurance demands of ­match-​­play and the necessity to per-
form intense efforts repeatedly and recover from these when called upon, both in and
out of ball possession. T ­ ime-​­motion analyses provide information on the overall vol-
ume of exercise, represented by the overall distance covered, while the total distances
covered at various exercise intensities offer global measures of the physiological strain
imposed on players (­Strudwick & Iaia, 2018). Information on the ratio of ­exercise-­​
­­to-​­rest periods and ­h igh-​­intensity versus ­low-​­intensity outputs (­using the time spent
and/­or distance covered in each) is pertinent. Indices such as h ­ igh-​­metabolic load and
speed exertion and dynamic stress loads are commonly used.
The creation of a typical match profile can be used as part of the foundation from
which daily and weekly training workload is structured and tailored to ensure that
players are replicating or ­over-​­or ­under-​­loading match demands. For example, a prac-
titioner may use a simple 4 vs. 4 ­small-​­sided game (­SSG, pitch size: 25 × 30 m, ­3-​­min
duration) to overload mechanical work (­accelerations, decelerations, and changes of
direction events), whereas a 10 vs. 10 SSG (­pitch size: 102 × 67 m, ­30-​­min) can over-
load total and ­h igh-​­intensity distance compared to relative match demands (­Lacome
et al., 2018b).
Profiling the frequency of repeated h ­ igh-​­intensity efforts and time spent in recov-
ery as well as the type of recovery activity (­active or passive) between discrete intense
bouts of exercise is particularly pertinent when designing h ­ igh-​­intensity condition-
ing drills to simulate match demands. For example, simple isolated repeated ­h igh-​
i­ ntensity drills could be designed using w ­ ork-​­recovery data derived from ­match-​­play
analyses. Sets of multiple h ­ igh-​­intensity bouts (>19.1 km h-​­1) separated by approx-
imately ­60-​­s recovery intervals (­Bradley et al., 2009) or incorporating shorter and
longer ­b etween-​­bout recovery intervals based on the data reported in ­Table 16.3.
Analysis of the locomotor activity during recovery intervals between consecutive
­h igh-​­intensity efforts can also be used to impact upon h ­ igh-​­intensity drill design.
Data gathered in France showed that recovery phases were mostly active in na-
ture with 37% of movements performed at velocities ranging from 7.1 to 19.7 km h-​­1
(­Carling, Le Gall & Dupont, 2012).
The most intense or peak 5­ -​­min blocks of m ­ atch-​­play running activity provide crit-
ical information for designing fi ­ eld-​­based conditioning drills. Information collected
on these most intense periods of play helps quantify “­worst case” match scenarios
(­Carling et al., 2019). An analysis of the length of recovery and running outputs fol-
lowing peak activity periods can give an indication of player ability to resist transient
fatigue, as well as having implications for fitness training regimens. In a group of pro-
fessional players, following a peak period of activity, h ­ igh-​­intensity distance remained
reduced by up to 30% in the 5th minute after, in comparison to the match average
(­Schimpchen, Gopaladesikan & Meyer, 2020). ­High-​­intensity conditioning drills can
provide the necessary training stimulus to help players respond to such demands. For
262 Christopher Carling and Naomi Datson
­Table 16.3 M
 ean recovery duration between sprints using individualised speed thresholds and
frequency of recovery periods according to the time elapsed between consecutive
sprints, collectively and in relation to positional role in German Bundesliga players
(­data adapted from Schimpchen et al., 2016)

­ entre-​
C
Recovery All players ­forwards
duration (­n = 2514) Defenders Midfielders (­n = 263)

Central Fullbacks Holding Wide Attacking

(­n = 296) (­n = 559) (­n = 518) (­n = 655) (­n = 223)

Mean 274.3 415.8 275.1 232.8 243.7 299.2 255.7

recovery
time (­s)
% <30 s 12.3 7.1 11.3 20.0 9.8 10.1 12.7
% 30.­1–​ 6.9 4.7 6.9 5.3 6.3 6.8 8.8
6­ 0 s
% >60 s 80.9 88.2 81.8 64.7 84.0 83.1 78.5

example, a 4 vs. 4 SSG drill ensures players perform the same relative number of accel-
erations and player load to that observed in a typical ­5-​­min peak match activity period
(­1.7 vs. 1.6 and = 248, vs. 227, respectively) (­Dalen et al., 2019).
Players must be able to perform at maximum levels consistently throughout m ­ atch-​
p
­ lay. Running performance is commonly analysed individually or collectively across
halves or towards the end of games (­e.g., final ­15-​­min interval) to identify whether
the team or an individual within the collective unit is susceptible to accumulated fa-
tigue. However, determining to what extent the reduction in running activity across
match periods can realistically be considered “­meaningful” is problematic (­Carling,
2013). Analysis of physical efforts such as in the first 5 min of play of the match and
immediately after the ­half-​­time pause, might give an idea of physical “­readiness”
of players and has implications for the intensity and duration of w ­ arm-​­up routines.
For example, the quantification of running outputs during ­warm-​­up practices in
substitutes in English professional soccer led to modification of their ­pre-­​­­pitch-​
­entry routines, subsequently improving physical performance ­on-­​­­pitch- ​­entry (­Hills
et al. 2020a).
Characterising match demands across age categories can potentially be used to es-
tablish ­age-​­specific performance profiles. Ramos et al. (­2019) reported substantially
higher values in match demands in senior versus U/­20 and U/­17 female Brazilian na-
tional team players, suggesting a need to tailor physical preparation for entry into
the adult professional game. However, m ­ atch-​­running performance develops nonlin-
early across age categories with large individual variations (Saward et al. 2016; see
­Figure 16.3). In addition, m ­ atch-​­running activity should not be considered a marker
of player potential to “­make the grade” (­Carling & Collins, 2017) especially as there is
generally little association between competitive physical performance and “­success”
in professional soccer. Nevertheless, it remains pertinent to characterise the demands
across different leagues and competitions. The distance covered at high intensities was
inferior in the English Premier League when compared with the Championship, while
players moving down from the former to compete in the latter demonstrated substan-
tially higher physical outputs (­Bradley et al., 2013).
 Analysis of physical performance in match-play 263

3000

2500

2000
(m)

1500

1000

500

0
U9 U10 U11 U12 U13 U14 U15 U16 U17 U18
(n=23) (n=61) (n=84) (n=90) (n=117) (n=132) (n=79) (n=138) (n=112) (n=150)

­Figure 16.3 ­High-​­intensity m
­ atch-​­running performance in elite youth soccer players ac-
cording to age group (­data adapted from Saward et al., 2016).

Finally, t­ ime-​­motion analyses can help tailor physical conditioning programmes

to account for the statistically significant differences in athletic demands re-
ported earlier across individual playing positions. Yet, in r­eal-​­world terms, the
“­m agnitude” of some of these differences is questionable, potentially raising doubts
about the practical necessity for ­p osition-​­specific fitness training interventions
(­C arling, 2013), especially when based solely on simple volume and intensity met-
rics. An integrated approach assimilating physical, tactical, and technical data is
more pertinent for training. Innovative recent work (­Bradley et al., 2018, 2019) has
translated the movement patterns, technical skills, and tactical actions associated
with ­h igh-​­intensity efforts into practical metrics that can be employed to construct
­p osition-​­specific attacking and defending conditioning drills. For example, ­full-​
­backs and wide midfielders frequently produce more ­h igh-​­intensity efforts when
running to overlap and “­r un the channel” followed by crosses when compared to
other positions.

Player monitoring and management

Sports scientists and fitness practitioners aim to ensure that players perform consist-
ently from one match to the next across the entire season. Current physical fitness lev-
els should always enable them to express themselves tactically and technically, while
reducing the risk of injury. Contemporary schedules require participation in ­one-​­or
­two-​­match weekly ­m icro-​­cycles. A greater exposure to ­match-​­play and subsequent
running loads can favour the maintenance and/­or improvement of physical capaci-
ties relevant to performance (­Dalen & Lorås, 2019). This factor has implications for
managing preparation of the squad and especially the training requirements of start-
ing and ­non-​­starting players, particularly during ­one-​­match weeks. ­High-​­intensity
264 Christopher Carling and Naomi Datson
compensation sessions can be implemented for used or unused substitutes in relation
to m ­ atch-​­play demands (­Buchheit et al., 2020).
Impairments in physical, physiological, and perceptual performance indices can
occur for up to 72 h following m ­ atch-​­play (­Carling et al., 2018). F ­ orty-​­eight hours af-
ter the game is probably the most critical time as muscle soreness tends to be at its
highest level although the time course and magnitude of these changes are ­individual-​
­dependent (­Strudwick & Iaia, 2018). Quantifying the physical efforts in any one match
can help to ascertain the potential magnitude of ensuing ­post-​­match fatigue, hence
readiness to train, and management of future exposure and training content. It is note-
worthy that for every 1­ 00-​­m run above 19.8 km h-​­1 during soccer m ­ atch-​­play, creatine
kinase activity measured 24 h p ­ ost-​­match can increase by 30% and countermovement
jump peak power output can decrease by 0.5% (­Hader et el., 2019). Therefore, a larger
than usual volume of h ­ igh-​­intensity running could incrementally impact on recovery
time and subsequently readiness to train.
During congested periods where two matches are played per week, players may be
at risk of exposure while not fully recovered, potentially increasing the propensity of
underperformance and injury. As such, there is potential for utilising data derived
from ­time-​­motion analyses to determine the extent to which players are “­coping” with
such schedules. Yet, collective analyses of m ­ atch-­​­­to-​­match performance using meas-
ures of total distance run and that covered in h ­ igh-​­intensity generally report statisti-
cally ­non-​­significant drops across either short or longer congested schedules, implying
that teams are able to maintain running performance (­Julian et al., 2020). It has been
suggested that these ­distance-​­based variables lack sensitivity and alternative measures
quantifying the frequency of shorter h ­ igh-​­intensity locomotor actions are necessary
(­Arruda et al., 2015). Strong associations have been reported between the frequency of
hard accelerations and changes of direction and the magnitude of ­post-​­match fatigue
determined by decrements in physical, physiological, and perceptual performance in-
dices (­Nedelec et al., 2014).
The large ­match-­​­­to-​­match variability (% CV) reported generally both across the
season, and specifically when successive matches are separated by minimal recov-
ery time (­linked in part to the contextual factors discussed earlier in this chapter),
potentially masks any “­meaningful” drops in collective and individual running pro-
files across congested periods (­Carling et al., 2015). A recent study has attempted to
establish the practical significance of individual m ­ atch-­​­­to-​­match changes in running
performance using a Minimum Effects Testing framework to highlight changes be-
yond “­normal” ­match-­​­­to-​­match variability (­­Oliva-​­Lozano et al., 2020). The authors
suggested that ­between-​­match individual changes of ±~­10–​­15% in measures of total
distance, total accelerations and maximum running velocity were of practical signifi-
cance. A more holistic approach to performance monitoring during fixture congestion
is necessary via integration of tactical and technical indices into the match profile.

Implications for injury prevention

In professional m­ atch-​­play, the mean distance and duration of sprint runs are rel-
atively short with distances rarely exceeding 20 m and 4 s in duration and the oc-
currence of ­near-­​­­to-​­maximal speed running bouts is low (­Buchheit et al., 2020).
However, ­time-​­motion analysis has shown a potential link between injury risk and
 Analysis of physical performance in match-play 265
sprinting when the distance and duration of individual sprint runs were substan-
tially greater than the habitual profile of the player. Physical training typically aims
to mimic the physical intensity and movement patterns of m ­ atch-​­play but can result
in u­ nder-​­exposure to h­ igh-​­speed running owing to the use of smaller areas, par-
ticularly in ­small-​­sided games in training (­Buckthorpe et al., 2019). Players may be
underprepared to respond on the rare occasions they must perform a longer sprint
and, as such, are at increased risk of injury. Accordingly, researchers have shown
that exposure to bouts of maximal velocity running (>95% maximum velocity) can
produce a protective effect and help reduce hamstring injury risk in team sports
players (­Malone et al., 2018).
The quantification of peak periods of match locomotor activity is considered im-
portant to help prepare players for the most intense periods of ­match-​­play. Research-
ers have demonstrated a harmful association for the volume of sprinting performed
prior to injury occurrences in professional soccer m ­ atch-​­play (­Carling et al., 2010;
Gregson et al., 2020). Gregson and colleagues (­2020) recommended preparing play-
ers to sustain and repeat s­ print-​­type activity during m­ atch-​­play as part of any injury
prevention strategy. While exercise bouts requiring multiple sprints repeated over a
short time are relatively rare (­Schimpchen et al., 2016), players must be able to respond
physically and not “­break down” when play requires them to perform these “­worse
case” scenarios.
Finally, ­time-​­motion data have potential for use in monitoring running performance
on return to competition. Portillo et al. (­2020) and Whiteley et al. (­2020) reported that
following a muscular injury (­causing >8 days lay off) match ­h igh-​­intensity outputs
(­distance covered and/­or maximum speed) can be considerably affected.

Future directions and conclusions

Processes are slowly evolving from the generation of data that provide a rudimentary
description of what has happened to intelligent systems that attempt to answer why it
happened, then predict what might happen and inform prescription to make it happen.
Within these processes, current technologies within the contemporary match perfor-
mance analysis ecocycle are constantly being supplanted by improved or novel tools
enabling r­ eal-​­time and simultaneous capture of different sources of information, nota-
bly via wearable sensors. These include sensors embedded in smart clothing and foot-
wear or worn as simple patches placed on the skin or even ingested orally. A myriad
of information relating to biochemical markers, heart rate patterns, neuromuscular
activity, joint speeds, contact forces, and 3D motion is progressively complementing
data habitually gathered on running volume and intensity. Irrespective of the technol-
ogy adopted, it is imperative that strong evidence relating to validity and reliability in
addition to safety checks is independently established. In addition, machine or deep
learning model approaches to automatise sport movement recognition are showing
strong potential to enhance both the efficiency and accuracy of sport performance
analysis (­Cust et al., 2019). A pertinent and practical example in soccer is work de-
scribed by Bradley (­2020) combining techniques from machine learning and neural
network analyses to facilitate the contextualisaton and classification of the tactical
purpose of h ­ igh-​­intensity activities (­e.g., overlapping run for a full back) and collec-
tively for the team (­e.g., closing opposition players).
266 Christopher Carling and Naomi Datson
Automatised and intelligent systems exist to aid analysis and interpretation of the
masses of complex data generated. These notably help to separate the “­noise” from
the “­signal” within datasets to identify meaningful changes in performance outputs,
as well as providing insightful key actionable indicators and advanced statistical mod-
els. Recently, machine learning techniques have predicted workload responses to aid
periodisation of future training sessions (­Jaspers et al., 2018, Rossi et al., 2018). Addi-
tional work, notably in conjunction with the expert knowledge of elite practitioners,
is required to further advance this area. Finally, advanced graphic telestration tools
(­e.g., Coachpaint by Chyron Hygo) and data visualisation dashboards designed using
business intelligence software (­e.g., Tableau, Microsoft Power BI) are being increasingly
employed by sports scientists and conditioning coaches. These aid translation of data
into ­eye-​­catching, easy to understand and impactful soccer visuals engaging coach ­buy-​
i­ n and supporting ­decision-​­making processes (­Lacome, Simpson & Buchheit, 2018a).
In this chapter, we provided a brief overview of the different technologies commonly
used to collect data on physical performance in contemporary professional soccer
­match-​­play. We presented examples of published data from the accumulated scientific
knowledge base illustrating general and ­position-​­specific demands, the occurrence of
fatigue, as well as contextual factors that impact performance in competition. Finally,
information on how the data generated from analyses can be used in practice to objec-
tively impact upon d ­ ecision-​­making processes by supporting the physical conditioning
elements of player development and match preparation was discussed. It is clear that
both the knowledge base and expertise relating to physical performance in ­match-​
p
­ lay have grown considerably, particularly over the last decade, playing a key role in
aiding sports scientists and practitioners join up the many components underpinning
performance in soccer.

References
Abbott, W., Brickley, G., & Smeeton, N. J. (­2018). Physical demands of playing position within
English Premier League academy soccer. Journal of Human Sport and Exercise, 13(­2), ­285–​
­295. https://­doi.org/­10.14198/­jhse.2018.132.04
Aquino, R., Carling, C., Maia, J., Vieira, L. H. P., Wilson, R. S., Smith, N., Almeida, R.,
Gonçalves, L. G. C., ­Kalva-​­Filho, C. A., Garganta, J., & Puggina, E. F. (­2020a). Relation-
ships between running demands in soccer m ­ atch-​­play, anthropometric, and physical fitness
characteristics: a systematic review. International Journal of Performance Analysis in Sport,
20(­3), ­534–​­555. https://­doi.org/­10.1080/­24748668.2020.1746555
Aquino, R., Carling, C., Palucci Vieira, L. H., Martins, G., Jabor, G., Machado, J., Santiago,
P., Garganta, J., & Puggina, E. (­2020b). Influence of situational variables, team formation,
and playing position on match running performance and social network analysis in Brazilian
professional soccer players. Journal of Strength and Conditioning Research, 34(­3), ­808–​­817.
https://­doi.org/­10.1519/­jsc.0000000000002725
Aquino, R. L. Q. T., Gonçalves, L. G. C., Vieira, L. H. P., Oliveira, L. P., Alves, G. F., Santi-
ago, P. R. P., & Puggina, E. F. (­2016). Biochemical, physical and tactical analysis of a simu-
lated game in young soccer players. Journal of Sports Medicine and Physical Fitness, 56(­12),
­1554–​­1561
Arruda, A. F. S., Carling, C., Zanetti, V., Aoki, M. S., Coutts, A. J., & Moreira, A. (­2015).
Effects of a very congested match schedule on b ­ ody-​­load impacts, accelerations, and run-
ning measures in youth soccer players. International Journal of Sports Physiology and Perfor-
mance, 10(­2), ­248–​­252. https://­doi.org/­10.1123/­ijspp.­2014- ​­0148
 Analysis of physical performance in match-play 267
Atan, S. A., Foskett, A., & Ali, A. (­2016). Motion analysis of match play in New Zealand U13
to U15 ­age-​­group soccer players. Journal of Strength and Conditioning Research, 30(­9), ­2416–​
­2423. https://­doi.org/­10.1519/­JSC.0000000000001336
Bradley, P. S. (­2020). Football Decoded: Using Match Analysis & Context to Interpret the
Demands. Independently published.
Bradley, P. S., & Ade, J. D. (­2018). Are current physical match performance metrics in elite soc-
cer fit for purpose or is the adoption of an integrated approach needed? International Journal
of Sports Physiology and Performance, 13(­5), ­656– ​­664. https://­doi.org/­10.1123/­ijspp.­2017- ​­0433
Bradley, P. S., Carling, C., Gomez Diaz, A., Hood, P., Barnes, C., Ade, J., Boddy, M., Krustrup,
P., & Mohr, M. (­2013). Match performance and physical capacity of players in the top three
competitive standards of English professional soccer. Human Movement Science, 32(­4), ­808–​
­821. https://­doi.org/­10.1016/­j.humov.2013.06.002
Bradley, P. S., Dellal, A., Mohr, M., Castellano, J., & Wilkie, A. (­2014). Gender differences in
match performance characteristics of soccer players competing in the UEFA Champions
League. Human Movement Science, 33, ­159–​­171. https://­doi.org/­10.1016/­j.humov.2013.07.024
Bradley, P S, Di Mascio, M., Mohr, M., Fransson, D., Wells, C., Moreira, A., Castellano, J.,
Gómez, A., & Ade, J. (­2018). Can modern football match demands be translated into novel
training and testing modes? Aspetar Sports Medicine Journal, 7(­June), ­9 –​­13.
Bradley, P. S., Di Mascio, M., Peart, D., Olsen, P., & Sheldon, B. (­2010). H ­ igh-​­intensity activity
profiles of elite soccer players at different performance levels. Journal of Strength and Condi-
tioning Research, 24(­9), ­2343–​­235. https://­doi.org/­10.1519/­jsc.0b013e3181aeb1b3
Bradley, P. S., M ­ artin-​­Garcia, A., Ade, J. D., & G ­ omez-​­Diaz, A. (­2019). Position specific &
positional play training in elite football: context matters. Football Med & Perform, 29, ­31–​­35.
Bradley, P. S., Sheldon, W., Wooster, B., Olsen, P., Boanas, P., & Krustrup, P. (­2009). ­High-​
­intensity running in English FA premier league soccer matches. Journal of Sports Sciences,
27(­2), ­159–​­168. https://­doi.org/­10.1080/­02640410802512775
Buchheit, M., Allen, A., Poon, T. K., Modonutti, M., Gregson, W., & Di Salvo, V. (­2014). Inte-
grating different tracking systems in football: multiple camera s­ emi-​­automatic system, local
position measurement and GPS technologies. Journal of Sports Sciences, 32(­20), ­1844–​­1857.
https://­doi.org/­10.1080/­02640414.2014.942687
Buchheit, M., ­Mendez-​­Villanueva, A., Simpson, B. M., & Bourdon, P. C. (­2010). ­Repeated-​
­sprint sequences during youth soccer matches. International Journal of Sports Medicine,
31(­10), ­709–​­716. https://­doi.org/­10.1055/­­s-­​­­0 030-​­1261897
Buchheit, M., & Simpson, B. M. (­2017). ­Player-​­tracking technology: ­half-​­full or ­half-​­empty
glass? International Journal of Sports Physiology and Performance, 12(­s2), ­S2–​­S35. https://­doi.
org/­10.1123/­ijspp.­2016-​­0499
Buchheit, M., Simpson, B. M., Hader, K., & Lacome, M. (­2021). 5(2), 105–110 Occurrences
of ­near-­​­­to-​­maximal ­speed-​­r unning bouts in elite soccer: insights for training prescrip-
tion and injury mitigation. Science and Medicine in Football, 1-6 https://­doi.org/­10.1080/
­24733938.2020.1802058
Buckthorpe, M., Wright, S., ­Bruce-​­Low, S., Nanni, G., Sturdy, T., Gross, A. S., Bowen, L.,
Styles, B., Della Villa, S., Davison, M., & Gimpel, M. (­2019). Recommendations for ham-
string injury prevention in elite football: translating research into practice. British Journal of
Sports Medicine, 53(­7), ­449– ​­456. https://­doi.org/­10.1136/­­bjsports-­​­­2018- ​­099616
Bush, M. D., Archer, D. T., Hogg, R., & Bradley, P. S. (­2015). Factors influencing physical and
technical variability in the English premier league. International Journal of Sports Physiology
and Performance, 10(­7), ­865– ​­872. https://­doi.org/­10.1123/­ijspp.­2014- ​­0484
Carling, C. (­ 2013). Interpreting physical performance in professional soccer ­ match-​­play:
should we be more pragmatic in our approach? Sports Medicine, 43(­8), ­655–​­663. https://­doi.
org/­10.1007/­­s40279-­​­­013-­​­­0 055-​­8
Carling, C., Gregson, W., McCall, A., Moreira, A., Wong, delP., & Bradley, P. S. (2015).
Match running performance during fixture congestion in elite soccer: research issues and
268 Christopher Carling and Naomi Datson
future directions. Sports medicine (Auckland, N.Z.), 45(5), 605–613. https://doi.org/10.1007/
s40279-015-0313-z
Carling, C., Bradley, P., McCall, A., & Dupont, G. (­2016). ­Match-­​­­to-​­match variability in ­h igh-​
­speed running activity in a professional soccer team. Journal of Sports Sciences, 34(­24), ­2215–​
­2223. https://­doi.org/­10.1080/­02640414.2016.1176228
Carling, C., & Collins, D. (­2017). Comment on match analysis of U9 and U10 English premier
league academy soccer players using a global positioning system. Journal of Strength and
Conditioning Research, 31(­2), ­e61–​­e63. https://­doi.org/­10.1519/­jsc.0000000000000466
Carling, C., & Dupont, G. (­2011). Are declines in physical performance associated with a reduc-
tion in ­skill-​­related performance during professional soccer ­match-​­play? Journal of Sports
Sciences, 29(­1), ­63–​­71. https://­doi.org/­10.1080/­02640414.2010.521945
Carling, C., Lacome, M., McCall, A., Dupont, G., Le Gall, F., Simpson, B., & Buchheit, M.
(­2018). Monitoring of p ­ ost-​­match fatigue in professional soccer: welcome to the real world.
Sports Medicine, 48(­12), ­2695–​­2702. https://­doi.org/­10.1007/­­s40279-­​­­018-­​­­0935-​­z
Carling, C., Le Gall, F., & Dupont, G. (­2012). Analysis of repeated ­h igh-​­intensity running
performance in professional soccer. Journal of Sports Sciences, 30(­4), ­325–​­336. https://­doi.
org/­10.1080/­02640414.2011.652655
Carling, C., Le Gall, F., & Reilly, T. P. (­2010). Effects of physical efforts on injury in elite soc-
cer. International Journal of Sports Medicine, 31(­03), ­180–​­185. https://­doi.org/­10.1055/­­s-­​­­0 029-​­
1241212
Carling, C., McCall, A., Harper, D., & Bradley, P. S. (­2019). The use of microtechnology to
quantify the peak match demands of the football codes: a systematic review. Sports Medicine,
49(­2), ­343–​­345. https://­doi.org/­10.1007/­­s40279-­​­­018-­​­­1032-​­z
Castellano, J., & Casamichana, D. (­2010). Heart rate and motion analysis by GPS in beach soc-
cer. Journal of Sports Science and Medicine, 9(­1), ­98–​­103. http://­w ww.jssm.org
Curtis, R. M., Huggins, R. A., Benjamin, C. L., Sekiguchi, Y., Adams, W. M., Arent, S. M.,
Jain, R., Miller, S. J., Walker, A. J., & Casa, D. J. (­2020). Contextual factors influencing
external and internal training loads in collegiate men’s soccer. Journal of Strength and Condi-
tioning Research, 34(­2), ­374–​­381. https://­doi.org/­10.1519/­jsc.0000000000003361
Cust, E. E., Sweeting, A. J., Ball, K., & Robertson, S. (­2019). Machine and deep learning for ­sport-​
­specific movement recognition: a systematic review of model development and performance.
Journal of Sports Sciences, 37(­5), ­568– ​­600. https://­doi.org/­10.1080/­02640414.2018.1521769
Dalen, T., & Lorås, H. (­2019). Monitoring training and match physical load in junior soccer
players: starters versus substitutes. Sports, 7(­3), 70. https://­doi.org/­10.3390/­sports7030070
Dalen, T., Sandmæl, S., Stevens, T., Hjelde, G. H., Kjøsnes, T. N., & Wisløff, U. (­2021). Differ-
ences in acceleration and h ­ igh-​­intensity activities between s­ mall-​­sided games and peak peri-
ods of official matches in elite soccer players. Journal of Strength and Conditioning Research.
35(7), 2018–2024 10.1519/­JSC.0000000000003081. Advance online publication.
Datson, N., Drust, B., Weston, M., & Gregson, W. (­2019). Repeated ­h igh-​­speed running in elite
female soccer players during international competition. Science and Medicine in Football,
3(­2), ­150–​­156. https://­doi.org/­10.1080/­24733938.2018.1508880
Datson, N., Drust, B., Weston, M., Jarman, I. H., Lisboa, P. J., & Gregson, W. (­2017). Match
physical performance of elite female soccer players during international competition.
Journal of Strength and Conditioning Research, 31(­9), ­2379–​­2387. https://­doi.org/­10.1519/
­JSC.0000000000001575
Dellal, A., Chamari, K., Wong, D. P., Ahmaidi, S., Keller, D., Barros, R., Bisciotti, G. N., &
Carling, C. (­2011). Comparison of physical and technical performance in European soccer
­match-​­play: Fa Premier League and La Liga. European Journal of Sport Science, 11(­1), ­51–​­59.
https://­doi.org/­10.1080/­17461391.2010.481334
Di Salvo, V., Baron, R., Tschan, H., Calderon Montero, F. J., Bachl, N., & Pigozzi, F. (­2007).
Performance characteristics according to playing position in elite soccer. International Jour-
nal of Sports Medicine, 28(­3), ­222–​­227. https://­doi.org/­10.1055/­­s-­​­­2006-​­924294
 Analysis of physical performance in match-play 269
Di Salvo, V., Gregson, W., Atkinson, G., Tordoff, P., & Drust, B. (­2009). Analysis of high in-
tensity activity in premier league soccer. International Journal of Sports Medicine, 30(­3), ­205–​
­212. https://­doi.org/­10.1055/­­s-­​­­0 028-​­1105950
Di Salvo, V., Baron, R., ­González-​­Haro, C., Gormasz, C., Pigozzi, F., & Bachl, N. (­2010). Sprint-
ing analysis of elite soccer players during European champions league and UEFA cup matches.
Journal of Sports Sciences, 28(­14), ­1489–​­1494. https://­doi.org/­10.1080/­02640414.2010.521166
Drust, B., Atkinson, G., & Reilly, T. (­2007). Future perspectives in the evaluation of the physio-
logical demands of soccer. Sports Medicine, 37(­9), ­783– ​­805. https://­doi.org/­10.2165/­­0 0007256-
­​­­200737090-​­0 0003
Fereday, K., Hills, S. P., Russell, M., Smith, J., Cunningham, D. J., Shearer, D., McNarry, M., &
Kilduff, L. P. (­2020). A comparison of rolling averages versus discrete time epochs for assess-
ing the w ­ orst-​­case scenario locomotor demands of professional soccer m ­ atch-​­play. Journal of
Science and Medicine in Sport, 23(­8), ­764–​­769. https://­doi.org/­10.1016/­j.jsams.2020.01.00
Gregson, W., Drust, B., Atkinson, G., & Salvo, V. (­2010). ­Match-­​­­to-​­match variability of ­h igh-​
­speed activities in premier league soccer. International Journal of Sports Medicine, 31(­04),
­237–​­242. https://­doi.org/­10.1055/­­s-­​­­0 030-​­1247546
Gregson, W., Di Salvo, V., Varley, M.C., Modonutti, M., Belli, A., Chamari, K., Weston, M.,
Lolli, L., & Eirale, C. (2020). Harmful association of sprinting with muscle injury occurrence
in professional soccer match-play: a two-season, league wide exploratory investigation from
the Qatar Stars League. Journal of Science and Medicine in Sport, 23(2), 134–138. https://doi.
org/10.1016/j.jsams.2019.08.289
Hader, K., Rumpf, M. C., Hertzog, M., Kilduff, L. P., Girard, O., & Silva, J. R. (­2019). Monitor-
ing the athlete match response: can external load variables predict p ­ ost-​­match acute and resid-
ual fatigue in soccer? a systematic review with m ­ eta-​­analysis. Sports ­Medicine –​­ Open, 5(­1), 48.
­Harkness-​­Armstrong, A., Till, K., Datson, N., & Emmonds, S. (­2021). Whole and peak physical
characteristics of elite youth female soccer m ­ atch-​­play. Journal of Sports Sciences, ­39(12),
1320–1329 https://­doi.org/­10.1080/­02640414.2020.1868669
Harper, D. J., Carling, C., & Kiely, J. (­2019). ­High-​­intensity acceleration and deceleration de-
mands in elite team sports competitive match play: a systematic review and ­meta-​­analysis
of observational studies. Sports Medicine, 49(­12), ­1923–​­1947. https://­doi.org/­10.1007/­­s40279-
­​­­019-­​­­01170-​­1
Hills, S. P., Barrett, S., Hobbs, M., Barwood, M. J., Radcliffe, J. N., Cooke, C. B., & Russell, M.
(­2020a). Modifying the ­pre-​­pitch entry practices of professional soccer substitutes may con-
tribute towards improved m ­ ovement-​­related performance indicators on ­match-​­day: a case
study. PloS One, 15(­5), e0232611. https://­doi.org/­10.1371/­journal.pone.0232611
Hills, S. P., Barrett, S., Thoseby, B., Kilduff, L. P., Barwood, M. J., Radcliffe, J. N., Cooke, C.
B., & Russell, M. (­2022). Quantifying the peak physical ­match-​­play demands of professional
soccer substitutes following ­pitch-​­entry: assessing contextual influences. Research Quarterly
for Exercise and Sport, ­93(2), 270-281 https://­doi.org/­10.1080/­02701367.2020.1823308
Hunter, F., Bray, J., Towlson, C., Smith, M., Barrett, S., Madden, J., Abt, G., & Lovell, R. (­2015).
Individualisation of ­time-​­motion analysis: a method comparison and case report series.
International Journal of Sports Medicine, 36(­1), ­41–​­48. https://­doi.org/­10.1055/­­s-­​­­0 034-​­1384547
Ingebrigtsen, J., Dalen, T., Hjelde, G. H., Drust, B., & Wisløff, U. (­2015). Acceleration and
sprint profiles of a professional elite football team in match play. European Journal of Sport
Science, 15(­2), ­101–​­110. https://­doi.org/­10.1080/­17461391.2014.933879
Jaspers, A., De Beéck, T. O., Brink, M. S., Frencken, W. G. P., Staes, F., Davis, J. J., & Helsen,
W. F. (­2018). Relationships between the external and internal training load in professional
soccer: what can we learn from machine learning? International Journal of Sports Physiology
and Performance, 13(­5), ­625–​­630. https://­doi.org/­10.1123/­ijspp.­2017-​­0299
Julian, R., Page, R. M., & Harper, L. D. (­2021). The effect of fixture congestion on performance
during professional male soccer ­match-​­play: a systematic critical review with ­meta-​­analysis.
Sports Medicine, ­51(2), 255-273 https://­doi.org/­10.1007/­­s40279-­​­­020-­​­­01359-​­9
270 Christopher Carling and Naomi Datson
Krustrup, P., Mohr, M., Steensberg, A., Bencke, J., Klær, M., & Bangsbo, J. (­2006). Mus-
cle and blood metabolites during a soccer game: implications for sprint performance.
Medicine and Science in Sports and Exercise, 38(­6), ­1165–​­1174. https://­doi.org/­10.1249/­01.
mss.0000222845.89262.cd
Lacome M., Simpson, B. M., & M. Buchheit. (­2018a). Part 2: Monitoring training status with
­player-​­tracking technology: still on the road to Rome. Aspetar Sports Medicine Journal, 7,
­57–​­66.
Lacome, M., Simpson, B. M., Cholley, Y., Lambert, P., & Buchheit, M. (­2018b). ­Small-​­sided
games in elite soccer: does one size fit all? International Journal of Sports Physiology and Per-
formance, 13(­5), ­568–​­576. https://­doi.org/­10.1123/­ijspp.­2017-​­0214
Linke, D., Link, D., Weber, H., & Lames, M. (­2018). Decline in match running performance in
football is affected by an increase in game interruptions. Journal of Sports Science and Med-
icine, 17, ­662–​­667. http://­l ibrary1.nida.ac.th/­termpaper6/­sd/­2554/­19755.pdf
Lovell, R., & Abt, G. (2013). Individualization of time-motion analysis: a case-cohort example.
International Journal of Sports Physiology and Performance, 8(4), 456–458. https://doi.org/
10.1123/ijspp.8.4.456
Malone, J. J., Lovell, R., Varley, M. C., & Coutts, A. J. (­2017). Unpacking the black box: ap-
plications and considerations for using GPS devices in sport. International Journal of Sports
Physiology and Performance, 12(­s2), ­S2– ​­S18. https://­doi.org/­10.1123/­ijspp.­2016- ​­0236
Malone, S., Owen, A., Mendes, B., Hughes, B., Collins, K., & Gabbett, T. J. (­2018). ­High-​­speed
running and sprinting as an injury risk factor in soccer: can w ­ ell-​­developed physical quali-
ties reduce the risk? Journal of Science and Medicine in Sport, 21(­3), ­257–​­262. https://­doi.org/­
10.1016/­j.jsams.2017.05.016
Mara, J. K., Thompson, K. G., Pumpa, K. L., & Morgan, S. (­2017a). Quantifying the ­h igh-​­speed
running and sprinting profiles of elite female soccer players during competitive matches us-
ing an optical player tracking system. Journal of Strength and Conditioning Research, 31(­6),
­1500–​­1508. https://­doi.org/­10.1519/­JSC.0000000000001629
Mara, J. K., Thompson, K. G., Pumpa, K. L., & Morgan, S. (­2017b). The acceleration and
deceleration profiles of elite female soccer players during competitive matches. Journal of
Science and Medicine in Sport, 20(­9), ­867–​­872. https://­doi.org/­10.1016/­j.jsams.2016.12.078
Mohr, M., Krustrup, P., & Bangsbo, J. (­2005). Fatigue in soccer: a brief review. Journal of
Sports Sciences, 23(­6), ­593–​­599. https://­doi.org/­10.1080/­02640410400021286
Nedelec, M., McCall, A., Carling, C., Legall, F., Berthoin, S., & Dupont, G. (­2014). The influence
of soccer playing actions on the recovery kinetics after a soccer match. Journal of Strength
and Conditioning Research, 28(­6), ­1517–​­1523. https://­doi.org/­10.1519/­jsc.0000000000000293
Ohmuro, T., Iso, Y., Tobita, A., Hirose, S., Ishizaki, S., Sakaue, K., & Yasumatsu, M. (­2020). Physi-
cal match performance of Japanese ­top-​­level futsal players in different categories and playing
positions. Biology of Sport, 37(­4), ­359–​­365. https://­doi.org/­10.5114/­BIOLSPORT.2020.96322
­Oliva-​­Lozano, J. M., Muyor, J. M., Fortes, V., & McLaren, S. J. (­2021). Decomposing the
variability of match physical performance in professional soccer: implications for mon-
itoring individuals. European Journal of Sport Science, 2­1(11), 1588-1596 https://­ doi.
org/­10.1080/­17461391.2020.1842513
Osgnach, C., Poser, S., Bernardini, R., Rinaldo, R., & Di Prampero, P. E. (­2010). Energy cost
and metabolic power in elite soccer: a new match analysis approach. Medicine and Science in
Sports and Exercise, 42(­1), ­170–​­178. https://­doi.org/­10.1249/­MSS.0b013e3181ae5cfd
Paul, D. J., Bradley, P. S., & Nassis, G. P. (­2015). Factors affecting match running performance
of elite soccer players: shedding some light on the complexity. International Journal of Sports
Physiology and Performance, 10(­4), ­516–​­519. https://­doi.org/­10.1123/­IJSPP.­2015-​­0 029
Piras, A., Raffi, M., Atmatzidis, C., Merni, F., & Di Michele, R. (­2017). The energy cost of
running with the ball in soccer. International Journal of Sports Medicine, 38(­12), ­877–​­882.
https://­doi.org/­10.1055/­­s-­​­­0 043-​­118340
 Analysis of physical performance in match-play 271
Portillo, J., Abián, P., Calvo, B., Paredes, V., & ­Abián-​­Vicén, J. (­2020). Effects of muscular inju-
ries on the technical and physical performance of professional soccer players. The Physician
and Sportsmedicine, 48(­4), ­437– ​­441. https://­doi.org/­10.1080/­0 0913847.2020.1744485
Ramos, G. P., Nakamura, F. Y., Penna, E. M., Wilke, C. F., Pereira, L. A., Loturco, I., Capelli,
L., Mahseredjian, F., S ­ ilami-​­Garcia, E., & Coimbra, C. C. (­2019). Activity profiles in U17,
U20, and senior womenʼs Brazilian national soccer teams during international competitions.
Journal of Strength and Conditioning Research, 33(­12), ­3414–​­3422. https://­doi.org/­10.1519/­jsc.
0000000000002170
Reilly, T. (­2005). An ergonomics model of the soccer training process. Journal of Sports Sciences,
23(­6), ­561–​­572. https://­doi.org/­10.1080/­02640410400021245
Ribeiro, J. N., Gonçalves, B., Coutinho, D., Brito, J., Sampaio, J., & Travassos, B. (­2020). Activ-
ity profile and physical performance of match play in elite futsal players. Frontiers in Psychol-
ogy, 11. https://pubmed.ncbi.nlm.nih.gov/32793058/
Rossi, A., Pappalardo, L., Cintia, P., Iaia, F. M., Fernàndez, J., & Medina, D. (­2018). Effective
injury forecasting in soccer with GPS training data and machine learning. PLoS one, 13(­7),
e0201264. https://­doi.org/­10.1371/­journal.pone.0201264
Russell, M., Sparkes, W., Northeast, J., Cook, C. J., Love, T. D., Bracken, R. M., & Kilduff, L.
P. (­2016). Changes in acceleration and deceleration capacity throughout professional soccer
­match-​­play. Journal of Strength and Conditioning Research, 30(­10), ­2839–​­2844. https://­doi.
org/­10.1519/­JSC.0000000000000805
Saward, C., Morris, J. G., Nevill, M. E., Nevill, A. M., & Sunderland, C. (­2016). Longitudinal
development of ­match-​­running performance in elite male youth soccer players. Scandina-
vian Journal of Medicine and Science in Sports, 26(­8), ­933–​­942. https://­doi.org/­10.1111/­sms.
12534
Schimpchen, J., Gopaladesikan, S., & Meyer, T. (­2021). The intermittent nature of player phys-
ical output in professional football matches: an analysis of sequences of peak intensity and
associated fatigue responses. European Journal of Sport Science, 2­ 1(6), 793-802 https://­doi.
org/­10.1080/­17461391.2020.1776400
Schimpchen, J., Skorski, S., Nopp, S., & Meyer, T. (­2016). Are “­classical” tests of ­repeated-​
­sprint ability in football externally valid? A new approach to determine i­n-​­game sprinting
behaviour in elite football players. Journal of Sports Sciences, 34(­6), ­519–​­526. https://­doi.
org/­10.1080/­02640414.2015.1112023
Scott, D., Haigh, J., & Lovell, R. (­2020). Physical characteristics and match performances in
women’s international versus ­domestic-​­level football players: a ­2-​­year, ­league-​­w ide study.
Science and Medicine in Football, 4(­3), ­211–​­215. https://­doi.org/­10.1080/­24733938.2020.1745265
Scott, D., & Lovell, R. (­2018). Individualisation of speed thresholds does not enhance the d ­ ose-​
­response determination in football training. Journal of Sports Sciences, 36(­13), ­1523–​­1532.
https://­doi.org/­10.1080/­02640414.2017.1398894
Simim, M. A. M., Da Mota, G. R., Marocolo, M., Da Silva, B. V. C., De Mello, M. T., & Brad-
ley, P. S. (­2018). The demands of amputee soccer impair muscular endurance and power in-
dices but not match physical performance. Adapted Physical Activity Quarterly, 35(­1), ­76–​­92.
https://­doi.org/­10.1123/­apaq.­2016- ​­0147
Strudwick, A. J., & Iaia, F. M. (­2018). Physical preparation of elite soccer players. In W. Greg-
son & M. Littlewood (­Eds.), Science in Soccer: Translating Theory into Practice (­pp.­63–​­83).
London: Bloomsbury Publishing.
Taberner, M., O’keefe, J., Flower, D., Philips, J., Morgans, R., Cohen, DD., Richter, C., Carling,
C. (­2020). Interchangeability of position tracking technologies; can we merge the data? Sci-
ence & Medicine in Football, 4, ­76– ​­81. https://­doi.org/­10.1080/­24733938.2019.1634279
Trewin, J., Meylan, C., Varley, M. C., Cronin, J., & Ling, D. (­2018). Effect of match factors on
the running performance of elite female soccer players. Journal of Strength and Conditioning
Research, 32(­7), ­2002–​­2009. https://­doi.org/­10.1519/­jsc.0000000000002584
272 Christopher Carling and Naomi Datson
Varley, M. C., Elias, G. P., & Aughey, R. J. (­2012). Current ­match-​­analysis techniques’ underes-
timation of intense periods of h ­ igh-​­velocity running. International Journal of Sports Physiol-
ogy and Performance, 7(­2), ­183–​­185. https://­doi.org/­10.1123/­ijspp.7.2.183
Vescovi, J. D. (­2012). Sprint profile of professional female soccer players during competitive
matches: female athletes in motion (­FAiM) study. Journal of Sports Sciences, 30(­12), ­1259–​
­1265. https://­doi.org/­10.1080/­02640414.2012.701760
Weston, M., Batterham, A. M., Castagna, C., Portas, M. D., Barnes, C., Harley, J., & Lovell,
R. J. (­2011). Reduction in physical match performance at the start of the second half in elite
soccer. International Journal of Sports Physiology and Performance, 6(­2), ­174–​­182. https://­doi.
org/­10.1123/­ijspp.6.2.174
White, A., Hills, S. P., Hobbs, M., Cooke, C. B., Kilduff, L. P., Cook, C., Roberts, C., & Russell,
M. (­2020). The physical demands of professional soccer goalkeepers throughout a w ­ eek-​­long
competitive microcycle and transiently throughout m ­ atch-​­play. Journal of Sports Sciences,
38(­8), ­848–​­854. https://­doi.org/­10.1080/­02640414.2020.1736244
Whiteley, R., Massey, A., Gabbett, T., Blanch, P., Cameron, M., Conlan, G., Ford, M., & Wil-
liams, M. (­2021). Match h ­ igh-​­speed running distances are often suppressed after return
from hamstring strain injury in professional footballers. Sports Health: A Multidisciplinary
Approach, 194173812096445. 13(3), 290-295 https://­doi.org/­10.1177/­1941738120964456
Lovell, R., & Abt, G. (2013). Individualization of time-motion analysis: a case-cohort exam-
ple. International Journal of Sports Physiology and Performance, 8(4), 456-458. https://doi:
10.1123/ijspp.8.4.456
Gregson, W., Di Salvo, V., Varley, M.C., Modonutti, M., Belli, A., Chamari, K., Weston, M.,
Lolli, L., & Eirale, C. (2020). Harmful association of sprinting with muscle injury occurrence
in professional soccer match-play: a two-season, league wide exploratory investigation from
the Qatar Stars League. Journal of Science and Medicine in Sport, 23(2), 134-138. https://doi.
org/10.1016/j.jsams.2019.08.289
17 Technical and tactical match analysis
Allistair P. McRobert, Javier ­Fernández-​­Navarro and
Laura Seth

Introduction
Over the past two decades, match analysis has become an integral part of the coaching
process, coupled with an increase in published research on the topic (­Sarmento et al., 2018,
2014). The considerable growth of match analysis is due to an increase in performance
analysts with specific expertise and developments in software, making it more accessi-
ble to coaches, players, clubs, and organisations. The systems have become easier to use
through integration of digital video footage and computer technology, so there is no longer
a need for analysts with computer science or statistics degrees (­James, 2006). Licensed
and ­subscription-​­based ­self-​­coding software such as hudlsportscode (­https://­hudl.
com), nacsport (­https://­nacsport.com), Dartfish (­https://­dartfish.com), and LongoMatch
(­https://­longomatch.com) are ­cost-​­effective or free platforms that have increased the inte-
gration of performance analysis into the ­coach-­​­­athlete-​­sport science relationship (­Drust,
2010; Lago, 2009). In addition, valid and reliable ­semi-​­automated computer tracking, lo-
cal position measurement (­LPM), and global position systems (­GPS) that log event data
and monitor player position, velocity, and movement patterns provide large volumes of
technical, tactical, and physical performance data (­Bradley, O’Donoghue, Wooster, &
Tordoff, 2007; Cummins, Orr, O’Connor, & West, 2013; Frencken, Lemmink, & Del-
leman, 2010; Olthof, Frencken, & Lemmink, 2018; Valter, Adam, Barry, & Marco,
2006). Companies such as Stats Perform (­https://­statsperform.com), Second Spectrum
(­
https://­secondspectrum.com), and Chyron Hego (­ https://­
chyron.com) provide coding
and analysis services during and after the match. Whereas LPM and GPS companies like
Catapult (­https://­catapultsports.com), STATSports (­https://­statsports.com), and Inmotio
(­https://­inmotio.eu) allow sports scientists to monitor players during training and matches.
Prior to these advancements, analysis of technical and tactical performance in team
games was completed through game observation. These qualitative game observations
were less objective, comprehensive, and systematic. Using the subjective observer impres-
sions slowed the analysis process and relied on the coaches’ experiences and expertise. In
contrast, quantitative game observations are more objective and comprehensive due to
systematic categorisation of behavioural data (­Memmert, Lemmink, & Sampaio, 2016).
Furthermore, majority of clubs integrate performance analysis data into their work-
flows so that it informs the ­decision-​­making processes of key stakeholders (­i.e., coaches
and players). Performance analysts often use video and data for ­pre-​­match analysis, live
feedback, ­post-​­match analysis and feedback, opposition analysis, scouting/­recruitment
analysis, trend data analysis, data visualisation, and video telestration (­Jones, Rands, &
Butterworth, 2020; Wright, Atkins, Jones, & Todd, 2013).

DOI: 10.4324/9781003148418-21
274 Allistair P. McRobert et al.
The earliest published match analysis research was by Reep and Benjamin (­1968),
and for further background on how Reep influenced soccer notational and perfor-
mance analysis, see Pollard (­2002). Since then, scientific literature has significantly
increased and the area now has international societies (­e.g., International Society
of Performance Analysis of Sport), specialist journals (­e.g., International Journal
of Performance Analysis in Sport, Journal of Quantitative Analysis in Sports, Sci-
ence and Medicine in Football), international conferences (­e.g., World Congress
of Performance Analysis in Sport, World Congress on Science and Soccer), and
published books (­e.g., Jayal, McRobert, Oatley, & O’Donoghue, 2018; McGarry,
O’Donoghue, & Sampaio, 2013). However, there are often disconnects between re-
search and application due to a lack of context (­e.g., opposition style of play, home
advantage, current s­ core-​­line, and officiating decisions) and s­ituation-​­specific in-
formation (­e.g., the pitch location where actions took place, quality of the pass or
ball control, quality of player d ­ ecision-​­making and skill) on variables measured
(­Carling, Wright, Nelson, & Bradley, 2013; Mackenzie & Cushion, 2012; Sarmento
et al., 2014). More recently, researchers have access to larger event and positional
data sets so that they can use multiple performance indicators to apply analytical
approaches such as multivariate statistical approaches, spatiotemporal analysis,
machine learning, and social network analysis (­for more detail, see Herold, Goes,
Nopp, Bauer, Thompson, & Meyer, 2019; Jayal, McRobert, Oatley, & O’Donoghue,
2018; Sarmento et al., 2018).
In this chapter, we describe the role of performance analysis in the coaching pro-
cess, principles and moments of play, tactics and strategies, key performance indica-
tors, and an overview of ­match-​­play research during set plays and open play. Finally,
we review some current approaches in soccer performance analysis that use analytical
techniques to assess multiple performance indicators.

Performance analysis in the coaching process

The provision of performance analysis, feedback, and future planning are important
considerations in the coaching process. Traditionally, coaching interventions were
based on subjective observations, which could potentially be unreliable and inaccu-
rate because they are based on perceptions, biases, and previous experiences. For ex-
ample, ­international-​­level soccer coaches could only recall 30% of key variables that
determined match success and were less than 45% correct in a postgame assessment
of events (­Franks & Miller, 1991). Therefore, a coaching process model was proposed
that included performance analysis (­Maslovat & Franks, 2008). The primary purpose
of ­video-​­based performance analysis in the coaching process is to provide objective in-
formation and feedback about performance that allow coaches and players to modify
technical behaviour and tactical ­decision-​­making. After players perform, subjective
coach observations and evaluations are combined with objective information cap-
tured by the performance analyst. This information is used to identify and enhance
strengths or to improve weaknesses. In addition, a database of past events included
in the review and interpretation phase can inform the planning and implementation
of future practice interventions or competition (­see ­Figure 17.1). Data profiling and
benchmarking allow the tracking of performance trends across games and seasons,
and the analysis of the opposition so that appropriate strategies and tactics can be
prepared.
 Technical and tactical match analysis 275

Coach
observes

Coach Coach
Athlete Performance
plans conducts
performs analysed
practice practice

Past results
accounted for

­Figure 17.1 The coaching process.

Source: Adapted from Maslovat & Franks, 2008.

Coaches perceive performance analysis to be beneficial to the coaching process as

a support tool that facilities learning and develops mutual understanding between the
coach and player (­Groom, Cushion, & Nelson, 2011). A survey of elite professional and
­semi-​­professional coaches reported that 84% had access to full video or edited clips
following most games (­16%), or after every game (­68%), on the same day (­56%), or the
following day (­16%), and that they shared feedback with the team (­86%), individual
players (­83%), and small groups (­73%) (­Wright, Atkins, & Jones, 2012). A survey of
elite soccer performance analysts reported that they used an external company (­70%)
and/­or a ­self-​­coding software (­88%) to provide ­post-​­match analysis (­81%), ­post-​­match
feedback (­71%), ­pre-​­match analysis (­79%), live analysis (­79%), and scouting/­opposition
analysis (­54%) of individuals and team/­s (­Wright et al., 2013). Finally, coaches, play-
ers, and performance analysts suggest that performance analysis impacts team and
individual performance, develops game understanding and ­decision-​­making and is
essential when developing their playing style and tactics (­Groom & Cushion, 2005;
Reeves & Roberts, 2017; Wright, Atkins, & Jones, 2013).

Soccer principles and moments of play, tactics, and strategies

Players and team actions are influenced by the cooperation of teammates and the or-
ganisation of the opposition, the large degrees of freedom and variability, and the skill
of a player to act in specific conditions (­Garganta, 2009). Gréhaigne et al. (­1997) iden-
tified space and time, information, and organisation as the main challenges in soccer.
Therefore, tactical match performance depends on the quality of individual players or
team actions in space and time during match play to be successful (­Memmert, Lem-
mink, & Sampaio, 2016). Performance analysis, specifically tactical modelling, can
be used to identify regular or random game features during attacking and defensive
play, providing information on player and team efficacy, and creating benchmarks for
training.
276 Allistair P. McRobert et al.
To achieve the primary objectives of scoring while not conceding goals, teams main-
tain ball possession so they can invade space directly in front of the goal (­i.e., scoring
zone) to score, whereas defending teams reduce available space and attempt to regain
possession. Wade (­1996) identified attack, defence, and preparation or midfield play as
the three main phases of soccer. Teams develop strategies and tactics to plan their own
attacking and defensive actions across the phases, while anticipating and responding
to their opponents.
Strategy and tactics influence game outcomes and are fundamental to successful
performance in soccer (­Carling, Williams & Reilly, 2007; Yiannakos & Armatas,
2006). Strategy is defined as the plans, principles of play or action guidelines that
inform players and team interactions during the game (­Hewitt, Greenham, & Nor-
ton, 2016). For example, attacking strategies involve moving players to field positions
where they can receive the ball or score, overlap their teammate and defensive player
in the direction of the goal to exploit space, or increase the width and depth of team
surface area to create space in critical areas and/­or a player numerical advantage. In
contrast, defensive strategies involve the immediate delaying of opposition attacking
play once it regains possession through the restriction of passing options and time
to make the pass, and/­or the increase of player density, and structure (­i.e., defensive
shape) in defensive areas.
In addition, strategies are influenced by playing style, defined as the general behav-
iour of the team to achieve attacking and defensive objectives. Attacking playing styles
include direct, possession or elaborate, counterattacking, total soccer, and crossing,
whereas defending playing styles include low pressure and high pressure (­Bangsbo &
Peitersen, 2000; Garganta et al., 1997; Pollard et al., 1988; Wright et al., 2011). Team
strategy and specific playing styles inform the subsidiary units (­e.g., defending back
four) and individual player position roles and responsibilities so that instructions
known as tactics can be provided.
Tactics, or tactical ­decision-​­making, is defined as specific attacking and defensive
actions executed as a solution to anticipated situations influenced by the opposition.
In addition, tactical changes occur based on team and player attributes, player injury/­
substitution, quality of opposition, current match status (­i.e., winning, drawing, or los-
ing), and/­or match location (­i.e., home, or away). Tactics determine how teams manage
space and time, and individual (­i.e., ­one-­​­­on-​­one attacking and defending events with
or without the ball) and group actions (­i.e., the cooperation between subsidiary units
to achieve objectives) (­Fradua et al., 2013; Garganta, 2009). Tactics are often changed
to gain an advantage during competition, influenced by contextual and situational
factors, and the interaction between and within the two teams (­Rein & Memmert,
2016). Therefore, strategy and tactics inform team, unit, and individual player tactical
­decision-​­making prior to and during the game.
In addition, during the game, one team will be in a phase of play that impacts the
opposition’s phase of play, and vice versa. Dynamical systems theory has been used to
describe the interaction between two teams and how perturbations alter the rhythmic
flow of attacking and defending (­Gréhaigne et al., 1997; McGarry, Anderson, Wal-
lace, Hughes, & Franks, 2002). For example, an attacking phase may influence op-
position tactics used in the defensive phase based on the position of players on the
field in relation to the ball during a possession transition. However, to describe the
playing style and tactics during these phases of play, a framework to segment the game
is required. Hewitt et al. (­2016) stated that moments of play can be categorised as
 Technical and tactical match analysis 277

Established
Attack

Transition Transition
From Defense Set From Attack
to Attack Pieces to Defence

Established
Defense

­Figure 17.2 The five moments of play (Hewitt et al., 2016).

one of the following five categories: Established Attack; Transition from Attack to
Defence; Established Defence; Transition from Defence to Attack; and Set Plays (­see
­Figure 17.2). For further simplicity, moments of play were grouped into three phases:
(­1) Established Offense and Defence; (­2) Transitional Play; (­3) and Set Plays. The ter-
minology used to describe these phases is widely used by coaches, players, analysts,
and researchers to describe strategy, playing styles, and tactics.

Key performance indicators in soccer

Performance indicators are a selection or combination of action variables that de-
scribe some or all aspects of performance and should relate to successful or unsuc-
cessful performance of actions or outcome of events (­Hughes & Bartlett, 2002). Match
analysis is employed to describe and define technical and tactical performance using
discrete events (­i.e., counts or frequencies) and categorical data (­i.e., time and loca-
tion) to assess how these performance indicators differ between successful and un-
successful teams, and/­or individual players (­Nevill, Atkinson, Hughes, & Cooper,
2002). Team analysis provides information on how effectively they applied their play-
ing style, strategies, and tactics, whereas subsidiary unit and individual analysis pro-
vide information on their contribution. Tactical and technical performance indicators
are analysed, and performance profiles are created so that data can be compared to
previous games and opponents. However, caution is required when comparing due
to the m
­ atch-­​­­to-​­match variability found in performance indicators (­Gregson, Drust,
Atkinson, & Salvo, 2010; Liu, Gomez, Gonçalves, & Sampaio, 2015). Therefore, when
presenting a performance profile of a team, subsidiary unit or individual, means of
278 Allistair P. McRobert et al.
variables analysed need to have stabilised so that normative profiles can be established
(­Hughes, Evans & Wells, 2001; O’Donoghue, 2017).
Previously, indicators were classified based on the quality of performance (­e.g., passes
per possession) and scoring indicators (­e.g., goals scored). Researchers attempted to
identify key performance indicators associated with successful teams and outcomes in
the World Cup (­Franks, 2005; Liu, Gomez, L ­ ago-​­Peñas, & Sampaio, 2015; ­Ruiz-​­Ruiz,
Fradua, F­ ernández-​­GarcÍa, & Zubillaga, 2013), Women’s World Cup (­Barreira & Da
Silva, 2016; ­Iván-​­Baragaño, Maneiro, Losada, & Ardá, 2021; Kubayi & Larkin, 2020),
Euro Cup (­Casal, 2019; Yiannakos & Armatas, 2006), Champions League (­A lmeida,
Ferreira, & Volossovitch, 2014; ­Lago-​­Peñas, ­Lago-​­Ballesteros, & Rey, 2011), English
Premier League (­Adams, Morgans, Sacramento, Morgan, & Williams, 2013; Brad-
ley, ­Lago-​­Peñas, Rey, & Gomez Diaz, 2013; Bush, Barnes, Archer, Hogg, & Brad-
ley, 2015), Spanish La Liga (­Castellano, Alvarez, Figueira, Coutinho, & Sampaio,
2013; ­Lago-​­Peñas & Dellal, 2010), and German Bundesliga (­Hiller, 2014; Vogelbein,
Nopp, & Hökelmann, 2014; Yue, Broich, & Mester, 2014). These studies mostly fo-
cused on goals, shots, possession, and passing patterns prior to a goal as an attempt to
predict future team outcomes (­Franks, 2005; Jones, James, & Mellalieu, 2004; Taylor,
Mellalieu, & James, 2005).

Soccer ­match-​­play research

To date, most soccer research has analysed set plays or open play, with the former
focusing on corner kicks, penalty kicks, and free kicks, and the latter mainly on at-
tacking play. Implications and effectiveness of defensive strategies and tactics are then
inferred based on the opponents attacking play.

Analysis of open play

Since Reep and Benjamin’s (­1968) seminal work demonstrated that approximately 80%
of goals were from passing sequences of three passes or fewer, with a goal scored every
10 shots, there has been a debate on whether longer or shorter passing sequences are
more effective strategies, with literature reporting mixed findings. Since then, studies
have reported that more goals are scored from shorter passing sequences, which are
more frequent than longer passing sequences, however, once the data are normalised,
longer passing sequences are more effective (­Franks, 2005; Tenga, Holme, Ronglan, &
Bahr, 2010a). In addition to passing sequences, longer possession durations are typ-
ically associated with successful teams, however, differences in length of passing se-
quence durations have been reported between international teams and the English
Premier League (­Carling & Williams, 2008; Jones et al., 2004; Tenga & Sigmundstad,
2011). Furthermore, more goals are scored in the second half of games, and midfield-
ers and forwards score more goals than any other position (­Acar et al., 2009; Barreira
et al., 2013; Grant et al., 1998; Partridge et al., 1993; Taylor, Mellalieu, & James, 2005;
Yiannakos & Armatas, 2006; Yi, Jia, Liu, & Gomez, 2018). Goal scoring and associ-
ated scoring variables are measured to determine performance efficiency, however,
goal prevalence is low in soccer compared to other invasion games. Therefore, ad-
ditional behaviour patterns and event data need to be collected and analysed. For
example, shots at goal have been measured, specifically shot location, shot outcome
(­i.e., goal, ­on-​­target, ­off-​­target, goalkeeper save, and blocked), shot frequency, actions
 Technical and tactical match analysis 279
prior to the goal (­i.e., pass, cross, free kick, and corner kick), and player/­s involved
(­­Lago-​­Ballesteros & ­Lago-​­Peñas, 2010; Bate, 1988; Collet, 2013; Corbellini et al., 2013;
Chervenjakov, 1988; Ensum et al., 2005; Franks, 2005; Garganta et al., 1997; Hughes &
Churchill, 2005; Hughes & Franks, 2005; Hughes et al., 1988; ­Lago-​­Peñas et al., 2011;
Mara, Wheeler, & Lyons, 2012; Yi et al., 2018). Shots are more likely to produce a goal
if they are taken closer to the goal and in central positions, so attacking third and pen-
alty area entries have been examined. Teams winning games in the World Cup 2006
made more penalty area entries, and that there was a moderate correlation between
the number of entries and the likelihood of scoring a goal (­­Ruiz-​­Ruiz et al., 2013).
Tenga and colleagues (­2010a, 2010b) analysed 1,688 o ­ pen-​­play possessions in the
Norwegian male professional league. They defined a score box possession as an entry
into the score box in front of the goal with a high degree of control (­i.e., space and
time for the attacking team to perform intended actions). A strong correlation was
reported between score box possessions and shooting opportunities, and a 1% scoring
probability based on an average of scoring three goals and having 280 possessions
per match. In addition, when playing against an imbalanced defence, counterattack
possession types were more effective than elaborate possession play (­Tenga, Holme,
Ronglan, & 2010a; 2010b; Tenga, Ronglan, & Bahr, 2010). However, from the 1,688
open play possessions, only 80 (­4.7%) led to scoring opportunities and 167 (­9.9%) to
score box possessions, whereas other outcomes (­i.e., no score box possession, or pos-
session lost in the defensive, middle, or attacking third) occurred for the remaining
1,441 (­85.4%) possessions (­Tenga, Ronglan, & Bahr, 2010). Therefore, it would be use-
ful to understand what happens during the large proportion of possessions that do not
lead to score box possessions or scoring opportunities.
Previously, researchers focusing on ball possession explored the association between
successful performance, pitch areas where possession is maintained, and maintenance
of possession close to the opponent goal as an indicator of a successful attack (­­Bell-​
W
­ alker, McRobert, Ford, & Williams, 2007; Breen, Iga, & Ford, 2006; Franks, 2005;
Jones et al., 2004; L­ ago-​­Peñas & Dellal, 2010; Tenga & Sigmundstad, 2011). Conversely,
having more possessions does not always lead to scoring opportunities and goals
(­Bate, 1988; Wright et al., 2011). Moreover, like other performance indicators, posses-
sion is influenced by contextual factors, such as match location (­i.e., home or away),
match status (­i.e., winning, drawing, or losing), and quality of the opposition (­Gomez,
Parmar, & Travassos, 2020; ­Lago-​­Peñas & Dellal, 2010; ­Lago-​­Peñas & ­Gómez-​­Lopez,
2014; ­Lago-​­Peñas, Gomez, & Pollard, 2017; Paixão, Sampaio, & Almeida, 2015; Taylor,
Mellalieu, James, & Shearer, 2008), and once these factors are accounted for, posses-
sion becomes a poor predictor of outcome (­Collet, 2013).

Analysis of set plays

Researchers have estimated that between 30% and 40% of goals are scored from set
plays (­Casal, Maneiro, Ardá, Losada, & Rial, 2015). Siegle and Lames (­2012) reported
an average of 108 interruptions per match, with t­hrow-​­ins (­40), and free kicks (­33)
the most frequent, whereas goal kicks (­17), corner kicks (­10), substitutions (­4), and
­k ick-​­offs (­3) were less frequent. Set plays such as free kicks, penalty kicks, corners,
goal kicks, and t­hrow-​­ins occur when the ball runs out of the playing area or play
is stopped due to a foul. These events have certain advantages because the player of
the team executing the restart controls the timing from a stable situation, where the
280 Allistair P. McRobert et al.
opposition must respect distance rules, therefore, the player has an opportunity to
advance the ball into a g­ oal-​­scoring position or take a shot at goal (­Maneiro et al.,
2019). Furthermore, successful domestic and international teams were more efficient
with a set ­play-­​­­to-​­goal ratio of 1:7 compared to 1:15 for unsuccessful teams (­Carling,
Williams, & Reilly, 2005).
Despite the relatively low frequency of corner kicks, they can often be a determining
factor in match outcomes. In tournament knockout stages (­i.e., UEFA Champions
League 2010/­2011, World Cup 2010, and Euro 2012), only 26% of corners resulted in
an attempt at goal and 2.2% as a goal, however, 76% of matches ended in a draw or
win if a goal was scored from a corner (­Casal et al., 2015). Similarly, 25% of corners
resulted in an attempt at goal and 3.7% as a goal in the 2018 World Cup (­Kubayi &
Larkin, 2019). In the English Premier League 2011/­2012 season, 31% attempts at goal
and 13.3% of goals came from corners, whereas 34% attempts at goal and 4.6% of
goals came from corners in the FA Women’s Super League 2017/­2018 season (­Beare &
Stone, 2019; Pulling, Robins, & Rixon, 2013). In contrast, the top and bottom six teams
had only 10% of attempts at goal from corners during the English Premier League
2015/­2016 season, with 67% of matches ending in a draw or win if a goal was scored
from one (­Strafford, Smith, North, & Stone, 2019). Moreover, the likelihood of corner
goal attempts increased when attacking strategies involved deliveries to the far post,
a dynamic attacking move involving three or four attackers, whereas defensive strate-
gies involving zonal marking slightly reduced goal attempts compared to ­one-­​­­to-​­one
marking (­Strafford et al., 2019; Casal et al., 2015; De Baranda & ­Lopez-​­Riquelme,
2012; Pulling et al., 2013).
Penalty kicks provide a clear ­goal-​­scoring opportunity that can decide the re-
sult of a match. The success rates of penalty kicks in professional soccer leagues
and tournaments range from 70% to 85% (­A lmeida, Volossovitch, & Duarte, 2016;
­Bar-​­Eli, Azar, Ritov, ­Keider-​­Levin & Schein, 2007; Horn, de Waal, & Kraak, 2020;
Hughes & Wells, 2002; L ­ opez-​­Botella & Palao, 2007). In tournament ­shoot-​­outs be-
tween ­1982–​­1998 and ­2002–​­2008, penalty kicks had a success rate of 76% and 73%,
respectively, whereas success rate during match play between 2002 and 2008 was 68%
compared to 85% between 1982 and 1998 (­Dalton, Guillon, & Naroo, 2015; McGarry &
Franks, 2000). Moreover, the number of penalty kicks awarded and success rate are in-
fluenced by strike direction, goalkeeper reaction time, ball speed, foot used, positional
role, player age, time period, match status, and venue (­A lmeida et al., 2016; Fariña,
Fábrica, Tambussi & Alonso, 2013; Horn et al., 2020; Jordet, Hartman, Visscher, &
Lemmink 2007; ­Lopez-​­Botella & Palao, 2007). Jamil et al. (­2020) reported variations
in individual (­i.e., length of ­r un-​­ups, strike direction, type of shot, and foot used) and
situational variables (­i.e., time period, match status, and venue) across four European
soccer leagues (­i.e., English Premier League, Spanish La Liga, German Bundesliga,
and Italian Serie A) when analysing penalty kick success.
Free kicks are an important component of performance in soccer, however, there is
limited research on this aspect compared to corner and penalty kicks. In tournaments,
teams take three indirect free kicks per match aimed at scoring, 21.8% are attempts at
goal, 9.3% are on target, and 2.9% were goals (­Casal, Maneiro, Ardá, Losada, & Rial,
2014). During the 2007 Women’s World Cup, one goal was scored every 4.6 games
from free kicks, ball flights times were significantly faster for goals and all goals were
scored within 7 m of the goal (­Alcock, 2010). In the German Bundesliga, Link et al.
(­2016) reported 34.9 free kicks per game, 5.8 were less than 35 m from the goal, 22.2%
 Technical and tactical match analysis 281
were attempts at goal, while the remaining resulted in a pass or cross. Moreover, they
used geostatistical approaches, specifically variograms of position (­2D location of the
free kick), density (­number of free kicks in each sector), interruption time (­time from
foul to ball in play), distance to wall, players in the wall, rule violation, laterality, type
of play, outcome of shot, and outcome of cross to provide continues spatial profiles of
free kicks. In conclusion, ­free-​­kick crosses into the penalty area are less likely to result
in a goal, and it might be more effective to increase passes from side free kicks and use
short passes and dribbles to enter the penalty area.

Current approaches in soccer performance analysis

Attempting to identify performance indicators to predict performance has generated
mixed results, often due to interpretation of definitions, access to appropriate and
larger datasets, and the difficulty in including contextual and situational variables
(­Carling et al., 2013; Mackenzie & Cushion, 2012). Therefore, analysts adopted a re-
ductionist approach in which performance indicators are used to segment the video
into critical moments from the game that can provide feedback to the coach and play-
ers. More recently, the availability of additional event and positional data has allowed
researchers to develop new methods to contextualise performance. Analytical tech-
niques are used to assess multiple performance indicators, such as behaviour indexes,
multifactorial statistical approaches, social network analysis, spatiotemporal analysis,
and machine learning.
Kempe et al. (­2014) developed the Index of Game Control (­IGC) and Index of Offen-
sive Behaviour (­IOB) to evaluate playing styles and tactics. IGC was calculated using
several passing and passing success parameters (­i.e., passes per action, passing di-
rection, target player passes, passing success rate, and forward passing success rate),
whereas IOB combined IGC, duration and distance of actions, and game speed (­i.e.,
mean passes per attack, game speed, mean time of attack, gain of possession, dis-
tance per attack, and relative ball possession). The most successful teams preferred
the possession style and had a higher score for ICG. F ­ ernandez-​­Navarro et al. (­2019)
developed the Possession Effectiveness Index (­PEI) based on expected goals and ball
movement points to evaluate playing style effectiveness and the influence of contextual
variables (­i.e., match status, venue, and quality of opposition). Linear mixed mod-
els showed that direct play, counterattack, maintenance, and crossing effectiveness
increased when teams were winning by two or more goals. Counterattack increased
when winning and reduced when losing by one goal, whereas direct play increased
when losing by two or more goals. Playing away negatively affected direct play, main-
tenance, and high pressure, with all styles reduced when playing stronger opposition.
Factor analysis, specifically principal component analysis can be used to cluster
performance indicators into fewer factors that represent playing styles (­­Fernandez-​
N­ avarro, Fradua, Zubillaga, Ford, & McRobert, 2016). They extracted six factors that
defined eight attacking (­i.e., direct vs. possession, crossing vs. no crossing, wide vs.
narrow possession, and fast vs. slow progression) and four defending styles (­i.e., pres-
sure on wide vs. central areas, low vs. high pressure) in the English Premier League
and Spanish La Liga. Using these factors, playing style profiles can be created (­see
­Figure 17.3), for example, Everton F.C. had an attacking playing style involving direct,
no crossing, narrow possession, with fast progression, and a defensive style of low and
central areas pressure. In comparison, F.C. Barcelona had an attacking style involving
282 Allistair P. McRobert et al.

(A)
Factor 1 (Possession directness)

Factor 6 (Progression of the attack)

(B)
Factor 3 (Use of crosses)

Factor 4 (Possession width)

(C)
Factor 2 (Width of ball regain)

Factor 5 (Defensive ball pressure)

­Figure 17.3 Soccer team’s styles of play. Attacking styles of play: (­a) factors 1 and 6,
(­b) factors 3 and 4. Defensive styles of play: (­c) factors 2 and 5.
Notes: Numbers assigned to the teams for figure interpretation were: Atletico de Madrid (­1), Barce-
lona (­2), Betis (­3), Bilbao (­4), Celta (­5), Deportivo (­6), Espanyol (­7), Mallorca (­8), Osasuna (­9), Real
Madrid (­10), Real Sociedad (­11), Sevilla (­12), Valencia (­13), Zaragoza (­14), Arsenal (­15), Aston Villa
(­16), Bolton (­17), Chelsea (­18), Everton (­19), Liverpool (­20), Manchester City (­21), Manchester United
(­22), Portsmouth (­23), Tottenham (­24), West Ham (­25), Wigan (­26) for season ­2006–​­2007; and Atletico
de Madrid (­27), Barcelona (­28), Bilbao (­29), Getafe (­30), Levante (­31), Osasuna (­32), Real Madrid (­33),
Real Sociedad (­34), Valencia (­35), Villareal (­36), Zaragoza (­37) for season ­2010–​­2011.
Barcelona (­­2006–​­2007) highlighted in black. Everton (­­2006–​­2007) highlighted in grey.
 Technical and tactical match analysis 283
possession, no crossing, narrow possession, fast progression, and a defensive style of
high and central pressure. Gomez et al. (­2018) included additional performance indi-
cators and examined the effects of venue (­i.e., home vs. away) and team ranking. They
extracted eight factors (­i.e., ball possession, ending actions, individual challenges,
counterattack, set pieces, transitional play, fouling actions, and free kicks) and re-
ported specific tactical trends based on team rankings and venue.
Social network analysis can provide insights into strategies and tactics by exam-
ining passing connectivity between players. Players in this analysis are seen as a
network of nodes linked by passing connections to provide team connectivity and
cohesiveness metrics, which further understanding of how teams coordinate actions
and identify the most connected players (­Clemente, Martins, Kalamaras, Wong, &
Mendes, 2015; Clemente, Martins, Wong, Kalamaras, & Mendes, 2017; Mclean et al.,
2018a). Mclean et al. (­2018b) used notational and social network analysis to examine
­goal-​­scoring passing networks (­GSPN) characteristics in the 2016 Euros as a func-
tion of match status and pitch location. GSPN were highly variable, match status
influenced the networks, and high team connectivity did not determine the GSPN
between successful and unsuccessful teams or the group and knockout stages, how-
ever, degree centrality measures can be used to determine prominent pitch zones
during matches.
Due to positional tracking data availability, spatiotemporal approaches such as
Voronoi diagrams and centroid analysis have been used to analyse tactical behaviours
during attacking and defensive phases, transitions, and critical moments such as goals
(­Fonseca, Milho, Travassos, Araújo, & Lopes, 2013; Frencken, Poel, Visscher, & Lem-
mink, 2012). Centroid analysis characteristics such as centroid position (­average posi-
tion of the outfield players) provide information on how teams move across the pitch,
whereas increases and decreases in team surface area (­total space covered by out-
field players) provide information on team space control when attacking or defending.
Frencken et al. (­2012) examined ­inter-​­team distance dynamics during critical match
events. Match events identified through longitudinal ­inter-​­team distance related to
defending players moving forwards or backwards after a longitudinal pass, whereas
lateral ­inter-​­team distance corresponded with defending players moving laterally after
a sideways pass. Fonseca et al. (­2012) used Voronoi diagrams to understand how op-
posite teams coordinate player locations to define and adjust their dominate regions
during a game. They reported that players from the team in possession were further
apart from each other, whereas defending players were closer.
Finally, de Jong et al. (­2020) used three different analytical approaches to identify
technical determinants of female soccer match outcomes from a larger sample (­1,390
team performances) and range of variables (­450). First, a ­data-​­driven approach used
450 variables for feature selection. Second, a rational approach involved two authors
selecting a range of variables (­74) relevant to coaches to reduce ­over-​­fitting and in-
crease practical application. Third, a ­literature-​­driven approach selected 16 variables
from previous literature, so comparisons were possible. Match outcome was modelled
using generalised linear modelling and decision trees for variables in each analytical
approach. They reported that the rational and ­data-​­driven approaches outperformed
the ­literature-​­driven approach when predicting match outcome, with higher prediction
accuracies compared to studies on male soccer. Furthermore, the strongest determi-
nants of match outcome were scoring first, intentional assists relative to the opponent,
percentage of shots on goal saved by the goalkeeper relative to the opponent, shots on
goal relative to the opponent, and the percentage of successful duels.
284 Allistair P. McRobert et al.
Future directions and conclusions
Soccer is a ­goal-​­striking invasion game where two opposing teams attempt to score
goals while not conceding goals. Therefore, most researchers have analysed perfor-
mance indicators during set plays and open plays to predict performance. Set plays
such as corner, penalty, and free kicks account for ­30–​­40% of goals scored and are
often a deciding factor in winning. In addition, due to the dynamic nature of soccer
and low prevalence of goals and goal attempts, open play analysis has focused on
possession and passing sequences, however, they have produced mixed results when
predicting performance. Researchers have included situational and contextual varia-
bles such as pitch location, pass quality, skills and d
­ ecision-​­making quality, opposition
quality and style of play, home advantage, and score line to provide further depth.
More recently, availability of event and positional data, and use of analytical tech-
niques such as behaviour indexes, multifactorial statistical approaches, social network
analysis, spatiotemporal analysis, and machine learning provide further insights into
playing styles, tactical behaviour, and better contextualise performance. More impor-
tantly, spatiotemporal approaches using tracking data provide information on tactical
behaviour during defensive and attacking play, whereas previously, defensive effec-
tiveness and tactics have been inferred based on the opponent’s attacking play.
In future, researchers should continue to explore the use of these analytical tech-
niques so that we can provide additional information on how teams control space dur-
ing attacking and defending play. In addition, the recent growth and investment in
the women’s game means that event and positional data are becoming more available,
however, published research is still limited. Recently, in conjunction with FIFA and
Adidas, Science and Medicine in Football has announced a women’s football special
issue.
Performance analysis is an integral part of the coaching process that merges objec-
tive data with subjective coach observations so that technical and tactical behaviours
can be modified. In addition, databasing information allows tracking of performance
trends and analysis of opposition strategy and tactics. Moreover, due to advancements
in technology, coaches, players, and analysts access information almost immediately
to develop game understanding, d ­ ecision-​­making, playing style, and tactics.

References
Acar, M. F., Yapicioglu, B., Arikan, N., Yalcin, S., Ates, N., & Ergun, M. (­2009) Analysis of
goals scored in the 2006 World Cup. In T. Reilly & F. Korkusuz (­eds.), Science and Football
VI (­p­­p. ­235–​­242). London: Routledge.
Adams, D., Morgans, R., Sacramento, J., Morgan, S., & Williams, M. D. (­2013). Successful
short passing frequency of defenders differentiates between top and bottom four English
premier league teams. International Journal of Performance Analysis in Sport, 13(­3), ­653–​­668.
http://­d x.doi.org/­10.1080/­24748668.2013.11868678
Alcock, A. (­2010). Analysis of direct free kicks in the women’s football world cup 2007. Euro-
pean Journal of Sport Science, 10(­4), ­279–​­284. http://­doi.org/­10.1080/­17461390903515188
Almeida, C. H., Ferreira, A. P., & Volossovitch, A. (­2014). Effects of match location, match
status and quality of opposition on regaining possession in UEFA champions league. Journal
of Human Kinetics, 41(­1), ­1–​­12. http://­doi.org/­10.2478/­­hukin-­​­­2014- ​­0 048
Almeida, C. H., Volossovitch, A., & Duarte, R. (­2016). Penalty kick outcomes in UEFA club
competitions (­­2010-​­2015): the roles of situational, individual and performance factors. Inter-
national Journal of Performance Analysis in Sport, 16(­2), ­508–​­522. http://­doi.org/­10.1080/­
24748668.2016.11868905
 Technical and tactical match analysis 285
Bangsbo, J., & Peitersen, B. (­2000). Soccer Systems and Strategies, Champaign,
IL: Human Kinetics.
­Bar-​­Eli, M., Azar, O. H., Ritov, I., ­Keider-​­Levin, Y. & Schein, G. (­2007). Action bias among
elite soccer goalkeepers: the case of penalty kicks. Journal of Economic Psychology, 28, ­606–​
­621. http://­doi.org/­10.1016/­j.joep.2006.12.001
Barreira, J., & Da Silva, C. E. (­2016). National teams in women’s soccer world cup from 1991
to 2015: participation, performance and competitiveness. Journal of Physical Education and
Sport, 16(­3), ­795-​­799. http://­doi.org/­10.7752/­jpes.2016.03126
Barreira, D., Garganta, J., Pinto, T., Valente, J., & Anguera, M.T. (­2013). Do attacking game
patterns differ between first and second halves of soccer matches in the 2010 FIFA world
cup? In H. Nunome, B. Drust, & B. Dawson (­eds.), Science and Football VII (­p­­p. ­193–​­198).
London: Routledge.
Bate, R. (­1988). Football chance: tactics and strategy. In T. Reilly, A. Lees, K. Davids, & W. J.
Murphy (­eds.), Science and Football (­p­­p. ­293–​­301). London: E & FN Spon.
Beare, H., & Stone, J. A. (­2019). Analysis of attacking corner kick strategies in the FA women’s
super league 2017/­2018. International Journal of Performance Analysis in Sport, 19(­6), ­893–​
­903. http://­doi.org/­10.1080/­24748668.2019.1677329
­Bell-​­Walker, J., McRobert, A., Ford, P., & Williams, A. M. (­2007). A quantitative analysis of
successful teams at the 2006 World Cup finals. Insight: The FA Coaches Association Journal,
Autumn/­Winter, ­36–​­43.
Bradley, P. S., L ­ ago-​­Peñas, C., Rey, E., & Gomez Diaz, A. (­2013). The effect of high and
low percentage ball possession on physical and technical profiles in English FA premier
league soccer matches. Journal of Sports Sciences, 31(­12), ­1261–​­1270. http://­doi.org/­10.1080/
­02640414.2013.786185
Bradley, P., O’Donoghue, P., Wooster, B., & Tordoff, P. (­2007). The reliability of prozone match
viewer: a ­v ideo-​­based technical performance analysis system. International Journal of Perfor-
mance Analysis in Sport, 7(­3), ­117–​­129.
Breen, A., Iga, J., Ford, P., & Williams, A. M. (­2006). World cup ­2006 – ​­Germany. A quantitative
analysis of goals scored. Insight: The FA Coaches Association Journal, Autumn/­Winter, ­44–​­53.
Bush, M., Barnes, C., Archer, D. T., Hogg, B., & Bradley, P. S. (2015). Evolution of match per-
formance parameters for various playing positions in the English Premier League. Human
Movement Science, 39, 1–11. https://doi.org/10.1016/j.humov.2014.10.003
Carling, C., & Williams, A. M. (­2008). Match analysis and elite soccer performance: integrating
science and practice. In T. Reilly (­ed.), Science and Soccer (­p­­p. ­32–​­47). Maastricht, Nether-
lands: Shaker Publishing.
Carling, C., Williams, A.M., & Reilly, T. (2005). Handbook of Soccer Match Analysis: A Sys-
tematic Approach to Improving Performance (1st ed.). Routledge, London. https://doi.
org/10.4324/9780203448625
Carling, C., Wright, C., John Nelson, L., & S Bradley, P. (­2013). Comment on performance
analysis in football: a critical review and implications for future research. Journal of Sports
Sciences, 32(­1), ­2 –​­7. http://­doi.org/­10.1080/­02640414.2013.807352
Casal, C. A. (2019). Offensive Transitions in High-Performance Football: Differences Between
UEFA Euro 2008 and UEFA Euro 2016. Fpsyg-10-01230.Tex, 10, 1–10. https://doi.org/10.3389/
fpsyg.2019.01230
Casal, A. C., Maneiro, R., Ardá, T., Losada, J. L., & Rial, A. (­2014). Effectiveness of indirect
free kicks in elite soccer. International Journal of Performance Analysis in Sport, 14(­3), ­744–​
­760. http://­doi.org/­10.1080/­24748668.2014.11868755
Casal, C. A., Maneiro, R., Ardá, T., Losada, J. L. & Rial, A. (­2015). Analysis of corner kick
success in elite football. International Journal of Performance in Sport, 15(­2), ­430–​­451. http://­
doi.org/­10.1080/­24748668.2015.11868805
Casal, C. A. (2019). Offensive Transitions in High-Performance Football: Differences Be-
tween UEFA Euro 2008 and UEFA Euro 2016. Fpsyg-10-01230.Tex, 10, 1–10. https://doi.
org/10.3389/fpsyg.2019.01230
286 Allistair P. McRobert et al.
Castellano, J., Alvarez, D., Figueira, B., Coutinho, D., & Sampaio, J. (­2013). Identifying the
effects from the quality of opposition in a football team positioning strategy. International
Journal of Performance Analysis in Sport, 13(­3), ­822–​­832.
Chervenjakov, M. (­1988). Assessment of the playing effectiveness of soccer players. In T. Reilly,
A. Lees, K. Davids, & W. J. Murphy (­eds.), Science and Football (­p­­p. ­288–​­292). London: E &
FN Spon.
Clemente, F. M., Martins, F. M. L., Kalamaras, D., Wong, P. D., & Mendes, R. S. (­2015). Gen-
eral network analysis of national soccer teams in FIFA world cup 2014. International Journal
of Performance Analysis in Sport, 15(­1), ­80–​­96. http://­doi.org/­10.1080/­24748668.2015.11868778
Clemente, F. M., Martins, F. M. L., Wong, P. D., Kalamaras, D., & Mendes, R. S. (­2017). Mid-
fielder as the prominent participant in the building attack: A network analysis of national
teams in FIFA world cup 2014. International Journal of Performance Analysis in Sport, 15(­2),
­704–​­722. http://­doi.org/­10.1080/­24748668.2015.11868825
Collet, C. (­2013). The possession game? A comparative analysis of ball retention and team suc-
cess in European and international football, ­2007–​­2010. Journal of Sports Sciences, 31(­2),
­123–​­136. http://­doi.org/­10.1080/­02640414.2012.727455
Corbellini, F., Volossovitch, A., Andrade, C., Fernandes, O., & Ferreira, A. P. (­2013). Contextual ef-
fects on the free kick performance: a case study with a Portuguese professional soccer team. In H.
Nunome, B. Drust, & B. Dawson (­eds.), Science and Football VII (­p­­p. ­217–​­222). London: Routledge.
Cummins, C., Orr, R., O’Connor, H., & West, C. (­2013). Global positioning systems (­GPS) and
microtechnology sensors in team sports: a systematic review. Sports Medicine, 43(­10), ­1025–​
1­ 042. http://­doi.org/­10.1007/­­s40279-­​­­013-­​­­0 069-​­2
Dalton, K., Guillon, M., & Naroo, S. A. (­2015). An analysis of penalty kicks in elite football
post 1997. International Journal of Sport Coaching, 10(­5), ­815–​­827. http://­doi.org/­10.1260/­­1747-
​­9541.10.5.815
De Baranda, P. S., & ­Lopez-​­Riquelme, D. (­2012). Analysis of corner kicks in relation to match
status in the 2006 world cup. European Journal of Sport Science, 12(­2), ­121–​­129. http://­doi.
org/­10.1080/­17461391.2010.551418
de Jong, L. M. S., Gastin, P. B., Angelova, M. B., & Dwyer, D. B. (­2020). Technical determi-
nants of success in professional women’s soccer: a wider range of variables reveals new in-
sights. PLoS ONE, 15(­10), e0240992. http://­doi.org/­10.1371/­journal.pone.0240992
Drust, B. (­2010). Performance analysis research: meeting the challenge. Journal of Sports
Sciences, 28(­9), ­921–​­922. http://­doi.org/­10.1080/­02640411003740769
Ensum, J., Pollard, R., & Taylor, S. (­2005). Applications of logistic regression to shots at goal
in association football. In T. Reilly, J. Cabri, & D. Araujo (­eds.), Science and Football V
(­p­­p. ­211–​­218). London: Routledge.
Fariña, A. R., Fábrica, G., Tambussi, P. S., & Alonso, R. (­2013). Taking the goalkeeper’s side
in association football penalty kicks. International Journal of Performance Analysis in Sport,
13(­1), ­96–​­109. http://­doi.org/­10.1080/­24748668.2013.11868634
­Fernandez-​­Navarro, J., Fradua, L., Zubillaga, A., & McRobert, A. P. (­2019). Evaluating the ef-
fectiveness of styles of play in elite soccer. International Journal of Sports Science & Coaching,
14(­4), ­514–​­527. http://­doi.org/­10.1177/­1747954119855361
­Fernandez-​­Navarro, J., Fradua, L., Zubillaga, A., Ford, P. R., & McRobert, A. P. (­2016).
Attacking and defensive styles of play in soccer: analysis of Spanish and English elite teams.
Journal of Sports Sciences, 34(­24), ­2195–​­2204. http://­doi.org/­10.1080/­02640414.2016.1169309
Fonseca, S., Milho, J., Travassos, B., & Araújo, D. (­2012). Spatial dynamics of team sports
exposed by Voronoi diagrams. Human Movement Science, 31(­6), ­1652–​­1659. http://­doi.org/­
10.1016/­j.humov.2012.04.006
Fonseca, S., Milho, J., Travassos, B., Araújo, D., & Lopes, A. (­2013). Measuring spatial interac-
tion behavior in team sports using superimposed Voronoi diagrams. International Journal of
Performance Analysis in Sport, 13(­1), ­179–​­189.
 Technical and tactical match analysis 287
Fradua, L., Zubillaga, A., Caro, Ó., Iván ­Fernández-​­García, Á., ­Ruiz-​­Ruiz, C., & Tenga, A.
(­2013). Designing s­mall-​­sided games for training tactical aspects in soccer: extrapolating
pitch sizes from ­full-​­size professional matches. Journal of Sports Sciences, 31(­6), ­573–​­581.
http://­doi.org/­10.1080/­02640414.2012.746722
Franks, I. M. (­2005). Analysis of passing sequences, shots and goals in soccer. Journal of Sports
Sciences, 23(­5), ­509–​­514. http://­doi.org/­10.1080/­02640410410001716779
Franks, I. M., & Miller, G. (­1991). Training coaches to observe and remember. Journal of Sports
Sciences, 9(­3), ­285–​­297. http://­doi.org/­10.1080/­02640419108729890
Frencken, W. G. P., Lemmink, K. A. P. M., & Delleman, N. J. (­2010). ­Soccer-​­specific accuracy
and validity of the local position measurement (­LPM) system. Journal of Science and Medi-
cine in Sport, 13(­6), ­641–​­645. http://­doi.org/­10.1016/­j.jsams.2010.04.003
Frencken, W., Poel, H. de, Visscher, C., & Lemmink, K. (­2012). Variability of i­nter-​­team dis-
tances associated with match events in e­lite-​­standard soccer. Journal of Sports Sciences,
30(­12), ­1207–​­1213. http://­doi.org/­10.1080/­02640414.2012.703783
Garganta, J. (­2009). Trends of tactical performance analysis in team sports: bridging the gap
between research, training and competition. Revista Portuguesa De Ciências Do Desporto,
9(­1), ­81– ​­89. http://­doi.org/­10.5628/­r pcd.09.01.81
Garganta, J., Maia, J., & Basto, F. (­1997). Analysis of ­goal-​­scoring patterns in European top
level soccer teams. In J. Bangsbo, T. Reilly & A. M. Williams (­eds.), Science and Football III
(­p­­p. ­246–​­250). London: E & FN Spon.
Gomez, M.-​­Á., Mitrotasios, M., Armatas, V., & L ­ ago-​­Peñas, C. (­2018). Analysis of playing
styles according to team quality and match location in Greek professional soccer. Inter-
national Journal of Performance Analysis in Sport, 18(­6), ­986–​­997. http://­doi.org/­10.1080/
­24748668.2018.1539382
Gomez, M.-​­Á., Reus, M., Parmar, N., & Travassos, B. (­2020). Exploring elite soccer teams’
performances during different m ­ atch-​­status periods of close matches’ comebacks. Chaos,
Solitons & Fractals, 132, 109566. http://­doi.org/­10.1016/­j.chaos.2019.109566
Grant, A., Reilly, T., Williams, A. M., & Borrie, A. (­1998). Analysis of the goals scored in the
1998 world cup. Insight: The FA Coaches Association Journal, 2(­1), ­18–​­20.
Gregson, W., Drust, B., Atkinson, G., & Salvo, V. D. (­2010). M ­ atch-­​­­to-​­match variability of
­h igh-​­speed activities in premier league soccer. International Journal of Sports Medicine, 31(­4),
­237–​­242. http://­doi.org/­10.1055/­­s-­​­­0 030-​­1247546
Gréhaigne, J.-​­F., Bouthier, D., & David, B. (­1997). ­Dynamic-​­system analysis of opponent rela-
tionships in collective actions in soccer. Journal of Sports Sciences, 15(­2), ­137–​­149. http://­doi.
org/­10.1080/­026404197367416
Groom, R., & Cushion, C. (­2005). Using of video based coaching with players: a case study. Inter-
national Journal of Performance Analysis in Sport, 5(­3), ­40–​­46. http://­doi.org/­10.1080/­24748668.
2005.11868336
Groom, R., Cushion, C., & Nelson, L. (­2011). The delivery of v­ ideo-​­based performance analysis
by England youth soccer coaches: towards a grounded theory. Journal of Applied Sport Psy-
chology, 23(­1), ­16–​­32. http://­doi.org/­10.1080/­10413200.2010.511422
Herold, M., Goes, F., Nopp, S., Bauer, P., Thompson, C., & Meyer, T. (­2019). Machine learning
in men’s professional football: current applications and future directions for improving at-
tacking play. International Journal of Sports Science & Coaching, 14(­6), ­798–​­817. https://­doi.
org/­10.1177/­1747954119879350
Hewitt, A., Greenham, G., & Norton, K. (2016). Game style in soccer: what is it and can we
quantify it? International Journal of Performance Analysis in Sport, 16(1), 355–372. https://doi.
org/10.1080/24748668.2016.11868892
Hiller, T. (­2014). The importance of players in teams of the German Bundesliga in the season
2012/­­2013 – ​­a cooperative game theory approach. Applied Economics Letters, 22(­4), ­324–​­329.
http://­doi.org/­10.1080/­13504851.2014.941527
288 Allistair P. McRobert et al.
Horn, M., de Waal, S., & Kraak, W. (­2020). ­In-​­match penalty kick analysis of the 2009/­10 to
2018/­19 English premier league competition. International Journal of Performance Analysis in
Sport, 21(­1), ­139–​­155. http://­doi.org/­10.1080/­24748668.2020.1855052
Hughes, M. D., & Bartlett, R. M. (2002). The use of performance indicators in performance anal-
ysis. Journal of Sports Sciences, 20(10), 739–754. https://doi.org/10.1080/026404102320675602
Hughes, M. D., & Churchill, S. (­2005). Attacking profiles of successful and unsuccessful teams
in Copa America 2001. In T. Reilly, J. Cabri, & D. Araujo (­eds.), Science and Football V
(­p­­p. ­221–​­224). London: Routledge.
Hughes, M., Evans, S., & Wells, J. (2001). Establishing normative profiles in performance anal-
ysis. International Journal of Performance Analysis in Sport, 1(1), 1 -26. https://doi.org/10.108
0/24748668.2001.11868245
Hughes, M. D., Robertson, K., & Nicholson, A. (­1988). Comparison of patterns of play of
successful and unsuccessful teams in the 1986 world cup for soccer. In T. Reilly, A. Lees,
K. Davids, & W. J. Murphy (­e ds.), Science and Football ( ­p­­p. ­363–​­367). London: E & FN
Spon.
Hughes, M., & Wells, J. (­2002) Analysis of penalties taken in s­ hoot-​­outs. International Journal
of Performance Analysis in Sport, 2(­1), ­55-​­72. https://­doi.org/­10.1080/­24748668.2002.11868261
Hughes, M., & Franks, I. (2005). Analysis of passing sequences, shots and goals in soccer. Jour-
nal of Sports Sciences, 23(5), 509–514. https://doi.org/10.1080/02640410410001716779
­Iván-​­Baragaño, I., Maneiro, R., Losada, J. L., & Ardá, A. (­2021). Multivariate analysis of the
offensive phase in ­h igh-​­performance women’s soccer: a mixed methods study. Sustainability,
13(­11), 6379. http://­doi.org/­10.3390/­su13116379
James, N. (­2006). Notational analysis in soccer: past, present and future International Journal
of Performance Analysis in Sport, 6(­2), ­67–​­81.
Jamil, M., Littman, P., & Beato, M. (­2020). Investigating ­i nter-​­league and ­i nter-​­nation variations
of key determinants for penalty success across European football. International Journal of
Performance Analysis in Sport, 20(­5), ­892–​­907. http://­doi.org/­10.1080/­24748668.2020.1794720
Jayal, A., McRobert, A. P., Oatley, G., & O’Donoghue, P. (­2018). Sports Analytics: Analysis,
Visualisation and Decision Making in Sports Performance (­1st ed.). Routledge. http://­doi.
org/­10.4324/­9781315222783
Jones, D., Rands, S., & Butterworth, A. D. (­2020). The use and perceived value of telestration
tools in elite football. International Journal of Performance Analysis in Sport, 20(­3), ­373–​­388.
http://­doi.org/­10.1080/­24748668.2020.1753965
Jones, P., James, N., & Mellalieu, S. (­2004). Possession as a performance indicator in soccer.
International Journal of Performance Analysis in Sport, 4(­1), ­98–​­102.
Jordet, G., Hartman, E., Visscher, C., & Lemmink, K. A. P. M. (­2007). Kicks from the penalty
mark in soccer: the roles of stress, skill, and fatigue for kick outcomes. Journal of Sports
Sciences, 25(­2), ­121–​­129. http://­doi.org/­10.1080/­02640410600624020
Kempe, M., Vogelbein, M., Memmert, D., & Nopp, S. (­2014). Possession vs. direct play: eval-
uating tactical behavior in elite soccer. International Journal of Sports Science, 4(­6a), ­35–​­41.
http://­doi.org/­10.5923/­s.sports.201401.05
Kubayi, A., & Larkin, P. (­2019). Analysis of teams’ corner kicks defensive strategies at the FIFA
world cup 2018. International Journal of Performance Analysis in Sport, 19(­5), ­809–​­819. http://­
doi.org/­10.1080/­24748668.2019.1660547
Kubayi, A., & Larkin, P. (­2020). Technical performance of soccer teams according to match
outcome at the 2019 FIFA women’s world cup. International Journal of Performance Analysis
in Sport, 20(­5), ­908–​­916. http://­doi.org/­10.1080/­24748668.2020.1809320
Lago, C. (­2009). The influence of match location, quality of opposition, and match status on
possession strategies in professional association football. Journal of Sports Sciences, 27(­13),
­1463–​­1469. http://­doi.org/­10.1080/­02640410903131681
­Lago-​­Ballesteros, J., & ­Lago-​­Peñas, C. (­2010). Performance in team sports: identifying the keys
to success in soccer. Journal of Human Kinetics, 25, ­85–​­91.
 Technical and tactical match analysis 289
­Lago-​­Peñas, C., & Dellal, A. (­2010). Ball possession strategies in elite soccer according to the
evolution of the m ­ atch-​­score: the influence of situational variables. Journal of Human Kinet-
ics, 25(­1), ­293–​­298. http://­doi.org/­10.2478/­­v10078-­​­­010-­​­­0 036-​­z
­Lago-​­Peñas, C., & G ­ ómez-​­Lopez, M. (­2014). How important is it to score a goal? the influence
of the scoreline on match performance in elite soccer. Perceptual and Motor Skills, 119(­3),
­774–​­784. http://­doi.org/­10.2466/­23.27.PMS.119c32z1
­Lago-​­Peñas, C., Gomez, M. Á., & Pollard, R. (­2017). Home advantage in elite soccer matches.
A transient effect? International Journal of Performance Analysis in Sport, 17(­­1–​­2), ­86–​­95.
http://­doi.org/­10.1080/­24748668.2017.1304024
­Lago-​­Peñas, C., ­Lago-​­Ballesteros, J., & Rey, E. (­2011). Differences in performance indicators
between winning and losing teams in the UEFA champions league. Journal of Human Kinet-
ics, 27, ­135–​­146. http://­doi.org/­10.2478/­­v10078-­​­­011-­​­­0 011-​­3
Link, D., Kolbinger, O., Weber, H., & Stöckl, M. (­2016). A topography of free kicks in soccer.
Journal of Sports Sciences, 34(­24), ­2312–​­2320. http://­doi.org/­10.1080/­02640414.2016.1232487
Liu, H., Gomez, M.-​­Á., Gonçalves, B., & Sampaio, J. (­2015). Technical performance and ­match-­​
­­to-​­match variation in elite football teams. Journal of Sports Sciences, 34(­6), ­509–​­518. http://­
doi.org/­10.1080/­02640414.2015.1117121
­Lopez-​­Botella, M., & Palao, J. (­2007). Relationship between laterality of foot strike and shot
zone on penalty efficacy in specialist penalty takers. International Journal of Performance
Analysis in Sport, 7(­3), ­26–​­36. http://­doi.org/­10.1080/­24748668.2007.11868407
Mackenzie, R., & Cushion, C. (­ 2012). Performance analysis in football: a critical review
and implications for future research. Journal of Sports Sciences, 31(­6), ­639–​­676. http://­doi.
org/­10.1080/­02640414.2012.746720
Maneiro, R., Casal, C. A., Álvarez, I., Moral, J.E., López, S., Ardá, A., & Losada, J. L. (­2019).
Offensive transitions in h ­ igh-​­p erformance football: differences between UEFA Euro 2008 and
UEFA Euro 2016. Frontiers in Psychology, 10, 1230. http://­doi.org/­10.3389/­fpsyg.2019.01230
Mara, J. K., Wheeler, K. W., & Lyons, K. (­2012). Attacking strategies that lead to goal scor-
ing opportunities in high level women’s football. International Journal of Sports Science &
Coaching, 7(­3), ­565–​­577. http://­doi.org/­10.1260/­­1747-​­9541.7.3.565
Maslovat, D., & Franks, I. (­2008). The need for feedback. In M. Hughes & I. Franks (­Eds.),
The Essentials of Performance Analysis: An Introduction (­p­­p. ­1–​­7). London, UK: Routledge.
McGarry, T., & Franks, I. M. (­2000). On winning the penalty ­shoot-​­out in soccer. Journal of
Sports Sciences, 18(­6), ­401– ​­409. https://­doi.org/­10.1080/­02640410050074331
McGarry, T., Anderson, D. I., Wallace, S. A., Hughes, M. D., & Franks, I. M. (­2002). Sport
competition as a dynamical s­ elf-​­organizing system. Journal of Sports Sciences, 20(­10), ­771–​
­781. http://­doi.org/­10.1080/­026404102320675620
McGarry, T., O’Donoghue, P., & Sampaio, A. J. (­2013). Routledge Handbook of Sports Perfor-
mance Analysis. London: Routledge.
Mclean, S., Salmon, P. M., Gorman, A. D., Stevens, N. J., & Solomon, C. (­2018b). A social
network analysis of the goal scoring passing networks of the 2016 European Football Cham-
pionships. Human Movement Science, 57, ­400– ​­408. http://­doi.org/­10.1016/­j.humov.2017.10.001
Mclean, S., Salmon, P. M., Gorman, A. D., Wickham, J., Berber, E., & Solomon, C. (­2018a). The
effect of playing formation on the passing network characteristics of a professional football
team. Human Movement, 19(­5), ­14–​­22. http://­doi.org/­10.5114/­h m.2018.79416
Memmert, D., Lemmink, K. A. P. M., & Sampaio, J. (­2016). Current approaches to tactical
performance analyses in soccer using position data. Sports Medicine, 47(­1), ­1–​­10. http://­doi.
org/­10.1007/­­s40279-­​­­016-­​­­0562-​­5
Nevill, A. M., Atkinson, G., Hughes, M. D., & Cooper, S.-​­M. (­2002). Statistical methods for
analysing discrete and categorical data recorded in performance analysis. Journal of Sports
Sciences, 20(­10), ­829–​­844. http://­doi.org/­10.1080/­026404102320675666
O’Donoghue, P. (­2017). Normative profiles of sports performance. International Journal of Per-
formance Analysis in Sport, 5(­1), ­104–​­119. http://­doi.org/­10.1080/­24748668.2005.11868319
290 Allistair P. McRobert et al.
Olthof, S. B. H., Frencken, W. G. P., & Lemmink, K. A. P. M. (­2018). ­Match-​­derived rela-
tive pitch area changes the physical and team tactical performance of elite soccer play-
ers in ­small-​­sided soccer games. Journal of Sports Sciences, 36(­14), ­1557–​­1563. http://­doi.
org/­10.1080/­02640414.2017.1403412
Paixão, P., Sampaio, J., & Almeida, C. H. (­2015). How does match status affects the passing
sequences of ­top-​­level European soccer teams? International Journal of Performance Analysis
in Sport, 15(­1), ­229–​­240. https://­doi.org/­10.1080/­24748668.2015.11868789
Partridge, D., Mosher, R. E., & Franks, I. (­1993). A computer assisted analysis of technical
­p erformance – ​­A comparison of the 1990 world cup and intercollegiate soccer. In T. Reilly,
J. Clarys, & A. Stibbe (­eds.), Science and Football II (­p­­p. ­221–​­231). London: E & FN Spon.
Pollard, R. (­2002). Charles reep (­­1904-​­2002): pioneer of notational and performance analysis in foot-
ball. Journal of Sports Sciences, 20(­10), ­853–​­855. https://­doi.org/­10.1080/­026404102320675684
Pollard, R., Reep, C., & Hartley, S. (­1988). The quantitative comparison of playing styles in
soccer. In T. Reilly, A. Lees, K. Davids, & W. J. Murphy (­eds.), Science and Football (­p­­p. ­309–​
­315). London: E & FN Spon.
Pulling, C., Robins, M., & Rixon, T. (­2013). Defending corner kicks: analysis from the English
premier league. International Journal of Performance Analysis in Sport, 13(­1), ­135–​­148. https://­
doi.org/­10.1080/­24748668.2013.11868637
Reep, C., & Benjamin, B. (­1968). Skill and chance in association football. Journal of the Royal
Statistical Society: Series A (­G eneral), 131(­4), ­581–​­585. https://­doi.org/­10.2307/­2343726
Reeves, M. J., & Roberts, S. J. (­2017). Perceptions of performance analysis in elite youth
football. International Journal of Performance Analysis in Sport, 13(­1), ­200–​­211. http://­doi.
org/­10.1080/­24748668.2013.11868642
Rein, R., & Memmert, D. (­2016). Big data and tactical analysis in elite soccer: future challenges
and opportunities for sports science. Springer Plus, 5(­1), ­1–​­13. http://­doi.org/­10.1186/­­s40064-
­​­­016-­​­­3108-​­2
­Ruiz-​­Ruiz, C., Fradua, L., ­Fernández-​­GarcÍa, Á., & Zubillaga, A. (­2013). Analysis of entries
into the penalty area as a performance indicator in soccer. European Journal of Sport Science,
13(­3), ­241–​­248. http://­doi.org/­10.1080/­17461391.2011.606834
Sarmento, H., Clemente, F. M., Araújo, D., Davids, K., McRobert, A. P., & Figueiredo,
A. (­2018). What performance analysts need to know about research trends in associa-
tion football (­­2012–​­2016): a systematic review. Sports Medicine, 48(­4), ­799–​­836. http://­doi.
org/­10.1007/­­s40279-­​­­017-­​­­0836-​­6
Sarmento, H., Marcelino, R., Anguera, M. T., Campanico, J., Matos, N., & Leitão, J. C. (­2014).
Match analysis in football: a systematic review. Journal of Sports Sciences, 32(­20), ­1831–​­1843.
http://­doi.org/­10.1080/­02640414.2014.898852
Siegle, M., & Lames, M. (­2012). Game interruptions in elite soccer. Journal of Sports Sciences,
30(­7), ­619– ​­624. http://­doi.org/­10.1080/­02640414.2012.667877
Strafford, B. W., Smith, A., North, J. S., & Stone, J. A. (­2019). Comparative analysis of the
top six and bottom six teams’ corner kick strategies in the 2015/­2016 English premier
league. International Journal of Performance Analysis in Sport, 19(­6), ­904–​­918. http://­doi.
org/­10.1080/­24748668.2019.1677379
Taylor, B. J., Mellalieu, D. S., & James, N. (­2005). A comparison of individual and unit tactical
behaviour and team strategy in professional soccer. International Journal of Performance
Analysis in Sport, 5(­2), ­87–​­101. http://­doi.org/­10.1080/­24748668.2005.11868329
Taylor, J. B., Mellalieu, S. D., James, N., & Shearer, D. A. (­2008). The influence of match location,
quality of opposition, and match status on technical performance in professional association
football. Journal of Sports Sciences, 26(­9), ­885–​­895. http://­doi.org/­10.1080/­02640410701836887
Tenga, A., & Sigmundstad, E. (­2011). Characteristics of ­goal-​­scoring possessions in open play:
comparing the top, i­n-​­between and bottom teams from professional soccer league. Interna-
tional Journal of Performance Analysis in Sport, 11(­3), ­545–​­552. http://­doi.org/­10.1080/­24748668.
2011.11868572
 Technical and tactical match analysis 291
Tenga, A., Holme, I., Ronglan, L. T., & Bahr, R. (­2010a). Effect of playing tactics on achiev-
ing ­score-​­box possessions in a random series of team possessions from Norwegian pro-
fessional soccer matches. Journal of Sports Sciences, 28(­3), ­245–​­255. http://­doi.org/­10.1080/­
02640410903502766
Tenga, A., Holme, I., Ronglan, L. T., & Bahr, R. (­2010b). Effect of playing tactics on goal scor-
ing in Norwegian professional soccer. Journal of Sports Sciences, 28(­3), ­237–​­244. http://­doi.
org/­10.1080/­02640410903502774
Tenga, A., Ronglan, L. T., & Bahr, R. (­2010). Measuring the effectiveness of offensive m ­ atch-​
­play in professional soccer. European Journal of Sport Science, 10(­4), ­269–​­277. http://­doi.
org/­10.1080/­17461390903515170
Valter, D. S., Adam, C., Barry, M., & Marco, C. (­2006). Validation of prozone®: a new ­v ideo-​
­based performance analysis system. International Journal of Performance Analysis in Sport,
6(­1), ­108–​­119.
Vogelbein, M., Nopp, S., & Hökelmann, A. (­ 2014). Defensive transition in s­occer – are
​­
prompt possession regains a measure of success? A quantitative analysis of German
­Fußball-​­Bundesliga 2010/­2011. Journal of Sports Sciences, 32(­11), ­1076–​­1083. http://­doi.
org/­10.1080/­02640414.2013.879671
Wade, A. (­1996). Principles of Team Play. Pennsylvania: Reedswain Inc.
Wright, C., Atkins, S., & Jones, B. (­2011). An analysis of elite coaches’ engagement with per-
formance analysis services (­match, notational analysis and technique analysis). International
Journal of Performance Analysis in Sport, 12(­2), ­436– ​­451. http://­doi.org/­10.1080/­24748668.
2012.11868609
Wright, C., Atkins, S., Jones, B., & Todd, J. (­2013). The role of performance analysts within the
coaching process: performance analysts survey. International Journal of Performance Analy-
sis in Sport, 13(­1), ­240–​­261. http://­doi.org/­10.1080/­24748668.2013.11868645
Wright, C., Atkins, S., Polman, R., Jones, B., & Sargeson, L. (­2011). Factors associated with
goals and goal scoring opportunities in professional soccer. International Journal of Perfor-
mance Analysis in Sport, 11(­3), ­438–​­449. https://­doi.org/­10.1080/­24748668.2011.11868563
Yi, Q., Jia, H., Liu, H., & Gomez, M.-​­Á. (­2018). Technical demands of different playing posi-
tions in the UEFA champions league. International Journal of Performance Analysis in Sport,
18(­6), ­926–​­937. http://­doi.org/­10.1080/­24748668.2018.1528524
Yiannakos, A., & Armatas, V. (­2006). Evaluation of the goal scoring patterns in European
Championship in Portugal 2004. International Journal of Performance Analysis in Sport, 6(­1),
­178–​­188.
Yue, Z., Broich, H., & Mester, J. (­2014). Statistical analysis for the soccer matches of the first
Bundesliga. International Journal of Sports Science & Coaching, 9(­3), ­553–​­560. http://­doi.
org/­10.1260/­­1747-​­9541.9.3.553
18 Monitoring training
Barry Drust and Laura Bowen

Introduction
Monitoring training is a key aspect of soccer science. It is commonly researched by
academics as well as ubiquitously implemented in most sport science support pro-
grammes in ­elite-​­level clubs. The shared interest provides opportunity for conceptual
and pragmatic discussions amongst those interested in providing effective solutions
to the challenge of understanding the demands associated with preparation strategies
(­and performance). In this chapter, we attempt to present content that is indicative
of current scientific thinking and contemporary practice. By presenting these diverse
viewpoints, we provide a broad perspective on current opinions and the future chal-
lenges that may exist in the field.

The importance of monitoring training

Superior systems and organisational approaches to training have the potential to
provide important competitive advantages. As training is a ­process-​­effective training
requires regulation (­Sands et al., 2017). The monitoring of training represents an im-
portant feedback tool by which “­data” can be collected to determine if individuals are,
in general terms, both completing and adapting to the training that is planned by the
coach/­practitioner (­Impellizzeri et al., 2020). Over the last decade, the interest in train-
ing monitoring in elite soccer has risen exponentially with monitoring used to sup-
port the planning of training at both team and individual levels (­Buchheit & Simpson,
2017). This information is, therefore, a key component of both s­ hort-​­and ­long-​­term
­decision-​­making in relation to both the exercise that players need to be prepared for
competition and an understanding of their subsequent response to that exercise (­West
et al., 2021). As such, the effective monitoring of training load is an important part of
the sports science support strategy of most elite teams to both improve performance
and reduce injury risk.

Scientific and conceptual considerations for the monitoring of training

Training monitoring should involve describing both the exercise (­what the player does)
and response (­how the player changes behaviour or perceives the exercise (­Impellizzeri
et al., 2020; see ­Figure 18.1). These outcomes are often operationalised as the exter-
nal and internal load (­Brink et al., 2010). The external load is the physical activity
prescribed in the training programme (­the quality, quantity, and organisation of the

DOI: 10.4324/9781003148418-22
 Monitoring training 293

Metabolic

STIMULUS
Type External Internal Outcome Feedback Training
Intensity Load Load Decisions
Volume Maladaptation
No Effect Modify
Adaptation Don’t
modify
Mechanical

­Figure 18.1 A schematic representation of the role on monitoring training in supporting

the training process.

exercises selected) that ultimately induces a specific psychophysiological response

(­i.e., internal load). Assessing these components allows the practitioner to under-
stand whether the external load has induced the planned acute psychophysiological
response (­internal load) and whether that load has induced the expected adaptations
(­indirectly assessed by measuring the training outcome). Impellizzeri et al. (­2020) and
Gray et al. (­2018) have suggested that less is frequently understood about the internal
than the external load. This state of play may be a consequence of the increased dif-
ficulty in capturing these internal responses compared to the relative ease with which
the external load can be captured (­West et al., 2021). Traditional approaches to as-
sessing the internal response have focussed on variables that are broadly classified as
“­metabolic” (­e.g., cardiovascular variables, indications of the energy systems used to
support the activity). Soccer activities also lead to “­mechanical” stresses on tissues
in the musculoskeletal system (­e.g., cartilage, bone, muscle, and tendon tissue; Van-
renterghem et al., 2017). This mechanical stress is considered important for structural
and functional adaptations of the musculoskeletal system (­Kjaer, 2004). This mechan-
ical l­ oad-​­adaptation pathway has previously been largely overlooked in approaches to
monitoring (­Vanrenterghem et al., 2017), but its importance is now recognised. Failure
to meet the target internal responses in either system represents a training error that
can be used as feedback to modify the training plan (­feedback loop) (­see ­Figure 18.1).
By applying these processes, the effectiveness of training can be enhanced. These im-
provements are, however, a direct consequence of the ability of the information to be
operationalised by the coach and athlete (­Viru & Viru, 2000).

Important principles for monitoring training

The application of these general concepts and principles to the specific demands of
soccer is important. Boullosa et al. (­2020) identified several important considerations
that are key to monitoring training load in sports such as soccer compared to more
individual sports that have traditionally been the focus of research related to training
load. Team sports don’t require players to maximise their fitness levels as is common
in some individual sports that are determined largely by time to completion. The mul-
tifactorial nature of performance and the requirements to constantly peak and taper
due to the competitive schedule require an approach that is more associated with op-
timising performance across prolonged timescales than supporting periodic ­one-​­off
294 Barry Drust and Laura Bowen
maximal efforts. Training is also a collective activity and is not frequently planned in
detail around individual needs. The large number of contextual factors (­e.g., playing
position) further complicate the relationship between the internal and external load
for any individual (­Boullosa et al., 2020) compared to more individual ­athlete-​­centred
approaches. Although the rationale for monitoring training may be similar in soccer
to those used with individual athletes, the nuances do combine to necessitate an ap-
proach that is specific to the sport.
Attempts to individualise training load monitoring are an important consideration in
soccer. Individualising training load monitoring might include tailoring the approach
used to collect, analyse, and interpret data based on the type of training completed.
For example, different approaches may be important for more ­g ym-​­based sessions or
those associated with the rehabilitation process than those used for ­field-​­based train-
ing. Individualisation from the perspective of training monitoring approaches for
distinct players is also key. Researchers suggest that the response to both an exercise
stimulus and to the period immediately following that exercise is highly individual
(­Becker et al., 2020). This conclusion suggests that relying on group approaches, espe-
cially with respect to data analysis and interpretation may be limited due to the loss
of specific detail around the data associated with players (­Helms et al., 2020; Sands
et al., 2017). Such attempts represent a more systematic approach to defining the se-
lection and use of markers of specific stress and adaptation processes of the player in
question than adopting more general guidelines (­Sands et al., 2017). West et al. (­2021)
argued that both the internal and external responses may be important to consider at
the individual level. The extent to which an individualised approach to training load
monitoring can be adopted is probably a function of pragmatics such as cost and time.
While it is obvious that it will not be practically possible to employ a strategy that is
100% bespoke, some aspects of individuality are important for an effective protocol.
Individualising training load monitoring may provide the basis for the diversification
of monitoring approaches to include methodologies that do not evaluate the players’
response to training per se but rather a broader range of factors that relate to issues that
have the potential to impact the adaptive process (­by influencing either the response to
exercise or the that in the acute phase following the completion of exercise; Boullosa
et al., 2020). The competitive schedule exposes players to high levels of background stress
(­e.g., public and media attention) as well as frequent travel to play games (­often across in-
ternational borders and time zones). Such things are in themselves a source of “­stress” as
they can create an environment for the elite player where important lifestyle factors such
as dietary routines and sleep habits are n­ on-​­conventional. It may, therefore, be important
to consider the implementation of approaches that can provide objective information
on more general lifestyle factors as experienced by players. Such ­multi-​­dimensional ap-
proaches could include sleep, nutrition, and general life stress (­Pelka et al., 2017). The
specific nature of the strategy for these modifiable factors may not be uniform across the
season and could change as a function of the specific challenge that may be relevant to
the team and/­or individual player at a specific point in the preparation/­competition cycle.
From a conceptual perspective, an effective strategy to monitor training load need to
be flexibly applied and involve multiple methods and outcome variables. Approaches
should not be “­one size fits all” but rather should be tailored in relation to the con-
text (­Impellizzeri et al., 2020) as no single measure captures training load effectively
(­Maughan et al., 2020; Wiig et al., 2020). Any measurement variable or method may
provide useful information if the approach makes logical sense and is well understood
 Monitoring training 295

Theoretical Considerations

Relevance to Scientific Measurement

Analysis and
the purpose underpinning consistency and
interpretation
intended accuracy

Approach to monitoring training

Cost Low time Low Easy to use Ease of data Simplicity of Accessible
demands demand analysis and feedback
for staff for interpretation
athlete
Practical Considerations

­Figure 18.2 Some theoretical and practical considerations in monitoring training.

by the practitioner (­Maughan et al., 2020). This understanding should include a critical
appraisal of the reliability, validity, and utility of the data being collected. Depending
on resources and context, this may be done through several routes, such as: (­i) existing
independent validation; (­ii) partnering with universities or industry to perform new
validation work; or (­iii) internal validation work (­West et al., 2021).

Potential approaches for monitoring training

The previous section outlined some of the important conceptual considerations that
are important to any training monitoring strategy. This section outlines broad ap-
proaches that are commonly used within soccer. While there is typically always a fo-
cus on the latest theoretical information in the choice of method used, pragmatics play
just as important a part in the strategy (­see ­Figure 18.2).
The specifics of training load monitoring strategies and techniques used in elite
soccer are often not publicly available as such information is thought to provide a
competitive advantage. This fact makes it difficult to accurately report the exact pro-
cedures used by clubs. The widespread availability of p ­ ractice-​­based information
(­professional articles and podcasts) and scientific articles (­Akenhead & Nassis, 2016;
Weston, 2018) provide some insight into both current industry practices and the use-
fulness of a given technique for tracking training load (­Benson et al., 2020). While a
consensus seems to exist on the potential approaches used to collect data, thoughts on
their relative effectiveness are a little less coherent. This section briefly describes the
methods commonly used as opposed to providing an ­in-​­depth critical evaluation of
each of these approaches.

Wearable devices
Wearable devices, particularly those that measure the movement characteris-
tics of players are seen as fundamental for training monitoring. Wearable devices
296 Barry Drust and Laura Bowen
essentially include sensor(­s) and associated firmware to collect the data and software
to analyse and store information (­Sperlich et al., 2020). Devices may include a single
sensor or more commonly multiple sensors such as global positioning or local posi-
tioning system and an IMU (­which frequently consists of an accelerometer (­s enses
segmental acceleration), a gyroscope (­s enses angular displacement), and a magneto-
meter (­s enses orientation); Willy, 2018). It is important to adhere to recommended
guidelines for data collection, processing, and reporting when using wearables
(­Malone et al., 2017). These include the use of suitable garments in which to wear
the device, consistent use of the same unit and quality control procedures for data
collection (­e.g., number of satellites connected and appropriate horizontal dilution
of precision) and analysis (­e.g., consistent use of the same manufacturer firmware
and threshold bands used for calculation of metrics) (­Malone et al., 2020). The use
of data from these devices is a major area of research and discussion for scientists
and practitioners, respectively (­Buchheit & Simpson, 2017) with uncertainty around
the most appropriate metrics to use and how information can be most effectively
reported back to key stakeholders (­i.e., coaches and athletes) (­Malone et al., 2020).
Current research (­Kalkhoven et al., 2020) also continues to critically evaluate the
usefulness of data from these systems in reflecting the actual loads experienced by
the body’s tissues during exercise.

Evaluating physiological responses

Another popular approach for training monitoring is based on evaluating physiologi-
cal responses. These internal responses may be assessed within an exercise session (­to
evaluate the demand associated with the activity) or may be completed ­post-​­exercise
(­to attempt to evaluate the impact that the exercise has had on the individual). ­Post-​
­exercise responses are typically measured at a variety of time points that could range
from immediately ­post-​­exercise up to 72 h after the session has finished. Heart ­rate-​
­related assessments remain a very popular example of this type of approach as the
equipment is easily accessible, cheap, and easy to administer.
Measuring concentrations of biomarkers in body fluids (­e.g., blood and saliva) rep-
resent another popular approach. Pedlar et al. (­2019) have suggested that such ap-
proaches can be used to assess both the efficacy of training interventions and the
capacity to tolerate training load. A wide range of parameters (­e.g., creatine kinase,
glutamine, and ­C-​­reactive proteins) can be typically measured. Such approaches are
thought to be effective when they involve frequent measurements and interpretation
that is individualised (­Becker et al., 2020). Considerations related to sample collec-
tion, such as the control of ­pre-​­testing conditions (­such as the time of day, posture,
and fasting/­hydration status) and the analysis and storage of samples are important
(­Pedlar et al., 2019). The development of robust procedures for these types of testing
programmes can, therefore, result in significant operational considerations and costs.
Another approach that can broadly be fitted under this category is performance
assessments. These approaches are useful as a tool for monitoring training as the
performance on a given task broadly reflects the status of the physiological system(­s)
of an individual following exercise. In some cases, these data may reflect aspects of
the psychological state of the individual (­e.g., motivation). This may mean that such
approaches may give a more holistic indication of the player’s status. Common as-
sessments include neuromuscular assessments such as the ­counter-​­movement jump or
 Monitoring training 297
assessment of specific relevant muscle groups (­hamstrings, groins, etc.) (­Halson, 2014).
They may also include ­sub-​­maximal running tests (­Rago et al., 2020) that incorporate
other physiological data, such as heart rate collected during and ­post-​­exercise.

Questionnaires and subjective evaluations

These approaches use scales or short questionnaires to enable the player to provide
subjective feedback to coaches/­practitioners on either the demands associated with ex-
ercise or their specific feelings about the impact of exercise on their physiological sta-
tus ­post-​­exercise. Rating of perceived exertion is probably the most popular approach
to subjectively evaluating the physical demands of a training session or a match us-
ing a simple scale. This subjective rating is then frequently multiplied by the session
duration to provide an indication of the overall training load (­Thorpe et al., 2016).
Other approaches that are developed to provide more specific information about the
demands placed on specific aspects of the body (­e.g., muscular, breathlessness, and
cognitive) are becoming popular as these have the potential to provide more detailed
information on the exact nature of the training demand (­Macpherson et al., 2019).
Questionnaires are the other subjective tool frequently used to monitor the response
to training (­e.g., the Hooper scale; Hooper & Mackinnon, 1995). These questionnaires
often comprise brief, ­single-​­question measurement of an aspect of wellbeing, such as
rating of general fatigue on a Likert scale (­Duignan et al., 2020). There is evidence for
the appropriateness of such approaches in the process of training monitoring (­Moalla
et al., 2016) (­­Table 18.1).

Monitoring training in practice

While there is a plethora of research regarding the approaches and outcomes of train-
ing processes, less is known about the implementation of training monitoring within
the practice.
Consequently, monitoring is rapidly becoming a minefield. As a sport scientist in
the elite game, it is no longer enough to be able to create a few graphs. Top clubs
are now recruiting data engineers and programmers to handle the mass of informa-
tion available. However, translating those pages of numbers and code to something
that positively effects ­on-​­pitch performance is still the job of practitioners. Therefore,
effective implementation of training load monitoring strategies would appear to be
important for future research, to inform player support and development, as well as
injury prevention.
In soccer, it is very unlikely that the person who decides what information to moni-
tor is also the player being monitored. Quite often, the person making those decisions
is also not designing and coaching the practice. Therefore, coach and player ­buy-​­in are
as important as what information to use. When trusting relationships with staff and
players are built, and the value of the information is collectively understood, an effec-
tive monitoring environment can be created. The aim of this environment is to inform
performance optimisation and injury risk reduction. The only purpose of monitoring
is to affect practice. Processes and data sources must be constantly reviewed to ensure
that this is the case. In the next section, we cover the application of player monitoring
in practice, including streamlining the useful information, creating an effective envi-
ronment, and most importantly impacting performance.
298 Barry Drust and Laura Bowen
­Table 18.1 Potential approaches for training load monitoring including outcome measures

Approach Category Example outcome measure(­s)

­Micro-​­electrical Wearable device • Total distance covered

mechanical system • ­High-​­speed running distance/­sprint distance
(­MEMS) devices • Accelerations/­decelerations
(­e.g., GPS) • ­Accelerometry-​­derived load (­e.g., playerload)
Heart rate Physiological • Heart rate during exercise (­average, peak, time
above a given %)
• Heart rate recovery
Blood Physiological • Blood lactate during/­after exercise
• Creatine kinase
Saliva Physiological • IgA
• Cortisol
Neuromuscular Physiological • Rate of force development
assessments • Peak force
(­e.g., ­counter-​ • Fatigue index
­movement jump, • Peak velocity
isometric strength • Impulse
assessment)
­Sub-​­maximal Physiological • Peak heart rate
assessments (­e.g., • Heart rate at a given time period following
­sub-​­maximal exercise
running tests)
Subjective rating Subjective • RPE
scales • Differential RPE
• Muscle soreness
• Sleep quality
• Fatigue
• Recovery
Questionnaires Subjective • Muscle soreness
• Sleep quality
• Fatigue
• Recovery

Streamlining data sources

With the wealth of data now available, practitioners may slip into the trap of think-
ing “­what can we measure?” rather than “­what do we need to know?”. The first step
should be to establish performance questions, specific to the athletes, the club, and the
competition. Knowing the answer to the questions should have the potential to affect
performance.
The next step should be to identify the tools or measures available to answer the
question. These tools should be ­evidence-​­based, rather than purely commercially
driven. While it may be a cliché, if it seems too good to be true, that usually is the case.
A gold standard strategy should include the most accurate equipment, rather than the
best packaged. Technological advances are providing evermore detailed information
that is of practical value. However, limitations in terms of validity and o ­ n-​­field use-
fulness are still present and often overlooked (­Buchheit & Simpson, 2017). The key
measurement principles of validity and reliability, as well as their practical efficacy,
should be core foundations upon which choices are based. This fact can be illustrated
by the challenges faced when measuring the mechanical loads that exist within applied
 Monitoring training 299
settings. Most commonly, GPS units with i­n-​­built accelerometers are used to quan-
tify these mechanical loads. Yet, existing research has found a lack of precision with
which these units measure certain ­spatio-​­temporal variables, such as changes in veloc-
ity (­Roe et al., 2017) or ­h igh-​­speed running (­Coutts & Duffield, 2010), as well as other
potentially relevant activities such as collisions (­Naughton et al., 2020).
Conversely, GPS has been found to be a valid and reliable measure of movement
patterns over lower speeds and greater distances (­Jennings et al., 2010; Portas et al.,
2010). The development of custom algorithms which use the data from integrated
­100-​­Hz accelerometers to improve accuracy (­Coutts & Duffield, 2010) alongside tech-
nological advancements and greater sampling frequencies have helped to reduce meas-
urement errors at higher velocities. For example, the recent release of ­18-​­Hz units has
resulted in a further increase in the validity and reliability of distance measurements
and sprint mechanical properties than earlier units with lower sampling rates (­Hoppe
et al., 2018). Thus, understanding the limitations is vital when determining the best
tool for answering a performance question. In the case of GPS, descriptions of basic
measurements such as distance and speed during training and match play can be an-
swered with a sufficient level of certainty (­Aughey, 2011). However, the quantification
of ­h igh-​­velocity movements and changes of direction must be interpreted with varying
levels of caution, depending on the device used. Accordingly, GPS does not provide a
feasible proxy measure of the mechanical loads experienced by specific tissues. These
shortcomings likely contribute to the many inconsistent results associating GPS data
with injury (­Kalkhoven et al., 2021).
Regardless of the tool, if the validity or reliability is not known, it should not be
used. Monitoring can be expensive, and some accuracy may have to be traded off
for affordability. Regardless, accuracy still must be tested, to ascertain the error of
measurement. Ultimately, if you do not know if it measures what it says it does, you
may as well just guess the answer to your performance question. Validity and relia-
bility are not the only factors to consider; soccer is a ­fast-​­paced environment; and the
information must be analysed and fed back within an effective time frame to impact
performance. It is also e­ ver-​­changing so can the information be collected repeatedly
without a detrimental time cost? For example, a c­ ounter-​­movement jump on a force
platform can provide a valid and reliable measure of jump performance (­Heishman
et al., 2020). This testing can be done s­emi-​­regularly (­e.g., weekly or fortnightly)
within a squad gym session, resulting in minimal disturbance to the training schedule.
Improvements in jump performance over a season can be determined using a number
of ­evidence-​­based metrics (­e.g., concentric impulse (­Ns), jump height (­c m), and eccen-
tric peak force (­N); Merrigan et al., 2021), and the information can be feedback in real
time. However, to use the output measures of a ­counter-​­movement jump to indicate
neuromuscular fatigue, players would have to be tested multiple times, including a
baseline measure and various p ­ ost-​­exercises time points (­e.g., 0 h, 24 h, 48 h, and 72 h)
(­Gathercole et al., 2015). How many times a week would a coach allow for a squad to
be jump tested, at the sacrifice of time on the pitch? The ­cost-​­reward decision of what
and how often should always be made in relation to impact on performance. Stream-
lining information to ensure the optimal impact is a process that requires constant
review, reflection, and amendment. The process itself should include three questions.
First, and most importantly, will it make a difference to performance? Second, does it
accurately measure what it says it does? Third, can the information be used effectively
within environmental constraints?
300 Barry Drust and Laura Bowen
Building trust and coach ­buy-​­in
­ ub-​­optimal integration with coaches has been highlighted as one of the main factors
S
affecting the impact of monitoring in elite soccer (­Akenhead & Nassis, 2016). Effective
communication, supported by applied research and knowledge, may facilitate the re-
lationship between coach and practitioner, increasing the chances of monitoring being
impactful (­Ward et al., 2019).
Player b­ uy-​­in is also vital in ensuring consistency and accuracy of measurement.
To enhance compliance, players should have a basic understanding of why they are
being monitored and how the information is beneficial. Feedback should be con-
sistent, objective, and individualised where possible. To increase the chance of indi-
vidual ­buy-​­in, a basic understanding of how the player likes to receive information
(­e.g., verbally and visually) is recommended. Simple psychometric tests, such as the
DISC assessment (­Marston, 1928) may be used in practical settings to identify per-
sonality traits in athletes or coaches which can aid with relationship building. These
tests may give an indication of how feedback is best received by the individual,
what motivates them, and how they might respond to stress or pressure. This type
of information, along with the personal insights of the practitioner about players,
may provide a basis for personal communications that can add important addi-
tional information about the players’ status. These conversations, often dependent
on relationships, can provide opportunities for a player to communicate when they
feel they can push harder, and when they need thereby providing a useful insight for
programming.
Irrespective of the approach used, the purpose of training load monitoring is to
influence the training processes completed by the players to impact both the ­short-​
t­ erm response and the ­long-​­term training outcome. To impact this process, the data
collected must inform the decisions made by key stakeholders in the management
of players. It is important to consider the process by which information use is made
effective. One of the major challenges for scientists and coaches who collect training
data is to be able to make meaningful inferences on the efficacy of the training pro-
cesses for players and coaches (­Bourdon et al., 2017). Coach and player education,
focused mainly on how monitoring will improve performance, provides a platform
for effective communication and implementation. Their input on how the informa-
tion is fed back and used is vital to ensure support. Building relationships should in-
crease the impact of monitoring, only if this relationship consists of mutual trust and
understanding. Practitioners should provide clarity on what the information means
and how it will be used, highlighting the potential performance benefits, to maximise
adherence.
Monitoring should be used to inform decisions, not dictate them. There may be
times when information is ignored, as there is an alternative that is considered more
beneficial for performance. As elite sporting environments are ­p erformance-​­focused,
in those instances, it is the role of the sports science and medical staff to ensure the
players are prepared as best as possible for the required demands. Ideally, monitoring
tools should not be used to withdraw athletes from sessions part way through. Clarity
and trust between coach and practitioner should mean that monitoring can guide the
plan prior to execution and provide future recommendations if initial guidelines are
not adhered to. Consequently, monitoring solutions must be adaptable and considered
a part of the wider picture.
 Monitoring training 301

­Figure 18.3 A female player’s physical “­profile” compared to the squad average. The white
line is the player. The black line is the squad average. All testing scores have
been converted to z­ -​­scores to allow comparison on the same axis.

Monitoring for performance vs. injury prevention

As well as building relationships with coaches and players, the support staff should
have a level of trust between them to provide the best service to the players. Sports
scientists will typically prescribe high training loads which are aimed at enhancing
performance through physiological adaptation to stress. Conversely, the medical staff
advocate lower loads with the aim of reducing the risk of injury (­Ekstrand et al., 2019).
Both approaches have equal importance in maximising team success, however, the
demands must be planned in synergy to be effective (­Gabbett & Whiteley, 2017).
Quantification of training allows you to push the boundaries of what the players
can achieve, without it being beyond what they can tolerate. The ability to progress
training safely is hugely advantageous; players with developed physical qualities can
tolerate higher training demands, and exposure to larger amounts of training develops
physical qualities (­Gabbett et al., 2019). Therefore, not only is it important to monitor
training but also to test and monitor the physical qualities of the players. Strength, aer-
obic capacity, speed, power, and agility are key attributes needed to excel as a player.
Baselines should be established and revisited to ensure that the training programmes
are effectively developing the players. As mentioned earlier, the tests used to ascer-
tain this must be relevant, accurate, and practical. Some of the fi ­ eld-​­and ­g ym-​­based
tests regularly used to measure the key physical attributes include whole body or spe-
cific muscle strength assessments such as the isometric m ­ id-​­thigh pull or hamstring
strength tests (­e.g., Nordbord), tests of aerobic capacity (­maximal oxygen consumption
302 Barry Drust and Laura Bowen
or ­Yo–​­Yo intermittent recovery test level), sprint and agility tests (­e.g., 505 test), and
evaluations of horizontal and vertical power such as the c­ ounter-​­movement jump.
These tests can be completed in a day, or individually throughout the ­pre-​­season
and competitive calendar with very little disruption to the training schedule. Once all
the tests are complete, this information can be collated to “­profile” the players, iden-
tifying their strengths and areas for improvement to help inform training processes.
­Figure 18.3 shows an example of a female player’s results from one testing day. Her
results are compared against the squad average to display which attributes she excels
at, and which may be improved through a specific training programme.
Testing these attributes also highlights anything that might ­pre-​­dispose a player to
injury. Injury prevention should not be considered separate from performance, but
rather a contributing factor. Researchers have shown that team success is directly re-
lated to player availability (­Hagglund et al., 2013). Monitoring processes should, there-
fore, reflect this fact. Choosing tests that can be repeated regularly increases sensitivity
to significant changes in results, which may indicate an injury risk. For example, regu-
larly testing limb strength and symmetry during a Nordic hamstring fall allows you to
establish individual normative values. From this, you can identify significant changes
that may imply hamstring fatigue, or conversely improvements in strength.

Monitoring in daily practice

The readiness of a player to perform on the pitch is m ­ ulti-​­factorial, making it almost im-
possible to predict. However, collecting relevant and accurate information that span the
many factors associated with performance, allows an informed estimate of player read-
iness. Wellness or ­self-​­report questionnaires have proven to be one of the most effective
and sensitive monitoring tools (­McCall et al., 2016). They provide an internal measure of
player readiness and fatigue, with very little cost, and very high applicability across pop-
ulations. Most often players will be required to answer these questionnaires daily, within
an actionable time frame prior to training. Depending on the questionnaire used, the
players rate certain variables such as sleep quality, stress, and soreness on a given scale.
The literature recommends that these scores are used to detect meaningful change for an
individual, rather than allocating an arbitrary “­red flag” at a given value (­Saw et al., 2016).
­Figure 18.4 is an example of a w ­ ell-​­being report used daily in a team sport setting
to inform player readiness. The colour coding highlights the arbitrary score, whilst
icon to the right indicates a significant change from the player’s average score for that
variable based on the smallest worthwhile change (­e.g., if a player scores 5 for soreness,
but always scores 5 for soreness, the icon will not appear).
When monitoring female players, it is also important to track the menstrual cycle.
Tracking it in a similar way to wellness, to establish individual norms is recommended.
While still a relatively new area of research, it is accepted that there is large variation
in symptoms at different times in the cycle between people. While is very unlikely that
an athlete would have to withdraw from training or competition, some modification or
consideration may be required.
The daily training load is most often monitored using GPS. These data are mainly
used to provide feedback live and p ­ ost-​­session to coaches and players regarding the
physical demands of training/­match. Most commonly metrics such as total distance,
distance at different intensities, accelerations, decelerations, and speed are used to
describe physical outputs. More recently, daily GPS data are used to guide training
 Monitoring training 303

­Figure 18.4 An example ­well-​­being report illustrating shading coding and marks to help
inform player readiness.

programming and identify potential increases in injury risk through poor program-
ming. GPS is often combined with heart rate monitoring to determine both the external
and internal stress on the body. P
­ ost-­​­­session-​­rated perceived exertion (­RPE) scores are
commonly recorded. This requires the players to rate how hard the session felt, usually
out of ten. These scores can then be multiplied by the session duration to give an idea of
subjective load on the body. The advantage of this monitoring tool is that it is no cost
and can be used for any activity. However, scores can be influenced by mood and peers,
amongst other factors. Ultimately, there are a multitude of monitoring tools that can be
used to understand the factors affecting player readiness to perform. These tools have
a much more important role than to provide an objective result on a test. Those results
should indicate changes that can be made in practice to promote optimal performance.

­Long-​­term athlete monitoring

It is rare that a o­ ne-​­off data point can give enough information to properly under-
stand player status. Monitoring of any measure is usually done on a l­ong-​­term basis
to provide a greater understanding of player norms. L ­ ong-​­term monitoring allows
you to track progression or improvement, training tolerance, and growth and mat-
uration, as well as enhancing talent identification and benchmarking against other
players. Fitness testing is a good example of l­ong-​­term athlete monitoring. Physi-
cal qualities are often tested at the start of ­pre-​­season to identify player strengths
and weaknesses and to benchmark them against teammates. These tests are then
repeated throughout the season, usually every 6­ –​­8 weeks, to ascertain progression
and, therefore, the effectiveness of training programmes. Repeating these tests can
also give an indication of the effects of growth and maturation on physical qualities
in youth players.
­Long-​­term training monitoring using GPS is now also widely used. One of the
more recent methods of monitoring is known as the acute chronic training load ratio
(­ACWR). This typically involves the assessment of the absolute ­1-​­week training load
(­acute training load) relative to 4­ -​­week chronic training (­­4-​­week average acute training
load) (­Hulin, Gabbett, Lawson et al., 2016). A training load can then be calculated
indicating whether the individual’s acute workload is greater, less than or equal to the
preceding chronic workload they have been prepared for. If the chronic workload is
304 Barry Drust and Laura Bowen

­Figure 18.5 A graphical representation of the progressive increase of a player’s chronic

­h igh-​­speed running (­training load metric) over the course of 8 weeks. The
player begins with a chronic training load of 1,700 m representing a ­two-​
­match training load and is trained with the goal of progressively increasing
his chronic training load to the equivalent of three matches per week. The
periodisation model used a ­three-​­weekly cycle including a maintenance week
with an acute:chronic workload ratio (­ACWR) of ~1.­0 –​­1.2, an overload week
(~1.­4 –​­1.7), followed by a d
­ e-​­load (~0.85). Adapted from “­Recommendations
for hamstring injury prevention in elite football: translating research into
practice” (­Buckthorpe et al., 2018).

high and the acute workload is low, the player is w ­ ell-​­prepared. However, if the acute
workload “­spikes” beyond the chronic workload, the player is in a state of fatigue which
could be both detrimental to performance and increase the risk of injury (­Hulin, Gab-
bett, Caputi et al., 2016). The idea is to fluctuate training to allow both stimulus and
recovery, without the current (­acute) training being too high, or too low, versus their
normal (­chronic) training. Over time, the aim is to progressively increase the chronic
workload to improve tolerance. However, training at consistently high chronic train-
ing demands may result in s­ tress-​­related injuries (­Drew & Finch, 2016) and, therefore,
a workload “­c eiling” must be set. Below is an example of how the ACWR can be used
to plan and monitor training. The players may have two games within a week maxi-
mum, interspersed with light training. Thus, the equivalent of three games worth of
activity a week was used as the workload ceiling (­considered w ­ orst-​­case scenario). In
addition to the progressive increases in training, training content was periodised in
­3-​­week blocks (­based on (­Bowen et al., 2017), involving a ­de-​­load week, a maintenance
week, and an overload week (­­Figure 18.5). The ACWR thresholds for each of these
weeks were set at ~0.85 for a d ­ e-​­load, ~1.­0 –​­1.2 for a moderate week, and ~1.­4 –​­1.7 for
a high week (­Bowen et al., 2020) regardless of the external load metric used. Players
who did not regularly play in matches or were returning from injury, were provided
with t­ op-​­up conditioning across the required metrics to maintain sufficient acute and
chronic workloads.

Conclusions and future directions

It is clear from the information presented in this chapter that training load monitor-
ing is now a very important component of any sport strategy used within football.
 Monitoring training 305
This is largely the case irrespective of the population of interest (­e.g., children, fe-
males, and adult males) or level of play (­i nternational player, elite players in the high-
est league or those playing in lower divisions). While there are a range of monitoring
strategies available to practitioners they are all primarily focused on evaluating the
activities that players complete and the responses of individuals to these external
demands. These insights have the potential, when part of an effective ­decision-​
­making system, to help support the performance of players as well as reduce the
potential for injury. While such outcomes have some support within the scientific
literature the relative newness of both the available technology and the process of
training load monitoring still requires research studies to fully evidence base effec-
tive implementation.
As the rewards for successful performances continue to increase there will continue
to advance in training monitoring. These developments will likely take many forms
and be associated with data collection, data analysis/­interpretation, and reporting. It
is inevitable that new technologies and approaches will become available, which may
facilitate the “­invisible monitoring” suggested by West et al. (­2021). Advances in data
analysis may include better connections across different data streams and provide op-
portunities to both describe and predict performance outcomes across a variety of key
performance metrics. Faster and more detailed data visualisation techniques enable
this information to be more efficiently and effectively communicated to players and
coaches across multiple platforms. The rapid pace that technology develops makes
the exact nature of these developments difficult to predict. It is also unclear if these
changes will be a function of the need to better support performance and protect the
health of players or be primarily driven by the commercial considerations of the sport
and/­or a need to continue to impact the spectator experience. It will be important in
the future, as it is now, to ensure that any information on training that is provided is
useful to support ­decision-​­making.

References
Akenhead, R., & Nassis, G. P. (­2016). Training load and player monitoring in ­h igh-​­level foot-
ball: current practice and perceptions. Int J Sports Physiol Perform, 11(­5), ­587–​­593. https://­
doi.org/­10.1123/­ijspp.­2015- ​­0331
Aughey, R. J. (­2011). Applications of GPS to field sports. Int J Sports Physiol Perform, 6, ­295–​­310.
Becker, M., Sperlich, B., Zinner, C., & Achtzehn, S. (­2020). I­ ntra-​­individual and seasonal vari-
ation of selected biomarkers for internal load monitoring in U ­ -​­19 soccer players. Front Phys-
iol, 11, 838. https://­doi.org/­10.3389/­fphys.2020.00838
Benson, L. C., Raisanen, A. M., Volkova, V. G., Pasanen, K., & Emery, C. A. (­2020). Workload
­a-­​­­wear-​­ness: monitoring workload in team sports with wearable technology: a scoping re-
view. J Orthop Sports Phys Ther, 50(­10), ­549–​­563. https://­doi.org/­10.2519/­jospt.2020.9753
Boullosa, D., Casado, A., Claudino, J. G., ­Jimenez-​­Reyes, P., Rave, G., ­Castano-​­Zambudio,
A., ­Lima-​­Alves, A., de Oliveira, S. A., Jr., Dupont, G., Granacher, U., & Zouhal, H. (­2020).
Do you play or do you train? insights from individual sports for training load and injury risk
management in team sports based on individualization. Front Physiol, 11, 995. https://­doi.
org/­10.3389/­fphys.2020.00995
Bourdon, P. C., Cardinale, M., Murray, A., Gastin, P., Kellmann, M., Varley, M. C., Gabbett,
T. J., Coutts, A. J., Burgess, D. J., Gregson, W., & Cable, N. T. (­2017). Monitoring athlete
training loads: consensus statement. Int J Sports Physiol Perform, 12(­Suppl 2), ­S2161–​­S2170.
https://­doi.org/­10.1123/­IJSPP.­2017-​­0208
Bowen, L., Gross, A. S., Gimpel, M., B ­ ruce-​­Low, S., & Li, F. X. (­2020). Spikes in acute:chronic
workload ratio (­ACWR) associated with a ­5 –​­7 times greater injury rate in English premier
306 Barry Drust and Laura Bowen
league football players: a comprehensive ­3-​­year study. Br J Sports Med, 54(­12), ­731–​­738.
https://­doi.org/­10.1136/­­bjsports-­​­­2018- ​­099422
Bowen, L., Gross, A. S., Gimpel, M., & Li, F. X. (­2017). Accumulated workloads and the
acute:chronic workload ratio relate to injury risk in elite youth football players. Br J Sports
Med, 51(­5), ­452– ​­459. https://­doi.org/­10.1136/­­bjsports-­​­­2015- ​­095820
Brink, M. S., Nederhof, E., Visscher, C., Schmikli, S. L., & Lemmink, K. A. (­2010). Monitoring
load, recovery, and performance in young elite soccer players. J Strength Cond Res, 24(­3),
­597–​­603. https://­doi.org/­10.1519/­JSC.0b013e3181c4d38b
Buchheit, M., & Simpson, B. M. (­2017). ­Player-​­tracking technology: ­half-​­full or ­half-​­empty
glass? Int J Sports Physiol Perform, 12(Suppl 2), S235–S241.
Buckthorpe, M., Gimpel, M., Wright, S., Sturdy, T., & Stride, M. (­2018). Hamstring muscle
injuries in elite football: translating research into practice. Br J Sports Med, 52(­10), ­628–​­629.
https://­doi.org/­10.1136/­­bjsports-­​­­2017- ​­097573
Coutts, A. J., & Duffield, R. (­2010). Validity and reliability of GPS devices for measuring
movement demands of team sports. J Sci Med Sport, 13(­1), ­133–​­135. https://­doi.org/­10.1016/­j.
jsams.2008.09.015
Drew, M. K., & Finch, C. F. (­2016). The relationship between training load and injury, illness
and soreness: a systematic and literature review. Sports Med, 46(­6), ­861–​­883. https://­doi.
org/­10.1007/­­s40279-­​­­015-­​­­0459-​­8
Duignan, C., Doherty, C., Caulfield, B., & Blake, C. (­2020). S ­ ingle-​­item ­self-​­report measures of
­team-​­sport athlete wellbeing and their relationship with training load: a systematic review. J
Athl Train, 55(­9), ­944–​­953. https://­doi.org/­10.4085/­­1062-­​­­6050-​­0528.19
Ekstrand, J., Lundqvist, D., Davison, M., D’Hooghe, M., & Pensgaard, A. M. (­2019). Commu-
nication quality between the medical team and the head coach/­manager is associated with
injury burden and player availability in elite football clubs. Br J Sports Med, 53(­5), ­304–​­308.
https://­doi.org/­10.1136/­­bjsports-­​­­2018- ​­099411
Gabbett, T. J., Nielsen, R. O., Bertelsen, M. L., Bittencourt, N. F. N., Fonseca, S. T., Malone,
S., Moller, M., Oetter, E., Verhagen, E., & Windt, J. (­2019). In pursuit of the ‘­unbreakable’
athlete: what is the role of moderating factors and circular causation? Br J Sports Med, 53(­7),
­394–​­395. https://­doi.org/­10.1136/­­bjsports-­​­­2018- ​­099995
Gabbett, T. J., & Whiteley, R. (­2017). Two ­Training-​­load paradoxes: can we work harder and
smarter, can physical preparation and medical be teammates? Int J Sports Physiol Perform,
12(­Suppl 2), ­S250-​­S254. https://­doi.org/­10.1123/­ijspp.­2016-​­0321
Gathercole, R. J., Sporer, B. C., Stellingwerff, T., & Sleivert, G. G. (­2015). Comparison of the
capacity of different jump and sprint field tests to detect neuromuscular fatigue. J Strength
Cond Res, 29(­9), ­2522–​­2531. https://­doi.org/­10.1519/­JSC.0000000000000912
Gray, A. J., Shorter, K., Cummins, C., Murphy, A., & Waldron, M. (­2018). Modelling move-
ment energetics using global positioning system devices in contact team sports: limitations
and solutions. Sports Med, 48(­6), ­1357–​­1368. https://­doi.org/­10.1007/­­s40279-­​­­018-­​­­0899-​­z
Hagglund, M., Walden, M., Magnusson, H., Kristenson, K., Bengtsson, H., & Ekstrand, J.
(­2013). Injuries affect team performance negatively in professional football: an 1­ 1-​­year ­follow-​
­up of the UEFA champions league injury study. Br J Sports Med, 47(­12), ­738–​­742. https://­doi.
org/­10.1136/­­bjsports-­​­­2013-​­092215
Halson, S. L. (­2014). Monitoring training load to understand fatigue in athletes. Sports Med,
44(­Suppl 2), ­S139–​­S147. https://­doi.org/­10.1007/­­s40279-­​­­014-­​­­0253-​­z
Heishman, A. D., Daub, B. D., Miller, R. M., Freitas, E. D. S., Frantz, B. A., & Bemben, M.
G. (­2020). Countermovement jump reliability performed with and without an arm swing in
NCAA division 1 intercollegiate basketball players. J Strength Cond Res, 34(­2), ­546–​­558.
https://­doi.org/­10.1519/­JSC.0000000000002812
Helms, E. R., Kwan, K., Sousa, C. A., Cronin, J. B., Storey, A. G., & Zourdos, M. C. (­2020).
Methods for regulating and monitoring resistance training. J Hum Kinet, 74, ­23–​­42. https://­
doi.org/­10.2478/ ­­hukin-­​­­2020- ​­0 011
 Monitoring training 307
Hooper, S. L., & Mackinnon, L. T. (­1995). Monitoring overtraining in athletes. Recommenda-
tions. Sports Med, 20(­5), ­321–​­327. https://­doi.org/­10.2165/­­0 0007256-­​­­199520050-​­0 0003
Hoppe, M. W., Baumgart, C., Polglaze, T., & Freiwald, J. (­2018). Validity and reliability of GPS
and LPS for measuring distances covered and sprint mechanical properties in team sports.
PLoS One, 13(­2), e0192708. https://­doi.org/­10.1371/­journal.pone.0192708
Hulin, B. T., Gabbett, T. J., Caputi, P., Lawson, D. W., & Sampson, J. A. (­2016). Low chronic
workload and the acute:chronic workload ratio are more predictive of injury than b ­ etween-​
­match recovery time: a ­two-​­season prospective cohort study in elite rugby league players. Br
J Sports Med, 50(­16), ­1008–​­1012. https://­doi.org/­10.1136/­­bjsports-­​­­2015- ​­095364
Hulin, B. T., Gabbett, T. J., Lawson, D. W., Caputi, P., & Sampson, J. A. (­2016). The acute:chronic
workload ratio predicts injury: high chronic workload may decrease injury risk in elite rugby
league players. Br J Sports Med, 50(­4), ­231–​­236. https://­doi.org/­10.1136/­­bjsports-­​­­2015- ​­094817
Impellizzeri, F. M., Menaspa, P., Coutts, A. J., Kalkhoven, J., & Menaspa, M. J. (­2020). Train-
ing load and its role in injury prevention, part i: back to the future. J Athl Train, 55(­9), ­885–​
­892. https://­doi.org/­10.4085/­­1062- ­​­­6050-­​­­500-​­19
Jennings, D., Cormack, S., Coutts, A. J., Boyd, L., & Aughey, R. J. (­2010). The validity and
reliability of GPS units for measuring distance in team sport specific running patterns. Int J
Sports Physiol Perform, 5(­3), ­328–​­341. https://­doi.org/­10.1123/­ijspp.5.3.328
Kalkhoven, J. T., Watsford, M. L., Coutts, A. J., Edwards, W. B., & Impellizzeri, F. M. (­2021).
Training load and injury: causal pathways and future directions. Sports Med, 51(6),1137–1150.
https://­doi.org/­10.1007/­­s40279- ­​­­020- ­​­­01413- ​­6
Kalkhoven, J. T., Watsford, M. L., & Impellizzeri, F. M. (­2020). A conceptual model and de-
tailed framework for ­stress-​­related, s­train-​­related, and overuse athletic injury. J Sci Med
Sport, 23(­8), ­726–​­734. https://­doi.org/­10.1016/­j.jsams.2020.02.002
Kjaer, M. (­2 004). Role of extracellular matrix in adaptation of tendon and skeletal muscle to
mechanical loading. Physiol Rev, 84(­2), ­6 49– ​­698. https://­doi.org/­10.1152/­physrev.00031.2003
Macpherson, T. W., McLaren, S. J., Gregson, W., Lolli, L., Drust, B., & Weston, M. (­2019).
Using differential ratings of perceived exertion to assess agreement between coach and
player perceptions of soccer training intensity: an exploratory investigation. J Sports Sci,
37(­24), ­2783–​­2788. https://­doi.org/­10.1080/­02640414.2019.1653423
Malone, J. J., Barrett, S., Barnes, C., Twist, C., & Drust, B. (­2020). To infinity and beyond: the
use of GPS devices within the football codes. J Sci Med Footb, 4(1), 82–84.
Malone, S., Hughes, B., Roe, M., Collins, K., & Buchheit, M. (­2017). Monitoring player fitness,
fatigue status and running performance during an ­in-​­season training camp in elite Gaelic
football. J Sci Med Footb, 1(­3), ­229–​­236. https://­doi.org/­10.1080/­24733938.2017.1361040
Marston, W. M. (­1928). Emotions of Normal People. London: Routledge.
Maughan, P., Swinton, P., & MacFarlane, N. (­2020). Relationships between training load var-
iables in professional youth football players. Int J Sports Med, 42(7), 624–629. https://­doi.
org/­10.1055/­­a-­​­­1300-​­2959
McCall, A., Dupont, G., & Ekstrand, J. (­2016). Injury prevention strategies, coach compli-
ance and player adherence of 33 of the UEFA elite club injury study teams: a survey of
teams’ head medical officers. Br J Sports Med, 50(­12), ­725–​­730. https://­doi.org/­10.1136/
­­bjsports-­​­­2015-​­095259
Merrigan, J. J., Tufano, J. J., & Jones, M. T. (­2021). Potentiating effects of accentuated eccentric
loading are dependent upon relative strength. J Strength Cond Res, 35(­5), ­1208–​­1216. https://­
doi.org/­10.1519/­JSC.0000000000004010
Moalla, W., Fessi, M. S., Farhat, F., Nouira, S., Wong, D. P., & Dupont, G. (­2016). Relation-
ship between daily training load and psychometric status of professional soccer players. Res
Sports Med, 24(­4), ­387–​­394. https://­doi.org/­10.1080/­15438627.2016.1239579
Naughton, M., Jones, B., Hendricks, S., King, D., Murphy, A., & Cummins, C. (­2020). Quan-
tifying the collision dose in rugby league: a systematic review, m ­ eta-​­analysis, and critical
analysis. Sports Med Open, 6(­1), 6. https://­doi.org/­10.1186/­­s40798-­​­­019-­​­­0233-​­9
308 Barry Drust and Laura Bowen
Pedlar, C. R., Newell, J., & Lewis, N. A. (­2019). Blood biomarker profiling and monitoring
for h­ igh-​­performance physiology and nutrition: current perspectives, limitations and rec-
ommendations. Sports Med, 49(­Suppl 2), ­185–​­198. https://­doi.org/­10.1007/­­s40279-­​­­019-­​­­01158-​­x
Pelka, M., Schneider, P., & Kellmann, M. (­2017). Development of ­pre-​­and ­post-​­match morning
­recovery-​­stress states during ­in-​­season weeks in elite youth football. Sci Med Footb, 2(­2),
­127–​­132. https://­doi.org/­10.1080/­24733938.2017.1384560
Portas, M. D., Harley, J. A., Barnes, C. A., & Rush, C. J. (­2010). The validity and reliability of
­1-​­Hz and ­5-​­Hz global positioning systems for linear, multidirectional, and ­soccer-​­specific
activities. Int J Sports Physiol Perform, 5(­4), ­448–​­458. https://­doi.org/­10.1123/­ijspp.5.4.448
Rago, V., Krustrup, P., ­Martin-​­Acero, R., Rebelo, A., & Mohr, M. (­2020). Training load and
submaximal heart rate testing throughout a competitive period in a t­ op-​­level male football
team. J Sports Sci, 38(­­11–​­12), ­1408–​­1415. https://­doi.org/­10.1080/­02640414.2019.1618534
Roe, G., ­Darrall-​­Jones, J., Black, C., Shaw, W., Till, K., & Jones, B. (­2017). Validity of 1­ 0-​­HZ
GPS and timing gates for assessing maximum velocity in professional rugby union players.
Int J Sports Physiol Perform, 12(­6), ­836–​­839. https://­doi.org/­10.1123/­ijspp.­2016-​­0256
Sands, W. A., Kavanaugh, A. A., Murray, S. R., McNeal, J. R., & Jemni, M. (­2017). Modern
techniques and technologies applied to training and performance monitoring. Int J Sports
Physiol Perform, 12(­Suppl 2), ­S263–​­S272. https://­doi.org/­10.1123/­ijspp.­2016-​­0405
Saw, A. E., Main, L. C., & Gastin, P. B. (­2016). Monitoring the athlete training response: subjec-
tive ­self-​­reported measures trump commonly used objective measures: a systematic review.
Br J Sports Med, 50(­5), ­281–​­291. https://­doi.org/­10.1136/­­bjsports-­​­­2015- ​­094758
Sperlich, B., Holmberg, H. C., & Aminian, K. (­2020). Wearable Sensor Technology for Mon-
itoring Training Load and Health in the Athletic Population Swiss: Frontiers. https://­doi.
org/­10.3389/­­978-­​­­2-­​­­88963-­​­­462-​­0
Thorpe, R. T., Strudwick, A. J., Buchheit, M., Atkinson, G., Drust, B., & Gregson, W. (­2016).
Tracking morning fatigue status across ­i n-​­season training weeks in elite soccer players. Int J
Sports Physiol Perform, 11(­7), ­947–​­952. https://­doi.org/­10.1123/­ijspp.­2015- ​­0490
Vanrenterghem, J., Robinson, M. A., Nedergaard, N. J., & Drust, B. (­2017). Training load mon-
itoring in team sports: a novel framework separating physiological and biomechanical l­oad-​
­adaptation pathways. Sports Med, 47(­11), ­2135–​­2142.
Viru, A., & Viru, M. (­2000). Nature of training effects. In W. E. Garrett & D. T. Kirkendall
(­Eds.), Exercise and Sport Science, Philadelphia: Lippincott Williams & Wilkins (­p­­p. ­67–​­95).
Ward, P., Windt, J., & Kempton, T. (­2019). Business intelligence: how sport scientists can sup-
port organization decision making in professional sport. Int J Sports Physiol Perform, 14(­4),
­544–​­546. https://­doi.org/­10.1123/­ijspp.­2018- ​­0903
West, S. W., Clubb, J., ­Torres-​­Ronda, L., Howells, D., Leng, E., Vescovi, J. D., Carmody, S.,
Posthumus, M., ­Dalen-​­Lorentsen, T., & Windt, J. (­2021). More than a metric: how training
load is used in elite sport for athlete management. Int J Sports Med, 42(­4), ­300–​­306. https://­
doi.org/­10.1055/­­a-­​­­1268-​­8791
Weston, M. (­2018). Training load monitoring in elite English soccer: a comparison of practices
and perceptions between coaches and practitioners. Sci Med Footb, 2(­3), ­216–​­224. https://­doi.
org/­10.1080/­24733938.2018.1427883
Wiig, H., Andersen, T. E., Luteberget, L. S., & Spencer, M. (­2020). Individual response to ex-
ternal training load in elite football players. Int J Sports Physiol Perform, 15(­5), ­696–​­704.
https://­doi.org/­10.1123/­ijspp.­2019- ​­0453
Willy, R. W. (­2018). Innovations and pitfalls in the use of wearable devices in the prevention and
rehabilitation of running related injuries. Phys Ther Sport, 29, ­26–​­33. https://­doi.org/­10.1016/­j.
ptsp.2017.10.003
19 Utilising training and match
load data
Patrick Ward and Barry Drust

Introduction
To enhance player performance and mitigate injury, sports scientists have tried to un-
derstand ­player-​­generated data and explore underlying phenomena and hypotheses
within the applied setting. These types of investigations have commonly been directed
at evaluating the physical profiles of players, monitoring training, understanding peri-
odization, planning, and attempting to quantify the risk of injury. However, despite
a large amount of data being collected, there appears to be a disconnect between sci-
ence and practice. Prior research has indicated that sports scientists often lack “­­buy-​
­in” from relevant d ­ ecision-​­makers when it comes to the application of their findings
(­Akenhead & Nassis, 2016).
The void between science and practice is likely ­multi-​­factorial, however, one poten-
tial challenge is the lack of a framework to guide sports scientists within the applied
environment (­Bartlett & Drust, 2021). Scientists are trained in academia where the
approach to data analysis and reporting of findings is a ­well-​­documented process.
However, in the applied setting, the process of successful knowledge transfer appears
less clear. The consumers of i­nformation – ­​­­coaches – are
​­ often comprised of, from a
scientific perspective, a ­non-​­technical audience (­Bartlett & Drust, 2021). This issue
can be problematic as coaches are the primary ­decision-​­makers within sport and any
scientific reporting that gets “­lost in translation” will lead to a lack of application.
Another potential issue to the successful integration of science into practice is that
research within the sport is frequently driven by questions which are interesting to the
scientists as opposed to solving a problem that is relevant to the coach (­Bishop, 2008).
In the applied setting, the coach is the domain expert and primary ­decision-​­maker.
Therefore, rather than attempting to impart their own scientific agenda or interests
on the team, the sports scientist should embrace a role more akin to that found in the
business intelligence setting (­Ward et al., 2019). The sports scientist should begin by
understanding the problems and questions that are relevant to the coach. From there,
an infrastructure is created for data collection, cleaning, analysis, and reporting of
findings that helps to engage the coach in the scientific process. This type of engage-
ment can encourage an appreciation for the research process and hopefully lead to
greater application of the findings (­Hendricks, 2021).
Technological advances have made ­player-​­generated data common place in profes-
sional sports. In a survey of 41 elite professional soccer clubs, Akenhead and Nas-
sis (­2016) found that all teams are collecting data such as Global Positioning System
(­GPS), Rating of Perceived Exertion (­RPE), and Heart Rate (­HR) daily (­Akenhead &

DOI: 10.4324/9781003148418-23
310 Patrick Ward and Barry Drust
Nassis, 2016). The collection of such data is often directed at specific goals including
profiling players (­e.g., strength, speed, and fitness) or monitoring training loads to
help plan training sessions or identify injury risks. While the analysis of such data is
warranted, it is important to consider what the findings might mean to a coach and the
players, opening dialogue with them and trying to understand how such information
would help in daily practice. Key questions are: (­i) How will this information be used
in ­decision-​­making? and (­ii) How should the information be reported to be impactful
and meaningful to cause action?
Once the answer to these questions has been articulated, a clear plan for the pro-
ject lifecycle can be constructed. This plan can direct how the sports scientist will
identify the appropriate data, conduct analysis, and communicate their findings in
a concise and interpretable manner. Unfortunately, collecting large amounts of data
alone does not equate to success in sports. Success comes from the integration of
science into practice and the operationalization of findings in a way that allows the
coach to access relevant insights that help them make better decisions (­A lamar, 2013).
To this point, the focus of this chapter is to help applied sports scientists develop a
data reporting framework for enhancing “­­buy-​­in” with coaches and ­decision-​­makers
and ultimately improving their contribution to the sports organisation. Although this
chapter provides a framework for assessing training and matching physical load, it
is also applicable to other areas of sports science, such as performance analysis or
psychology.

Problem, plan, data, analysis, and conclusion cycle (­PPDAC)

Applied Sport Science Frameworks have previously been proposed providing sugges-
tions on exploring scientific questions in sport (­Bishop, 2008), working in the fast and
slow environment of ­pro-​­sport to generate insights (­Coutts, 2016), creating an under-
pinning business intelligence role for sports scientists (­Ward et al., 2019), and methods
of transferring knowledge to ­decision-​­makers (­Bartlett & Drust, 2021). While each of
these frameworks offers a different view as to how sports scientists can operate within
a team sport, they only deal with single components within the applied setting. In the
team sport environment, the sports scientist is required to perform all these tasks in
a succinct manner while allowing the primary d ­ ecision-​­makers to participate in the
process. In this way, the sports scientists can offer substantial value by overseeing the
project lifecycle from generating the problem statement through a method of sharing
results.
A formalized, e­ nd-­​­­to-​­end approach for answering research questions has been
conceptualized within the curriculum called the Problem, Plan, Data, Analysis, and
Conclusion (­PPDAC) cycle (­Wild & Pfannkuch, 1999; MacKay & Oldford 2000). As
seen in ­Figure 19.1, each step of the PPDAC cycle builds on the information gained
from the subsequent step, ensuring that the project progresses in a logical order.
This type of framework adds value by clearly defining the process, allowing for
­real-​­time communication with the d ­ ecision-​­maker and, if necessary, iterating the
process as additional information or objectives becomes available. The framework
helps to set expectations about the project timeline as n ­ on-​­technical audiences may
underestimate or be unaware of the length of time it takes for data acquisition, data
cleaning, analysis, and model validation before arriving at a conclusion worthy of
dissemination.
 Utilising training and match load data 311

­Figure 19.1 The Problem, Plan, Data, Analysis, and Conclusion (­PPDAC) cycle.

Problem and plan phases

Identifying problems to solve and establishing relevant questions should be done in
conjunction with the primary ­decision-​­makers (­e.g., sports coaches, fitness coaches,
and medical professionals) to ensure that the analysis and presentation of findings
are directed towards issues that are meaningful. Allowing domain experts to partic-
ipate in shaping the research question can also make communicating results easier,
as they feel as if they have been part of the process and had a contributory role in
planning the project. This type of back and forth, between the sports scientist and
­decision-​­maker, is essential in the Problem and Planning phases of the project lifecycle
as d
­ ecision-​­makers may not always be adept at asking questions in a clear and formal
manner. Obtaining clarity about the question being investigated ensures that time is
not wasted collecting meaningless data, which can be burdensome for the players and
coaches, or spending time performing analysis that is not specific to the question (­i.e.,
failing to answer the correct question). The sports scientist should feel they can com-
fortably question the questions of the ­decision-​­maker. This dialogue helps to refine the
question to a point where the results of the ensuing analysis are incorporated into the
­decision-​­making process as the ­decision-​­maker has been forced to think deeply about
that which they are asking and how they might use such information going forward.
Along with defining the question or problem statement, the way in which the question
is being asked is an important consideration. Understanding the type of question being
posed is necessary to help direct the analysis required to meet the intended goal. For
312 Patrick Ward and Barry Drust
example, there is a distinction between descriptive, explanatory, and predictive ques-
tions and the corresponding analyses designed to explore them (­Shumeli, 2010). Shumeli
(­2010) differentiates between the three by defining descriptive analysis as that which
summarizes data without having an explicit causal theory underpinning their inter-
pretation. In comparison, the explanatory analysis seeks to test causal hypotheses and
explain reasons for outcomes, whereas predictive analysis is directed towards develop-
ing statistical models to predict future outcomes. Discussing these differences with the
­decision-​­maker during the planning phase of the project lifecycle helps to direct the pro-
ject towards an analysis that is specific to how they will be using the results in practice.
For example, the question: “­How have the physical abilities of centre backs changed
over the past 10 years?” requires a different type of analysis compared to the question:
“­Has the pace of the game changed over the past 10 years, requiring centre backs to per-
form more h ­ igh-​­speed distance?”. These in turn differ to: “­Given the athletic qualities
and previous performance of this centre back, what would we forecast his next 4 years
to look like if we were to acquire him?”. The first question is purely descriptive and lacks
any explicit causal mechanism, simply summarizing changes within a positional group
over time. The second is more explanatory, where there is a potential causal hypothesis
to be tested (­What game changes have led to different ergonomic demands in the posi-
tion?). The final question is more predictive in nature, attempting to forecast the future
ability of a player, ultimately aiding the d­ ecision-​­makers with determining if the valua-
tion of the player is worth the current market price of acquiring him.
To illustrate these concepts, a soccer coach may initially want to know the fitness
level of their players when starting training camp. Rather than simply conducting a
­Yo–​­Yo fitness test and reporting the amount of distance covered and HR response for
each player, the sports scientist might ask the coach if they have considered how they
would like to apply the findings generated from the test. After some thought, the coach
might state they would like to use the information to not only identify those players who
require extra conditioning, but to decide upon the style of play the coach would like
to employ this season with these players, such as high pressing when out of possession
requiring frequent ­high-​­intensity running and sprinting. Following this discussion, the
sports scientist might perform a separate analysis on data of teams in the league who
played a similar style in prior seasons, attempting to understand the physical require-
ments of those players within that type of system. Such information allows for deeper
conversations with the coach regarding the findings from the fitness tests and additional
analysis, which can then help to shape discussions around training and match planning.

Data phase
Once the Problem and Planning phases of the project lifecycle have been agreed
upon, identifying data sources that are suitable to answer the question is the next
step. When acquiring such data, the sports scientist needs to ensure that it is clean
and free from error. This step is important as data in the applied environment can of-
ten be “­noisy”, leading to false signals and wrong conclusions, and causing d ­ ecision-​
m
­ akers to lose trust in the system. The increased interest in ­player-​­generated data in
professional sports has given rise to a substantial number of technology providers.
Unfortunately, just because something can be measured, does not mean that it is val-
uable and not all available technology offers the same level of fidelity when it comes
to the data provided. Returning to our example of the soccer coach attempting to
 Utilising training and match load data 313
set their team’s style of play, the sports scientist should not only ensure that the pre-­
season tests are valid and reliable but also that the data are being collected in a stand-
ardized manner by the staff. Additionally, analysis performed on previous seasons of
­league-​­wide tracking data should be appropriately cleaned and ­pre-​­processed so that
any insights gleaned from the analysis are accurate.

Validity
Valid tests or valid data are those that represent the construct that they purport to
measure (­Thomas et al., 2015). There are a few forms of validity that sports scientist
should be aware of, some of which are reviewed in ­Table 19.1. In the applied sport
setting, measures of criterion validity (­concurrent or predictive validity), are highly
applicable as they evaluate the relationship between the test and some form of crite-
rion measure.

Reliability
A measurement with good reliability is one that exhibits a high level of repeatability
when the activity is performed multiple times. Reliability is essential in applied sports
given that a measure cannot be valid if it is not reliable (­Thomas et al., 2015). For the
sports science practitioner, establishing the reliability of physical tests that will be
performed throughout the season is essential. A test that is not repeatable and consists
of high variability or “­noise” will have little utility when making decisions in practice,
as the signal for what is being measured will be difficult to identify.
For example, determining the reliability of the Y ­ o–​­Yo intermittent fitness test and cal-
culating its typical error of measurement (­TEM) is the first step in evaluating how useful
the test will be in practice. The TEM can be quantified as the standard deviation of the

­Table 19.1 Some examples of different forms of validity that a sport scientist might encounter
in the applied environment (­Thomas, Nelson, Silverman, 2015)

Validity type Definition Example

Logical/­face Face validity is validity that A 3­ 0-​­m sprint test has face validity for
validity visually appears to measure measuring player speed as the coaches
the performance it reports. and players can clearly see that players are
running as fast as possible.
Construct Construct validity describes Construct validity for ­session-​­RPE is defined
validity the way in which a test by how well it measures the ­psycho-​
measures an underlying ­biological state of players following exercise.
construct.
Concurrent Concurrent validity defines ­Player-​­worn GPS units have been shown to
validity the correlation between have concurrent validity when compared to
the test and a criterion laser timing (­the criterion measure).
measure, often a gold
standard measurement.
Predictive Predictive validity refers Predictive validity of the Y ­ o–​­Yo intermittent
validity to the ability of certain fitness test could be established by evaluating
variables to be able to whether the player’s results from the test, in
predict some form of some way, predict match physical output (­the
criterion measure. criterion of interest).
314 Patrick Ward and Barry Drust
­Table 19.2 Example of calculating typical error measurement and minimal difference for a
­test-​­retest trial

Player Test score 1 Test score 2 Difference

A 1,045 1,073 28
B 991 973 –​­18
C 1,062 1,084 22
D 1,075 1,109 – ​­66
E 1,064 1,145 81
F 1,083 1,101 18
G 1,107 1,069 –​­38
Standard deviation of difference (­SD) 48.6
TEM = SD2 34.3
Minimal Difference (­MD) = TEM × 1.962 95.2

difference scores divided by the square root of two (­­Table 19.2) (­Hopkins, 2000; Weir,
2005). Using the Y ­ o–​­Yo IR2 test as an example, the o ­ ff-​­season period would be a good
time to evaluate its t­ est-​­retest reliability. To perform this analysis, the players would run
the Y­ o–​­Yo IR2 test once and then wait 1­ –​­2 weeks and run it again. It is important to
ensure that the players are in similar physical states when performing the test (­e.g., per-
forming both tests on Monday morning following a weekend off from training). Assess-
ing reliability under these more stable environments is important as the goal is to attempt
to remove as much noise from the test as possible. If the ­Yo–​­Yo IR2 test displays a large
error in this controlled testing environment it might be difficult to extract meaningful
information from the test in the setting in which it is being applied, such as when using
the test multiple times during the season to evaluate whether player fitness is improving.
Quantifying validity and reliability not only verifies the quality of the data being col-
lected but also offers the ability to identify meaningful signals in measured outcomes,
called the minimum difference (­MD). Briefly, the MD is the smallest difference that would
need to be observed to be deemed important or relevant from a practical standpoint
(­Weir, 2005). Using the TEM from the reliability analysis, the minimum difference can be
calculated as: MD = TEM× 1.962. The multiplier, 1.96, is a critical z-​­score specific to the
95% confidence level; however, the practitioner could adjust this value if a different level
of confidence were desired. For example, a multiplier of 1.65 is used to represent a 90%
confidence level, whereas a multiplier of 2.58 would correspond to a 99% confidence level.
An example of calculating the TEM and MD in a t­est-​­retest trial can be seen in
­Table 19.2. The test has a typical error of 34.3 m and an MD of 95.3 m. The MD indi-
cates that an improvement of at least 95.3 m would need to be observed for the practi-
tioner to be confident at the 95% level as this shows a real change has occurred in the
test score because a change of this magnitude incorporates the test measurement error.
Once the data sources have been assessed for validity and reliability, and the quality
of the data has been assured, data analysis and communication of findings are the
final two steps of the project lifecycle.

Data analysis
Data analysis can range from basic to advanced statistical modelling, depending on the
complexity of the question being asked and the structure of data available. Statistics
and data science are fields unto themselves, and sports teams often employ analytics
 Utilising training and match load data 315
staff to handle projects requiring more advanced data skill sets. However, applied
sports scientists working in the fast, d ­ ay-­​­­to-​­day environment of professional sports
should be familiar with basic statistical analysis. A fast approach to sports science is
dependent on quickly producing simple, often descriptive, analysis that the coaches
can query, learn from, and integrate immediately into the weekly training structure
(­Coutts, 2016). For example, once the soccer team begins playing matches with their
new style, a ­post-​­game report can be generated that quickly provides the coach with
details about the h ­ igh-​­speed running volume performed by each player during the
game. Such information can be used to shape the upcoming weekly training plan.
Summarizing data is often a first step in exploring the underlying characteristics of
the data; however, such summary analysis can often answer questions that are relevant
to the d
­ ecision-​­makers and provide information to foster new questions or hypotheses.
This is particularly so when the question being asked is deceptive in nature. The two
most common descriptions of data are measures of central tendency and measures of
spread.

Central tendency
Measures of central tendency are statistics that serve to describe an entire dataset
using a single parameter, the middle or centre, value of the data. Two of the more com-
monly used measures of central tendency are the mean and median. These measures
are valuable for identifying the most likely value within the data and for comparing
changes in an individual or group. The mean is simply the arithmetic average and is
the most frequently used measure of central tendency when describing a dataset. The
mean is calculated by summing all the observations and dividing by the total number
of observations in the sample. In Example 19.1, the distance completed for five players
during training is summed together and then divided by the number of observations
(­N = 5 players) to obtain a group average of 11,297 m. Because the mean uses the entire
dataset, one of its main limitations is that it can be sensitive to outliers because it can
be pulled towards those values which are substantially higher or lower than the main
concentration of the data.

Example 19.1 The mean is calculated as the sum of all scores divided by the number of
samples.
316 Patrick Ward and Barry Drust

Example 19.2 The median represents the centre value of the data, whereby 50%
of the data is above it and 50% of the data is below it.

Conversely, the median value is the middle of the observations and represents the
50th percentile, where 50% of the data reside below and 50% of the data reside above
this value. Calculating the median is done by ranking the observations from highest to
lowest and identifying the middle value. In Example 19.2, once the data from Example
19.1 are organized in ascending order, the median is identified as 11,618 m (­Player A),
as this score is directly in the middle of the five observations. Because the median only
identifies the middle and does not consider other values within the data it is less sensi-
tive to outlier observations than the mean. When the data are normally distributed the
mean and the median will be nearly identical.

Spread
Measures of spread are used to represent the amount of variability within the dataset.
Measures of variance are frequently used to complement the single parameter meas-
ures of central tendency to provide a more complete representation of the data. The
four most common measures of spread are the variance, standard deviation, range,
and interquartile range. The first two are usually associated with the mean of the data,
whereas the latter two are often reported alongside the median.
Variance is used to describe the distance or deviation of each point relative to the
mean. The variance is calculated as the average of squared difference of each observa-
tion to the mean, as seen in Example 19.3. Because the differences are squared, the var-
iance is not on the same scale as the original data and is thus not directly interpretable.
As such, taking the square root of the variance produces the standard deviation, which
is now on the scale of the raw data and easier to understand. The data in Example 19.3
can be reported with a mean ± standard deviation of 11,297 ± 899.4 m. Another way
to report the standard deviation is to reflect it as a percentage, termed the coefficient
of variation, which is 8.0% for this dataset. To calculate the coefficient of variation,
divide the standard deviation by the mean and multiply that result by 100, allowing the
variability in data to be reported on a percentage scale (Example 19.3).
Unlike the variance, which looks at the relationship of each value to the mean, the
range simply reports the smallest and largest values observed within the data. In this
way, the range is a very crude measure of variability. Alternatively, the interquartile
range (­IQR) is used to provide a range of the largest concentration of the data. The
lower bound of IQR represents the 25th quartile, whereas the 75th quartile repre-
sents the upper bound of the IQR. The middle of the IQR is the median value (­50th
 Utilising training and match load data 317

Example 19.3 Calculation of variance, standard deviation, and coefficient of variation.

Example 19.4 The range and interquartile range (­IQR) for describing the spread of data.

percentile). Collectively, the IQR represents the inner 50% of the data and is, therefore,
less sensitive to outliers. Both the range and IQR of the above data can be seen in
Example 19.4.

Normal distribution
The shape of the data distribution can explain much about its underlying features and
help to put the above summary statistics into a better context. One of the more fre-
quently observed data distributions is that of the normal or ­bell-​­shaped distribution.
Understanding the properties of the normal distribution provides an appreciation for
the role the standard deviation plays in explaining how individual data points relate to
the population. Additionally, these properties can be used to calculate further descrip-
tive statistics that can be of value when visualizing and reporting data. The normal
distribution is represented by a single, central peak and data evenly distributed around
that peak with little or no bias in one direction or the other. ­Figure 19.1 shows a normal
distribution of the data from the total running distance in training for a soccer team.
Most of the scores are concentrated in the middle of the distribution, around the mean
318 Patrick Ward and Barry Drust

­Figure 19.2 The normal distribution represented as a density plot and a box plot.

(­1,016.2 m), represented by the red dashed line. Notice that there is less density of data
as the distribution moves further away from the centre (­mean). Because the standard
deviation considers the relationship of each data point to the mean, 68% of the data
reside ±1 standard deviation around the mean, 95% around ±2 standard deviations
from the mean, and 99.7% around ±3 standard deviations from the mean. Given these
properties of the normal distribution, it is easy to see why values larger than two or
three standard deviations are less frequent.
The bottom plot of F­ igure 19.2 visualizes the same data using a box plot, a common
visual used to accompany the median and IQR. The data in this example were sim-
ulated to be normally distributed, and therefore, the median value is nearly identical
to the mean of the distribution, as both values are right around a score of 1,016 m.
Visually this is seen by the black line in the middle of the box, the median value (­50th
percentile) being directly in line with the red dashed line (­mean) in the density plot
above it. The IQR, representing the data between the 25th and 75th percentiles, make
up the entire area of the box with points outside of the IQR being represented as the
“­whiskers” of the boxplot.
In addition to describing the properties of data, measures of central tendency and
spread can be utilized to convert the raw data into standardized scores. In this way,
data that are measured on different scales can now be compared equally. For example,
match total distance is substantially larger than match h ­ igh-​­speed running distances,
making it challenging to interpret these measurements, together, in their raw form and
determine how different the player is in both metrics relative to the group. However,
on a standardized scale, each data point is reflected relative to the central tendency
and variability of the sample data, allowing for a more direct comparison and easier
interpretation. Three common standardized scores use to report data in sport science
are percentile rank, z-​­scores, and t-​­scores.

Percentile rank
Percentile rank reports the data on a percentage scale (­­0–​­100%) where 50% represents
the measure of central tendency. The percentile rank represents the amount of data
in the population that is below the given score for the individual player. For example,
 Utilising training and match load data 319
A n example of transforming raw scores into percentile
­Table 19.3 
rank, z-​­score, and t-​­scores

Athlete Score Percentile rank Z-​­score T-​­score

A 11,618 0.64 0.4 53.6

B 9,763 0.04 –​­1.7 32.9
C 12,042 0.80 0.8 58.3
D 11,291 0.50 0.0 49.9
E 11,771 0.70 0.5 55.3

a soccer player who is reported to be in the 80th percentile for m ­ atch-​­day h

­ igh-​­speed
running has performed more ­h igh-​­speed running than 80% of the population of soccer
players they are being compared to. To calculate the percentile rank for Player B in the
data above (­­Table 19.2), first sort the scores from highest to lowest. Count the number
of scores below the score of interest. In this case, only one player (­Player D) scored
below Player B. Divide the number of scores below the score of interest by the total
number of observations in the dataset to determine the percentile rank for that indi-
vidual (­1/­5 = 20%). The percentile rank for each player’s score is shown in T ­ able 19.3.

Z-​­scores and t-​­scores

Z-​­scores are standardized scores where zero represents the mean and values above or
below zero represent the distance from the mean in standard deviation units. To con-
vert raw scores to z-​­scores, subtract the observed value from the average of the group
and then divide it by the standard deviation of test scores. An example of how z-​­scores
reflect the raw data can be seen in ­Table 19.3. Because the data is in standard deviation
units, observation for Player B (­z-​­score = –​­1.7), is interpreted to be 1.7 standard devia-
tions below the group mean.
While z-​­scores are common in science, they might not always resonate well with
coaches who have limited statistical knowledge. A way to make the ­z-​­score more palat-
able is to convert them into a t-​­score. Like a z-​­score, a t-​­score represents the raw data
in standard deviation units but does so on a ­0 –­​­­100-​­point scale where 50 represents
average with each ­10-​­point increment representing a one standard deviation change.
For example, 40 and 60 represent one standard deviation below and above the mean,
respectively. The relationship between t-​­scores and z-​­scores can be seen in column 3 of
­Table 19.3. Here, we notice that Player B’­s –​­1.7 z-​­score is converted into a t-​­score of 32.9.
Although data analysis and statistical modelling can be complicated, often re-
quiring sophisticated approaches to handle various interactions and relationships,
understanding the properties of the normal distribution, and calculating descriptive
statistics can be useful for the applied sport scientist. Moreover, converting the raw
data into standardized scores can aid ­decision-​­makers in comparing metrics that are
on different scales. Collectively, these basic approaches offer tremendous value when
reported in a clear way that is specific to the question posed.

Reporting findings
Unlike the academic environment, where the study findings are often communicated
in the form of a p
­ eer-​­reviewed publication, reporting conclusions in the applied setting
320 Patrick Ward and Barry Drust
needs to occur within appropriate time frames, depending on the nature of the infor-
mation and when it is required for ­decision-​­making. The soccer environment moves
at a fast pace, as coaches who are preparing players for weekly competitions require
information to be delivered in a timely manner so that decisions can be made for
planning the training process. Three of the most important time frames that the ap-
plied sport scientist should be aware of are: (­1) baseline; (­2) weekly; and (­3) monthly
reporting.

­1 Baseline testing:​­ At the start of a training camp or the ­pre-​­season, data are col-
lected to establish a baseline for players in various physical measurements, com-
pare players to each other or to some established norm, and to help with planning
the first phase of training and designing programs that are directed at improving
any identified limitations.
2 Weekly testing: Weekly testing is conducted to assess the ways in which players
might vary from one week to the next to mitigate any unwanted trends that could
predispose them to illness, injury, or poor performance. Examples of such test-
ing include ­counter-​­movement jumps to evaluate neuromuscular output, isomet-
ric muscle testing to expose any declines in strength or reporting of pain during
maximal contraction, and salivary measures, to identify any negative endocrine
changes.
3 Daily (­serial) testing:​­ Daily testing is the most frequent representation of player
training demands. Data collected daily provides practitioners with an immediate
glimpse into how the player performs each session. The type of training ­load-​
­specific measurements that occur in daily testing have often been dichotomized
into external and internal loads. External load reflects the actual demands of the
session, quantified with variables such as distance, speed, h­ igh-​­speed running, or
accelerations, whereas internal load represents the psychological or physiological
response of players to the session, as quantified by measures such as HR, training
impulse (­TRIMP) scores, and ­session-​­rating of perceived exertion (­Halson, 2014).

Presenting data across these time frames requires an understanding of how to convey
that which is meaningful. As such, reporting study findings should aid the reader in
deciphering the message and be void of superfluous information. The goal should be
to make it easy for those reading the report to orient themselves to the key takeaway
messages, ensuring that the data can complement future decisions.
One way to direct reader attention to the results of an analysis without using confus-
ing technical words or scientific jargon is through data visualisation. Common types
of data visualisation can be seen in F ­ igure 19.3. Each of these approaches conveys
data in a different way, specific to the message that needs to be communicated. The
selection of one approach over another depends on the type of data and the underlying
question. Often, the type of question being answered in an analysis is specific to the
data collection time frames discussed above. For example, weekly testing data would
be visualized in some form of comparison from 1 week to the next or from the current
week to baseline, whereas serial measurement data would be visualized as a time series
in which shifts and trends of data can be seen across the season.
Plots A and B in F
­ igure 19.3 are two methods of displaying the distribution of data,
as discussed in a previous section. Plot A represents the density of m ­ atch-​­day run-
ning volumes for a professional soccer club. The distribution here can be described as
 Utilising training and match load data 321
bimodal (­having two modes, or peaks), with most players performing around 11,000
m per match and a handful of players having less locomotor activity (­just under 5,000
m), most likely due to less playing time or injury during the match. Boxplots are an
alternative way to show the distribution of data and are particularly useful when try-
ing to compare distributions across different groups. The actual observations can be
overlayed, in the form of dots, to convey the sample size and more directly show the
density of data within the IQR. In Plot B, we can see that across the training weeks,
the median running distance is similar on Game ­Day –​­3 and Game ­Day –​­2, however,
Game ­Day –​­2 has more variance around the mean. Game ­Day –​­1 is clearly lower than
the other two training days, as it is closest to match day. Additionally, the reader can
observe that Game ­Day –​­2 and Game ­Day –​­1 have much larger sample sizes compared
to Game ­Day –​­3.
When attempting to convey the relationship between two continuous variables data
can be visualized using a ­xy-​­plot, as in Plot C. A linear relationship between training
duration and total distance run can easily be observed. The regression line allows the
reader to decipher this relationship more clearly. The upward slope indicates a posi-
tive correlation between the two variables, whereby as training time increases so does
total running distance. A regression model can underpin this type of plot, allowing
the d­ ecision-​­maker to input expected values for the training duration of upcoming
sessions and obtain a forecasted amount of total running distance, which can aid with
planning future training sessions. Such an approach represents a simple example of
predictive modelling that an applied sport scientist may be asked to develop. For ex-
ample, a regression model could be developed to create a training load calculator to
assist the coach in planning training. Using various features from historically collected
data, such as the training drills being prescribed for the upcoming session and the ex-
pected duration for each drill, the sports scientist can build a model that estimates the
expected training load for the upcoming training session. A discussion with the coach
about whether that expected load is appropriate for the players may transpire, leading
to adjustments to the training session.
Baseline testing data that aims to compare a player to the rest of the team or to
some physical standard is often visualized in a manner where player test scores are
standardized for the purpose of displaying all measurable data points on the same
scale, as discussed in the prior section. Plots D, E, and F show three ways of report-
ing the same standardized data. Plots D and E as z-​­score plots radar and bar chart
formats, respectively, and Plot F as a t-​­score. The straight line in the two bar charts
and the inner circle of the radar plot represent the population average while the bar
charts provide additional context by using a g­ rey-​­shaded region to show one standard
deviation above and below the average. This type of data visualization allows staff to
quickly identify the areas where each player is outside of normal. Because the data are
scaled, all variables can be represented on the same chart, enhancing communication
between staff members about player performance in a variety of physical qualities.
Reporting serial measurements and corresponding changes in players over the
course of a season is common in sport science. To provide context around time series
data of this nature, for example, comparing a player to their baseline or comparing a
player in a w­ eek-­​­­to-​­week test, the changes should be reflected relative to the change in
the measurement along with its corresponding typical error measurement and the MD
for a real change. For example, the weekly percentage change in h ­ igh-​­speed running
distance during training is visualized in ­Figure 19.3. Plot A provides a single overview
 322

a) b)
0.00020 8000

0.00015 6000

0.00010
4000

density
distance
0.00005
2000
0.00000
0 5000 10000 15000 20000 –3 –2 –1
Match Distance Day to Game
c)
15000
Patrick Ward and Barry Drust

10000

5000

Distance (m)
0
0 50 100 150
Training Duration (min)
d) e) f)
Vertical Jump 100
3
2 Athlete Athlete
0 75
Body 30m
Weight Spring
A A
–3 0 B 50 B
C C

z-score
T-score

D 25 D
Arrowhead –2
Height
Agility
0
30m Arrowhead Height Vertical Jump 30m Arrowhead Height Vertical Jump
Spring Agility Spring Agility
Test Test

­Figure 19.3 Some examples of common data visualization approaches.

 Utilising training and match load data 323
of each player relative to the TEM and MD. The point represents the observed per-
centage change for the player from one week to the next and the error bars indicate the
typical error measurement of weekly h ­ igh-​­speed running. The shaded region repre-
sents the minimal difference, above and below no change (­zero difference) compared
to the individual player baseline scores. The players exhibiting a change outside of the
shaded MD region are of interest in the report. The certainty that the change is real
can be further investigated by evaluating the error bars (­TEM) around the observed
change and how far they are outside of the MD region. This plot allows the staff to
quickly identify those players that display weekly changes that are outside of nor-
mal, aiding discussions about planning training for those individuals in the upcoming
training week.
Aside from looking at a single value of weekly change for the team, Plot B of
­Figure 19.4 provides a method of visualizing data for an individual player over time.
The visual representation of the data is like that of the team view above it (­Plot A) so
that the coach does not need to r­ e-​­orient themselves to new information. The only
change in Plot B is the x-​­axis now represents each week’s score for a single individual
across the season. Such information provides a way to investigate any unwanted or

10
Weekly Change

–10

A B C D E F G
Athlete
Weekly Change in Score

10

–10

1 2 3 4 5 6 7
Training Week

­Figure 19.4 Visualizing analysis of weekly change scores (­A) for an entire team, (­B) for a
single individual from week to week, or (­C) for an individual player for each
week relative to baseline.
324 Patrick Ward and Barry Drust

12500

10000
Distance Covered

7500

5000

2500

0 5 10 15 20 25
Training Session Number

­Figure 19.5 An example of a run chart for a professional soccer player. Total match dis-
tance is represented along with 1 and 2 standard deviation bands to alert the
viewer to sessions that are outside of normal ranges.

unplanned trends that might require special attention regarding managing the train-
ing process of individuals.
The visualization of trends in serial measurements, explained above, can be further
shown using a run chart, as seen in ­Figure 19.5 (­Perla et al., 2011; Anhøj & Olesen,
2014). Run charts provide further context in the form of threshold lines above and
below the average training distance for this individual; one standard deviation in blue
and two standard deviations in red.
Run rules are used to supplement run charts, as seen in ­Figure 19.6, as a means
of drawing attention to important points or patterns (­Callahan & Barisa, 2005;
Mohammed et al., 2008; Orme & Cox, 2001). Some of the commonly used run rules
to include are: (­1) an astronomical point, which is a data point falling outside of a
specified magnitude, for example, three SD (­either above or below the mean); (­2) two
out of three points beyond the two SD threshold; (­3) a run of six or more points on
the same side of the centre line; and, (­4) a run of five or more points all trending in
the same direction. A visual of these rules can be seen in F ­ igure 19.6(­a)–​­(­d) where the
respective rules are flagged for ­h igh-​­speed running in training by changing the colour
of the data point.
Evaluating charts as those seen in ­Figures 19.5 and 19.6 provide the sports scien-
tist and coach with a complete view of the training process and a method of assess-
ing for any divergent trends that may warrant further investigation or intervention
from the performance staff. Additionally, such approaches can be structured for
daily reporting whereby the run rules that the sports scientist would like to be
alerted about can be automatically highlighted without spending too much time
reviewing the charts for each player. This automated form of reporting allows the
final reporting of the analysis to be operationalized within the daily workflow of
the soccer club.
 Utilising training and match load data 325

a) b)
600
3 SD
700 2 SD

550
600
Variable

Variable
500 500

400

450
300
3 SD 2 SD
4 8 12 4 8 12
Day Day

c) d)
350

300 350
Variable

250
Variable 340

200
320

150

4 8 12 4 8 12
Day Day

Figure 19.6 (A) Astronomical point above or below the three SD control limits. (B) Two
out of three points above or below the two SD control limits. (C) Six or more
points on the same side of the centre line. (D) Six or more points all going in
the same direction.

Future directions and conclusions

The PPDAC cycle provides sports scientists with an ­easy-­​­­to-​­implement framework
for establishing a workflow within the soccer environment, taking them from devel-
oping a question to reporting the results of the analysis in a meaningful way that can
enhance ­decision-​­making within the club. To improve “­­buy-​­in” with coaches, sports
scientists need to engage them in the scientific process by allowing them to be active
from the question development and planning stages of the project lifecycle. Such an
approach not only gives the coach some level of ownership in the process but allows
the sports scientist to obtain clarity on the specific question they are trying to answer.
Once the question has been developed, the sports scientist needs to ensure that the
data used for analysis is clean and free from errors and meets some basic requirements
with respect to validity and reliability. The type of analysis that is used will depend
largely on the available data, the type of data, and the specific nature and goals of the
question. Once the final analysis is complete, the sports scientist needs to share the
results in a meaningful way. Reporting findings should be specific to the time frames
of the weekly cadence for which the information is required to aid ­decision-​­making.
Importantly, the sports scientist should develop a reporting strategy that provides the
coach with ­easy-­​­­to-​­interpret visuals that are free from “­clutter” and scientific jargon,
concisely summarizing the most relevant pieces of information from the analysis.
326 Patrick Ward and Barry Drust
References
Akenhead, R., & Nassis, G. P. (­2016). Training load and player monitoring in ­h igh-​­level foot-
ball: current practice and perceptions. Int J Sports Physiol Perf, 11(­5), ­587–​­593.
Alamar, B. C. (­2013). Sports Analytics: A Guide for Coaches, Managers, and Other Decision
Makers. New York, NY: Columbia University Press.
Anhøj, J., & Olesen, A. V. (­2014). Run charts revisted: a simulation study of run chart rules for
detection of ­non-​­random variation in health care processes. PLoS One, 9, ­1–​­13.
Bartlett, J. D., & Drust, B. (­2021). A framework for effective knowledge translation and per-
formance delivery of sport scientists in professional sport. Eur J Sport Sci, 21(­11), ­1579–​­1587.
Bishop, D. (­2008). An applied research model for the sport sciences. Sports Med, 38(­3), ­253–​­263.
Callahan, C. D., & Barisa, M. T. (­2005). Statistical process control and rehabilitation outcome:
the ­single-​­subject design reconsidered. Rehabil Psychol, 50, ­24–​­33.
Coutts, A. J. (­2016). Working fast and working slow: the benefits of embedding research in high
performance sport. Int J Sports Physiol Perf, 11(­1), ­1–​­2.
Halson, S. (­2014). Monitoring training load to understand fatigue in athletes. Sports Med,
44 Suppl 2(Suppl 2):S139-47, ­S139–​­S147.
Hendricks, S. (­2021). Rethinking innovation and the role of stakeholder engagement in sport
and exercise medicine. BMJ Open Sport & Exer Med, 7, ­1–​­4.
Hopkins, W. G. (­2000). Measures of reliability in sports medicine and science. Sports Med, 30,
­375–​­381.
MacKay, R. J., & Oldford, R. W. (­2000). Scientific method, statistical method, and the speed of
light. Stat Sci, 15(­3), ­254–​­278.
Mohammed, M. A., Worthington, M. A. P., & Woodall, W. H. (­2008). Plotting basic control
charts: tutorial notes for healthcare practitioners. Qual Saf Health Care, 17, ­137–​­145.
Orme, J. G., & Cox, M. E. (­2001). Analyzing ­single-​­subject design data using statistical process
control charts. Soc Work Res, 25, ­115–​­127.
Perla, R. J., Provost, L. P., & Murray, S. K., (­2011). The run chart: a simple analytical tool for
learning from variation in health care processes. BMJ Qual Saf, 20, ­46–​­51.
Shumeli, G. (­2010). To explain or to predict? Stat Sci, 25(­3), ­289–​­310.
Thomas, J. R., Nelson, J. K., & Silverman, S. J. (­2015). Research Methods in Physical Activity,
7th Ed. Champaign, IL: Human Kinetics.
Ward, P., Windt, J., & Kempton, T. (­2019). Business intelligence: how sport scientists can sup-
port organization decision making in professional sport. Int J Sports Physiol Perf, 14(­4),
­544–​­546.
Weir, J. P. (­2005). Quantifying ­test-​­retest reliability using the intraclass correlation coefficient
and the SEM. J Strength Cond Res, 19(­1), ­231–​­240.
Wild, C. J., & Pfannkuch, M. (­1999). Statistical thinking in empirical enquiry. Int J Stat Review,
67(­3), ­223–​­248.
Section E

Talent Identification, Growth,

and Development
20 Growth and maturation
Sean P. Cumming, Megan Hill, David Johnson,
James Parr, Jan Willem Teunnisen and
Robert M. Malina

Introduction
Soccer players are traditionally grouped by age for training and competition. Age
groups are easy to administer, generally aligned with the school year, and allow chil-
dren to play with their immediate peers. They are also ideal for matching players on
developmental attributes, such as experience, training age, and cognitive, m ­ otor-​
­neural, and social development (­Malina et al., 2019). Yet, age groups are not without
their limitations. Chronological age and physical development do not necessarily pro-
ceed in parallel (­Malina et al., 2004). Youth of the same age can demonstrate marked
variation in physical development, with some individuals growing and maturing well
in advance or behind their peers (­Johnson et al., 2017).
Individual differences in growth and maturation impact physical and p ­ sycho-​
­behavioural development (­Cumming et al., 2012). These consequences are especially
salient in sports such as soccer where greater size, strength, speed, and power are
considered desirable attributes (­Malina et al., 2015). Maturity has been shown to im-
pact physical fitness, match performance, and competitive equity in soccer; ultimately
impacting talent identification and development (­Cumming, 2018; Meylan et al., 2010).
Maturity is important to consider in the design, implementation, and evaluation of
training/­conditioning programmes, and in the prevention of injury (­Lloyd & Oliver,
2012; McKay et al., 2019).

Growth
Growth refers to specific changes in body size, physique, and/­or composition, and
can be considered in terms of the whole body or specific parts. Increases in body size
result from three processes: (­i) increases in cell numbers (­hyperplasia); (­ii) increases
in cell size (­hypertrophy); and (­iii) increases in cellular substances (­accretion) (­Malina
et al., 2004). As children grow, they become taller and heavier, gaining lean and fat
tissue, and their organs increase in size. Parts of the body grow at different rates and
times, resulting in changes in physique and body proportions. The legs, for example,
grow faster than the trunk during childhood; hence, the child becomes relatively ­long-​
­legged for their height. Heart volume and mass follow a growth pattern like weight,
whereas the lungs and lung functions grow proportionally to height.
The most assessed features of growth in soccer are stature (­height) and weight
(­mass), which are often expressed as ­mass-­​­­for-​­stature (­BMI). Measures of height,
weight, and BMI provide valuable insight into the growth, maturity, and health status

DOI: 10.4324/9781003148418-25
330 Sean P. Cumming et al.
of players (­Malina et al., 2015). Routine monitoring of growth status (­i.e., longitudinal
data) can be used to estimate growth rates (­i.e., height and weight velocity) (­Johnson,
2015); helping practitioners identify and confirm when players enter important stages
of development (­e.g., adolescent growth spurt). Rapid increases in growth rates may
also be indicative of a high maturation tempo and have been linked to increased injury
risk (­Kemper et al., 2015).
Mean heights and weights of male soccer players aged 1­ 0–​­18 years in studies span-
ning ­1978–​­1999 were, on average, consistently shorter and lighter compared to those
of players in studies spanning 2­ 000–​­2015. Mean height of youth players in the recent
samples approximate the reference median (­50th percentile) of U.S. growth charts at
about 10 years of age but was consistently above the reference median through to age
18 years. In contrast, the mean weights of soccer players were consistently between the
reference median and 75th percentile. Youth soccer players thus present, on average,
greater weights for height, likely reflecting a generally muscular physique.
In contrast to males, secular change in the heights and weights of female players
spanning 1­ 992–​­2020 was negligible. Heights and weights of adolescent players clas-
sified as skilled or local did not differ. The composite mean heights of female play-
ers were above the U.S. reference median at 9 and 10 years of age, approximated the
median at 1­ 1–​­14 years, and were then above the median and approximated the 75th
percentile of the reference at ­17–​­18 years of age. In contrast, body weights of female
players were consistently above the reference median and were approximately midway
between the median and 75th percentiles of the reference from 12 to 18 years of age.
Measures of height and weight, combined with assessments of skeletal age or m ­ id-​
h
­ eight of the biological parents, can be used to predict the adult height of a player.
Predicted adult height is of potential relevance to those involved in the identification
of future adult players. Above average height is an increasingly desired attribute for
centre backs and goalkeepers (­Carling et al., 2012). The limitations and errors of the
prediction equations should be noted, and 90% confidence intervals should be gener-
ated for predicted values. Any decisions pertaining to predicted adult height should
consider repeated measures over a sustained period of time and ‘­best case’ scenarios
(­i.e., upper limits of 90% confidence interval) (­Johnson, 2015).

Maturation
Biological maturation is the process of progress towards the adult state (­Malina et al.,
2004). It occurs, and can be assessed, within a range of biological systems, including
somatic, skeletal, sexual, endocrinal, and dental. Maturation can be defined in terms
of status, tempo, and timing. Status refers to the state of maturity attained at the
time of observation (­e.g., pubertal stage, skeletal age, or p
­ re-​­pubertal versus pubertal).
Timing refers to the age at which maturational events occur (­e.g., age at menarche, age
at peak height velocity (­PHV), and age at attaining a specific pubertal stage). Tempo
refers to the rate at which maturation proceeds.
Methods for assessing maturity status, timing, and tempo vary; each with its ad-
vantages and limitations (­Malina et al., 2004). Skeletal age is the most objective index
of maturity and can be estimated from birth to adulthood (­Gilli, 1996). Skeletal age
is normally evaluated from a standard ­hand-​­wrist radiograph, although DEXA/­MRI
scans can be used (­Romann & Fuchslocher, 2016). Several methods for estimating skel-
etal age exist, specifically the G
­ reulich-​­Pyle, Fels, and T
­ anner-​­Whitehouse methods.
 Growth and maturation 331
Skeletal age provides an estimate of maturity status, but not timing. However, the
discrepancy between skeletal and chronological age indicates whether a child is ad-
vanced, average, or delayed in maturity status. Limitations of this method include
expense, the need for specialised equipment, and a low dose of radiation exposure.
With modern technology, exposure to radiation is, however, minimal.
Sexual maturation refers to the development of secondary sex characteristics such as
pubic hair, breast development, changes in penis/­testes, and testicular volume. When
performed by a trained assessor, stages of each characteristic provide a valid and reli-
able indicator of maturity status at the time of observation. Concerns regarding player
welfare and safety have, however, led most soccer academies to exclude these methods.
­Non-​­invasive estimates of maturity status and timing based on anthropometry, la-
belled somatic maturation, are increasingly popular. Common methods include pre-
dicted maturity offset (­Mirwald et al., 2002) and percentage of predicted adult height
(­Malina et al., 2005). These methods can be implemented with routine measures of
growth status. Predicted maturity offset and percentage of predicted adult height op-
erate on the logic that the closer a player is to, respectively, PHV or predicted mature
stature, the more advanced they are in maturity status.
Maturity offset (­i.e., predicted time before or after PHV) is predicted with s­ex-​
s­ pecific equations that require chronological age, height, weight, sitting height, and
estimated leg length. Researchers examining the accuracy of the offset equations
have raised concerns about the suitability of this method in the general population
(­Kozieł & Malina, 2018; Malina et al., 2016, 2020; Malina & Kozieł, 2014a, 2014b) and
in soccer players (­Parr, Winwood, ­Hodson-​­Tole, Deconinck, Parry et al., 2020; Teunis-
sen et al., 2020). These studies compared predicted age at PHV with observed age at
PHV derived from several longitudinal data series. The prediction equations u ­ nder-​­
and ­over-​­estimated actual age at PHV in younger and older children, respectively, with
the error in prediction of age at PHV accentuated in early and late maturing youth.
Percentage of predicted adult height (­PPAH) at the time of observation assumes
that individuals who are closer to their adult height are more advanced in maturity sta-
tus. The use of PPAH as a maturity indicator was proposed by Roche and colleagues
(­Roche et al., 1983), while Malina and colleagues (­Malina et al., 2005, 2007, 2012)
first applied the protocol with young athletes. The method utilises height prediction
equations based on the Fels Longitudinal Study (­K hamis & Roche, 1994, 1995). The
equations require age, height, and weight of the child and heights of their biological
parents. As parental heights are generally reported, they are adjusted for overestima-
tion (­Epstein et al., 1995). After predicting adult height, the current height of the player
is expressed as a percentage of their predicted adult height. Using this approach, ma-
turity status can be expressed in absolute (­p ercentage of predicted adult height or
biological age) or relative (­­z-​­score relative to ­age-​­and ­sex-​­specific standards) terms.
More recently, this protocol was modified to include ­age-​­and ­gender-​­specific reference
data from the UK 1990 set to produce a proxy of ‘­biological age’ (­Gillison et al., 2017).
With a similar intention, protocols to convert PPAH, based on the Tanner Whitehouse
2 and ­K hamis-​­Roche height prediction equations have been used to estimate ‘­skeletal
age’ in youth (­Olivares et al., 2020). PPAH can be used to approximate when a player
enters the adolescent growth spurt, for example, age at t­ ake-​­off (≈85%), if they are cur-
rently in the interval of PHV (≈91%), or the beginning of the deceleration phase of the
adolescent growth spurt (≈96%) (­Sanders et al., 2017). This percentage band (≈­85–​­96%
of PPAH) was shown to correctly identify 91% of players as being within or outside the
332 Sean P. Cumming et al.
pubertal growth spurt in a longitudinal study of academy soccer players (­Parr, Win-
wood, ­Hodson-​­Tole, Deconinck, Parry et al., 2020).

Growth and maturation screening programmes

Youth soccer programmes should establish systematic policies and procedures for
monitoring the growth and maturation in youth players. Player heights and weights
should be measured every 3­ –​­4 months and the heights of their biological parents
should be assessed or ­self-​­reported and adjusted to the tendency for overestimation
(­Epstein et al., 1995). Measurement frequency is often increased during periods of
rapid growth; however, ­inter-​­and/­or ­intra-​­observer measurement variability can influ-
ence the accuracy of the estimated increments. To optimise the consistency and accu-
racy of the measurements, players should be measured with standardised procedures
in the morning and prior to training sessions (­Johnson, 2015).
The English Premier League launched a ‘­Growth and Maturation Screening Pro-
gramme’ in 2015 to monitor the growth and maturity status of all registered academy
players (­­U9–​­U16) (­Cumming, 2018). Player data are entered into the Premier League’s
Player Management Application (­PMA) which produces immediate estimates of pre-
dicted adult height (­w ith 50% and 90% confidence intervals), PPAH, estimated age at
PHV, and maturity offset timing and status. This information is used to: (­i) create in-
dividual player reports and team audits; (­ii) identify players entering periods of rapid
growth; (­iii) inform training design and delivery; (­iv) adjust fitness assessments for
maturity status; and (­v) group players by maturity status for training and competition
(­i.e., ­bio-​­bands). It should be noted that most PMA outputs utilise PPAH rather than
maturity offset as the preferred index of maturation.

Talent identification, evaluation, and development

As noted, the talent identification process is greatly impacted by individual variance in mat-
uration (­Carling et al., 2012; Hill, Scott, Malina et al., 2020; Johnson, 2015). As children,
boys who mature early are taller and heavier than their peers, however, it is not until pu-
berty that they possess marked advantages in both size and athleticism. Benefitting from an
earlier and more intense growth spurt, early maturing boys are heavier, taller, and possess
greater absolute and relative lean mass. As a result of these changes, early maturing boys
perform better on tests of strength, power, upper and lower body speed, agility, and aerobic/­
anaerobic capacity. The physical and functional advantages associated with early maturity
in boys are maintained through adolescence (­Malina et al., 2004) and it is only in adulthood
that these effects are attenuated, and in some cases reversed (­Lefevre et al., 2000).
As with boys, girls who mature early are taller and heavier in childhood, yet do
not present any noticeable advantages in functional capacities (­Malina et al., 2004,
2021). They also experience a more intense adolescent growth spurt, but pubertal gains
in lean mass are accompanied by relatively large gains in fat mass. Adolescent gains
in physical fitness in girls are, on average, not as marked as those observed in boys.
Although longitudinal data are limited, the impact of pubertal timing on physical
fitness in girls is mixed and less consistent. Early maturation does afford an advan-
tage in activities that require greater size or absolute strength (­Myburgh et al., 2016),
yet appears less conducive to tasks that demand relative strength, endurance, and/­or
movement of the body through space (­Malina et al., 2004).
 Growth and maturation 333
The physical and functional advantages associated with advanced maturation are ­well-​
d ­ ocumented in male soccer (­Meylan et al., 2010; Murtagh et al., 2018; Parr, Winwood,
­Hodson-​­Tole, Deconinck, Hill et al., 2020; Vandendriessche et al., 2012). Youth players
advanced in maturity status outperform their peers on tests of strength, speed, power,
agility, and endurance. The magnitude of these effects varies from small to moderate, yet
is substantial at the extremes of the maturity continuum (­Figueiredo et al., 2010). As with
the general population, the physical and athletic advantages associated with advanced
maturity status in soccer that emerge with puberty are maintained through adolescence
before attenuating in late adolescence (­Towlson et al., 2018). The earlier attenuation
likely reflects the systematic exclusion of late maturing players who lack the necessary
physical qualities to succeed (­de Silva et al., 2010; Konarski et al., 2020). The physical and
functional advantages of advanced maturity status are most likely to impact selection in
­mid-​­adolescence when variance in maturity is greatest; yet appear less relevant in late
adolescence. For example, among academy soccer players aged 1­ 6–​­18 years, three factors
correctly classified about 70% of the players as selected or d ­ e-​­selected, in order: technical
skill (­ball handling); tactical skill (­positioning and deciding); and functional skill (­peak
shuttle ­sprinting – ​­a measure of speed and agility). The selected and ­de-​­selected players
did not differ in size, task, and ego orientation and motivation (­Huijgen et al., 2014).
The English Premier League PMA provides age and maturity standards for all phys-
ical fitness tests; enabling academy staff to accommodate maturity status when evalu-
ating player fitness, better identify player strengths and weaknesses, and adjust training
programmes accordingly. For example, an early maturing player who is 12 years of age
may record a 3­ 0-​­m dash time that places them at the 75th centile for their age group, yet
only the 30th centile for their maturational status (­Cumming et al., 2017).
Research investigating m ­ aturity-​­associated variance in the fitness of female play-
ers is limited and most studies have employed the offset method. As such, caution
is warranted in interpreting the results of these studies. That said, absolute and rel-
ative peak force appears to increase successively in female players across the ­pre-​­,
circa, and ­post-​­PHV stages (­Emmonds et al., 2017). Performances on tests of strength
(­isometric ­m id-​­thigh pull), speed (­­10-​­ to ­30-​­m sprint), agility (­505 test), lower body
power (­­counter-​­movement jump), and aerobic capacity (­­Yo–​­Yo test) also improve with
advancing maturity in females (­Emmonds et al., 2020). There was, however, a decline
in relative peak force that occurred ­between –​­0.5 and + 0.5 years of PHV, which may
have reflected pubertal gains in fat mass. Reduction in relative strength during the
growth spurt may increase injury risk in female players, especially those associated
with acceleration, deceleration, and/­or change of direction.
Emerging evidence suggests that the physical and functional advantages associated
with advanced maturity status in males generalise to the soccer field. This research is
largely limited to males competing in more select and/­or academy programmes. Using
GPS to examine ­maturity-​­associated variation in match running performance among
U14 players, the early maturing players (­defined by predicted maturity offset) covered
the greater distance at high speed (>16 Km h –​­1), achieved higher peak speeds, and
engaged in more ­h igh-​­and repeated ­h igh-​­intensity actions per minute (>1) than late
maturing peers (­Buchheit & ­Mendez-​­Villanueva, 2014). Similarly, advanced maturity
status based on percentage of predicted adult stature among U14 male players was
associated with greater distance covered, total distance at high speed, total distance
at very high speed; maximum speed, and the number of accelerations from zone 4 to
zone 6 (­Parr et al., 2021). The associations were, however, attenuated when nesting of
334 Sean P. Cumming et al.
repeated performances across matches was statistically controlled. In terms of the
match performance, academy players advanced in maturity status based on PPAH,
played more match minutes and, controlling for minutes played, engaged in more at-
tacking actions, produced more shots and goals, and had higher percentages of suc-
cessful passes and long passes (­Johnson, 2021).
Maturity status in boys has been shown to impact coach evaluations of performance
(­Hill, Scott, McGee et al., 2020b). Specifically, coaches rated more mature ­U14–​­U16
players as performing better than their later maturing peers in matches. This bias
coincided with the emergence of a selection gradient for players advanced in maturity
status that increased with age. In contrast, later maturing U12 players were awarded
higher match grades by coaches. Further analysis suggested that earlier maturing U12
players experienced a temporary decrement in performance associated with the onset
of the growth spurt. More specifically, a general decline in match performance was
observed across all players categorised as ‘­circa PHV’ (­­86–​­95% PPAH), regardless of
age, before returning to previous standards when exiting this phase of development
(>96% PPAH) (­Hill, Scott, McGee et al., 2020a). The preceding observations highlight
the need to consider both maturity status and timing when evaluating players. In this
context, it is important to compare the match performances and grades of adolescent
players when they compete as the most and least mature players within a competitive
­age-​­group and note when players are in the middle of a growth spurt.
A selection gradient exists in youth soccer towards boys advanced in maturation. It
emerges at the onset of the adolescent growth spurt and increases with age and level
of competition. A study of academy players in England and Qatar found ­60–​­80% of
­U16–​­U17 players to be advanced in maturation, with only ­2–​­3% being late (­Johnson
et al., 2017) (­­Figure 20.1). The bias is most evident amongst goalkeepers, defenders,

80

70

60

50

40

30

20

10

0
U9 U10 U11 U12 U13 U14 U15 U16
Early On Time Late

­Figure 20.1 The percentages of male academy players by maturation status across compet-
itive age groups. Adapted from Johnson et al., 2017.
 Growth and maturation 335
forwards, and those playing central positions. The presence of a bias does vary rela-
tive to the method used to estimate maturity. Studies employing PPAH (­Hill, Scott,
Malina et al., 2020), sexual maturity status (­Malina et al., 2013), or ­Greulich-​­Pyle, Fels,
and TW2 RUS skeletal ages (­Malina et al., 2011) have consistently observed a selec-
tion bias towards more mature players (­Malina, 2011). In contrast, TW3 RUS skeletal
ages were systematically lower than TW2 RUS skeletal ages by about 1 year beginning
at 11 years; as a result, the number of players classified as late maturing increased
while the number classified as early maturing decreased (­Malina et al., 2018; see also
Malina, 2017).
The impact of maturity status on the selection and retention of female soccer play-
ers is unclear (­Malina et al., 2021). Most studies suggest that adolescent female soccer
players tended to be ‘­on time’ or slightly delayed. Mean ages at menarche based on the
retrospective method in seven studies of soccer players ranged from 12.7 to 13.0 years
of age, whereas the median age at menarche based on the status quo method was 12.9
years; standard deviations of between 0.7 and 1.3 years (­Malina et al., 2021). The mean
ages of menarche in the soccer players were within the expected ranges for European
and North American populations. Studies of skeletal age in female soccer players are
limited. An early study suggested average or ‘­­on-​­time’ maturity status (­Novotny, 1981),
while a recent study showed variation between the G ­ reulich-​­Pyle and Fels methods
of assessment (­Martinho et al., 2021). Among U ­ 13–​­U17 players, skeletal age was, on
average, advanced relative to chronological age with the Fels method, whereas skeletal
age was advanced among U13 and U14 players, equal to chronological age among U15
players, but delayed relative to chronological age among U16 and U17 players with the
­Greulich-​­P yle method.

Maturity status and training

To optimise training effects and reduce injury risk, practitioners should recognise
and accommodate for individual differences in growth and maturity status. Training
gains are most efficacious when they complement the physiological adaptations that
occur with normal growth and maturation, a concept labelled as synergistic adaptation
(­Lloyd & Oliver, 2012). Prior to puberty, gains in speed, power, and strength are best
achieved through activities that promote enhanced neuromuscular adaptation and co-
ordination. By inference, training activities for ­pre-​­pubertal players should focus on
the development of technique and functional competence. Maximum gains in speed,
strength, and power ­post-​­puberty are, however, best achieved through a combination
of neuromuscular and structural (­i.e., hypertrophy) adaptation, with the latter result-
ing from the hormonal and metabolic changes that accompany puberty.
The Youth Physical Developmental Model provides a logical and ­evidence-​­based
framework for designing and implementing training and conditioning programmes for
young athletes (­Llyod & Oliver, 2012). Separate models exist for male and female ath-
letes with each identifying the specific ages and stages of maturity when various fitness
components and training modalities should be emphasised. Allowing for technical
competence and psychological readiness, young athletes should be grouped relative to
maturity status. Prior to puberty (­e.g., <85% PPAH), boys and girls should engage in
­low-​­structured activities that facilitate neural adaptations in speed, strength, power,
agility, and s­ port-​­specific skills through neuromuscular adaptation in l­ow-​­structured
activities, with a reduced emphasis upon hypertrophy, endurance and/­or metabolic
336 Sean P. Cumming et al.
conditioning. However, with the onset of the adolescent growth spurt (­­89–​­95% PPAH),
and especially during its latter stages (>95% PPAH), a greater emphasis can be placed
on activities that promote hypertrophy and adaptation of the anaerobic system.

Maturity status and injury

The interval of the adolescent growth spurt is a period of development when athletes
are more susceptible to overuse and g­ rowth-​­related injuries (­Johnson et al., 2020; van
der Sluis et al., 2014; Wik et al., 2020). With an accelerated rate of linear growth, the
physes, apophyses, and articular surfaces are less resistant to compressive, shear, and
tensile forces than immature or mature bone due to a lack of collagen or calcified
tissue (­McKay et al., 2019). ­Age-​­adjusted decreases in bone mineral content during
the growth spurt may also contribute to a greater risk of injury in adolescent players
(­Jackowski et al., 2009). Furthermore, rapid and differential timing growth of different
segments of the body during adolescence differentially influences limb lengths, muscle
mass, and moments of inertia (­Adirim & Cheng, 2003), leading some youth to expe-
rience delays or regressions in motor control that may adversely impact injury risk; a
phenomenon commonly referred to as ‘­adolescent awkwardness’.
­Non-​­contact injuries are prevalent in youth sports and comprise ­53–​­72% of injuries
in ­h igh-​­level male youth soccer players of age ­9 –​­21 years (­Jones et al., 2019). Moreo-
ver, growth and overuse injuries accounted for 6.6% of all injuries among a combined
sample of players from six youth academies (­Read et al., 2018). Common examples of
overuse injuries related to growth among youth soccer players include chondromala-
cia, ­Sinding-­​­­Larsen-​­Johansson syndrome, ­Osgood-​­Schlatter disease, Sever’s disease,
osteochondritis dissecans, and lower body stress fractures. A retrospective study of
maturity status based on percentage of attained adult height at the time of observa-
tion and injury in academy players in Spain suggested a specific pattern related to
the incidence of overuse injuries and stages of the growth spurt. Following a gradi-
ent of distal to proximal growth, cases of Sever’s disease clustered around the start
of the growth spurt (­85% PPAH), whereas the majority of ­Osgood-​­Schlatter’s cases
approximated the peak of the growth spurt (­89% PPAH) (­Monasterio et al., 2021).
­Growth-​­related injuries related to the spine, lower back (­spondylolysis), and hip (­e.g.,
ischial tuberosity) occurred following the peak of the growth spurt and during the
deceleration phase.
Puberty is a developmental stage that sees increases in other injuries, such as
anterior cruciate ligament (­ACL) injuries. ACL injuries are three and a half times
more likely in female athletes compared to males with these gender differences oc-
curring at the onset of puberty (­Voskanian, 2013). The exact stage of puberty at
which this gender discrepancy arises is unclear and further research is warranted
to better understand this process. Gender differences in hormonal profiles in addi-
tion to functional and structural differences, such as the Q angle and knee ligament
laxity, are likely contributors to this increased likelihood of knee injury in females.
The mechanism of ACL injuries is often cutting or landing, therefore, considera-
tion of neuromuscular recruitment patterns and landing techniques is paramount
(­Voskanian, 2013). Monitoring the tempo and timing of the growth spurt could have
a meaningful impact on understanding the risk between early and late maturing girls
and the age at which specific injury prevention programmes are introduced. Such
programmes should include activities emphasising the lower body and core strength,
 Growth and maturation 337
balance, coordination, fundamental movement skills, and ­sport-​­specific techniques
of jumping and landing to mitigate the risk of k ­ nee-​­related injuries during this stage
of development.
Research investigating the impact of growth and maturation upon injury in youth
soccer is limited, yet suggests a heightened risk during periods of rapid growth (­Price
et al., 2004). Available data suggest that injuries among male adolescent players were
associated with an estimated higher rate of growth at the time of injury compared
to ­non-​­injured players (­Rommers et al., 2020). Other data suggest an association be-
tween estimated rates of growth in height and leg length with a greater risk of bone
and growth plate injuries in adolescent track and field athletes (­Wik et al., 2020). The
interval of the adolescent growth spurt is also associated with an increased likelihood
of injury (­Bult et al., 2018; van der Sluis et al., 2014); although most of the studies
have used the offset method and should, and thus should be interpreted with caution.
Using PPAH as the indicator of maturity status, players with percentages of predicted
adult height between 88% and 95% (­interpreted as circa PHV) presented a signifi-
cantly higher incidence and burden of injury compared to players estimated as ­pre-​
P­ HV (­Johnson et al., 2020).
A reduction in injury incidence and burden through the growth spurt should be
possible through regular assessment of growth and maturity status, consideration of
training load and content, and careful monitoring of injury symptomology (­McKay
et al., 2019). The onset of the growth spurt (­i.e., age at t­ ake-​­off) typically occurs at 85%
of PPAH, before peaking at 91% of PPAH, and decelerating at 95% of PPAH. Rates of
growth in both stature and mass accelerate during the growth spurt from ­5 –​­6 cm and
­2–​­3 kg per year, to ­9 –​­10 or ­8 –​­9 cm and ­9 –​­10 kg per year in boys and girls, respectively.
An example of how to identify ‘­­at-​­risk’ players is presented in ­Figure 20.1. The ma-
turity status/­g rowth velocity heat map developed by Johnson and colleagues at AFC
Bournemouth illustrates the interaction between growth rate and percentage of pre-
dicted adult height on injury incidence (­­Figure 20.2a) and injury burden (­­Figure 20.2b)
in academy players across a competitive season. Risk for injury incidence peaks at
approximately ­92–​­93% of PPAH and among players growing at a rate of 1­ 0–​­15 cm per
year, whereas injury burden is greatest ­post-​­PHV and among players in the declaration
phase of the growth spurt.
Jan Willem Teunnisen, a movement scientist and performance coach at AFC Ajax,
proposed a strategy to reduce injury risk and better manage player development as
youth enter and transition through puberty (­Wormhoudt et al., 2017). The strategy
involves the modification of training load and content (­exercise diversification per
phase: ­pre-​­, during, and ­post-​­PHV) and is implemented as players enter the growth
spurt. Modifications include a reduction in training load and activities that involve
significant amounts of acceleration and deceleration; coupled with increased empha-
sis upon activities that develop and/­or maintain coordination, balance, core control
and strength, mobility, and the ­re-​­training of fundamental and s­ port-​­specific skills.
These strategies are described in a model presented by Towlson and colleagues (­2021)
(­­Figure 20.3). Applying these strategies across a competitive season, sports scientists
at AFC Bournemouth reported marked reductions in injury incidence and burden
among players identified as being within the growth spurt. Although these results are
encouraging, further research is required to validate these findings and better under-
stand the mechanisms underlying the benefits and most appropriate training loads and
content to reduce injury risk in adolescent players.
338 Sean P. Cumming et al.

­Figure 20.2a and b Heat maps showing the combined effects of growth rate and POAH on
estimated (­A) injury likelihood and (­B) injury burden.

­Figure 20.3 Use of percentage of predicted adult stature to determine location in adoles-

cent growth curve in young athletes.
Source: Reproduced with permission. Towlson, C., Salter, J., Ade, J. D., et al. (­2020). M ­ aturity-​
­associated considerations for training load, injury risk, and physical performance in youth soccer:
one size does not fit all. J Sport Health Sci. Published online September 19, 2020. Copyright© [2020].
doi: 10.1016/­j.jshs.2020.09.003.
 Growth and maturation 339
Maturity status and fitness testing
Fitness testing is employed for the purposes of talent identification, monitoring
player development, and evaluating the effectiveness of training programmes. Vari-
ance in maturation status can enhance or confound performance on fitness tests, with
more mature players outperforming their later maturing peers. As part of their Elite
Player Performance Plan, the English Premier League developed ­academy-​­wide ­age-​­
and ­maturity-​­specific standards for all physical fitness tests, including ­30-​­m sprint,
­counter-​­movement jump, 505 agility tests and Y­ o–​­Yo test of aerobic endurance. Acad-
emy staff have the capacity to judge players relative to age and maturity standards
and, therefore, are better able to identify player strengths and weaknesses. A boy who
has matured early may perform at the 90th centile for his age groups in the 3­ 0-​­m
sprint, yet place at the 30th centile when compared against players of similar maturity
status. Thus, an apparent strength is a weakness when considered from a developmen-
tal perspective and coaches should consider adjusting the training for this player to
place a greater emphasis on speed work.

Maturity status and competition: ­bio-​­banding

As discussed previously, variance in maturation status can create competitive inequity
within age groups. Inequity in competition disadvantages both early and late matur-
ing boys. The pressure to win encourages early maturing boys to play to their physical
and functional strengths, neglecting the use and development of the technical, tactical,
and psychological skills that are necessary to succeed at the professional level. Con-
versely, the equally, if not more talented late maturing players are less able to succeed
and/­or demonstrate their ability/­potential and, thus, more likely to be overlooked or
excluded.
To accommodate individual differences in growth and maturity, it has historically
been suggested that youth should be grouped based on their physical development,
often labelled as ­maturity-​­matching. ­Bio-​­banding is a current manifestation of the
­maturity-​­matching strategy (­Malina et al., 2019). ­Bio-​­banding in soccer was first im-
plemented in England in the early 1990s where a ­bio-​­banding metric based on size and
weight was employed to group players relative to their physical development. Although
this strategy was successfully implemented within the Football Association (­FA)
School of Excellence at Lilleshall, any application outside of the centre was limited.
The English Premier League recently revisited the concept of b ­ io-​­banding in 2015
as part of its Elite Player Performance Plan (­Cumming, 2018). It was hoped that b ­ io-​
­banded games would promote competitive equity and provide new learning oppor-
tunities and challenges for early and late maturing youth, whilst providing coaches
with the opportunity to better evaluate players in different contexts. Working with
the Premier League, the academies used the percentage of predicted adult height to
group players relative to maturity status. B ­ io-​­bands of 5% of predicted adult stat-
ure were used to group players (­i.e., ­85–​­90% PPAH; ­90–​­95% PPAH) across a series of
­bio-​­banded festival tournaments delivered as part of the academy games programme
(­Cumming et al., 2018).
The ­bio-​­banded format was received positively by the players, with 47 of 48 players
interviewed ­post-​­tournament recommending the inclusion of ­bio-​­banding within the
existing games programme. Early and late maturing players did, however, support the
340 Sean P. Cumming et al.
initiative for different reasons (­Cumming et al., 2018). Players advanced in maturity
described the ­bio-​­banded games as physically more challenging, better learning expe-
riences and an opportunity to compete with and learn from older, more experienced
players. They found they were unable to rely on their physical advantages, placing
greater emphasis on technical, tactical, and psychological skills. They described the
game as faster, noting less time to make decisions and receive and release the ball. In
contrast, late maturing players described their ­bio-​­banded games as less physically
challenging yet appreciated having greater opportunity to use and demonstrate their
physical, technical, and tactical abilities. The older late maturing boys took positions
of leadership, organising, motivating, and mentoring their younger peers. Of note,
both early and late maturing players described the games as being less physical and
more technically and tactically oriented, and as an opportunity to meet and make new
friends.
Since the English Premier League’s inaugural tournaments, a number of studies
have investigated the benefits and challenges of b ­ io-​­banding, often using GPS and
video analysis technology (­Abbott et al., 2019; Bradley et al., 2019; Reeves et al., 2018;
Romann et al., 2020; Thomas et al., 2017; Towlson et al., 2020). Collectively, these
studies supported the tenets of ­bio-​­banding, highlighting benefits for early and late
maturing players, and changes in game demands. ­Bio-​­banded formats encourage
a more technical/­tactical style of play that involves more short passes and touches
(­particularly within the defensive half), greater frequencies of tackles, duels, and set
pieces. The ­bio-​­banding format also led to less long passing, heading, dribbling, dis-
tance covered in jogging, running and ­h igh-​­speed running, yet greater physical ex-
ertion among early maturing players. In s­ mall-​­sided games, b ­ io-​­banding resulted in
greater equity in terms of physical and psychological challenges (­Towlson et al., 2020).
In an investigation of the perceived benefits and disadvantages of ­bio-​­banding among
stakeholders within a professional English Academy, several psychological, social,
and technical/­tactical advantages associated with the b ­ io-​­banded format were noted
(­Reeves et al., 2018). Late maturing players benefitted in terms of confidence and tech-
nical and tactical development, whereas early maturing players benefitted from the
novel and more physical challenges. Potential negatives of ­bio-​­banding were noted,
notably, the social stigma associated with asking players to train and compete with
youth that were chronologically younger. The latter observation highlights the need
to educate players, parents, and coaches on the purpose and potential benefits of ­bio-​
b
­ anding and to remove stigma associated with the process of ‘­playing up or down’ age
groups. Overall, results of studies of b­ io-​­banding are interesting and promising, but
the need for further research is essential.

Future programmes
To provide greater equity and opportunity for late maturing and/­or relatively young
players, the Belgian FA developed a ‘­Futures’ programme. This strategy groups play-
ers based on developmental status, limiting age, and m ­ aturity-​­associated variance in
size and athleticism. To identify talented late developers, coaches and scouts observing
fixtures are encouraged to identify players that demonstrate a winning mindset, future
physical potential, insight into the game, body, and ball control, learning ability, and
­self-​­development. These players are selected for a national future team that trains in par-
allel with national junior age group teams and compete against smaller nations. Since
 Growth and maturation 341
its inception, several other European nations have adopted and implemented equivalent
Futures programmes, including Ireland, the Czech Republic, Denmark, and Sweden.

Future directions and conclusions

Variance in maturity status and timing has important implications for the identifi-
cation and development of youth players. Although maturity status and timing are
genotypic characteristics of individual players, coaches, and practitioners can assess,
monitor, and accommodate these individual differences by altering training, content,
competition, behaviours, and expectations. In doing so, we can overcome the chal-
lenges presented by individual differences in growth and maturation, optimising the
opportunities and challenges for early, o­ n-​­time and late maturing youth. B
­ io-​­banding,
though still in its infancy, represents one strategy that may help coaches, scouts, and
practitioners deal with these challenges. It should not be considered as a replacement
for age group competition but should be viewed as an adjunct to and perhaps as part of
a diverse and dynamic approach to games programmes. Further research is required
to determine the effectiveness of various ­bio-​­banding strategies in youth soccer and
the ages at which these strategies should be introduced. That said, ­bio-​­banding rep-
resents an important first step in addressing some of the challenges presented by the
individuality of physical growth and biological maturation, and the journey towards
an efficient and effective model of talent identification and development.

References
Abbott, W., Williams, S., Brickley, G., & Smeeton, N. J. (­2019). Effects of b ­ io-​­banding upon
physical and technical performance during soccer competition: a preliminary analysis.
Sports, 7(­8), 193.
Adirim, T. A., & Cheng, T. L. (­2003). Overview of injuries in the young athlete. Sports Medicine,
33(­1), ­75–​­81.
Bradley, B., Johnson, D., Hill, M., McGee, D., K ­ ana-​­Ah, A., Sharpin, C., Sharp, P., Kelly, A.,
Cumming, S. P., & Malina, R. M. (­2019). B ­ io-​­banding in academy football: player’s percep-
tions of a maturity matched tournament. Annals of Human Biology, 46(­5), ­400– ​­408.
Buchheit, M., & ­Mendez-​­Villanueva, A. (­2014). Effects of age, maturity and body dimensions
on match running performance in highly trained u ­ nder-​­15 soccer players. Journal of Sports
Sciences, 32(­13), ­1271–​­1278.
Bult, H. J., Barendrecht, M., & Tak, I. J. R. (­2018). Injury risk and injury burden are related to
age group and peak height velocity among talented male youth soccer players. Orthopaedic
Journal of Sports Medicine, 6(­12), 2325967118811042.
Carling, C., Le Gall, F., & Malina, R. M. (­2012). Body size, skeletal maturity, and functional
characteristics of elite academy soccer players on entry between 1992 and 2003. Journal of
Sports Sci, 30(­15), ­1683–​­1693.
Cumming, S. P. (­2018). A game plan for growth: how football is leading the way in the considera-
tion of biological maturation in young male athletes. Annals of Human Biology, 45(­5), ­373–​­375.
Cumming, S. P., Brown, D. J., Mitchell, S., Bunce, J., Hunt, D., Hedges, C., Crane, G., Gross,
A., Scott, S., & Franklin, E. (­2018). Premier League academy soccer players’ experiences of
competing in a tournament ­bio-​­banded for biological maturation. Journal of Sports Sciences,
36(­7), ­757–​­765.
Cumming, S. P., Lloyd, R. S., Oliver, J. L., Eisenmann, J. C., & Malina, R. M. (­2017). B ­ io-​
­banding in sport: applications to competition, talent identification, and strength and condi-
tioning of youth athletes. Strength & Conditioning Journal, 39(­2), ­34–​­47.
342 Sean P. Cumming et al.
Cumming, S. P., Sherar, L. B., Pindus, D. M., ­Coelho-­​­­e-​­Silva, M. J., Malina, R. M., & Jardine,
P. R. (­2012). A biocultural model of m ­ aturity-​­associated variance in adolescent physical ac-
tivity. International Review of Sport and Exercise Psychology, 5(­1), ­23–​­43.
de Silva, M. C., Figueiredo, A. J., Simoes, F., Seabra, A., Natal, A., Vaeyens, R., Philippaerts,
R., Cumming, S. P., & Malina, R. (­2010). Discrimination of u ­ -​­14 soccer players by level and
position. International Journal of Sports Medicine, 31(­11), ­790–​­796.
Emmonds, S., Morris, R., Murray, E., Robinson, C., Turner, L., & Jones, B. (­2017). The influ-
ence of age and maturity status on the maximum and explosive strength characteristics of
elite youth female soccer players. Science and Medicine in Football, 1(­3), ­209–​­215.
Emmonds, S., Scantlebury, S., Murray, E., Turner, L., Robsinon, C., & Jones, B. (­2020). Physi-
cal characteristics of elite youth female soccer players characterized by maturity status. The
Journal of Strength & Conditioning Research, 34(­8), ­2321–​­2328.
Epstein, L. H., Valoski, A. M., Kalarchian, M. A., & McCurley, J. (­1995). Do children lose and
maintain weight easier than adults: a comparison of child and parent weight changes from six
months to ten years. Obesity Research, 3(­5), ­411–​­417.
Figueiredo, A. J., e Silva, M. J. C., Cumming, S. P., & Malina, R. M. (­2010). Size and maturity
mismatch in youth soccer players ­11-​­to ­14-­​­­years-​­old. Pediatric Exercise Science, 22(­4), ­596–​­612.
Gilli, G. (­1996). The assessment of skeletal maturation. Hormone Research in Paediatrics,
45(­Suppl. 2), ­49–​­52.
Gillison, F., Cumming, S., Standage, M., Barnaby, C., & Katzmarzyk, P. (­2017). Assessing the
impact of adjusting for maturity in weight status classification in a c­ ross-​­sectional sample of
UK children. BMJ Open, 7(­6), e015769.
Hill, M., Scott, S., Malina, R. M., McGee, D., & Cumming, S. P. (­2020). Relative age and mat-
uration selection biases in academy football. Journal of Sports Sciences, 38(­­11–​­12), ­1359–​­1367.
Hill, M., Scott, S., McGee, D., & Cumming, S. (­2020a). Coaches’ evaluations of match per-
formance in academy soccer players in relation to the adolescent growth spurt. Journal of
Science in Sport and Exercise, ­1–​­8.
Hill, M., Scott, S., McGee, D., & Cumming, S. P. (­2020b). Are relative age and biological ages
associated with coaches’ evaluations of match performance in male academy soccer players?
International Journal of Sports Science & Coaching, 16(2), 227–235 1747954120966886.
Huijgen, B. C., ­Elferink-​­Gemser, M. T., Lemmink, K. A., & Visscher, C. (­2014). Multidimen-
sional performance characteristics in selected and deselected talented soccer players. Euro-
pean Journal of Sport Science, 14(­1), ­2 –​­10.
Jackowski, S. A., Faulkner, R. A., Farthing, J. P., Kontulainen, S. A., Beck, T. J., & B ­ axter-​
­Jones, A. D. (­2009). Peak lean tissue mass accrual precedes changes in bone strength indices
at the proximal femur during the pubertal growth spurt. Bone, 44(­6), ­1186–​­1190.
Johnson, A. (­2015). Monitoring the immature athlete. Aspetar Sports Medicine Journal, 4(­4),
114–118.
Johnson, A., Farooq, A., & Whiteley, R. (­2017). Skeletal maturation status is more strongly
associated with academy selection than birth quarter. Science and Medicine in Football, 1(­2),
­157–​­163.
Johnson, D. (­2021). Growth, Maturation and B ­ io-​­banding in Youth Football.
Johnson, D., Williams, S., Bradley, B., Sayer, S., Murray Fisher, J., & Cumming, S. (­2020).
Growing pains: maturity associated variation in injury risk in academy football. European
Journal of Sport Science, 20(­4), ­544–​­552.
Jones, S., Almousa, S., Gibb, A., Allamby, N., Mullen, R., Andersen, T. E., & Williams, M.
(­2019). Injury incidence, prevalence and severity in ­h igh-​­level male youth football: a system-
atic review. Sports Medicine, 49(­12), ­1879–​­1899.
Kemper, G., Van Der Sluis, A., Brink, M., Visscher, C., Frencken, W., & E ­ lferink-​­Gemser, M.
(­2015). Anthropometric injury risk factors in ­elite-​­standard youth soccer. International Jour-
nal of Sports Medicine, 36(­13), ­1112–​­1117.
 Growth and maturation 343
Khamis, H. J., & Roche, A. F. (­1994). Predicting adult stature without using skeletal age: the
­K hamis-​­Roche method. Pediatrics, 94(­4), ­504–​­507.
Khamis, H., & Roche, A. (­ 1995). Predicting adult stature without using skeletal a­ge-​­ the
­K hamis-​­Roche method. Pediatrics, 95(­3), ­457–​­457.
Konarski, J., Krzykała, M., Skrzypczak, M., Nowakowska, M., C ­ oelho-­​­­e-​­Silva, M., Cumming,
S., & Malina, R. (­2020). Characteristics of select and n ­ on-​­select U15 male soccer players.
Biology of Sport, 38(­4), ­535–​­544.
Kozieł, S. M., & Malina, R. M. (­2018). Modified maturity offset prediction equations: val-
idation in independent longitudinal samples of boys and girls. Sports Medicine, 48(­1),
­221–​­236.
Lefevre, J., Philippaerts, R. M., Delvaux, K., Thomis, M., Vanreusel, B., Eynde, B. V., Claes-
sens, A. L., Lysens, R., Renson, R., & Beunen, G. (­2000). Daily physical activity and physical
fitness from adolescence to adulthood: a longitudinal study. American Journal of Human
Biology, 12(­4), ­487–​­497.
Lloyd, R. S., & Oliver, J. L. (­2012). The youth physical development model: a new approach to
­long-​­term athletic development. Strength & Conditioning Journal, 34(­3), ­61–​­72.
Malina, R. M., Bouchard, C., & ­Bar-​­Or, O. (­2004). Growth, Maturation, and Physical Activity.
Champaign Human Kinetics.
Malina, R. M. (2011). Skeletal age and age verification in youth sport. Sports medicine, 41,
925–947.
Malina, R. M., e Silva, M. C., & Figueiredo, A. J. (2013). Growth and maturity status of youth
players. In Science and soccer (pp. 319–344). Routledge.
Malina, R. M., Figueiredo, A. J., & Coelho-e-Silva, M. J. (2017). Body size of male youth soccer
players: 1978–2015. Sports Medicine, 47, 1983–1992.
Malina, R. M., Coelho-e-Silva, M. J., Figueiredo, A. J., Philippaerts, R. M., Hirose, N., Peña
Reyes, M. E., ... & Buranarugsa, R. (2018). Tanner–Whitehouse skeletal ages in male youth
soccer players: TW2 or TW3?. Sports Medicine, 48, 991-1008.
Malina, R. M., Choh, A. C., Czerwinski, S. A., & Chumlea, W. C. (­2016). Validation of maturity
offset in the Fels longitudinal study. Pediatric Exercise Science, 28(­3), ­439–​­455.
Malina, R. M., Coelho E Silva, M. J., Figueiredo, A. J., Carling, C., & Beunen, G. P. (­2012).
Interrelationships among invasive and ­non-​­invasive indicators of biological maturation in
adolescent male soccer players. Journal of Sports Sciences, 30(­15), ­1705–​­1717.
Malina, R. M., Cumming, S. P., Morano, P. J., Barron, M., & Miller, S. J. (­2005). Maturity
status of youth football players: a noninvasive estimate. Medicine and Science in Sports and
Exercise, 37(­6), ­1044–​­1052.
Malina, R. M., Cumming, S. P., Rogol, A. D., ­Coelho-­​­­e-​­Silva, M. J., Figueiredo, A. J., Konar-
ski, J. M., & Kozieł, S. M. (­2019). ­Bio-​­banding in youth sports: background, concept, and
application. Sports Medicine, 4­ 9(11):1671–1685
Malina, R. M., Dompier, T. P., Powell, J. W., Barron, M. J., & Moore, M. T. (­2007). Validation
of a noninvasive maturity estimate relative to skeletal age in youth football players. Clinical
Journal of Sport Medicine, 17(­5), ­362–​­368.
Malina, R. M., & Kozieł, S. M. (­2014a). Validation of maturity offset in a longitudinal sample
of Polish boys. Journal of Sports Sciences, 32(­5), ­424–​­437.
Malina, R. M., & Kozieł, S. M. (­2014b). Validation of maturity offset in a longitudinal sample
of Polish girls. Journal of Sports Sciences, 32(­14), ­1374–​­1382.
Malina, R. M., Kozieł, S. M., Králik, M., Chrzanowska, M., & Suder, A. (­2020). Prediction
of maturity offset and age at peak height velocity in a longitudinal series of boys and girls.
American Journal of Human Biology, 33(6), e23551.
Malina, R. M., Martinho, D. V., ­Valente-­​­­dos-​­Santos, J., ­Coelho-­​­­e -​­Silva, M. J., & Kozieł, S. M.
(­2021). Growth and maturity status of female soccer players: a narrative review. International
Journal of Environmental Research and Public Health, 18(­4), 1448.
344 Sean P. Cumming et al.
Malina, R. M., Rogol, A. D., Cumming, S. P., e Silva, M. J. C., & Figueiredo, A. J. (­2015). Bio-
logical maturation of youth athletes: assessment and implications. British Journal of Sports
Medicine, 49(­13), ­852–​­859.
Martinho, D. V., Coelho‐e‐Silva, M. J., Valente‐dos‐Santos, J., Minderico, C., Oliveira, T. G.,
Rodrigues, I., Conde, J., Sherar, L. B., & Malina, R. M. (­2021). Assessment of skeletal age in
youth female soccer players: agreement between Greulich‐Pyle and Fels protocols. American
Journal of Human Biology, 34(1), e23591.
McKay, C. D., Cumming, S. P., & Blake, T. (­2019). Youth sport: friend or Foe? Best Practice &
Research Clinical Rheumatology, 33(­1), ­141–​­157.
Meylan, C., Cronin, J., Oliver, J., & Hughes, M. (­2010). Talent identification in soccer: the role
of maturity status on physical, physiological and technical characteristics. International
Journal of Sports Science & Coaching, 5(­4), ­571–​­592.
Mirwald, R. L., B ­ axter-​­Jones, A. D., Bailey, D. A., & Beunen, G. P. (­2002). An assessment of
maturity from anthropometric measurements. Medicine and Science in Sports and Exercise,
34(­4), ­689–​­694.
Monasterio, X., Gil, S., ­Bidaurrazaga-​­Letona, I., Lekue, J., Santisteban, J., ­Diaz-​­Beitia, G.,
­Martin-​­Garetxana, I., Bikandi, E., & Larruskain, J. (­2021). Injuries according to the per-
centage of adult height in an elite soccer academy. Journal of Science and Medicine in Sport,
24(­3), ­218–​­223.
Murtagh, C. F., Brownlee, T. E., O’Boyle, A., Morgans, R., Drust, B., & Erskine, R. M. (­2018).
Importance of speed and power in elite youth soccer depends on maturation status. The
Journal of Strength & Conditioning Research, 32(­2), ­297–​­303.
Myburgh, G. K., Cumming, S. P., Silva, M. C. E., Cooke, K., & Malina, R. M. (­2016). ­Maturity-​
­associated variation in functional characteristics of elite youth tennis players. Pediatric Exer-
cise Science, 28(­4), ­542–​­552.
Novotny, V. (­1981). Veranderungen des Knochenalters im Verlauf einer mehrjahrigen sportli-
chen Belastung. Medezin Und Sport, 21, ­44–​­47.
Olivares, L. A. F., De León, L. G., & Fragoso, M. I. (­2020). Skeletal age prediction model from
percentage of adult height in children and adolescents. Scientific Reports, 10(­1), ­1–​­10.
Parr, J., Winwood, K., ­Hodson-​­Tole, E., Deconinck, F. J., & Cumming, S. P. (­i n review). Matu-
rity Associated Differences in Match Running Performance in Elite Male Youth Soccer Players,
Champaign: Human Kinetics.
Parr, J., Winwood, K., ­Hodson-​­Tole, E., Deconinck, F. J., Hill, J. P., Teunissen, J. W., & Cum-
ming, S. P. (­2020). The main and interactive effects of biological maturity and relative age on
physical performance in elite youth soccer players. Journal of Sports Medicine, 2020, 1–11.
Parr, J., Winwood, K., ­Hodson-​­Tole, E., Deconinck, F. J., Parry, L., Hill, J. P., Malina, R. M., &
Cumming, S. P. (­2020). Predicting the timing of the peak of the pubertal growth spurt in elite
male youth soccer players: evaluation of methods. Annals of Human Biology, 47(­4), ­400– ​­408.
Price, R., Hawkins, R., Hulse, M., & Hodson, A. (­2004). The football association medical re-
search programme: an audit of injuries in academy youth football. British Journal of Sports
Medicine, 38(­4), ­466–​­471.
Read, P. J., Oliver, J. L., De Ste Croix, M. B., Myer, G. D., & Lloyd, R. S. (­2018). An audit
of injuries in six English professional soccer academies. Journal of Sports Sciences, 36(­13),
­1542–​­1548.
Reeves, M. J., Enright, K. J., Dowling, J., & Roberts, S. J. (­2018). Stakeholders’ understand-
ing and perceptions of b ­ io-​­banding in j­unior-​­elite football training. Soccer & Society, 19(­8),
­1166–​­1182.
Roche, A. F., Tyleshevski, F., & Rogers, E. (­1983). ­Non-​­invasive measurements of physical ma-
turity in children. Research Quarterly for Exercise and Sport, 54(­4), ­364–​­371.
Romann, M., & Fuchslocher, J. (­2016). Assessment of skeletal age on the basis of D ­ XA-​­derived
hand scans in elite youth soccer. Research in Sports Medicine, 24(­3), ­185–​­196.
 Growth and maturation 345
Romann, M., Lüdin, D., & Born, D.-​­P. (­2020). B ­ io-​­banding in junior soccer players: a pilot
study. BMC Research Notes, 13(­1), ­1–​­5.
Rommers, N., Rössler, R., Goossens, L., Vaeyens, R., Lenoir, M., Witvrouw, E., & D’Hondt, E.
(­2020). Risk of acute and overuse injuries in youth elite soccer players: body size and growth
matter. Journal of Science and Medicine in Sport, 23(­3), ­246–​­251.
Sanders, J. O., Qiu, X., Lu, X., Duren, D. L., Liu, R. W., Dang, D., Menendez, M. E., Hans, S.
D., Weber, D. R., & Cooperman, D. R. (­2017). The uniform pattern of growth and skeletal
maturation during the human adolescent growth spurt. Scientific Reports, 7(­1), ­1–​­9.
Teunissen, J. W., Rommers, N., Pion, J., Cumming, S. P., Rössler, R., D’Hondt, E., Lenoir, M.,
Savelsbergh, G. J., & Malina, R. M. (­2020). Accuracy of maturity prediction equations in
individual elite male football players. Annals of Human Biology, 47(­4), ­409–​­416.
Thomas, C. H., Oliver, J., Kelly, A., & Knapman, H. (­2017). A pilot study of the demands of
chronological age group and b ­ io-​­banded match play in elite youth soccer. Graduate Journal
of Sport Exercise and Physical Education Research, 1, s10.
Towlson, C., Cobley, S., Parkin, G., & Lovell, R. (­2018). When does the influence of maturation
on anthropometric and physical fitness characteristics increase and subside? Scandinavian
Journal of Medicine & Science in Sports, 28(­8), ­1946–​­1955.
Towlson, C., MacMaster, C., Gonçalves, B., Sampaio, J., Toner, J., MacFarlane, N., Barrett, S.,
Hamilton, A., Jack, R., & Hunter, F. (­2020). The effect of ­bio-​­banding on physical and psy-
chological indicators of talent identification in academy soccer players. Science and Medicine
in Football, 5(4), 280–292
Towlson, C., Salter, J., Ade, J. D., Enright, K., Harper, L. D., Page, R. M., & Malone, J. J. (­2021).
­Maturity-​­associated considerations for training load, injury risk, and physical performance
in youth soccer: One size does not fit all. Journal of Sport and Health Science, 10(­4), ­403–​­412.
van der Sluis, A., ­Elferink-​­Gemser, M., ­Coelho-­​­­e-​­Silva, M., Nijboer, J., Brink, M., & Visscher,
C. (­2014). Sport injuries aligned to peak height velocity in talented pubertal soccer players.
International Journal of Sports Medicine, 35(­04), ­351–​­355.
Vandendriessche, J. B., Vaeyens, R., Vandorpe, B., Lenoir, M., Lefevre, J., & Philippaerts, R.
M. (­2012). Biological maturation, morphology, fitness, and motor coordination as part of a
selection strategy in the search for international youth soccer players (­age ­15–​­16 years). Jour-
nal of Sports Sciences, 30(­15), ­1695–​­1703.
Voskanian, N. (­2013). ACL Injury prevention in female athletes: review of the literature and
practical considerations in implementing an ACL prevention program. Current Reviews in
Musculoskeletal Medicine, 6(­2), ­158–​­163.
Wik, E. H., Martínez‐Silván, D., Farooq, A., Cardinale, M., Johnson, A., & Bahr, R. (­2020).
Skeletal maturation and growth rates are related to bone and growth plate injuries in adoles-
cent athletics. Scandinavian Journal of Medicine & Science in Sports, 30(­5), ­894–​­903.
Wormhoudt, R., Savelsbergh, G. J., Teunissen, J. W., & Davids, K. (­2017). The Athletic Skills
Model: Optimizing Talent Development Through Movement Education. London: Routledge.
21 Talented or developmentally advanced?
How player evaluation can be improved
Stephen Cobley, Chris Towlson, Shaun Abbott,
Michael Romann and Ric Lovell

Introduction
For professional soccer clubs, being able to accurately identify and optimally develop
youth potential – commonly known as talent identification and development (TID;
Cobley, Schorer, & Baker, 2012; Williams & Reilly, 2000) – is valuable both in per-
formance and financial terms. For instance, if soccer clubs can develop promising
youth players and facilitate their transition to higher-level (senior) performance, there
are potential performance benefits. Similarly, if developed high-performing players
attract interest from other clubs, potential financial benefits may occur from transfer
fees. Yet, while TID systems have become progressively systematised and professional-
ised in practice (Winand, 2010) via club academies (or local ‘feeder’ programmes), the
capability to achieve the professional-level is fraught with complexity and challenges
(Cobley, Schorer, Baker, 2020). To illustrate, data across sports contexts highlight only
relatively low percentages (~30%) of youth remain within TID systems for ≥3 years
(Güllich, 2014; Güllich & Emrich, 2012). In soccer specifically, <1% of boys recruited
to player development centres in youth soccer in England go on to forge a professional
career (Read, Oliver, De Ste Croix, Myer, & Lloyd, 2016). Such evidence questions the
validity and rationality for TID-related early selection, player differentiation, and spe-
cialisation (Baker, Cobley & Fraser-Thomas, 2009; Güllich & Cobley, 2017).
There are potentially multiple theoretical and practical explanations as to why soccer
TID systems presently may not be (acceptably) effective, either in terms of inaccurate
identification or sub-optimal (or even inhibitory) training and development practices.
More gravitated explanations highlight limitations in considering (and developing)
the multi-factorial, holistic, facets of performance (Reilly, Williams, Nevill, & Franks,
2000; Vaeyens, Lenoir, Williams, & Philippaerts, 2008). The complex interactions that
occur over time between individual player characteristics and qualities of the devel-
opment environment have also been highlighted (Cobley, 2016). Here individual char-
acteristics refer to – for example – genetic (e.g., neurological and biological stage of
development; gene allele adaptability), physical (e.g., aerobic and anaerobic capacities),
and cognitive (e.g., executive functioning: early-age stimulation) characteristics as well
as technical (e.g., motor coordination and skill development), social (e.g., quality of
family relationships and support), and emotional (e.g., empathetic and responsive to
others) skills or constraints. Whereas qualities of the immediate developmental envi-
ronment refer to factors such as coaching knowledge and expertise; coaching social
and interaction skills; and the types of training activities deployed (including volumes
and intensities) according to developmental stages of game involvement. On this basis,

DOI: 10.4324/9781003148418-26
 How player evaluation can be improved 347
it can be proposed that variability in developmental environment qualities can lead to
group-level differences in development. Likewise, when considering interactions with
pre-existing individual characteristics (and constraints), similar environmental qual-
ities and exposure, may lead to varied individualised player response qualities over
time [Note: wider influential club-organisational and environmental factors could also
be listed and considered as impacting player development].

Inter-player developmental differences: relative age

and maturation status
While acknowledging the potential range of multi-factorial interactions related to
youth player development, in this chapter, we focus on inter-player biological devel-
opmental differences as a foundational concern. Two sources of developmental dif-
ference are examined, namely: relative age and maturational status. We examine these
factors, as both independently (and potentially interactively) influence facets of per-
formance, particularly in youth development stages. They both confound the process
of youth player selection and evaluation (Pearson, Naughton, & Torode, 2006), when
using either subjective (e.g., scout or coach judgement) or objective assessment meth-
ods (e.g., standardised measurement testing procedures), leading to relative age (RA)
and maturity biases (Cobley & Till, in press). The influence of these factors on per-
formance is not stable, but rather transient over time; with individual players – for
instance – illustrating differing maturational development trajectories. In a general
sense, their influence increases from childhood to adolescence (9–16 years in boys),
with progressive reductions toward adulthood (16+ years), but their effects on future
player evaluation, TID de(selection), and game involvement can be long-lasting. In the
following sections, we explain the relationships between relative age, biological matu-
ration, and facets of athletic performance with reference to youth and academy-level
soccer; and illustrate RA and maturity biases. Importantly, we then outline a strategy
to address these relationships and inequalities (i.e., RA or maturation-based correc-
tive adjustment procedures). We explain how these can be deployed to account for
player developmental differences; helping improve the accuracy of player evaluation
and selection practices.
Relative age refers to the interaction between a player’s ‘birth date’ and dates used
for chronological age-grouping. As such, a coincidental individual-environment in-
teraction can generate age-based developmental differences (i.e., up to potentially 364
days for each annual age-group across 8–18 years), assuming players follow a similar,
normative growth and maturational trajectory (Cobley, Romann, Javet, Abbott, &
Lovell, 2020). Typically, ‘relatively older’ players are considered as those whose birth-
date reside within the 1st quartile (Q1) of a cut-off date (e.g., UK youth soccer = Sept–
Nov). By contrast, ‘relatively younger’ players’ birthdates reside in the last quartile
(i.e., Q4; UK soccer = June–August). Independently, RA influences soccer-related per-
formance indices in youth ages. However, potential inter-player anthropometric and
physiological performance-related differences can be exacerbated (or reduced) when
considered alongside maturational status (see Cobley et al., 2020).
Maturation is regarded as a process of growth towards the mature adult state (Ma-
lina, 1994), with component features of timing, tempo, and magnitudes of change in
body size and associated capabilities (Malina, Bouchard, & Bar-Or, 2004). Geneti-
cally and hormonally driven, the timing of re-accelerated (maturational) adolescent
348 Stephen Cobley et al.
growth in Caucasian populations can typically vary between 13 and 15 years in males
(i.e., ‘normative maturing’), assuming a normatively distributed sample (i.e., where ap-
proximately 68% of the sample is represented). Nonetheless, peak maturation-­related
growth can occur – although observed with less-expected frequency (estimated at
15.85% of a sample) – at 11–12 (i.e., ‘earlier maturing’) and 15–16 years of age (i.e.,
‘later maturing’); Philippaerts et al., 2006; Simpkin, Sayers, Gilthorpe, Heron & Till-
ing, 2017). Body size and feature characteristics (e.g., height, body mass, muscle, and
fat tissue composition change) are all affected by re-accelerated growth. For instance,
rudimentary height gain for the ‘normative maturer’ occurs around 14.0 years, with
approximately 10–12 cm/year of gain (i.e., peak height velocity – PHV) commonly
apparent, before progressive reductions in post-PHV years. For Caucasian females,
the ‘normative’ age range for peak maturation-related growth occurs between 11 and
13 years of age, with potentially ‘earlier’ and ‘later-maturity’ timing initiating at 9.5–
11 and 13–14 years, respectively. For the ‘normative maturing’ female, typical height
gains have been estimated at 9–10 cm/year peaking at 12 years, before the progres-
sive reduction in post-PHV years (Kelly et al., 2014; Granados, Gebremariam, & Lee,
2015). Similar maturity-timing variations lead to distinct developmental curves across
chronological years (e.g., 10–18 years of age) for other anthropometric (weight – see,
e.g., Carrascosa et al., 2018) and physiological indices (e.g., strength – see, e.g., Morris
et al., 2018; Emmonds et al., 2017). As such, soccer players who reside within similar
age-groups (i.e., 11–16 in males; 10–15 in females) may differ markedly according to
maturation status and correspondingly connected anthropometric and physiological
characteristics.

Relative age and maturation influences on performance facets

Multi-centre studies have identified small, although practically meaningful anthro-
pometric and physiological advantages that are conferred to Q1 vs Q4 players at the
earliest stages of the TID cycle (e.g., under 10–13 age-groups) in soccer. These ad-
vantages include (although not exhaustive) stature, body mass, sprinting, agility, and
jumping (Deprez et al., 2015b; Lovell et al., 2015). The influence of RA upon several
physiological qualities is also demonstrated in cross-sectional (Towlson, Cobley, Par-
kin, & Lovell, 2018) and longitudinal youth soccer studies (Fransen et al., 2017) where
performance trajectories were modelled. In Figure 21.1, the chronological and RA
relationships with the (a) agility (T-test – Semenick, 1990) and (b) multi-stage fitness
test ([20-m MSFT]; i.e., an aerobic capacity test – Leger & Lambert, 1982) are shown.
Within the plots, the isolated black solid circles (●) denote two example players in the
under 13s age-group (N = 123), with the highest and lowest relative age; note their
performance differences. A summary of modelled differences in males in the under
10s age-group – considered a pre-maturation stage – is provided in Table 21.1. The
hypothetical, maximal estimated advantages, afforded to the ‘relatively oldest’ (Q1)
player based on two studies reviewed in Table 21.1 correspond (and often exceed) the
difference magnitudes observed in studies. That said, superior anthropometric and
physiological qualities based on RA have been consistently observed in selected (or
more successful) academy players (Deprez, Fransen, Lenoir, Philippaerts, & Vaeyens,
2015a; Patel, Nevill, Smith, Cloak, & Wyon, 2020).
The performance advantages afforded to the relatively older player, due to predicted
advances in normative growth, influence positional role allocation (Towlson et al.,
 How player evaluation can be improved 349

Figure 21.1a, b T
 he relationship between chronological and relative age with (a) the agility
(T-test), and (b) with the multi-stage fitness test (20-m MFST) in UK soccer
academy players (N = 969; Towlson et al., 2018).
Notes: Black solid change the shape here to solid circles (●) denote example individuals (n = 2) with
the highest and lowest relative age in the under 13s age-group (N = 123).

Table 21.1 M
 odelled differences in physiological performance indices according to relative age
between two hypothetical youth male soccer players at the entry point to the talent
development process (i.e., under 10 age-group)

Physiological test Study Player A (Q1) Player B (Q4) Difference

(Age = 9.00 years) (Age = 9.99 years)

Agility (T-test) Fransen et al. 9.70 s 9.50 s 0.20 s

Towlson et al. 12.15 s 11.76 s 0.39 s
Yo–Yo IR1 Fransen et al. 621 m 821 m 200 m
Multi-stage fitness test Towlson et al. 1023 m 1190 m 167 m
10-m Sprint Fransen et al. 2.25 s 2.19 s 0.06 s
Towlson et al. 1.99 s 1.95 s 0.04 s
20-m Sprint Fransen et al. 3.94 s 3.83 s 0.11 s
Towlson et al. 3.64 s 3.57 s 0.07 s
Vertical jump Towlson et al. 21.1 cm 23.0 cm 1.9 cm
Standing broad jump Fransen et al. 151.4 cm 160.6 cm 9.2 cm

Notes: Data estimated via digitisation of published segmented regression plots (physiological test ~
­chronological age). IR1 = Intermittent recovery test – level 1.

2017), playing opportunities (Vaeyens, Philippaerts, & Malina, 2005), and perfor-
mance outcomes (Augste & Lames, 2011) within TID systems. As a stable advantage
across youth ages (if dates for age-grouping do not change), RA can thus relate to di-
verging Q1 vs Q4 player development paths at least until growth differences diminish.
There is no data available on the relationships between RA and soccer performance
indices in female players. Although it is suspected that such relationships are limited
to earlier age-groups, with lower inter-player differences and with more complex rela-
tionships (Smith, Weir, Till, Romann, & Cobley, 2018).
In older age-groups, several researchers have either shown RA differences of smaller
effect magnitude (Deprez et al., 2013; Lovell et al., 2015) or no distinct disadvantages
350 Stephen Cobley et al.
were apparent for relatively younger players within youth academies (Carling, Le Gall,
Reilly, & Williams, 2008; Skorski, Skorski, Faude, Hammes, & Meyer, 2016). While
initially seeming to contrast with prior findings, either advanced normative growth
(e.g., Patel, Nevill, Cloak, Smith, & Wyon, 2019) or advanced, earlier, biological mat-
uration (Müller, Gonaus, Perner, Müller, & Raschner, 2017) may provide the explana-
tions. In other words, anthropometric and physiological profile homogeneity may have
occurred via selection in later age-groups. Lovell et al. (2015), for example, identified
that under 10 Q4 players were between the 75th and 91st centile in population stature,
whereas Q1 players resided around the 50th centile for their chronological age. While
in older age-groups, relatively younger academy players were advanced in biological
maturation terms for their respective chronological age.
The potential for substantial inter-player variation in both maturation timing and
tempo influences many performance facets. These include aerobic capacity, sprinting
speed, agility, and strength (Deprez et al., 2013; Lovell et al., 2015), which collec-
tively can also influence physical match performance outcomes (Lovell et al., 2019).
Whilst the influence of maturation has asynchronous relationships across adoles-
cence (Philippaerts et al., 2006; Towlson et al., 2018), maturation is generally associ-
ated with accelerated physiological development. Towlson et al. (2018) captured these
changing, dynamic, relationships when modelling cross-sectional data across 900+
players who were participating in 23 UK soccer academies (Tiers 2–4). Figure 21.2
shows, for instance, relationships between maturity status and performance in the (a)
agility (T-test) and (b) 20-m MSFT. Within the plots, the isolated black solid circles
(●) denote two example players in the under 13s age-group (N = 123), with the highest
and lowest relative age. However, the white markers (○) identify two players with the
highest and lowest maturity status at under 13s, but who had the exact same relative
age: demonstrating the independent influence of maturation status on performance
indices.

Figure 21.2a, b T
 he relationship between maturity status (YPHV) with (a) the agility
(T-test) and (b) with the multi-stage fitness test (20-m MFST) in UK soccer
academy players (N = 969; Towlson et al., 2018).
Notes: Black solid squares (■) denote example individuals (n = 2) with the highest and lowest relative
age in the under 13s age-group (N = 123). White squares (□) denote example individuals (n = 2) with
the highest and lowest maturity status when chronological age was the same in the under 13s sample
(N = 123).
 How player evaluation can be improved 351
Table 21.2 Modelled differences in physical qualities according to biological maturity between
two elite-youth male soccer players within the same chronological age (14.3-years
old; i.e., under 15 age-group)

Anthropometric or Player A Player B Difference

physiological test (YPHV = – 0.65) (YPHV = 1.02)

Stature 154.5 cm 171.3 cm 16.8 cm

Body mass 46.2 kg 63.9 kg 17.7 kg
Agility (T-test) 10.43 s 9.79 s 0.64 s
Multi-stage fitness test 1733 m 2051 m 318 m
10-m Sprint 1.77 s 1.63 s 0.14 s
20-m Sprint 3.22 s 2.95 s 0.27 s
Vertical jump 29.3 cm 33.2 cm 3.9 cm

Notes: Stature, body mass, and somatic maturity data taken from two national-level youth players.
­Physiological test data estimated via digitisation of Towlson et al. (2018) segmented regression plots
(­physiological test ~ YPHV). YPHV = Years from peak height velocity.

Using the derived regression parameters, estimated performance differences can be

forecasted between players of similar chronological age (14.3 years), but who were at
different stages of biological maturation. In this case, the inter-player differences in
maturity timing are relatively modest (1.67 years), considering maturation status within
a similar age-group can be as much as six years (Johnson, Doherty, & Freemont, 2009).
The anthropometric and physiological differences predicted for the two individual
players are summarised in Table 21.2. Comparison of difference magnitudes in Tables
21.1 and 21.2 demonstrates the potential greater impact of maturity status if matura-
tion timing (and thus status) is highly varied between players. Nevertheless, caution is
required as these differences are transient, with some athletic capacities in ‘late matur-
ing’ males often exceeding those of their ‘earlier-maturing’ peers in late (adult) years
(Lefevre, Beunen, Steens, Claessens, & Renson, 2009; Pearson et al., 2006).

Relative age and maturational biases in youth soccer

Given the relationships between RA and maturation with performance facets and
identified (changing) inter-player differences within and across age-groups, it is per-
haps not surprising for participation and selection biases to exist in youth soccer. In
RA terms, biases are associated with the over-valuing and selection of players born
within the first and second quartiles of a given age-group (Cobley et al., 2009; Lovell
et al., 2015). For example, in Lovell et al.’s sample (N = 1212) of UK academy soccer
players, which spanned adolescence (i.e., under 9–18 age-groups), 48.6% were relatively
older (Q1) players. By comparison, only 9.2% of selected academy players were rela-
tively younger (Q4). Of these players, odds ratio (OR) statistics revealed Q1 players
were 5.3 (95% CI 4.08–6.83) times more likely to be selected than Q4s, with the bias
strongest at under 13–16 age-groups (i.e., OR = 5.45–6.13); time-points coinciding with
periods of accelerated growth (Towlson et al., 2018).
Such biases or inequalities are not new or unknown in soccer (Cobley et al., 2009).
In fact, the original soccer-related studies were published almost three decades ago
(Barnsley et al., 1992), with Helsen et al. (1998) showing clear over-representations of
relatively older Q1 (31–46%) compared to Q4 (6.8–18%) within a sample of selected Bel-
gium youth soccer players (6–16 years old). Despite such prevalence, at the turn of the
352 Stephen Cobley et al.
millennia (i.e., data from 2000/01) and when again examining a similar context, Helsen
et al. (2012) noted that little had changed a decade later (i.e., 2010/11; Q1 = 31.9%, Q4 =
18.4%). Relative age and maturation bias continue to influence soccer player evalu-
ation and selection processes across the globe (see data from Spain – Mujika et al.,
2009; France – Delorme, Boiché, & Raspaud, 2010; Brazil – Costa, Albuquerque, &
Garganta, 2012; Germany – Skorski et al., 2016; and China – Li et al., 2020).
The robustness of developmental biases likely occurs due to the consistent applica-
tion of chronological age groupings, which don’t account for the often transient large
between-player maturity-related differences in anthropometry and physical fitness
characteristics (Philippaerts et al., 2006; Towlson et al., 2018). Relatively older play-
ers are often – although not always – the beneficiaries of early exposure to normative
growth curves (Malina et al., 2004, 2000), possessing superior anthropometrical di-
mensions (e.g., stature) and performance characteristics (e.g., power, speed, strength,
and endurance; Carling et al., 2012, 2009; Vaeyens et al., 2006). This explanation for
RA and maturational biases in participation and selection is commonly known as the
maturation-selection hypothesis (Cobley et al., 2009; Helsen et al., 2005). Jackson and
Comber (2020) also illustrated the cumulative probability of academy retention was
higher for relatively older players and correspondingly lower for relatively younger
players (i.e., Q4). Thus, relatively younger players are systematically disadvantaged,
and implicitly discriminated against in terms of de-selection, particularly in player
positions favouring enhanced maturity-related anthropometric and physiological
characteristics (Towlson et al., 2017). Such trends stand glaringly opposed to wider
knowledge and understanding of inter-player developmental differences being tempo-
rary; short-lived within the adolescence timespan; and with reducing/subsiding differ-
ences post-maturation (Till, Cobley, O’Hara, Chapman, & Cooke, 2013; Lovell et al.,
2015), suggesting biases also reflect TID inaccuracy.

Removing inter-player developmental differences and biases to improve

player evaluation
While RA and maturity-selection biases persist, practical attempts have been sug-
gested or implemented to remove or reduce their impact. These include the crea-
tion of shorter (e.g., 9-month) and/or rotating age group cut-off dates in other sports
contexts (i.e., ice-hockey – Boucher & Halliwell, 1991; Hurley, Lior, & Tracze, 2001),
along with proposals to group players based on stature and body mass classifications
­(Baxter-Jones, 1995; Musch & Grondin, 2001). In outlining a range of strategies, with
reference to team sports, Cobley (2016, 2017) promoted organisational policies target-
ing: (i) the delay of age time-points for structured competition; and relatedly, (ii) the
delay of age time-points when tiers of selective representation occur (i.e., post-matu-
ration). Targeted more specifically to youth soccer, Mann and van Ginneken (2017)
illustrated how the use of ‘RA ordered’ shirt-numbering could help prevent RA bias in
coach assessment and player evaluation. Furthermore, maturity status ‘bio-banding’
(see Cumming et al., 2018) – as opposed to age-grouping – has also been implemented
and evaluated in terms of impact upon player game involvement and coach evaluation
(see Bradley et al., 2019; Romann, Lüdin, & Born., 2020; Towlson et al., 2021). Mean-
while, developed in the sports contexts of track and field and swimming, ‘corrective
performance adjustments procedures’ (Romann & Cobley, 2015) also show potential
for soccer application.
 How player evaluation can be improved 353
Relative age and maturation-based corrective adjustment procedures
Corrective Adjustment Procedures (CAPs) refer to the process of purposefully re-
moving the underlying influence of either RA or maturation status differences from
age-group performance and player evaluation (Cobley, Abbott, Moulds, Hogan, &
Romann, 2020). Whether considering specific sport events (e.g., 100 m in athletics) or
as part of performance testing within a sport (e.g., soccer), objective measurements
(i.e., centimetres, seconds, etc.; Moesch, Elbe, Hauge, & Wikman, 2011) are used to
determine performance relative to others. Therefore, the relationships between RA
or maturation status and the performance measure can be directly plotted, and quan-
tified, with reference to multiple or single age-group cohorts. Subsequently, trendline
properties in these relationships are utilised to adjust individual performance to a
standardised RA (e.g., relatively oldest individual in an age-group) or maturation sta-
tus (e.g., individual with highest maturity status in an age-group) within the larger
cohort. Such adjusting generates a ‘correctively adjusted performance’ measure (e.g.,
sprint time in seconds); one which estimates performance based on a RA or matura-
tion-matched status across all individuals within a particular age-group.
CAPs were first utilised by Romann and Cobley (2015) in their examination of
7,000+ Swiss male junior athletic 60-m sprinters aged 8–15 years old. The relatively
older were expectedly over-represented as Q1 v Q4 ORs ranged between 2.11 and 1.55
at 9- to 15-year-olds, respectively. But, when examining the ‘Top 50–10%’ of sprint
times (i.e., not the whole sample), Relative age effect (RAE) size increased in each
age group (i.e., OR range = 2.61–5.03). To address these biases, the negative linear
trendline between decimal age and sprint performance was used (see Figure 21.1 in
Romann & Cobley, 2015). The expected difference in performance times from being 1
day to 1 year younger for each age group was calculated. Given sprinter decimal age
on the day of participation, each sprinter’s performance time was then adjusted rela-
tive to the oldest sprinter within an age-group, generating a ‘corrected performance
time’. Importantly, when re-examining the ‘Top 50–10%’ of ‘corrected sprint times’,
RAE inequalities were removed in almost all age-groups. Only in isolated younger
age-groups at specific performance levels (i.e., under 9 and 10 in ‘Top 50%’ of sprint
times) did typical RAEs remain, likely due to the higher frequency of relatively older
individuals volunteering to participate. Since, RA-based CAPs have been successfully
tested in youth males (Cobley et al., 2019) and females (Abbott et al., 2020) swimming
using substantive longitudinal sampling and more advanced analytical approaches.
More recently, Abbott et al. (2021) trialled the application of Maturation-based
(Mat-) CAPs on 700+ Australian male regional/state-level 100 m front-crawl swim-
mers aged 12–17 years. Abbott and colleagues first identified an overwhelming and
consistent over-representation of ‘early-maturing’ swimmers across all age-groups
and section levels (‘Top 50%’ & ‘Top 25%’ of swim times). Notably, there was a com-
plete absence of ‘late-maturing’ swimmers. Using the curvilinear relationship between
maturation status and swim performance, Abbott et al., adjusted individual swim
performance times relative to the most mature swimmer in each age-group. Then,
when maturity distributions of ‘corrected performance times’ were examined across
the ‘Top 50%’ and ‘25%’, maturity biases within the sample were removed. Thus, RA-
and Mat-CAPs provide a strategy to remove respective RA or maturational influences
from performance, prevent short-term (de-)selection biases, and increase the accuracy
of youth athlete evaluation.
354 Stephen Cobley et al.
RA- and Mat-CAPs can be applied to youth soccer. However, determining individual
performance in soccer is different to sprinting and swimming. Quantifying individual
performance within a team-game context is not easily isolated, with ­inter-dependence
with other ‘in-game’ team factors relative to the opposition necessary. Instead, indi-
vidual performance can be indirectly assessed via assessments deemed as facet compo-
nents of ‘in-game’ performance (e.g., physiological aerobic and anaerobic capacities,
sprint speed etc.). Therefore, to illustrate, we return to Towlson et al.’s (2018) data on
969 youth academy soccer players (aged 8–18 years). In Figure 21.1, the relationships
between chronological and RA with (a) agility and (b) 20 m MSFT performance are
plotted. The curvilinear trendlines along with 95% confidence intervals (shaded area
about the trendline) are shown.
Table 21.3 provides a summary of raw and correctively adjusted Agility performance
data for the ‘Top-five’ raw ranked players; five of the ‘relatively youngest’ players; and
five players with the lowest maturation status in the Under 13 academy sample. For
each of these player categories, raw rank; agility time; RA quartile; maturation status;
and maturation category (relative to normative population distributions) are shown.
In the ‘Top-five’ performers, the favourable benefit from earlier RA and/or advanced
maturation status is descriptively apparent. The next three columns provide the Rela-
tive Age-based (RA-CAPS) correctively adjusted agility time; percentage change from
the raw time; and adjusted rank, with the relatively oldest individual in the Under 13s
age-group used as the reference. The final three columns show the maturation-based
(Mat-CAPS) correctively adjusted agility time; percentage change from the raw time;
and adjusted rank with the player of the highest maturation status in the Under 13s
acting as the reference.
For the ‘Top-five’ performers, results identify minimal changes in time, percentage
change in time, or rank from RA-CAPs, though with slightly greater changes from
Mat-CAPs. These changes are somewhat expected, given the increased likelihood of
being relatively older and/or of maturation status to attain ‘Top-five’ performance (i.e.,
closer proximity to the reference player). Here, recognise the changes in rank order,
with some players descending out of the ‘Top-five’ (e.g., raw rank 5 - rank 15 following
Mat-CAPs). In other words, such cases could be potentially ‘over-valued’ in terms of
physical agility, due to advanced developmental differences.
When reviewing the five relatively youngest players, their comparatively slower
agility performance time and rank status relative to the ‘Top-five’ performers can be
immediately identified, along with the likelihood of lower maturation status. Follow-
ing RA-based corrective adjustments, a 3.1–3.3% reduction in performance time was
apparent, with increases in rank occurring (rank change range = 5–14). Similarly,
when reviewing five players of the lowest maturation status within the academy sam-
ple, firstly note the absence of ‘later maturing’ players in the academy. Second – and
expectedly – slower raw agility times and ranks are apparent. But, following Mat-
CAPS, individual performance times were reduced by 7.4–9.1%, with rank increases
ranging between 9–33. Interestingly, one player jumped from outside the ‘Top 20’ to
being ranked second, suggesting that some case players might be ‘under-valued’ or less
well recognised due to developmental differences. It is in relation to these case players,
where RA and Mat-CAPs could have positive, informative, value.
With reference to 20 m MSFT data, Table 21.4 similarly provides a summary of raw
and correctively adjusted results for Towlson et al.’s (2018) Under 13 sample. In the 20
m MSFT, the ‘Top-five’ performing players were not necessarily all relatively older or
Table 21.3 Agility test performance according to ‘top-five ranked’, ‘relatively youngest’, and ‘lowest maturation status’ youth academy football
players (under 13 years). Relative age and maturity status corrective adjustment procedures determined adjusted performance scores and
ranks based on the relatively oldest (*) and most mature male player (†), respectively

+ Age group Rank Agility Decimal Maturity Category RA adj. % Adj. Mat. adj. % Adj.
age status time* Change* rank* time† Change† rank†

Raw top-5 performers Under 13 1 9.63 12.59 –0.31 Early 9.49 –1.47 1 9.48 –1.59 5
Under 13 2 9.83 12.82 –1.09 Normative 9.77 –0.62 5 9.33 –5.09 1
Under 13 3 9.85 12.90 –0.85 Normative 9.82 –0.30 7 9.45 –3.96 3
Under 13 4 9.89 12.61 –0.76 E.Norm 9.75 –1.39 3 9.54 –3.50 7
Under 13 5 9.91 12.36 –0.42 Early 9.68 –2.28 2 9.71 –2.01 15
Relatively youngest Under 13 114 11.68 12.01 –1.69 Normative 11.32 –3.08 109
Under 13 86 11.02 12.01 –1.40 E.Norm 10.66 –3.26 74
Under 13 102 11.3 12.01 –1.59 Normative 10.94 –3.17 93
Under 13 70 10.86 12.01 –1.13 E.Norm 10.50 –3.30 56
Under 13 71 10.88 12.03 –1.61 Normative 10.53 –3.23 58
Lowest maturation Under 13 22 10.30 12.11 –1.96 Normative 9.36 –9.12 2
status
Under 13 108 11.56 12.23 –1.86 Normative 10.67 –7.64 99
Under 13 67 10.85 12.22 –1.84 Normative 9.97 –8.06 34
Under 13 95 11.15 12.34 –1.76 Normative 10.32 –7.44 66
Under 13 76 10.92 12.16 –1.73 Normative 10.10 –7.47 44
Reference 1* – Under 13 14 10.16 12.99 – 0.68 Normative
relatively oldest
Reference 2† – most Under 13 10 10.05 12.99 0.08 Early
mature

Notes: E. Norm = Early normative maturity timing based on sample-specific APHV M ± SD.
How player evaluation can be improved
355
 356

Table 21.4 Multi-stage fitness test performance according to ‘top-five’ ranked’, ‘relatively youngest’, and ‘lowest maturation status’ youth academy
football players (under 13 years). Relative age and maturity status corrective adjustment procedures determined adjusted performance
scores and ranks based on the relatively oldest (*) and most mature male player (†), respectively

Age group Rank Distance Decimal Maturity Category RA Adj. % Adj. Mat. Adj. % Adj.
age status distance* Change* rank* distance† Change† rank†

Raw Top-5 Under 13 1 2,400 12.96 –0.77 Normative 2,404 0.16 1 2,547 6.11 1
Performers
Stephen Cobley et al.

Under 13 2 2,280 12.91 –0.85 Normative 2,291 0.47 5 2,441 7.06 4

Under 13 3 2,260 12.55 –1.17 Normative 2,341 3.57 2 2,482 9.83 3
Under 13 4 2,260 12.44 –1.29 Normative 2,324 2.85 4 2,504 10.81 2
Under 13 5 2,200 12.12 –0.83 Early 2,327 5.78 3 2,357 7.13 6
Relatively Under 13 24 1,860 12.01 –1.69 Normative 2,004 7.75 15
Youngest
Under 13 72 1,480 12.01 –1.40 E.Norm 1,624 9.74 61
Under 13 101 1,260 12.01 –1.59 Normative 1,404 11.41 99
Under 13 40 1,720 12.01 –1.13 E.Norm 1,864 8.36 30
Under 13 46 1,640 12.03 –1.61 Normative 1,781 8.59 41
Lowest Under 13 70 1,500 12.11 –1.96 Normative 1,883 25.51 45
Maturation
Status
Under 13 56 1,540 12.23 –1.86 Normative 1,900 23.38 43
Under 13 56 1,540 12.22 –1.84 Normative 1,897 23.18 44
Under 13 90 1,380 12.34 –1.76 Normative 1,719 24.57 68
Under 13 37 1,740 12.16 –1.73 Normative 2,074 19.18 26
Reference 1* Under 13 79 1,460 12.99 – 0.68 Normative
- Relatively
Oldest
Reference 2† - Under 13 22 1,880 12.99 0.08 Early
Most Mature

Notes: E. Norm = Early normative maturity timing based on sample-specific APHV M ± SD.
 How player evaluation can be improved 357
earlier maturing, though advantages were still expectedly gained (see Figures 19.1a,
b and 19.2a, b). When RA-CAPs and Mat-CAPs were applied to the ‘Top-five’, there
were again lesser percentage changes in performance via RA-CAPs (0.2–5.8%) ver-
sus Mat-CAPs (6.1–10.8%), and there was minimal change in rank order. Nonetheless,
when reviewing results on the five relatively youngest players, their distance ran, and
rank was expectedly lower. Following RA-CAPs, their performances increased by an
estimated 7.7–11.4%, with corresponding rank improvements ranging between 2 and 11
(note: one case rank changed from 24 to 15). When Mat-CAPs were applied to the five
players of the lowest maturation status, their correctively adjusted estimated distance
ran increased by 19.2–25.5%, with rank order changes ranging between 11 and 25.

Future directions and conclusions

If advanced inter-individual developmental differences are contra-indicators of youth
soccer talent and player evaluation procedures, and CAPs can be considered as a via-
ble strategy to implement, then several future directions can be recommended. Prin-
cipally, soccer organisations and their practitioners (e.g., youth academy managers,
coaches, scouts) should measure (and track) RA and maturity status. These indices
should also be integrated within player evaluation and (de-)selection processes. To fa-
cilitate a more objective approach, with inter-player developmental differences consid-
ered, this chapter recommends assessing relationships between RA and/or maturation
status with physical performance indices, and then apply RA- or Mat-CAPs. Never-
theless, whilst pitched as beneficial, existing RA- or Mat-CAP studies also highlight
caution.
Within soccer, CAPs appear best placed to be applied as part of fitness testing
or physiological assessments. As CAPs estimate an adjusted performance value,
measurement accuracy is paramount. Therefore, the accuracy and limitations of
­somatic-based maturation estimates along with the precision (or error) for each per-
formance measurement must be considered (see e.g., Mills, Baker, Pacey, Wollin, &
Drew (2017). The application of the most accurate methods - where feasible – is recom-
mended. Furthermore, a substantially large reference sample must be acquired, with
consistent data across (relative) age and/or maturation status necessary to generate ac-
curate reference trendlines and regression parameters (Cobley et al., 2020). To address
measurement concerns; non-linearity in maturation-associated growth trajectories
(i.e., higher or lower growth tempo in short-time periods); and, the need for validity in
correctively adjusted performance estimates, regular testing and CAPs application is
recommended (e.g., two to three times per year; Towlson et al., in press). Finally, the
respective demands of soccer physiological tests should also be considered. As tests
have different underpinning (and inter-acting) anthropometric, physiological, move-
ment coordination (technical) skill and biomechanical demands, the degree to which
developmental differences (also at a given age) influences performance should be con-
sidered. Such variation will partially explain why RA- and Mat-CAPs may lead to
greater or lesser changes in performance adjustment (e.g., see agility vs 20-m MSFT).
Change estimates are also expected to vary according to the age and sex of the samples
examined.
If precautionary messages are addressed, we predict corrected performance indices
will help enable practitioners to: (i) better evaluate physical performance attainment
relative to others; (ii) determine which other physiological, biomechanical, technical,
358 Stephen Cobley et al.
and psychological factors may be accounting for better or worse performance relative
to others; (iii) identify differing developmental trajectories between players; and (iv)
identify necessary training interventions (e.g., strength and conditioning) to optimise
player development. If achieved, the accuracy of player evaluation in the short term
will be improved, which may subsequently contribute toward achieving greater effec-
tiveness in long-term player development programmes.

References
Abbott, S., Hogan, C., Castiglioni, M. T., Yamauchi, G., Mitchell, L. J., Salter, J., ... & Co-
bley, S. (2021). Maturity-related developmental inequalities in age-group swimming: The
testing of `Mat-CAPs’ for their removal. Journal of Science and Medicine in Sport, 24(4),
397–404.
Abbott, S., Moulds, K., Salter, J., Romann, M., Edwards, L., & Cobley, S. (2020). Testing the
application of corrective adjustment procedures for removal of relative age effects in female
youth swimming. Journal of Sports Sciences, 38(10), 1077–1084. https://doi.org/10.1080/0264
0414.2020.1741956
Augste, C., & Lames, M. (2011). The relative age effect and success in German elite U-17 soccer
teams. Journal of Sports Sciences, 29(9), 983–987. http://doi.org/10.1080/02640414.2011.574719
Baker, J., Cobley, S., & Fraser‐Thomas, J. (2009). What do we know about early sport specialisa-
tion? Not much! High Ability Studies, 20(1), 77–89. https://doi.org/10.1080/13598130902860507
Barnsley, R. H., Thompson, A. H., & Legault, P. (1992). Family planning: football style. The
relative age effect in football. International Review for the Sociology of Sport, 27(1), 77–87.
Baxter-Jones, A. D. (1995). Growth and development of young athletes. Sports Medicine, 20(2),
59–64.
Boucher, J., & Halliwell, W. (1991). The Novem system: a practical solution to age grouping.
Canadian Association for Health, Physical Education, and Recreation, 57(1), 16–20.
Bradley, B., Johnson, D., Hill, M., McGee, D., Kana-Ah, A., Sharpin, C., Sharp, P., Kelly, A.,
Cumming, S. P., & Malina, R. M. (2019, Aug). Bio-banding in academy football: player’s
perceptions of a maturity matched tournament. Annals of Human Biology, 46(5), 400–408.
https://doi.org/10.1080/03014460.2019.1640284
Carrascosa, A., Yeste, D., Moreno-Galdó, A., Gussinyé, M., Ferrández, Á., Clemente, M., &
Fernández-Cancio, M. (2018). Pubertal growth of 1,453 healthy children according to age at
pubertal growth spurt onset: the Barcelona longitudinal growth study. Anales de Pediatria,
89(3), 144–152. https://doi.org/10.1016/j.anpedi.2017.11.018
Carling, C., Le Gall, F., Reilly, T., & Williams, A. M. (2008). Do anthropometric and fit-
ness characteristics vary according to birth date distribution in elite youth academy soc-
cer players? Scandinavian Journal of Medicine and Science in Sports, 19(1), 3–9. http://doi.
org/10.1111/j.1600-0838.2008.00867.x
Carling, C., Le Gall, F., Reilly, T., & Williams, A. (2009). Do anthropometric and fitness
characteristics vary according to birth date distribution in elite youth academy soccer
players? Scandinavian Journal of Medicine and Science in Sports, 19(1), 3–9. https://doi.
org/10.1111/j.1600-0838.2008.00867.x
Carling, C., Le Gall, F., & Malina, R. M. (2012). Body size, skeletal maturity, and functional
characteristics of elite academy soccer players on entry between 1992 and 2003. Journal of
Sports Sciences, 30(15), 1683–1693. https://doi.org/10.1080/02640414.2011.637950
Cobley, S. (2017). Growth and Maturation in Athlete Development: An Educational Resource for
Sporting Organisations (pp. 1–29). Canberra, Australia: Australian Institute of Sport.
Cobley, S. (2016). Talent identification and development in youth sport. In K. Green & A. Smith
(Eds.), Routledge Handbook of Youth Sport (pp. 476–491). Abingdon: Routledge.
 How player evaluation can be improved 359
Cobley, S., & Till, K. (in press). Talent identification, development, and the young rugby player.
In C. Twist & Paul Worsfold (Eds.), The Science of Rugby (2nd Ed.). Abingdon: Routledge.
Cobley, S., Baker, J., & Chorer, J. (2012). Identification and development of sport talent: a brief
introduction to a growing field of research and practice. In J. Baker, S. Cobley, & J. Schorer
(Eds.), Talent Identification and Development in Sport: International Perspectives (pp. 1–10).
London: Routledge (Taylor & Francis).
Cobley, S. P., Baker, J., Wattie, N., & McKenna, J. (2009). Annual age-grouping and athlete
development. Sports Med, 39(3), 235–256. https://doi.org/10.2165/00007256-200939030-00005
Cobley, S., Abbott, S., Eisenhuth, J., Salter, J., McGregor, D., Romann, M. (2019). Remov-
ing relative age effects from youth swimming: the development and testing of corrective ad-
justment procedures. Journal of Science and Medicine in Sport, 22(6), 735–740. https://doi.
org/10.1016/j.jsams.2018.12.013
Cobley, S., Abbott, S., Moulds, K., Hogan, C., Romann, M. (2020). Re-balancing the relative
age effect scales: meta-analytical trends, causes, and corrective adjustment procedures as a
solution. In J. C. Dixon, S. Horton, L. Chittle, & J. Baker (Eds.), Relative Age Effects in Sport
International Perspectives (pp. 136–153). New York: Routledge.
Cobley, S., Romann, M., Javet, M., Abbott, S., & Lovell, R. (2020). The shifting sands of time: mat-
uration and athlete development. In J. Baker, S. Cobley, & J. Schorer (Eds.), Talent Identification
and Development in Sport International Perspectives (2nd Ed.), (pp. 81–98). Abingdon: Routledge
(Taylor & Francis) Abingdon, Oxon, United Kingdom: Routledge (Taylor & Francis).
Costa, I. T. D., Albuquerque, R. M., & Garganta, J. (2012). Relative age effect in Brazilian
soccer players: a historical analysis. International Journal of Performance Analysis in Sport,
12(3), 563–570. https://doi.org/10.1080/24748668.2012.11868619
Cumming, S. P., Brown, D. J., Mitchell, S., Bunce, J., Hunt, D., Hedges, C., Crane, G., Gross,
A., Scott, S., Franklin, E., Breakspear, D., Dennison, L., White, P., Cain, A., Eisenmann,
J. C., & Malina, R. M. (2018). Premier league academy soccer players’ experiences of com-
peting in a tournament bio-banded for biological maturation. Journal Sports Science, 36(7),
757–765. https://doi.org/10.1080/02640414.2017.1340656
Deprez, D. N., Fransen, J., Lenoir, M., Philippaerts, R. M., & Vaeyens, R. (2015a). A retrospec-
tive study on anthropometrical, physical fitness, and motor coordination characteristics that
influence dropout, contract status, and first-team playing time in high-level soccer players
aged eight to eighteen years. Journal of Strength and Conditioning Research, 29(6), 1692–1704.
http://doi.org/10.1519/JSC.0000000000000806
Deprez, D., Buchheit, M., Fransen, J., Pion, J., Lenoir, M., Philippaerts, R. M., & Vaeyens, R.
(2015b). A longitudinal study investigating the stability of anthropometry and soccer-specific
endurance in pubertal high-level youth soccer players. Journal of Sports Science and Medi-
cine, 14(2), 418–426.
Deprez, D., Coutts, A., Fransen, J., Deconinck, F., Lenoir, M., Vaeyens, R., & Philip-
paerts, R. (2013). Relative age, biological maturation and anaerobic characteristics in elite
youth soccer players. International Journal of Sports Medicine, 34(10), 897–903. http://doi.
org/10.1055/s-0032-1333262
Delorme, N., Boiché, J., & Raspaud, M. (2010). Relative age and dropout in French male soccer.
Journal of Sports Sciences, 28(7), 717–722. https://doi.org/10.1080/02640411003663276
Emmonds, S., Morris, R., Murray, E., Robinson, C., Turner, L., & Jones, B. (2017). The influ-
ence of age and maturity status on the maximum and explosive strength characteristics of
elite youth female soccer players. Science and Medicine in Football, 1(3), 209–215. https://doi.
org/10.1080/24733938.2017.1363908
Fransen, J., Bennett, K. J. M., Woods, C. T., French-Collier, N., Deprez, D., Vaeyens, R., &
Lenoir, M. (2017). Modelling age-related changes in motor competence and physical fitness
in high-level youth soccer players: implications for talent identification and development.
Science and Medicine in Football, 1(3), 203–208. http://doi.org/10.1080/24733938.2017.1366039
360 Stephen Cobley et al.
Granados, A., Gebremariam, A., & Lee, J. M. (2015). Relationship between timing of peak
height velocity and pubertal staging in boys and girls. Journal of Clinical Research inPediatric
Endocrinology, 7(3), 235–237. https://doi.org/10.4274/jcrpe.2007
Güllich, A. (2014). Selection, de-selection and progression in German football talent promo-
tion. Eur Journal of Sport Sci, 14(6), 530–537. https://doi.org/10.1080/17461391.2013.858371
Güllich, A. & Cobley, S. (2017). On the efficacy of talent identification and talent development
programmes. In J. Baker, S. Cobley, J. Schorer, & N. Wattie (Eds.), Routledge Handbook of
Talent Identification and Development in Sport (pp. 80–98). Abingdon: Routledge. (Taylor &
Francis).
Güllich, A. & Emrich, E. (2012). Individualistic and collectivistic approach in athlete support
programmes in the German high-performance sport system. European Journal of Sport and
Society, 9, 243–268. https://doi.org/10.1080/16138171.2012.11687900
Helsen, W. F., Baker, J., Michiels, S., Schorer, J., Van Winckel, J., & Williams, A. M. (2012).
The relative age effect in European professional soccer: did ten years of research make any
difference? Journal of Sports Sciences, 30(15), 1665–1671. https://doi.org/10.1080/02640414.20
12.721929
Helsen, W. F., Van Winckel, J., & Williams, A. M. (2005). The relative age effect in youth
soccer across Europe. Journal of Sports Sciences, 23(6), 629–636. https://doi.org/10.1080/
02640410400021310
Helsen, W. F., Starkes, J. L., & Van Winckel, J. (1998). The influence of relative age on success
and dropout in male soccer players. American Journal of Human Biology, 10(6), 791–798.
https://doi.org/10.1002/(SICI)1520-6300(1998)10:6%3C791::AID-AJHB10%3E3.0.CO;2-1
Hurley, W., Lior, D., & Tracze, S. (2001). A proposal to reduce the age discrimination in Cana-
dian minor hockey. Can Public Policy – Analyse de Politiques, 27(1), 65–75.
Jackson, R. C., & Comber, G. (2020). Hill on a mountaintop: a longitudinal and cross-sectional
analysis of the relative age effect in competitive youth football. Journal of Sports Sciences,
38(11–12), 1352–1358. https://doi.org/10.1080/02640414.2019.1706830
Johnson, A., Doherty, P. J., & Freemont, A. (2009). Investigation of growth, development, and
factors associated with injury in elite schoolboy footballers: prospective study. BMJ (Clinical
Research Ed), 338, b490. https://doi.org/10.1136/bmj.b490
Kelly, A., Winer, K. K., Kalkwarf, H., Oberfield, S. E., Lappe, J., Gilsanz, V., & Zemel, B. S.
(2014). Age-based reference ranges for annual height velocity in US children. The Journal
of Clinical Endocrinology & Metabolism, 99(6), 2104–2112. https://doi.org/10.1210/jc.20134455
Lefevre, J., Beunen, G., Steens, G., Claessens, A., & Renson, R. (2009). Motor performance
during adolescence and age thirty as related to age at peak height velocity. Annals of Human
Biology, 17(5), 423–435. http://doi.org/10.1080/03014469000001202
Léger, L. A., & Lambert, J. (1982). A maximal multistage 20-m shuttle run test to predict VO2
max. European Journal of Applied Physiology and Occupational Physiology, 49(1), 1–12.
Li, Z., Mao, L., Steingröver, C., Wattie, N., Baker, J., Schorer, J., & Helsen, W. F. (2020). Rel-
ative age effects in elite Chinese soccer players: implications of the ‘one-child’ policy. PloS
ONE, 15(2), e0228611. https://doi.org/10.1371/journal.pone.0228611
Lovell, R., Towlson, C., Parkin, G., Portas, M., Vaeyens, R., & Cobley, S. (2015). Soccer player
characteristics in English lower-league development programmes: the relationships between
relative age, maturation, anthropometry and physical fitness. PLoS ONE, 10(9), e0137238.
http://doi.org/10.1371/journal.pone.0137238
Lovell, R., Fransen, J., Ryan, R., Massard, T., Cross, R., Eggers, T., & Duffield, R. (2019).
Biological maturation and match running performance: a national football (soccer) fed-
eration perspective. Journal of Science and Medicine in Sport, 22(10), 1139–1145. http://doi.
org/10.1016/j.jsams.2019.04.007
Malina, R.M. (1994). Physical growth and biological maturation of young athletes. Exercise
and Sport Sciences Reviews, 22, 280–284.
 How player evaluation can be improved 361
Malina, R. M., Reyes, M. P., Eisenmann, J., Horta, L., Rodrigues, J., & Miller, R. (2000).
Height, mass and skeletal maturity of elite Portuguese soccer players aged 11–16 years. Jour-
nal of Sports Sciences, 18(9), 685–693. https://doi.org/10.1080/02640410050120069
Malina, R. M., Bouchard, C., & Bar-Or, O. (2004). Growth, Maturation, and Physical Activity.
Champaign: Human Kinetics Publishers.
Mann, D. L., & van Ginneken, P. J. (2017). Age-ordered shirt numbering reduces the selection
bias associated with the relative age effect. Journal of Sports Sciences, 35(8), 784–790. https://
doi.org/10.1080/02640414.2016.1189588
Mills, K., Baker, D., Pacey, V., Wollin, M., & Drew, M. K. (2017). What is the most accurate
and reliable methodological approach for predicting peak height velocity in adolescents?
A systematic review. Journal of Science and Medicine in Sport, 20(6), 572–577. https://doi.
org/10.1016/j.jsams.2016.10.012
Moesch, K., Elbe, A. M., Hauge, M. L., & Wikman, J. M. (2011). Late specialisation: The key
to success in centimeters, grams, or seconds (cgs) sports. Scandinavian Journal of Medicine &
Science in Sports, 21(6), 282–290. https://doi.org/10.1111/j.1600-0838.2010.01280.x
Morris, R., Emmonds, S., Jones, B., Myers, T. D., Clarke, N. D., Lake, J., Ellis, M., Singleton,
D., Roe, G., & Till, K. (2018). Seasonal changes in physical qualities of elite youth soccer
players according to maturity status: comparisons with aged matched controls. Science and
Medicine in Football, 2(4), 272–280. https://doi.org/10.1080/24733938.2018.1454599
Mujika, I., Vaeyens, R., Matthys, S. P., Santisteban, J., Goiriena, J., & Philippaerts, R. (2009).
The relative age effect in a professional football club setting. Journal of Sports Sciences,
27(11), 1153–1158. https://doi.org/10.1080/02640410903220328
Müller, L., Gonaus, C., Perner, C., Müller, E., & Raschner, C. (2017). Maturity status influences
the relative age effect in national top level youth alpine ski racing and soccer. PLoS ONE,
12(7), e0181810. http://doi.org/10.1371/journal.pone.0181810
Musch, J., & Grondin, S. (2001). Unequal competition as an impediment to personal develop-
ment: a review of the relative age effect in sport. Developmental Review, 21(2), 147–167. https://
doi.org/10.1006/drev.2000.0516
Patel, R., Nevill, A., Cloak, R., Smith, T., & Wyon, M. (2019). Relative age, maturation, an-
thropometry and physical performance characteristics of players within an elite youth foot-
ball academy. International Journal of Sports Science & Coaching, 14(6), 714–725. http://doi.
org/10.1177/1747954119879348
Patel, R., Nevill, A., Smith, T., Cloak, R., & Wyon, M. (2020). The influence of birth quartile,
maturation, anthropometry and physical performances on player retention: observations
from an elite football academy. International Journal of Sports Science & Coaching, 15(2),
121–134. http://doi.org/10.1177/1747954120906507
Pearson, D. T., Naughton, G. A., & Torode, M. (2006). Predictability of physiological testing
and the role of maturation in talent identification for adolescent team sports. Journal of Sci-
ence and Medicine in Sport, 9(4), 277–287. http://doi.org/10.1016/j.jsams.2006.05.020
Philippaerts, R. M., Vaeyens, R., Janssens, M., Van Renterghem, B., Matthys, D., Craen, R.,
Bourgois, J., Vrijens, J., Buenen, G., & Malina, R.M. (2006). The relationship between peak
height velocity and physical performance in youth soccer players. Journal of Sports Sciences,
24(3), 221–230. http://doi.org/10.1080/02640410500189371
Read, P. J., Oliver, J. L., De Ste Croix, M. B., Myer, G. D., & Lloyd, R. S. (2016). The scien-
tific foundations and associated injury risks of early soccer specialisation. Journal of Sports
Sciences, 34(24), 2295–2302. https://doi.org/10.1080/02640414.2016.1173221
Reilly, T., Williams, A. M., Nevill, A., & Franks, A. (2000). A multidisciplinary approach
to talent identification in soccer. Journal of Sports Sciences, 18(9), 695–702. https://doi.
org/10.1080/02640410050120078
Romann, M., Lüdin, D., & Born, D. P. (2020). Bio-banding in junior soccer players: a pilot
study. BMC Research Notes, 13(1), 240. https://doi.org/10.1186/s13104-020-05083-5
362 Stephen Cobley et al.
Romann, M., & Cobley, S. (2015). Relative age effects in athletic sprinting and corrective ad-
justments as a solution for their removal. PLoS ONE, 10(4), e0122988. https://doi.org/10.1371/
journal.pone.0122988
Semenick, D. (1990). Tests and measurements: the T-test. Strength & Conditioning Journal,
12(1), 36–37.
Simpkin, A. J., Sayers, A., Gilthorpe, M. S., Heron, J., & Tilling, K. (2017). Modelling height in
adolescence: A comparison of methods for estimating the age at peak height velocity. Annals
of Human Biology, 44(8), 715–722. https://doi.org/10.1080/03014460.2017.1391877
Skorski, S, Skorski, S., Faude, O., Hammes, D., & Meyer, T. (2016). The relative age effect
in German elite youth soccer: implications for a successful career. International Journal of
Sports Physiology and Performance, 11(3), 370–376. http://doi.org/10.1123/ijspp.2015-0071.
Smith, K., Weir, P., Till, K., Romann, M., Cobley, S. (2018). Relative age effects across and
within female sport contexts: a systematic review and meta-analysis. Sports Medicine, 48(6),
1451–1478. https://doi.org/10.1007/s40279-018-0890-8
Till, K., Cobley, S., O’Hara, J., Chapman, C., Cooke, C. (2013). A longitudinal evaluation of
anthropometric and fitness characteristics in junior rugby league players considering playing
position and selection level. Journal of Science and Medicine in Sport, 16(5), 438–443. https://
doi.org/10.1016/j.jsams.2012.09.002
Towlson, C., Cobley, S., Midgley, A. W., Garrett, A., Parkin, G., & Lovell, R. (2017). Relative
age, maturation and physical biases on position allocation in elite youth soccer. International
Journal of Sports Medicine, 38(3), 201–209. http://doi.org/10.1055/s-0042-119029
Towlson, C., Cobley, S., Parkin, G., & Lovell, R. (2018). When does the influence of maturation
on anthropometric and physical fitness characteristics increase and subside? Scandinavian
Journal of Medicine and Science in Sports, 28(8), 1946–1955. http://doi.org/10.1111/sms.13198
Towlson, C., Salter, J., Ade, J. D., Enright, K., Harper, L. D., Page, R. M., & Malone, J. J.
(2020). Maturity-associated considerations for training load, injury risk, and physical per-
formance within youth soccer: One size does not fit all. Journal of Sport and Health Science.
https://doi.org/10.1016/j.jshs.2020.09.003
Towlson, C., MacMaster, C., Gonçalves, B., Sampaio, J., Toner, J., MacFarlane, N., ... & Abt,
G. (2021). The effect of bio-banding on physical and psychological indicators of talent identi-
fication in academy soccer players. Science and Medicine in Football, 5(4), 280–292.
Towlson, C., Salter, J., Ade, J. D., Enright, K., Harper, L. D., Page, R. M., & Malone, J. J. (2021).
Maturity-associated considerations for training load, injury risk, and physical performance
in youth soccer: One size does not fit all. Journal of Sport and Health Science, 10(4), 403–412.
Vaeyens, R., Philippaerts, R. M., & Malina, R. M. (2005). The relative age effect in soccer: a
match-related perspective. Journal of Sports Sciences, 23(7), 747–756. http://doi.org/10.1080/
02640410400022052
Vaeyens, R., Lenoir, M., Williams, A. M., & Philippaerts, R. M. (2008). Talent identifica-
tion and development programmes in sport. Sports Medicine, 38(9), 703–714. https://doi.
org/10.2165/00007256-200838090-00001
Vaeyens, R., Malina, R. M., Janssens, M., Van Renterghem, B., Bourgois, J., Vrijens, J., &
Philippaerts, R. M. (2006). A multidisciplinary selection model for youth soccer: the Gh-
ent youth soccer project. British Journal of Sports Medicine, 40(11), 928–934. http://dx.doi.
org/10.1136/bjsm.2006.029652
Williams, A. M., & Reilly, T. (2000). Talent identification and development in soccer. Journal of
Sports Sciences, 18(9), 657–667. https://doi.org/10.1080/02640410050120041
Winand, M., (2010). The global sporting arms race. An international comparative study on
sports policy factors leading to international sporting success (SPLISS). European Sport
Management Quarterly, 10(5), 613–615, https://doi.org/10.1080/16184742.2010.524242
22 Talent identification and talent promotion
Arne Güllich and Paul Larkin

Introduction
Many soccer federations and professional clubs worldwide have established talent
identification (­TID) and talent promotion programmes (­TPPs) at local, regional, and
national levels. The most common TPPs are national and regional u ­ nder-​­age selection
squads (­typically ages ­12–​­19 years) and the youth soccer academies of professional
clubs (­starting at 8­ –​­14, operating up to 19 years). Youth academies operate almost year
around and provide ­day-­​­­to-​­day training and competition for players, whereas ­under-​
­age national and regional selection teams typically gather for training camps and tour-
naments for several weeks annually. In Germany, there is an additional programme,
“­talent bases,” where regional federations offer practice sessions on the weekend to
players who are considered promising but are not among the ~10,000 players selected
for an academy. The talent identification and talent promotion processes of these pro-
grammes are the focus of this chapter.
The aim of TPPs is to identify and select the most promising talents and promote
their ­long-​­term performance development into adulthood. TPPs provide extensive re-
sources and interventions to youth players (­Ford et al., 2020; Larkin & Reeves, 2018;
Larsen et al., 2013, 2020). These include training and competing with equals who have
a similar performance level; participation in national and international leagues and
tournaments; expanded training volumes; educated, professional f­ull-​­time and ­part-​
t­ ime coaches; ­h igh-​­profile facilities and equipment; support staff providing physiother-
apy, sports medicine, performance diagnostics, nutritional counselling, psychological
support, and academic assistance; school timetables adjusted to the soccer schedule;
residency; and transportation. The common belief is that providing a ­h igh-​­profile
training environment with a multitude of resources will facilitate the progression of
promising talents into the highest professional competitions.

Key terms
A soccer talent is a young player during the early periods of their athletic career who
possesses the potential to develop into an elite performer in adulthood (­Güllich &
­Cobley, 2017; Johansson & Fahlén, 2017). Following recent conceptions of talent de-
velopment (­see Fransen & Güllich, 2018; Sarmento et al., 2018), one’s potential is cul-
tivated and realised through a ­multi-​­year t­ ask-​­related training process. This training
process and its effectiveness are moderated by physiological (­e.g., responsiveness to
stimuli and load tolerance), psychological (­e.g., learning, motivation, ­self-​­regulation,

DOI: 10.4324/9781003148418-27
364 Arne Güllich and Paul Larkin
and coping), and environmental factors (­e.g., opportunities, facilities, teammates,
TPPs, family, and school). Accordingly, “­ talent” is considered as a ­ task-­​­­
person-​
­environment concept, rather than just a person concept. Talent indicators can thus be
in the person and their interaction with the task and the environment.
Talent search comprises the scouting activities to discover previously unknown tal-
ents. TID is the identification of talents and distinction from ­non-​­talents; that is, the
distinction of young players who possess a greater or lower potential for future, adult
high performance. Talent selection is the selection of players for admittance to a TPP.
A TPP is designed to promote the ­long-​­term performance development of selected
talents. Scholars and practitioners have used different terms for these programmes.
Some labelled them “­talent development programmes.” We refrain from using this
term because talents may develop within and outside these programmes. Further-
more, some used “­TID” as an umbrella term referring to all the processes of search-
ing, identifying, selecting, and promoting talents. We suggest that the central purpose
of these programmes is to promote talent development, where TID is instrumental to
talent selection and selection is instrumental to talent promotion.
In the following sections, we first review the available evidence on TID processes,
including coaches’ perspectives and the prognostic validity of potential talent indi-
cators, and then review TPPs, including the effects of early TPP involvement and the
functioning of TPPs.

Talent identification and selection

Coaches in TPPs make annual selection decisions among two populations: (­i) the se-
lection among new applicants for admittance to the TPP, which may include players
preselected and suggested by scouts; and (­ii) the selection among TPP participants
who are dismissed or retained for the next season. As reflected in Williams and Reilly’s
(­2000) model of soccer talent (­updated by Williams et al., 2020), coaches may con-
sider the overall playing performance of players and/­or certain potential talent indica-
tors, including physique (­e.g., height and weight), physical abilities (­e.g., speed, agility,
power, endurance, and flexibility), p ­ erceptual-​­technical b
­ all-​­control skills (­e.g., first
touch, dribbling, passing, and shooting), ­p erceptual-​­tactical skills (­e.g., orientation,
anticipation, and situational ­decision-​­making), and psychological and psychosocial
characteristics (­e.g., motivation, ­self-​­regulation, and social skills). These may be as-
sessed by coaches viewing players in matches, training sessions, or invited trials (­e.g.,
invited training sessions or games; “­­open-​­door talent days”) either with or without
standardised tests of potential talent indicators.

Coach perspectives on TID

Researchers have recently started to investigate the factors coaches consider when
making talent identification and selection decisions (­Larkin et al., 2020). To under-
stand the nuanced thought processes of coaches during this process, researchers used
qualitative, descriptive designs, such as interviewing or concurrent verbal reporting
of experienced soccer coaches (­Christensen, 2009; Larkin & O’Connor, 2017; Lund &
Söderström, 2017; Reeves et al., 2019). Coaches value a range of player characteris-
tics including ­p erceptual-​­technical skills (­e.g., first touch; dribbling; passing accuracy;
­one-­​­­versus-​­one skill; and ball control under pressure); ­p erceptual-​­tactical skills (­e.g.,
 Talent identification and talent promotion 365
­ ecision-​­making; game awareness; game intelligence; ability to read the play; and
d
anticipate ­game-​­play); and psychological attributes (­e.g., character; positive attitude;
drive to succeed; winning mindset; willingness to learn; and coachability) as the most
important traits when assessing talent (­Bergkamp et al., 2022; Christensen, 2009; Lar-
kin & O’Connor, 2017; Lund & Söderström, 2017; Reeves et al., 2019; Saether, 2014;
Williams et al., 2020). Lund and Söderström (­2017) added that knowledge of current
elite player qualities and the values and belief system of a club are also important
factors.
It should be acknowledged, however, that these findings can only report the con-
structs coaches verbalise. Their selection decisions partly rest on some intuitive “­g ut
instinct” (­Christensen, 2009; Roberts et al., 2019), and there is perhaps further tacit
knowledge that is inaccessible. Furthermore, for several constructs, the relevant stud-
ies did not describe what exactly they are, how they manifest, and what exactly the
coach evaluates, for example, “­character,” “­positive attitude,” “­drive to succeed,”
“­w inning mindset,” “­w illingness to learn,” “­game awareness,” “­game intelligence,”
and “­coachability.” In addition, the objectivity and i­nter-​­individual consistency of
player assessment by coaches were mostly not reported. However, Jokuschies et al.
(­2017) found that different coaches consider different aspects of a player, which ques-
tions the objectivity of these evaluations.
Quantitative, ­cross-​­sectional studies compared players selected (­i.e., ­talent-​­identified)
or dismissed by TPPs, thereby describing player characteristics that predict the likeli-
hood to be selected. It has generally been found that selected players were biologically
more mature, taller, faster, and stronger, and showed better p ­ erceptual-​­technical ­ball-​
c­ ontrol skills, and ­perceptual-​­tactical skills, than ­non-​­selected counterparts; they also
differed in several psychological characteristics (­see Murr et al., 2018; Sarmento et al.,
2018; Williams et al., 2020). However, being selected does not necessarily imply being
talented, and as ­cross-​­sectional studies do not consider future performance develop-
ment, they cannot evaluate TID and the validity of selection decisions. Investigating
the prognostic validity requires ­multi-​­year longitudinal prospective studies.

Prognostic validity of potential talent indicators

The critical quality criterion of TID procedures is their prognostic validity for which
the central research question is: To what extent do individual differences in talent
indicators at the time of TID procedures predict individual differences in later, adult
performance? That is, did ­h igher-​­performing adult players show greater values of
childhood/­adolescent talent indicators than l­ ower-​­p erforming adult players did? These
questions are investigated by ­long-​­term longitudinal studies that determine potential
talent indicators of players during childhood/­adolescence and their playing level as
adults.
Youth players’ current overall playing performance may be relevant in two regards.
First, coaches seek to have strong youth players in their team. Second, coaches and
scouts search for talents in higher leagues, cups, and tournaments rather than lower
ones. Therefore, playing in high youth competitions facilitates the chance to be seen
by TPP coaches and scouts.
The extent to which higher youth playing performance correlates with higher adult
playing performance, to our knowledge, has not been reported in the literature. Neverthe-
less, the following data allow for relevant inferences. The annual player turnover within
366 Arne Güllich and Paul Larkin
TPPs suggests that 43% of u ­ nder-​­age ­national-​­team players are replaced with new, exter-
nal players every year. Furthermore, of all ­national-​­level youth players, 37.7% continued
to play at a national level 2 years later, 9.2% after 5 years, and only 4.3% after 8 years (­see
­references in Table 22.1). Out of 636 ­U16–​­U21 national team players, 37 (­5.8%) went on to
play in the senior national team (­Schroepf & Lames, 2017); of 283 U15 national team play-
ers, one (­0.4%) achieved a nomination for the senior national team (­Güllich, 2014). Likewise,
only 5.9% of all senior national team players had played in the U15 national team and 26.5%
in the U19 national team. Furthermore, of all German first Bundesliga players, only 10.1%
had played in the highest U15 division, and 37.9% in the highest U19 division (­Güllich, 2014).
­Twenty-​­seven studies published between 2009 and 2021 have investigated the prog-
nostic validity of potential talent indicators longitudinally (­see ­Table 22.1). They con-
sidered player evaluations by coaches, physique (­i.e., height, weight, and % body fat),
physical abilities (­i.e., speed, agility, power, endurance, and flexibility), ­p erceptual-​
t­echnical skills (­i.e., dribbling, passing, shooting, and juggling), ­p erceptual-​­tactical
skills (­i.e., recognition and anticipation of game situations, orientation, and situational
­decision-​­making), psychological and psychosocial characteristics (­i.e., ­self-​­concept,
motivation, ­self-​­regulation, and parental support), and multidimensional approaches
combining various predictors, using linear and n ­ on-​­linear analyses.
All studies were from W ­ est-​­European countries (­Austria, Belgium, Finland, France,
Germany, the Netherlands, Norway, Portugal, Switzerland, and the UK). T ­ wenty-​­five
studies involved male players and two studies female players. Ten investigations in-
volved baseline samples of ­under-​­age national team or youth academy players while
the other 17 involved lower-level or more heterogeneous samples involving general
primary pupils or youth players from regional teams, bases, or clubs. Five studies
recorded potential talent indicators at baseline ages up to 10 years, 21 studies at ­11–​­14
years, and 16 studies at 15 years and older (­the sum exceeds the number of studies
because several studies considered various ages). Twenty studies involved relatively
short prediction periods of up to 4 years, whereas 18 studies included predictions over
5 or more years. Fourteen investigations considered playing performance within youth
age groups, with eight studies using the ­junior-­​­­to-​­senior transition (­e.g., ­U18–​­U21),
and five investigations considered adult peak playing performance. Of the latter, four
studies used rather relaxed success criteria, such as obtaining a professional contract
or being on the roster of ­1st–​­3rd or ­1st–​­5th league clubs.
A central finding is that the existing evidence on the prognostic validity of potential
soccer talent indicators is characterised by great heterogeneity and inconsistency. For
each of the potential talent indicators, some studies reported positive predictive effects
on later playing performance, whereas these findings were countered by other studies
(­or the same study).
­Table 22.2 summarises quantitative findings on the prognostic validity of the po-
tential talent indicators in terms of the range of reported effects and s­ ample-​­weighted
mean determination coefficients (rw2) across all studies. The prognostic validity of each
potential talent indicator was inconsistent between studies and, synthesising all studies,
was generally poor: mean determination coefficients rw2 ranged from 0.1% to 3.5%. That
is, on average, player evaluations by coaches and variables of player physique, physical
abilities, ­ball-​­control skills, p
­ erceptual-​­tactical skills, and psychological characteris-
tics, each only explained 3.5% or less of the variance of later playing performance.
Player assessment by coaches did not generally have superior or inferior predic-
tive validity compared to standardised tests of the potential talent indicators, but the
 Talent identification and talent promotion 367
­Table 22.1 T
 he effect sizes for studies investigating predictive effects of potential talent
indicators of youth soccer players on their later playing performance. Upper half:
short prediction periods of ­1–​­4 years. Lower half: longer prediction periods of >4
years. Black figures: baseline samples from youth academies; grey figures: lower-
level or more heterogeneous baseline samples (­general primary pupils, participants
from regional soccer teams, bases, or clubs). Effects reported in original studies as
Cohen’s d, η 2p , odds ratio, or AUC were converted to r.

Positive effect No/­negligible/­negative

(­r ≥ 0.10) effect (­r < 0.10)

Short period (≤4 years)

Coach rating 14
Physique
Body height 2, 6, 18 18, 19, 21, 24
Body mass 6, 18 2, 18, 21, 24
% lean mass 2, 18 18
Physical abilities
Linear sprint speed 2, 4, 6, 7, 13, 20, 14, 18, 21, 24 4, 13, 20, 18, 19, 21
Agility 6, 13, 20, 14, 21, 24 7, 20, 14, 19, 21
(­Jumping) Power 2, 6, 18, 21 7, 18, 21, 24
Aerobic endurance 1, 4, 6, 14, 18, 24 4, 7, 18
Flexibility 7
Ball control skills
Dribbling 2, 13, 20, 14, 19, 24 13, 20, 19
Passing 13, 20, 14, 24 13, 20, 14, 19
Shooting 20, 14 13, 20, 19, 24
Juggling 14, 24
­Perceptual-​­tactical skills 6, 14, 17 7, 17
Psychological characteristics 6, 14, 27 6, 10, 14, 27
Multidimensional 6, 7, 14, 26, 27 2, 26, 27
Longer period (>4 years)
Coach rating 5, 23, 25
Physique
Body height 1, 8, 12, 18, 19 3, 5, 12, 18, 21, 22, 23, 24
Body mass 1, 12, 18, 22 3, 5, 8, 12, 18, 21, 22, 23, 24
% Lean mass 5, 18 1, 18
Physical abilities
Linear sprint speed 5, 7, 8, 9, 11, 12, 14, 21, 22 1, 3, 4, 7, 11, 12, 18, 22, 23, 24
Agility 5, 7, 11, 12, 15, 21, 22 11, 12, 22, 23, 24
(­Jumping) Power 7, 8, 9, 22 1, 3, 5, 7, 18, 21, 22, 23, 24
Aerobic endurance 3, 5, 8, 9, 18, 22 3, 7, 8, 18, 22, 23, 24
Flexibility 8 7, 8, 9
Ball control skills
Dribbling 5, 11, 12, 15, 23, 24 11, 12
Passing 5, 11, 12, 23, 24 11, 12
Shooting 12, 24 5, 11, 12
Juggling 23, 24
­Perceptual-​­tactical skills 7 7
Psychological characteristics 5, 23, 25 5, 23
Multidimensional 7, 8, 9, 12, 23, 25

1
Carling et al. (­2012), 2Deprez et al. (­2015), 3Dugdale et al. (­2021), 4Emmonds et al. (­2016), 5Figueiredo
et al. (­2019), 6Forsman et al. (­2016), 7Gonaus & Müller (­2012), 8Hohmann & Siener (­2021), 9Hohmann
et al. (­2018), 10Höner & Feichtinger (­2016), 11Höner & Votteler (­2016), 12Höner et al. (­2017), 13Höner et al.
(­2019), 14Höner et al. (­2021), 15Huijgen et al. (­2009), 16Jokuschies et al. (­2017), 17Kannekens et al. (­2011),
18
Le Gall et al. (­2010), 19Leyhr et al. (­2018), 20Leyhr et al. (­2020), 21Noon et al. (­2020), 22Saward et al. (­2020),
23
Sieghartsleitner et al. (­2019a), 24Sieghartsleitner et al. (­2019b), 25Van Yperen (­2009), 26Zuber et al. (­2014),
27
Zuber et al. (­2016).
368 Arne Güllich and Paul Larkin
­Table 22.2 A
 n overview of predictive effects of potential talent indicators of youth soccer
players on their later playing performance (­references reported in T ­ able 22.1).
Range (­m inimum, maximum), s­ ample-​­weighted mean effect ( rw2 ), and numbers
of reported effects (­k; greater numbers of effects than studies because several
studies reported various effects, e.g., across age categories). Effects reported in
original studies as Cohen’s d, η 2p , odds ratio, or AUC were converted to r.

Min r Max r Sample-​­weighted mean rw2 (%) k

Predictor variable ­

Coach rating 0.14 0.48 2.7% 7

Physique
Height1 –​­0.18 0.35 0.7% 40
Weight1 –​­0.20 0.38 0.8% 40
% Lean mass –​­0.05 0.27 0.6% 12
Physical abilities
Linear sprint speed –​­0.09 0.55 1.0% 72
Agility –​­0.07 0.48 0.5% 49
Power –​­0.22 0.23 0.4% 42
Aerobic endurance1,2 –​­0.61 0.59 0.3% 45
Flexibility 0.00 0.17 0.1% 7
Ball control skills
Dribbling 0.00 0.58 1.3% 34
Passing 0.04 0.36 0.9% 31
Shooting2 –​­0.29 0.23 0.5% 30
Juggling2 0.10 0.33 1.7% 9
­Perceptual-​­tactical skills –​­0.15 0.32 3.5% 14
Psychological characteristics –​­0.15 0.23 1.4% 9
Multidimensional evaluation1 0.18 0.72 18.0% 21
1
Among relatively homogeneous samples (­academy players), lower or no predictive effects: body height
rw2 = 0.0%; body weight rw2 = 0.0%; aerobic endurance rw2 = 0.0%; and multidimensional evaluation
rw2 = 7.4%.
2
Across prediction periods >4 years, no predictive effects: rw2 = 0.0%, respectively.

combination of coach evaluation with standardised motor and/­or psychological tests

showed better prognostic validity than either alone. Furthermore, multidimensional
approaches generally had higher, although mostly still low, predictive effects, with
3.2% < rw2 < 51.9%.
The average sensitivity of these multidimensional approaches was 65.4% and the spec-
ificity was 65.0% (­­sample-​­weighted means). Assuming a base rate of 1/­1,000 (­i.e., 1 of
1,000 youth players becomes a successful adult professional, for example, a national-level
player) – ​­quite a realistic estimate based on the figures of the performance development
discussed a­ bove – ​­the application of these TID approaches yields a hit rate for a TPP
of 0.2%. That is, two out of 1,000 positively t­ alent-​­identified players become successful
adult players. At the same time, 34.6% of the true talents are dismissed. Even when apply-
ing the strongest predictor model reported in the literature (­Sieghartsleitner et al., 2019a,
“­holistic model”: sensitivity 90%, specificity 87%), this only increases the hit rate of a TPP
to 0.7%. These calculations indicate that the low prognostic validity of TID procedures is
not due to deficient research or practice, but to the nature of the unsolvable problem (­i.e.,
the impossibility of reliable TID at a young age in association with the low base rate).
­Table 22.3 summarises major impediments to the prognostic validity of TID in soccer.
Given the inconsistent evidence and generally poor prognostic validity, a recom-
mendation to use any of the considered potential talent indicators in TID procedures
 Talent identification and talent promotion 369
­Table 22.3 S
ome impediments to reliable talent identification in youth soccer (­
following
Güllich & Cobley, 2017)

Constraints Issues

Characteristics One’s success rests on one’s own performance relative to other players’
of the task performance. Who the competitors will be in the future and what their
performance will be is uncertain and cannot be influenced.
Rules, playing tactics, and playing systems may have changed in the
future, leading to a demand for different types of players.
High playing performance can be achieved through many different
compositions of performance components, including physique, physical
abilities, ­p erceptual-​­technical, and ­p erceptual-​­t actical skills. The
complex components of the ­match-​­play performance are mutually
compensable.
The effect and weight of different predictors of playing performance
change across age and performance levels. (­For example, physique
and physical abilities predict differences in childhood/­adolescent
performance, but less so or not at all among the highest levels of adult
performance.)
Characteristics The rate of progress of the various performance components differs and
of the player also varies ­i ntra-​­i ndividually over time. ­Inter-​­i ndividual differences
in future ­long-​­term individual development of the performance
components are difficult to predict.
Initial performance advantages of biologically accelerated and of
relatively ­early-​­born players (­relative age effect, RAE) diminish in
adulthood.
The ­i ntra-​­individual development over time of psychological
characteristics varies ­i nter-​­i ndividually; their ­long-​­term future
development can hardly be predicted.
The participation history of players is typically not considered in TID
procedures. Furthermore, individual differences in ­long-​­term future
training of players, its quality, the ­player-​­coach match, and the
effectiveness of that training can hardly be predicted.
Characteristics The ­i ntra-​­individual development over time of parental support, c­ oach-​
of the a­ thlete relationship, peer relationships, and athlete services (­e.g.,
environment performance diagnostics, sports medicine, physiotherapy, nutritional
and psychological counselling) and their effects on performance
development vary ­i nter-​­i ndividually. Respective ­long-​­term future ­i nter-​
i­ ndividual differences can hardly be predicted.
Quality of tests Tests possess imperfect objectivity, reliability, and validity. The objectivity
of player evaluation by coaches is widely unstudied (­or unpublished)
to date. The retest reliability and differential developmental stability
of many psychological and psychosocial characteristics are uncertain.
Furthermore, several tests of ­p erceptual-​­technical ­ball-​­control skills
and ­p erceptual-​­tactical skills do not measure representative skills.
They typically record repeated standardised tasks under standardised
conditions (­e.g., series of passes against walls and dribbling through
a course of cones), tasks that do not occur in games. Critically, these
tests do not consider varying skill demands in game situations through
varying weather conditions, opponent and organisational pressure (­i.e.,
complexity of game situations), which are crucial to performance in
game situations.
370 Arne Güllich and Paul Larkin
would hardly be reconcilable with the ethos of science. Furthermore, some studies
reported the reliability of their tests incompletely and some failed to report it at all.
Where reported, the reliability was sometimes acceptable and in other cases unac-
ceptable (­e.g., Höner et al., 2019; Hohmann et al., 2018; Jokuschies et al., 2017; Leyhr
et al., 2018; Sieghartsleitner et al., 2019a, b; Zuber et al., 2016). For psychological and
psychosocial constructs, studies typically reported Cronbach’s α, but not the retest re-
liability and differential developmental stability, although these are critical to assess-
ments, especially during childhood/­adolescent development. Also, multidimensional
approaches were generally more predictive than each predictor alone. However, each
of the multidimensional approaches used different combinations of predictor varia-
bles and research has not identified an optimal set of predictors to date.

Talent promotion programmes

The central ‘­idea’ of TPPs is to select the most promising youth players, provide re-
sources and supportive interventions to facilitate their ­long-​­term training and com-
petition process, and thereby increase their likelihood to become a nationally or
internationally successful adult player (­not just a successful junior player). TPPs start
selecting players from a young age, mostly from ­8 –​­14 years, to secure young talents for
that TPP, before other TPPs, and to enable a long period of nurturing until the antici-
pated age of peak performance.
The general approach of TPPs implies two underlying premises: (­i) reliable TID at
a young age is possible; and (­ii) TPP resources and intervention measures applied to
the participants at a young age positively influence their ­long-​­term adult performance.
The falsification of the first premise (­TID) has been reported in the previous section.
We discuss the following questions:

1 What are participant perceptions of a TPP?

2 What effects do the TPP resources and intervention measures provided to partic-
ipants have on their ­long-​­term performance development?
3 Does early TPP involvement correlate with ­long-​­term adult performance?
Another question concerns part of the general approach of TPPs. Unlike the
central ‘­idea’ of TPPs mentioned above, annual selection and d ­ e-​­selection pro-
cedures imply revisions of previous selection decisions and the selection of new
‘­­side-​­entry players’ across age categories. Thus, a critical question is:
4 Does the population of h ­ igh-​­performing adult players develop from early selec-
tion and l­ ong-​­term continuous TPP nurture, or does this population rather emerge
via repeated procedures of selection, ­de-​­selection, and replacement of previous
participants across age categories?

Perceptions of TPP participants

Participants of one academy reported positive scores on s­ tress-​­recovery balance, need
satisfaction, psychological and social ­well-​­being, and s­ chool-​­related quality of life, and
they did not differ from recreational players (­Rongen et al., 2020). Furthermore, in sev-
eral studies, players rated the academy environment as positive (­Gangso et al., 2021;
Gesbert et al., 2021; Mitchell et al., 2021), typically reporting values of around 4­ –​­5 on 6­ -​
p
­ oint scales of the “­Talent Development Environment Questionnaire” (­TDEQ, Martin-
dale et al., 2010). However, the development of the TDEQ failed to consider whether the
 Talent identification and talent promotion 371
addressed environmental factors influence player performance development (­or other
l­ong-​­term outcomes, such as academic, health, or psychological wellbeing).
Academy players are aware that their clubs see them as an “­investment,” “­commodity,”
and a “­marketable asset” (­Christensen & Soerensen, 2009; Larsen et al., 2020; Manley
et al., 2012). They are aware that their chances to be promoted to the first team or an-
other professional team are minimal, often implying a permanent feeling of frustration.
The players perceive some inconsistency between management talk and action, in that
clubs externally display a focus on ­long-​­term player development, not immediate suc-
cess, whereas players perceive the expectation is to “­win every day” (­e.g., Larsen et al.,
2020). Likewise, players report that clubs say they want h ­ ome-​­grown players in their first
team, but increasingly recruit foreign players (­e.g., Larsen et al., 2020; Webb et al., 2020).
Academy players know they need a “­­back-​­up plan” implying future employment out-
side of soccer and are aware of the necessity of academic education (­Christensen & Soe-
rensen, 2009; Aalberg & Saether, 2016; Webb et al., 2020). All academies described in
the literature had some cooperation with schools providing modified educational pro-
grammes for the players (­e.g., flexible lesson times; exemption from lessons; individual
extra tuition; replacement of school subjects by sports subjects; and transportation ser-
vice; Christensen & Soerensen, 2009; Aalberg & Saether, 2016; Webb et al., 2020). Never-
theless, players report permanent high levels of stress from the conflicting time demands
of soccer and school. They often must make decisions between doing homework and
attending a soccer training session or game. Furthermore, a significant decline in exam
results and ­school-​­related quality of life and premature dropping out of school have been
reported (­Aalberg & Saether, 2016; Christensen & Soerensen, 2009; Rongen et al., 2020).
Players reported that clubs displayed priority of education to them and the public; how-
ever, in reality, soccer was clearly prioritised over academic outcomes (­Webb et al., 2020).
­De-­​­­selection – ​­which the vast majority of academy players experience at some ­time –​
i­mplies severe immediate and lasting psychological disturbances, including feelings of
loss of identity, confidence, and ­self-​­esteem; being a failure; depression; uncertainty, dis-
orientation, and anxiety regarding their future life; and of being left alone (­O’Halloran,
2019; Wilkinson, 2021). Blakelock et al. (­2016) found 55% of deselected players exhibited
clinical levels of psychological distress. These effects were exacerbated by the strong,
and often exclusive, athletic identity of players (­Mitchell et al., 2014; Rongen et al., 2020).
Finally, reports on the ­player-​­coach and ­player-​­staff relationships are heterogene-
ous. Players from two Scandinavian academies (­Aalberg & Saether, 2016; Larsen et al.,
2013) reported a culture of community, mutual respect, and open t­wo-​­way commu-
nication. Coaches and staff created an environment centred around ­player-​­staff re-
lationships, where everybody seeks to help players wherever possible regarding their
holistic development, ­self-​­awareness, and managing soccer and school. They also fa-
cilitate the empowerment of players by delegating as much responsibility as possible
to the player concerning physical and mental ­load-​­recovery balance, nutrition, leisure
activities, school, and time management, and by encouraging players to ask questions
and make suggestions on the practice design and game tactics.
On the other hand, players from an English academy (­Manley, 2012; Manley et al.,
2012) reported a culture of “­authoritarian environment,” “­discipline,” “­control,” and
“­surveillance.” This included continuous physical and ­techno-​­motor testing and evalu-
ation of each training session and game, with weekly reports to the manager, and data
documented in individual player files. Perhaps more significantly, the coaches, assistants,
conditioning staff, sports scientists, physiotherapists, teachers, tutors, teammates, and
even parents, reported observations of and conversations with players, both within and
372 Arne Güllich and Paul Larkin
away from the academy, as well as social media entries, to the manager without the player
being aware. Therefore, these individuals become the “­eyes and ears of the manager,”
with staff acknowledging they are “­monitoring them all the time” (­Manley, 2012; Manley
et al., 2012). Players thus experienced a “­silent mode of surveillance” leading to a culture
of “­suspicion” and “­distrust.”

Effects of TPP resources and intervention measures

The effects of TPP resources and intervention measures on l­ong-​­term player performance
development have not been empirically investigated in soccer TPPs. This is interesting given
the questions of how to design and organise a TPP and what resources and intervention
measures to provide to players are central to these programmes. This has two significant im-
plications. First, managers cannot make e­ vidence-​­based decisions in the designing and or-
ganisation of TPPs. Second, extensive research into TID is opposed by lacking research into
the purpose TID is undertaken for: the effects of TPPs. Nevertheless, the following sections
allow for respective inferences from empirical evidence, although not individual TPP meas-
ures, considering the ­long-​­term effects of early TPP involvement and annual player turnover.

Effects of early TPP involvement

Given that TPPs aim to involve participants from very young ages, often ­8 –​­14 years, a
critical question is whether earlier TPP involvement facilitates higher ­short-​­term jun-
ior performance and ­long-​­term adult performance. T ­ able 22.4 reviews the available ev-
idence. Each study reported comparisons between higher and ­lower-​­performing youth
or adult players regarding their age of selection for a youth academy or selection team.
For junior performance, the findings are inconsistent and generally inconclusive.
Overall, there is no consistent evidence indicating an association of higher junior per-
formance with earlier or later selection age. Results for adult performance are much
more consistent because a higher adult performance was associated with a later selec-
tion for TPPs and lower adult performance was associated with younger selection for
TPPs. This finding consistently applied among adult players at regional to national
playing levels and adult i­nternational-​­level compared to l­ower-​­performing players.
Most of the h­ ighest-​­performing adult players were not involved in a TPP at a particu-
larly young age, but developed outside of TPPs until later ages, and late “side-​­entry
players” were ­over-​­represented among the ­h ighest-​­performing adult players.

Player turnover within TPPs

TPP coaches and staff review their previous selection decisions at least annually. For
each season, they decide which players are retained through the next season and which
are dismissed and replaced with new “­­side-​­entry players.” The question of the extent
to which current players are dismissed (­i.e., a revision of previous selection decisions)
and replaced with new players is critical to understanding the functioning of TPPs.
This is commonly calculated for each ­season-­​­­to-​­season transition by the annual player
turnover within a TPP using the equation:
( number of entering players + number of dismissed players ) 2
Annual player turnover =
total number of players
­Table 22.5 shows the mean annual player turnover within youth soccer academies
was 29%. This turnover rate was similar, and did not significantly differ, across age
 Talent identification and talent promotion 373
­Table 22.4 The effects (­Cohen’s d) of the age of selection for a talent promotion programme
on later junior and adult playing performance. Academy = youth soccer academy;
L. = league; ­U-​­NT = ­u nder-​­age national team; ­A-​­NT = senior national ­A-​­team.
Note the sign of effects (­Cohen’s d): A positive effect indicates that higher eventual
performance was associated with higher (­later) entry age.

Study Country, sex, n Entry age Comparison groups Cohen’s d

sample

Junior performance
Dugdale et al., 2021 GBR, m Academy 537 Academy retained vs. dismissed +0.54
Ford & Williams, GBR, m Academy 32 Academy retained vs. dismissed –​­0.18
2012
Ford et al., 2009 GBR, m Academy 22 Academy retained vs. dismissed +0.27
Hendry & Hodges, GBR, m Academy 102 Academy retained vs. dismissed –​­0.87
2018
Huijgen et al., 2014 NED, m Academy 113 Academy retained vs. dismissed –​­0.45
Noon et al., 2020 GBR, m Academy 76 Academy retained vs. dismissed –​­0.50
­Sample-​­weighted mean +0.10

Adult performance
Güllich, 2014 GER, m ­1st–​­2nd 348 Academy 1st vs. 2nd League +0.18
League
Hendry & Hodges, GBR, m Academy 28 Academy U21 1st L. vs. below –​­0.07
2018
Hendry et al., 2019 CAN, f ­A-​­NT, 45 Academy ­A-​­NT vs. varsity +0.89
varsity
Roca et al., 2012 GBR, m 32 Academy Higher vs. lower skill +0.36
­Semi-​­prof.
Hendry et al., 2019 CAN, f ­A-​­NT, 45 ­U-​­NT ­A-​­NT vs. varsity +0.59
varsity
Hornig et al., 2016 GER, m 1st BL, 102 ­U-​­NT 1st L. vs. ­4th–​­6th L. +0.10
­4 –​­6th L.
Hornig et al., 2016 GER, m 1st 52 ­U-​­NT ­A-​­NT vs. 1st League +0.33
League
Güllich, 2014 GER, m ­U-​­NT 847 U­ -​­NT 1st vs. 3rd League +0.61
Güllich, 2014 GER, m ­U-​­NT 599 ­U-​­NT 1st vs. 2nd League +0.71
Güllich, 2014 GER, m ­1st–​­2nd 348 ­U-​­NT 1st vs. 2nd League +0.54
League
Güllich, 2014 GER, m 1st 321 ­U-​­NT ­A-​­NT vs. 1st League +0.25
League
Güllich, 2019 GER, f, 1st 29 ­U-​­NT ­A-​­NT vs. 1st League +0.78
League
Schroepf & Lames, GER, m ­U-​­NT 599 ­U-​­NT ­1st–​­3rd L. vs. lower +0.99
2017
Schroepf & Lames, GER, m ­U-​­NT 317 ­U-​­NT ­A-​­NT vs. below 3rd L. +0.81
2017
Schroepf & Lames, GER, m ­U-​­NT 389 ­U-​­NT ­A-​­NT vs. ­1st–​­3rd L. +0.28
2017
­Sample-​­weighted mean +0.58
374 Arne Güllich and Paul Larkin
­Table 22.5 The annual player turnover in TPPs and the proportion of identical players in a
squad after 3 and 5 years. Annual player turnover = [(­n new players + n dismissed
players)/­2]/­n squad size

Period of … Mean Persistence

annual after

Study Country, sex, Observation Age player 3 years 5 years

sample turnover

Youth soccer academies

Ford et al., 15 countries, m; 29 1 year ­U8–​­U21 29% 36% 18%
2020 academies, n ≈
7,000
Güllich, 2014 GER, m; 13 10 years ­U10–​­U19 25% 42% 24%
academies, n =
1,420
Noon et al., GBR, m; 1 academy, 5 years ­U10–​­U18 47% 12% 3%
2020 n = 76
­Sample-​­weighted mean 29% 37% 19%

­Under-​­age national teams

Güllich, 2014 GER, m; n = 1,059 13 years ­U15–​­U19 41% 21% 7%
Schroepf & GER, m; n = 636 13 years ­ 16–​­U21
U 46% 16% 4%
Lames, 2017
­Sample-​­weighted mean 43% 19% 6%

categories from U10 to U19. The finding implies that at any age, the odds that a current
participant will still be involved in an academy 3 years later is 37% and after 5 years
19%. Within the national u ­ nder-​­age selection teams, the mean annual turnover was
even higher, 43%. Therefore, the probability an u ­ nder-​­age national team player is still
in a national team 3 years later is 19% and after 5 years 6%.
­Figure 22.1 illustrates the proportions of ­under-​­11 participants of youth soccer acad-
emies and of ­under-​­15 national team players who remained in the programme through
subsequent age categories (­grey lines). As can be seen, the proportions drop contin-
uously to about 1% in adulthood. The figure also shows the proportion of successful
adult players in the first Bundesliga, Premier League, and senior ­national-​­team players
(­black lines) who were involved in a youth soccer academy or a national u ­ nder-​­age
selection team during junior age categories. A minority of the successful adult players
were selected for a youth academy before age 15 years, with only 6% of senior ­national-​
t­ eam players selected for a U15 selection team, and about half of them playing for an
­under-​­age selection team until age 19.
In sum, the observations suggest four inferences:

1­ TPP coaches revise most of their previous selection decisions within 3 or fewer years.
­2 Most of the young TPP players are “­overtaken” by other players who have a better de-
velopment outside TPPs regarding performance and/­or indicators of future potential.
3 Most of the early selected players do not become successful adult players while
most of the successful adult players were not selected at a particularly young age.
The populations of early selected players and successful adult players are not iden-
tical but are widely disparate populations.
 Talent identification and talent promotion 375

Persistence Academy Persistence National Team

Entry Academy Club Entry National Team
100% 100% 100% 100%

87%
80%

60%

53%
40%
36%

20% 19%

6% 9% 1%
0%
U11 U13 U15 U17 U19 22+

­Figure 22.1 P
 roportions of members of youth soccer academies and ­under-​­age national
teams persisting in the programme through subsequent age categories (­g rey
lines) and proportions of senior first Bundesliga/­Premier League players in-
volved in youth academies and of senior national team players involved in
u nder-​­
­ age national teams through previous age categories (­ black lines).
Aggregated data from Anderson & Miller, 2011; Güllich, 2014, 2019; Gross-
mann & Lames, 2015; Hornig et al., 2016; Schroepf & Lames, 2017.

­4 Rather than early identification and ­long-​­term continuous nurture of talents, the
functioning of the TPPs primarily rests on recurrent selection and ­de-​­selection
procedures across all age categories.

Conclusion and future directions

The idea of early identification of talents and their ­long-​­term continuous TPP nurture
reflects an institutionalised ideology rather than empirical reality. The functioning of
soccer TPPs rests on recurrent selection and d ­ e-​­selection procedures rather than ­long-​
t­ erm player development through continuous nurture. TPPs recruit large numbers of
young players and extend this number through high rates of player turnover. Players
are “­tried out”; some continue through several years to be assigned to the h ­ ighest-​
­performing and/­or most promising players while most are dismissed in the short term
and replaced with external players now considered to have higher performance and/­or
greater future promise. This also implies that TID mostly occurs a posteriori rather
than a priori.
Recent ­meta-​­analyses (­Güllich et al., 2022; Barth et al., 2022; including 23 studies
from soccer) show that some predictor effects differentiating higher vs. lower early jun-
ior performance are different and partly opposite to predictor effects differentiating
higher vs. lower ­long-​­term adult performance. ­Higher-​­performing juniors had greater
amounts of ­coach-​­led ­main-​­sport practice, less ­other-​­sports practice, and earlier
376 Arne Güllich and Paul Larkin
achievement of developmental performance milestones (­first national or international
championships and first nomination for a selection team) than ­lower-​­performing jun-
iors. In contrast, adult i­nternational-​­level athletes had less m­ ain-​­sport practice, more
childhood/­adolescent ­other-​­sports practice, and later achievement of performance
milestones than adult ­national-​­level athletes. Amounts of p ­ eer-​­led play in the main
sport or other sports generally had negligible effects on both junior and adult perfor-
mance. The findings were confirmed by studies comparing higher vs. ­lower-​­p erforming
youth soccer players and adult international vs. ­national-​­level players (­Güllich et al.,
2022; Barth et al., 2022, and ­Table 22.4).
TPPs preferably select the most advanced young players. Besides being biologically
accelerated, most of them have heavily invested in specialised soccer practice prior to
selection, with little or no ­other-​­sports practice. Once selected, the TPPs seek to further
accelerate their development through expanded soccer practice. Increasing childhood/­
adolescent specialised practice may rapidly improve junior performance but does not
facilitate the ­long-​­term player development into the highest adult performance levels.
At the same time, it magnifies the opportunity costs of players (­education, other hob-
bies, family, and friends) and risks of future motivational decline, burnout, and over-
use injuries (­Güllich et al., 2022; Barth et al., 2022, for reviews). In contrast, most of
the ­h ighest-​­performing adult players had moderate amounts of childhood/­adolescent
soccer training, practised various sports, and remained unaffected by the potential
negative effects of early TPP involvement, thereby buffering l­ong-​­term costs and risks
while growing their l­ong-​­term potential.
The impossibility of reliable early TID and uncertainty of the effects of TPP meas-
ures are associated with pronounced forms of functional decoupling of talk, decisions,
and actions of TPP management (­Brunson, 2002). Talk: early identification of talents;
­long-​­term player development; importance of education over soccer; ­home-​­grown
players in adult teams. Action: high annual player turnover; emphasis on current team
success; priority of soccer over academic outcomes; and increasing recruitment of for-
eign players.
From an applied perspective, the evidence suggests postponing selection for TPPs to
later ages and reduce opportunity costs of players, their w ­ ell-­​­­being-​­related costs, and
­long-​­term risks. Furthermore, one could expect that consistency of management talk
and action is a matter of course.
The available evidence has several limitations.

1 The major limitation is that the effects of TPP measures are widely unstudied.
The massive body of TID research is opposed by lacking investigation into the
purpose TID is done for.
­2 Most studies involved ­West-​­European male players. It is widely unknown whether
reported findings apply to female players and to other soccer cultures.
­3 Many TID studies were restricted to relatively short prediction periods within
youth ages and those considering adult performance used relatively relaxed suc-
cess criteria.
4 Many of the ­h ighest-​­performing adult players may not have been involved in stud-
ies because they were not considered for TPPs at a young age.
5 The objectivity (­i.e., ­inter-​­individual consistency) of ­coaches’ player evaluation
and the retest reliability and differential stability of childhood/­adolescent psycho-
logical and psychosocial characteristics were mostly not reported.
 Talent identification and talent promotion 377
The goal for future research is to investigate the effects of TPP resources and inter-
ventions provided to players. Such research should consider ­short-​­and ­long-​­term TPP
effects at different ages on future performance development of players but also their
academic, health, psychological, and psychosocial development. In this context, re-
searchers may investigate whether prioritising education over soccer or being entirely
upfront with players, parents, and the public would hamper the achievement of the
goals of TPPs.
The fact that an improvement of TID accuracy from ~65% to ~90% only increases
the TPP hit rate from 0.2% to 0.7% suggests the practical use of continued research
efforts into TID is questionable. If any, it may be interesting to attempt to access the
nuanced tacit knowledge of coaches in TID (­the content of their “­gut instinct”), defi-
nitions of several undefined constructs they use, and to investigate the objectivity of
their player assessment (­see also the review of Williams et al., 2020).
Finally, anecdotally, several outstanding players (­e.g., Lionel Messi, Andrés Iniesta,
Luís Figo, Johan Cruyff, and Franz Beckenbauer) had moderate physical abilities,
but outstanding ball control and understanding of game situations. Traditional TID
research fails to take account of such patterns. A question for future research may be
whether a combination of moderate levels in most characteristics with just one or two
outstanding characteristics is a more promising approach to TID.

References
Aalberg, R. R., & Sæther, S. A. (­2016). The talent development environment in a Norwegian
­top-​­level football club. Sport Science Review, 25(­­3 –​­4), ­159–​­182.
Anderson, G., & Miller, R. M. (­2011). The Academy System in English Professional Foot-
ball: Business Value or ‘­Following the Herd’? University of Liverpool Management School:
Research Paper Series No. 2011/­43.
Barth, M., Güllich, A., Macnamara, B. N., & Hambrick, D. Z. (­2022). Predictors of junior
versus senior elite performance are opposite: a systematic review and ­meta-​­analysis of par-
ticipation patterns. Sports Medicine, 52, 1399–1416.
Bergkamp, T. L., Frencken, W. G., Niessen, A. S. M., Meijer, R. R., & den Hartigh, R. J.
(­2022). How soccer scouts identify talented players. European Journal of Sport Science, 22(7),
994–1004.
Blakelock, D. J., Chen, M. A., & Prescott, T. (­2016). Psychological distress in elite adolescent
soccer players following deselection. Journal of Clinical Sport Psychology, 10(­1), ­59–​­77.
Brunson, N. (­2002). The Organization of Hypocrisy: Talk, Decision, and Actions in Organiza-
tions (­2nd ed.). Oslo: Copenhagen Business School Press.
Carling, C., Le Gall, F., & Malina, R. M. (­2012). Body size, skeletal maturity, and functional
characteristics of elite academy soccer players on entry between 1992 and 2003. Journal of
Sports Sciences, 30(­15), ­1683–​­1693.
Christensen, M. K. (­2009). ‘­A n eye for talent’: talent identification and the ‘­practical sense’ of
­top-​­level soccer coaches. Sociology of Sport, 26(­3), ­365–​­382.
Christensen, M. K., & Søerensen, J. K. (­2009). Sport or school? Dreams and dilemmas for
talented young Danish football players. European Physical Education Review, 15(­1), ­115–​­133.
Deprez, D., Fransen, J., Boone, J., Lenoir, M., Philippaerts, R., & Vaeyens, R. (­2015). Charac-
teristics of ­h igh-​­level youth soccer players: variation by playing position. Journal of Sports
Sciences, 33(­3), ­243–​­254.
Dugdale, J. H., Sanders, D., Myers, T., Williams, A. M., & Hunter, A. M. (­2021). Progression
from youth to professional soccer: a longitudinal study of successful and unsuccessful acad-
emy graduates. Scan dinavian Journal of Medicine & Science in Sports, 31(­Suppl. 1), ­73–​­84.
378 Arne Güllich and Paul Larkin
Emmonds, S., Till, K. A., Jones, B., Mellis, M., & Pears, M. (­2016). Anthropometric, speed and
endurance characteristics of English academy soccer players: do they influence obtaining a
professional contract at 18 years of age? International Journal of Sports Science & Coaching,
11(­2), ­2212–​­2218.
Figueiredo, A. J., C ­ oelho-­​­­e-​­Silva, M. J., Sarmento, H., Moya, J., & Malina, R. M. (­2019). Ado-
lescent characteristics of youth soccer players: do they vary with playing status in young
adulthood? Research in Sports Medicine, 28(­1), ­72–​­83.
Ford, P. R., Bordonau, J. L. D., Bonanno, D., Tavares, J., Groenendijk, C., Fink, C., ... & Di
Salvo, V. (­2020). A survey of talent identification and development processes in the youth
academies of professional soccer clubs from around the world. Journal of Sports Sciences,
38(­­11–​­12), ­1269–​­1278.
Ford, P., Ward, P., Hodges, N. J., & Williams, A. M. (­2009). The role of deliberate practice and
play in career progression in sport: the early engagement hypothesis. High Ability Studies,
20(­1), ­65–​­75.
Ford, P., & Williams, A. M. (­2012). The developmental activities engaged in by elite youth soc-
cer players who progressed to professional status compared to those who did not. Psychology
of Sport & Exercise, 13(­3), ­349–​­352.
Forsman, H., Blomqvist, M., Davids, K., Liukkonen, J., & Konttinen, N. (­2016). Identifying
technical, physiological, tactical and psychological characteristics that contribute to career
progression in soccer. International Journal of Sports Science & Coaching, 11(­4), ­505–​­513.
Fransen, J., & Güllich, A. (­2018). Talent identification and development in game sports. In R. F.
Subotnik, P. ­Olszewski-​­Kubilius, & F. C. Worrell (­Eds.), The Psychology of High Performance
(­p­­p. ­59–​­92). Washington, DC: American Psychological Association.
Gangsø, K., Aspvik, N. P., Mehus, I., Høigaard, R., & Sæther, S. A. (­2021). Talent development
environments in football: comparing the ­top-​­five and ­bottom-­​­­five-​­ranked football academies
in Norway. International Journal of Environmental Research & Public Health, 18(­3), 1321.
Gesbert, V., Crettaz von Roten, F., & Hauw, D. (­2021). Reviewing the role of the environment in
the talent development of a professional soccer club. PloS One, 16(­2), e0246823.
Gonaus, C., & Müller, E. (­2012). Using physiological data to predict future career progres-
sion in ­14-​­to ­17-­​­­year-​­old Austrian soccer academy players. Journal of Sports Sciences, 30(­15),
­1673–​­1682.
Grossmann, B., & Lames, M. (­2015). From talent to professional ­football – ​­youthism in Ger-
man football. International Journal of Sports Science & Coaching, 10(­6), ­1103–​­1113.
Güllich, A. (­2014). Selection, ­de-​­selection and progression in German football talent promo-
tion. European Journal of Sport Science, 14(­6), ­530–​­537.
Güllich, A. (­2019). “­­Macro-​­structure” of developmental participation histories and “­­micro-​
­structure” of practice of German female ­world-​­class and ­national-​­class football players.
Journal of Sports Sciences, 37(­12), ­1347–​­1355.
Güllich, A., & Cobley, S. (­2017). On the efficacy of talent identification and talent development
programmes. In J. Baker, S. Cobley, J. Schorer, & N. Wattie (­eds.), Routledge Handbook of
Talent Identification and Talent Development in Sport (­p­­p. ­80–​­98). London: Routledge.
Güllich, A., Macnamara, B. N., & Hambrick, D. Z. (­2022). What makes a champion? Early
multidisciplinary practice, not early specialization, predicts w ­ orld-​­class performance. Per-
spectives on Psychological Sciences, 17(1), 6–29.
Hendry, D. T., & Hodges, N. J. (­2018). Early majority engagement pathway best defines transi-
tions from youth to adult elite men’s soccer in the UK: a three t­ ime-​­point retrospective and
prospective study. Psychology of Sport & Exercise, 36, ­81–​­89.
Hendry, D. T., Williams, A. M., Ford, P. R., & Hodges, N. J. (­2019). Developmental activities
and perceptions of challenge for national and varsity women soccer players in Canada. Psy-
chology of Sport & Exercise, 43, ­210–​­218.
 Talent identification and talent promotion 379
Hohmann, A., & Siener, M. (­2021). Talent identification in youth soccer: prognosis of U17 soc-
cer performance on the basis of general athleticism and talent promotion interventions in
­second-​­g rade children. Frontiers in Sports and Active Living, 3:625645.
Hohmann, A, Siener, M., & He, Renye (­2018). Prognostic validity of talent orientation in soc-
cer. German Journal of Exercise and Sport Research, 48, ­478–​­488.
Höner, O., & Feichtinger, P. (­2016). Psychological talent predictors in early adolescence and
their empirical relationship with current and future performance in soccer. Psychology of
Sport & Exercise, 25, ­17–​­26.
Höner, O., Leyhr, D., & Kelava, A. (­2017). The influence of speed abilities and technical skills in
early adolescence on adult success in soccer: a l­ ong-​­term prospective analysis using ANOVA
and SEM approaches. PloS One, 12(­8), e0182211.
Höner, O., Murr, D., Larkin, P., Schreiner, R., & Leyhr, D. (­2021). Nationwide subjective and
objective assessments of potential talent predictors in elite youth soccer: an investigation of
prognostic validity in a prospective study. Frontiers in Sports & Active Living, 3, 115.
Höner, O., Raabe, J., Murr, D., & Leyhr, D. (­2019). Prognostic relevance of motor tests in elite
girls’ soccer: a ­five-​­year prospective cohort study within the German talent promotion pro-
gram. Science & Medicine in Football, 3(­4), ­287–​­296.
Höner, O., & Votteler, A. (­2016). Prognostic relevance of motor talent predictors in early adoles-
cence: a g­ roup-​­and i­ndividual-​­based evaluation considering different levels of achievement
in youth football. Journal of Sports Sciences, 34(­24), ­2269–​­2278.
Hornig, M., Aust, F., & Güllich, A. (­2016). Practice and play in the development of German
­top-​­level professional football players. European Journal of Sport Science, 16(­1), ­96–​­105.
Huijgen, B. C., ­Elferink-​­Gemser, M. T., Lemmink, K. A., & Visscher, C. (­2014). Multidimen-
sional performance characteristics in selected and deselected talented soccer players. Euro-
pean Journal of Sport Science, 14(­1), ­2 –​­10.
Huijgen, B. C., ­Elferink-​­Gemser, M. T., Post, W. J., & Visscher, C. (­2009). Soccer skill develop-
ment in professionals. International Journal of Sports Medicine, 30(­08), ­585–​­591.
Johansson, A., & Fahlén, J. (­2017). “­Simply the best, better than all the rest?” Validity issues in
selections in elite sport. International Journal of Sports Science & Coaching, 12(­4), ­470–​­480.
Jokuschies, N., Gut, V., & Conzelmann, A. (­2017). Systematizing coaches’ ‘­eye for talent’:
player assessments based on expert coaches’ subjective talent criteria in t­ op-​­level youth soc-
cer. International Journal of Sports Science & Coaching, 12(­5), ­565–​­576.
Kannekens, R., ­Elferink-​­Gemser, M. T., Visscher, C. (­2011). Positioning and deciding: key fac-
tors for talent development in soccer. Scandinavian Journal of Medicine & Science in Sports,
21(­6), ­846–​­852.
Larkin, P., Marchant, D., Syder, A., & Farrow, D. (­2020). An eye for talent: the recruiters’ role
in the Australian football talent pathway. PloS One, 15(­11), e0241307.
Larkin, P., & O’Connor, D. (­2017). Talent identification and recruitment in youth soccer: re-
cruiter’s perceptions of the key attributes for player recruitment. PloS One, 12(­4), e0175716.
Larkin, P., & Reeves, M. J. (­2018). ­Junior-​­elite football: time to ­re-​­position talent identification?
Soccer & Society, 19(­8), ­1183–​­1192.
Larsen, C. H., Alfermann, D., Henriksen, K., & Christensen, M. K. (­2013). Successful talent de-
velopment in soccer: the characteristics of the environment. Sport, Exercise, & Performance
Psychology, 2(­3), 190.
Larsen, C. H., Storm, L. K., Saether, S. A., Pyrdol, N., & Henriksen, K. (­2020). A world class
academy in professional football: the case of Ajax Amsterdam. Scandinavian Journal of Sport
and Exercise Psychology, 6(­2), ­33–​­43.
Le Gall, F., Carling, C., Williams, M., & Reilly, T. (­2010). Anthropometric and fitness charac-
teristics of international, professional and amateur male graduate soccer players from an
elite youth academy. Journal of Science & Medicine in Sport, 13(­1), ­90–​­95.
380 Arne Güllich and Paul Larkin
Leyhr, D., Kelava, A., Raabe, J., & Höner, O. (­2018). Longitudinal motor performance develop-
ment in early adolescence and its relationship to adult success: an ­8-​­year prospective study of
highly talented soccer players. PloS One, 13(­5), e0196324.
Leyhr, D., Raabe, J., Schultz, F., Kelava, A., & Höner, O. (­2020). The adolescent motor per-
formance development of elite female soccer players: a study of prognostic relevance for fu-
ture success in adulthood using multilevel modelling. Journal of Sports Sciences, 38(­­11–​­12),
­1342–​­1351.
Lund, S., & Söderström, T. (­2017). To see or not to see: talent identification in the Swedish foot-
ball association. Sociology of Sport Journal, 34(­3), ­248–​­258.
Manley, A. (­2012). Surveillance, Disciplinary Power and Athletic Identity: A Sociological Investi-
gation into the Culture of Elite Sports Academies. Doctoral dissertation, Durham University.
Manley, A., Palmer, C., & Roderick, M. (­2012). Disciplinary power, the oligopticon and rhizo-
matic surveillance in elite sports academies. Surveillance & Society, 10(­3/­4), ­303–​­319.
Martindale, R. J., Collins, D., Wang, J. C., McNeill, M., Lee, K. S., Sproule, J., & Westbury, T.
(­2010). Development of the talent development environment questionnaire for sport. Journal
of Sports Sciences, 28(­11), ­1209–​­1221.
Mitchell, T. O., Gledhill, A., Shand, R., Littlewood, M. A., Charnock, L., & Till, K. (­2021).
Players’ perceptions of the talent development environment within the English premier
league and football league. International Sport Coaching Journal, 8(­3), ­362–​­370.
Mitchell, T. O., Nesti, M., Richardson, D., Midgley, A. W., Eubank, M., & Littlewood, M.
(­2014). Exploring athletic identity in e­ lite-​­level English youth football: a c­ ross-​­sectional ap-
proach. Journal of Sports Sciences, 32(­13), ­1294–​­1299.
Murr, D., Feichtinger, P., Larkin, P., O’Connor, D., & Höner, O. (­2018). Psychological talent
predictors in youth soccer: a systematic review of the prognostic relevance of psychomotor,
­p erceptual-​­cognitive and ­p ersonality-​­related factors. PloS One, 13(­10), e0205337.
Noon, M. R., Eyre, E. L., Ellis, M., Myers, T. D., Morris, R. O., Mundy, P. D., ... & Clarke, N.
D. (­2020). The influence of recruitment age and anthropometric and physical characteristics
on the development pathway of English academy football players. International Journal of
Sports Physiology & Performance, 16(­2), ­199–​­207.
O’Halloran, L. M. (­2019). The Lived Experience of ‘­Critical Moments’ in Premier League Acad-
emy Football: A Descriptive Psychological Phenomenological Exploration. Liverpool: John
Moores University (­United Kingdom).
Reeves, M. J., McRobert, A. P., Lewis, C. J., & Roberts, S. J. (­2019). A case study of the use of
verbal reports for talent identification purposes in soccer: a Messi affair! PloS One, 14(­11),
e0225033.
Roberts, A. H., Greenwood, D. A., Stanley, M., Humberstone, C., Iredale, F., & Raynor, A.
(­2019). Coach knowledge in talent identification: a systematic review and ­meta-​­synthesis.
Journal of Science & Medicine in Sport, 22(­10), ­1163–​­1172.
Roca, A., Williams, A. M., & Ford, P. R. (­2012). Developmental activities and the acquisition
of superior anticipation and decision making in soccer players. Journal of Sports Sciences,
30(­15), ­1643–​­1652.
Rongen, F., McKenna, J., Cobley, S., Tee, J. C., & Till, K. (­2020). Psychosocial outcomes as-
sociated with soccer academy involvement: longitudinal comparisons against aged matched
school pupils. Journal of Sports Sciences, 38(­­11–​­12), ­1387–​­1398.
Saether, A. S. (­2014). Identification of talent in ­soccer – ​­what do coaches look for? ­https://
idrottsforum.org/sather140319/ (retrieved Aug. 14, 2021).
Sarmento, H., Anguera, M. T., Pereira, A., & Araújo, D. (­2018). Talent identification and devel-
opment in male football: a systematic review. Sports Medicine, 48, ­907–​­931.
Saward, C., Hulse, M., Morris, J. G., Goto, H., Sunderland, C., & Nevill, M. E. (­2020). Longitu-
dinal physical development of future professional male soccer players: implications for talent
identification and development? Frontiers in Sports & Active Living, 2, 578203.
 Talent identification and talent promotion 381
Schroepf, B., & Lames, M. (­2017). Career patterns in German football youth national ­teams–​­a
longitudinal study. International Journal of Sports Science & Coaching, 13(­3), ­405–​­414.
Sieghartsleitner, R., Zuber, C., Zibung, M., & Conzelmann, A. (­2019a). Science or coaches’
eye? – ​­Both! Beneficial collaboration of multidimensional measurements and coach assess-
ments for efficient talent selection in elite youth football. Journal of Sports Science & Medi-
cine, 18(­1), 32.
Sieghartsleitner, R., Zuber, C., Zibung, M., Charbonnet, B., & Conzelmann, A. (­2019b). Talent
selection in youth football: specific rather than general motor performance predicts future
player status of football talents. Current Issues in Sport Science, 4, 011.
Van Yperen, N. W. (­2009). Why some make it and others do not: identifying psychological
factors that predict career success in professional adult soccer. The Sport Psychologist, 23(­3),
­317–​­329.
Webb, T., Dicks, M., Brown, D. J., & O’Gorman, J. (­2020). An exploration of young professional
football players’ perceptions of the talent development process in England. Sport Manage-
ment Review, 23(­3), ­536–​­547.
Wilkinson, R. J. (­2021). A literature review exploring the mental health issues in academy foot-
ball players following career termination due to deselection or injury and how counselling
could support future players. Counselling & Psychotherapy Research, 21, ­859–​­868.
Williams, A. M., Ford, P. R., & Drust, B. (­2020). Talent identification and development in soc-
cer since the millennium. Journal of Sports Sciences, 38(­­11–​­12), ­1199–​­1210.
Williams, A. M., & Reilly, T. (­2000). Talent identification and development in soccer. Journal of
Sports Sciences, 18, ­657–​­667.
Zuber, C., Zibung, M., & Conzelmann, A. (­2014). Motivational patterns as an instrument for pre-
dicting success in promising young football players. Journal of Sports Sciences, 33(­2), ­160–​­168.
Zuber, C., Zibung, M., & Conzelmann, A. (­2016). Holistic pattern as an instrument for pre-
dicting the performance of promising young soccer ­players – ​­a ­3-​­years longitudinal study.
Frontiers in Psychology, 7, 1089.
23 Modern approaches to scouting and
recruitment
David Piggott and Bob Muir

Introduction
Talent scouts are an essential part of talent identification and development systems
in all sports though their effectiveness has often been questioned by academics
(­Baker et al., 2019). In soccer, relatively little is known about the activities of scouts
or the processes by which they reach judgements about talent (­B ergkamp et al.,
2021). Nevertheless, one emerging recommendation in the literature is that more
structured systems with more explicit reasoning may support more accurate predic-
tions (­B ergkamp et al., 2021; Johnston & Baker, 2020; Larkin & O’Connor, 2017). In
this chapter, we describe and explain the process of developing and delivering such a
system for identifying young soccer players for international selection. Specifically,
we describe a process that took place within the ‘­Team Strategy and Performance’
department at the English FA (­T he FA) between 2018 and 2020, initiated by the
then ‘­Player Insights’ team, who was responsible for collecting information about
players to inform selection and development decisions. Some of the most important
information used in this process came from a team of dedicated scouts, or ‘­t alent
reporters’1, whose main role was to attend live games and submit reports on a small
number of players who were under consideration for international selection. Talent
reporters typically covered games in either the ‘­youth development phase’ (­Y DP,
­U15s–​­U17s) or the ‘­professional development phase’ (­PDP, U18s and U23s) and made
reports for the men’s pathway squads (­­U15–​­U21). During the lifetime of the pro-
ject, the first author (­David Piggott) was a f­ ull-​­time employee in the Player Insights
department and the second author (­Bob Muir) was a consultant commissioned to
design and deliver a Continuing Professional Development (­CPD) programme for
talent reporters.

Understanding scouts and scouting

Despite their centrality and obvious importance in the talent identification process,
the activities of scouts have been almost entirely overlooked by academics. To our

1 In international soccer, we use the term ‘­t alent reporter’ as opposed to ‘­s cout’ in recognition of the
different roles they perform. In club soccer, a ‘­s cout’ is searching for talent: they are seeking to detect
or identify talent. In international soccer, players of interest have already had some level of talent
confirmed by the academy system, so a ‘­t alent reporter’s’ role is to describe, in more detail, the specific
nature of the talent they see and consider if this will transfer into senior international soccer.

DOI: 10.4324/9781003148418-28
 Modern approaches to scouting and recruitment 383
knowledge, only three academic studies have sought to directly explore the views of
recruiters and scouts in professional soccer (­Bergkamp et al., 2021; Reeves et al., 2018;
Larkin & O’Connor, 2017), with a handful of others exploring the views and practices
of coaches, acting in a scouting capacity (­e.g., Christiensen, 2009; Jokuschies et al.,
2017; Lund & Sӧderstrӧm, 2017).
Reeves et al. (­2018) interviewed 37 professionals working across recruitment roles in
­category-​­one academies in the United Kingdom with the broad aim of understanding
the nature and function of their work. They revealed a reflective group of professionals
who had deep and extensive knowledge of the grassroots context; an awareness of bi-
ases towards early maturing players; and a holistic approach to talent prediction, based
on an attempt to consider (­albeit tacitly) multiple characteristics and environmental
factors (­e.g., a player’s family background). Similar conclusions were reached by Berg-
kamp et al. (­2021) in their survey of 125 recruiters working in professional soccer in the
Netherlands. They found that scouts working across the age groups tended towards a
structured approach to making predictions, combining assessment of different attrib-
utes (­principally technical skills), but ultimately making holistic appraisals in the final
analysis. These scouts, too, seemed to be aware of the dangers of making early assess-
ments based on physical attributes, ranking them well below technical, tactical, and
­psycho-​­social attributes when evaluating adolescent players. Finally, in their Delphi
poll of 20 selectors working in the regional system in Australia, Larkin and O’Connor
(­2017) found that selectors made holistic appraisals based on an assessment of a wider
range of technical, tactical, and psychological attributes. Perhaps due to the age of the
players involved (­i.e., U13), they ranked technical skills as relatively more important
and tended to place less value on physical attributes.
This portrait is highly consistent with the popular work of British journalist,
Michael Calvin, whose seminal book, The Nowhere Men (­Calvin, 2014), is another im-
portant source of information about scouts working in English soccer. Calvin outlines
an industry in transition, as ‘­big data’ and video analysts steadily invade the territory
that scouts have occupied for years. The scouts with whom Calvin spent time were
underpaid (­relative to other professionals in clubs), increasingly anxious about the
future of their industry and increasingly insecure and marginal, despite their expe-
rience, passion, and undoubted skill. Calvin also detailed the careful record keeping
of many scouts, a practice that enabled them to engage in thoughtful reflection about
their successes and ‘­the ones that got away’. These reflective capacities are the same as
those documented by Reeves et al. (­2018) though they also cast some doubt as to the
degree to which these reflections are systematic and, therefore, of limited impact in a
wider talent ID system.
An important conclusion common to these studies is that the deeper processes and
‘­decision rules’ applied by scouts to make predictions are largely implicit and, there-
fore, difficult to scrutinise. Whilst many scouts use structures such as checklists and
forms to help increase the reliability of assessments, the process by which the more
general holistic appraisal is m ­ ade – how
​­ they weight and combine the assessment of
a variety of attributes, in c­ ontext – seems
​­ to be tacit and, therefore, potentially in-
consistent (­Bergkamp et al., 2021). A strong recommendation from this small body
of research, therefore, is that talent ID systems in soccer should seek to adopt a more
structured and consistent approach to scouting, with more explicit rules and reason-
ing applied to d ­ ecision-​­making to enable more effective critical appraisal (­also see
Johnston & Baker, 2020).
384 David Piggott and Bob Muir
The accounts offered by these researchers and authors certainly resonate with our
own experiences in interacting directly with international talent reporters in our own
programme, and indirectly with scouts and recruiters from a range of professional
clubs (­through delivery on numerous FA talent ID courses). In our experience, scouts
are often aware of the biases they bring to the job (­e.g., Christiensen, 2009); are in-
creasingly (­if tacitly) knowledgeable about the multidimensional indicators of talent
or potential (­e.g., Jokuschies et al., 2017); and are often active in seeking support and
professional development to refine their craft. It was with an attitude of openness and
optimism, then, that we started this project: one in which we considered the scouts
to be the subject ‘­experts’ with a very deliberate aim of drawing on (­and drawing out)
their tacit knowledge to inform a new system of reporting on talent. The project also
aimed to address the recommendations from the research, in supporting scouts (­or
talent reporters) to develop and more explicit and consistent approach to the complex
process of identifying future international players.

The problem situation

At the time we began the project in the summer of 2018, a new ‘­Player Insights’ team
had recently been created at The FA. This team was tasked with creating systems
for collecting and making sense of a wider set of data about players. This included
data generated from a range of internal activities, such as physical testing data and
psycho-​­
­ behavioural notes, but also included externally generated performance
analysis data and scouting reports from live games. The Player Insights team was,
therefore, positioned at the ‘­hub’ of a wheel, with multiple forms of player data be-
ing fed into coaches (­who still made executive decisions over squad selection) with
the support of ‘­phase leads’ who oversaw selection meetings for each age group and
constantly updated the data available to coaches. In this sense, the team had been
created in line with recent recommendations improving talent forecasting (­cf., John-
ston & Baker, 2020).
As the flow of player data into and through the department began to increase, the
live game reporting was still deemed to be of central importance to the d ­ ecision-​
m
­ aking process. Coaches were keen to know how players were performing week
to week, and keen to pick up on ‘­soft intelligence’ that a talent reporter may have
gleaned from being present at the game (­e.g., specific instructions a coach may have
given, or a chat with a parent that might reveal a player was about to move clubs).
The systems for recording and reporting this information, however, had changed al-
most annually over the preceding 3 or 4 years, and it was felt that the system was not
supporting or enabling talent reporters to best use their considerable professional
resources.
Like many scouting systems that operate in clubs, the existing system was a mixture
of numerical scales (­to rate a player’s abilities in different domains), often referenced
to an ideal type ‘­positional profile’ (­cf., Towlson et al., 2019), followed by summary
statements where talent reporters were asked to make a holistic judgement about a
player’s potential (­Christiensen, 2009). This would typically lead to unhelpful abstract
generalisations of a player’s ability, such as ‘­he has a good first touch’ or ‘­moves well
for a big lad’. This type of system, applied in international soccer, was deemed prob-
lematic for two main reasons, which we summarise below as: (­1) the future game prob-
lem and (­2) the surrogate selector problem.
 Modern approaches to scouting and recruitment 385
The future game problem
Systems that reference positional profiles, with scales for ranking key abilities (­e.g.,
a ­full-​­back needs: to be able to cross the ball, stamina, 1v1 defensive skills), assume
that current senior players and the skills they possess, are appropriate ‘­models’ for the
players of the future. However, as the FA’s own Dick Bate noted over a decade ago:
‘­The game will evolve dramatically over the next two decades and it is critical that
those responsible for the development of our young players prepare for what is ahead.
Thinking forward and devising both programmes and practice to equip our players
for the future is paramount now’ (­The FA, 2010, p ­ . 20). The ongoing evolution of the
game is clear in the scientific research (­Harper et al., 2020), with significant changes
to, for example, the physical performance of players in different positions (­Bush et al.,
2015). Looking for current senior qualities in the players of the future, when the future
game will pose different challenges, seems to be based on flawed logic. This is one
of the many factors that makes forecasting talent very difficult (­Baker et al., 2019;
Johnston & Baker, 2020), and, therefore, posed a challenge to us in developing the new
system. We explain our response to this challenge in the next section.

The surrogate selector problem

In asking talent reporters to write summarised holistic judgements about players
(­irrespective of the quality or veracity of those judgements), they interfere with the
selector’s ability to come to informed judgements themselves. In club scouting, this is
often necessary given the large number of players they will have under consideration.
Coaches and heads of recruitment do not have time to scrutinise hundreds of reports
and prefer a simple ‘­referral’ from a scout: should we bring them in for a trial or not?
In international selection, however, there are far fewer players in the frame, and inter-
national coaches have far more time to carefully consider detailed reports (­at the FA,
coaches were also heavily involved in talent reporting). Moreover, it is arguably a more
difficult task to identify international potential from a homogenous group of highly
talented players, than to identify a talented player in a grassroots setting (­Bergkamp
et al., 2019). Hence, more detailed, and carefully compiled reports, are necessary to
make this difficult distinction between a potential professional and a potential inter-
national player.
In addition to these specific problems, it was also the case that the talent reporters
had developed their own style of reporting, leading to a high degree of variability in
the length and quality of reports. Some of these ‘­styles’ were preferred by coaches;
others were not. So, in summary, this is the situation we found ourselves in as we em-
barked on the project: (­1) we had a varied group of highly experienced and expert tal-
ent reporters who were constrained and frustrated by the current systems; (­2) we had
to find a way to overcome the ‘­future game’ and ‘­surrogate selector’ problems; and (­3)
we had to develop a system and framework that enabled the talent reporters to express
their individual expertise but with a higher degree of consistency across the group.

The solution: CPD and a framework for talent reporting

As noted above, the brief for the development of a new system was clear: we needed
to help create a more consistent method of reporting that generated richer, more
386 David Piggott and Bob Muir
detailed, contextualised information to assist coach ­decision-​­making in the selection
and development of youth international players. It was also clear that, as two people
with no prior experience in scouting, we would need to draw heavily on the expertise of
the talent reporters to inform this new system. We, therefore, couched the programme
of work within a CPD programme for the talent reporters, who were grateful for the
investment in them and eager to have a say in the development of the new system.

Design principles
In designing the CPD programme, we made several informed assumptions about the
talent reporters. First, we assumed they had a high level of professional ­expertise – ​­deep
tacit knowledge about talent, but also about the context and mechanisms surrounding
that talent in the English professional system (­Christiensen, 2009; Lund & Sӧderstrӧm,
2017; Reeves et al., 2018) – ​­that was not being maximised under the current system.
Second, we assumed that the talent reporters could and would respond positively to
educational activities that would help them become more aware of the ‘­biases’ influ-
encing their judgements (­cf., Mann & van Ginneken, 2017). And third, we knew that
programmes with similar goals, working to create more consistent and coherent talent
selection criteria among scouts in international soccer, had led to successful outcomes
(­cf., Jokuschies et al., 2017). Working with these assumptions, we drew on Gary Klein’s
triple path model of insight generation (­K lein, 2013) in designing the programme.
Klein (­2013) argues that when organisations try to improve performance, they often
focus on ‘­error reduction’ strategies (­e.g., introducing standards, controls, checklists,
and procedures), and neglect ‘­insight generation’ strategies. Insight generation, by
contrast, involves raising awareness of and discussing connections and contradictions
between views and ‘­changing the frame’ (­ways of looking at players), to replace flawed
explanatory stories with better ones. In our context, we, therefore, aimed not to in-
troduce new scouting forms and checklists, but to create opportunities for experts
to generate new insights about talent, and better explanations for how international
potential comes to be fulfilled (­or not).

Programme delivery
The CPD programme was delivered over an ­18-​­month period via ­semi-​­regular week-
end workshops (­i.e., every ­2 –​­3 months) and occasional larger events (­e.g., visits to in-
ternational camps and tournaments). The participants were 16 male p ­ art-​­time talent
reporters working for the FA, all of whom held a range of ­full-​­time and ­part-​­time jobs
in addition to their reporting roles. Among the group, there were teachers, sales ex-
ecutives, coaches, taxi drivers, and university and college lecturers. All had extensive
coaching and scouting qualifications and experience working as scouts in the profes-
sional game, often for multiple Premier League clubs. The CPD programme was split
into three broad phases, outlined in ­Figure 23.1.
In the first phase, our goal was to get to know the group, to share stories reflecting
beliefs and ideas about international talent, and to cultivate curiosity based on explor-
ing the differences in ideas (­contradictions). Towards the end of the phase, we created
very deliberate opportunities to notice clashes and contradictions by asking multiple
reporters to report on the same player, without consulting, before juxtaposing their re-
ports in the room. In this way, these early sessions served to surface and problematise
 Modern approaches to scouting and recruitment 387

Phase 3: Applying
and refining the
framework
Phase 2: Creating the • Developing a new
reporting form based
framework on the framework
• Discussing the aims of • Reporting at events
a framework and comparing
• Agreeing on the reports
framework • Generating good
Phase 1: Cultivating • Creating position- practice examples
curiosity specific resources
• Sharing ideas about
talent and potential
• Pointing out
contradictions and
curiosities

­Figure 23.1 A ­three-​­phase approach to talent reporter CPD.

the various biases and heuristics (­some helpful, some unhelpful) that the talent report-
ers held (­Miller et al., 2012).
By the second phase of the programme, we had developed some trust and rapport
with the group, surfaced some of the main socially constructed theories (­and biases
and heuristics) used by the reporters (­Christensen, 2009), and provoked some curios-
ity in the differences that existed between their emerging judgements. We, therefore,
agreed that it would be helpful to ­co-​­create a framework to help the group collectively
channel its insights and reduce inconsistences in reporting (­again, in line with the rec-
ommendations from the literature).

Developing the talent reporting framework

As we approached the challenge of developing a new framework, we had the future
game problem and surrogate selector problems in mind. We wanted the talent report-
ers to be able to communicate their deep knowledge about players and their potential
without having to do so in a simplified summarised judgement. We also wanted to
encourage the reporters to observe players in a different way to that informed by the
‘­player profile’ model, which runs afoul of the future game problem. The core idea we
introduced and discussed in phase 2, then, was very fundamental: it took us back to
a discussion of the basic demands of soccer and led us to a new, broader definition of
talent as ‘­the emerging ability to find effective solutions to the problems of the game’.
This thinking was directly influenced by the American philosopher, Bernard Suits,
and his famous definition of games as ‘­the voluntary attempt to overcome unnecessary
obstacles’. Suits (­1978) defines games as g­ oal-​­directed activities with rules (­the unneces-
sary obstacles) that prevent you from achieving the goal in the most efficient way. Games
388 David Piggott and Bob Muir

OUT OF POSSESSION IN POSSESSION

When they are out When they are in

of possession and in Q1.What performance possession and
the low block? problems does the player building the attack?
have to overcome across
different moments in the
game?
When they are out When they are in
Q3. How successful
of possession Q2. What
possession and
were their performance
and in the performance solutions creating the
solutions in responding
medium block? did the player create to the performance attack?
(their actions before, problems relative to their
during & after, and, on, role, position, state &
around & away from stage of the game
the ball)? & other contextual When they are in
When defending
factors? possession and
in the high press?
finishing the attack?

­Figure 23.2 The new talent reporter framework.

therefore present players with performance problems, that emerge in the conflict between
goals, rules, and opposition. In the early 1980s, Len Almond took this idea and used it
to classify sports into families, based on similarity in the goals, rules, and thus problems
they pose (­Harvey et al., 2017). For example, all invasion games require players, when in
possession, to solve the problems of ‘­keeping the ball’, ‘­moving it up the field/­court’, and
‘­penetrating a compact defensive unit to score in a central goal’ (­Mitchell et al., 2013). We
have used this idea elsewhere to support coaches to deepen their understanding of their
sports (­Piggott & Jones, 2020), and felt it could be usefully transferred to help us solve
the future game problem. So, we took Suits’ idea of sport as a ­problem-​­solving activity
and combined it with an existing framework that was used widely at the FA to classify
six ‘­moments of the game’ (­The FA, 2021) to build the framework (­see F ­ igure 23.2).
The framework was developed through a 2­ -​­day consultation with the group of talent
reporters who developed drafts and experimented with it in a live reporting setting.
The framework (­­Figure 23.2) asks reporters to observe and locate player’s actions in
different moments (­three in possession, three out of possession) in relation to the per-
formance problems they faced (­Q1) and describe the solutions they created, both on
and off the ball (­Q2), before judging their success in context (­Q3).
The basic idea of the framework, then, was that it invited a different way of thinking
about talent or potential that wasn’t bound to a fixed profile; it simply asked reporters
to consider how well players solved the problems of the game, in context (­e.g., relative to
their stage of development, the quality of the opposition, and the state of the game). We
reasoned that, as the problems of the game change in the future, the best players would be
those that could find the best solutions. This was our s­ hort-​­hand definition of potential,
and one that is referenced by international coaches elsewhere (­cf., Jokuschies et al., 2017).
As we began to experiment with the framework the first thing we noticed is that it invited
reporters to observe in much more detail than they had previously. For example, where a
scout’s attention may naturally drift away from a central defender during the ‘­finish the
 Modern approaches to scouting and recruitment 389
attack’ moment, the new framework required them to continuously observe the individu-
al’s actions throughout a game. Because talent reporters were frequently required to report
on two or three players in a game, the new framework posed a serious challenge to the tal-
ent reports’ ­attention-​­switching and ­note-​­taking abilities. Despite the challenge it posed,
early attempts yielded promising reports and there was a collective belief that we could get
faster and more efficient in applying the new framework as it became internalised.
An additional resource we created during phase 2 was a set of p ­ osition-​­specific per-
formance problems to ensure we were observing players in broadly the same way (­s ee
Q1 in F ­ igure 23.2). These p­ osition-​­specific problems were generated through small
­3 -​­hr workshops, conducted with three to four talent reporters, collectively observ-
ing video clips of a single position (­across all moments), with talent reporters noting
down and discussing the main performance problems the players faced. The goal of
each workshop was to agree on a small number of draft problems in each moment.
An example of the output generated from the workshops is presented in ­Figure 23.3.

Reporting with the framework

In the third and final phase of the programme, we ran events where the talent reporters
applied the new framework in live reporting situations. Typically, this would involve
groups of three reporters attending a game, watching the same player independently
(­equipped with F ­ igures 23.2 and 23.3, printed in small cards as an aide memoir), then
working together after the game to construct a joint report, based on a shared un-
derstanding of the principles. These discussions would often generate new insights
through making connections, noticing contradictions, and encouraging reporters to
consider players from different perspectives (­K lein, 2013).
­Table 23.1 contains an example report that was produced after one of these events.
In this case, it is a short report on a YDP player (­these reports were typically shorter
as it is typical to report on more players per game in the YDP). The report is clearly

Performance problems: how does the centre back...

LOW BLOCK
● Position themselves (relative to the ball, team-mates and BUILD THE ATTACK
opponents) in order to prevent penetrative passes and ● Find space and maintain possession against pressure?
runs? ● Position themselves (relative to the ball, team-mates and
● Prevent direct opponent getting clean contact on the ball opponents) in order to receive and play forwards?
in areas of threat?

MID BLOCK 5/6

● Help to set effective line depth and spacing between CREATE THE ATTACK
lines? ● Position themselves (relative to the ball, team-mates and
● Position themselves in order to force the ball away from opponents) in order to be able to recycle the ball and
areas of greatest threat? prevent counter attacks?
● Prevent direct opponents from receiving the ball facing ● Support team-mates to disrupt the opposition block?
the goal?

HIGH PRESS
● Position themselves (relative to the ball, team-mates and FINISH THE ATTACK
opponents) in order to prevent the balls between/behind ● Position themselves (relative to the ball, teammates and
lines? opponents) in order to be able to recycle the ball and
● Help to set effective line depth and spacing between prevent counter attacks?
lines?

­Figure 23.3 An example of performance problems by position (­c entral defender).

390 David Piggott and Bob Muir
broken down into sections for: match details and context; i­n-​­possession actions; ­out-­​
­­of-​­possession actions; and a summary and recommendation. The additional section
labelled ‘­­4-​­corner sensemaking’ was a section in which the reporters we asked to inter-
pret player actions through a developmental lens: in short, were some of the players’
actions strongly influenced by their state and stage of development (­physical, psycho-
logical, social, and technical)? This was a difficult section to complete and relied heav-
ily on reporters’ knowledge of adolescent development and their ability to observe
these characteristics in the field (­e.g., that a player might be close to peak growth,
based on observation of limb length and torso length and breadth).
In the final ­section – ​­the summary and ­recommendation – ​­the summary is intended
to capture the main points from the report, and the recommendation is made against
four categories: recommend (­this individual clearly has potential to be an international
player); monitor + (­this individual has potential that needs to be confirmed); monitor (­this
player has potential but there are reasons why it is not appropriate to report on him/­her
immediately); and not recommend (­there were no signs that this individual has potential
to be an international player). In the case of the player featured in the report above, the
recommendation was ‘­monitor’ because they had signs of potential (­positioning, con-
centration, and leadership) but made mistakes that could have been due to rapid growth,
a situation that would not change if they were observed again in the following month.
By the end of the programme, the Player Insights team were pleased with the progress
made in reforming the talent reporting system. As a direct illustration of the impact of
the system on reporting quality, ­Table 23.2 compares extracts from two reports gener-
ated on the same player, under the old and new systems. Hopefully, it is clear how much
more useful and specific information is present in the second report. Again, to repeat
what we said in the introductory sections, the flaws of the first report reflect the system,
not the resources or capability of the individual reporters. When provided with support
and a clear and flexible ­framework – one ​­ that encouraged them to make use of their
deep personal ­resources – ​­we found that talent reporters responded very positively.

Future directions and conclusions

In line with recommendations from the extant literature on scouting in soccer (­Bergkamp
et al., 2021), our project aimed to support talent reporters to raise their extensive tacit
knowledge to be more explicit and to develop and apply a flexible framework to create
a more consistent, systematic, and detailed approach to talent assessment. In helping
scouts and selectors to better understand their own processes and theories about talent
and potential, we aimed to create a ‘­method for checking the accuracy of our forecasts’
(­Johnston & Baker, 2020, ­p. 7). This process of recording forecasts and the reasoning
behind them as a basis for later scrutiny and improvement was in its infancy at the FA.
Forecasting in this context is a complex business involving the assessment of multiple
sources of information (­scouting report being just one among many) about multiple
interacting variables by a range of professionals over developmental time. There can
be, of course, no algorithm for prediction in such circumstances, so the best we can do
is to create a framework to support the consistent collection and interpretation of in-
formation about players, use it to make predictions, and then revisit those predictions
to test and adjust the theories on which they are based.
 Modern approaches to scouting and recruitment 391
­Table 23.1 An example short report (­for a YDP player) [team names redacted]

Player details Billy Tackle* (­born 2005, U15) #5 (­­left-​­sided CD)

*this is a pseudonym

Match details and This report covers performances in 2 × 5­ 0-​­min group games in the
context premier league U15s international tournament. The first a ­hard-​
f­ ought ­2 –​­1 win against Derby and the second a ­must-​­w in ­3 –​­0
performance against Olympiakos to win a place in the ­semi-​­final. The
pitch was slick and a little heavy in both games.
In possession Finish the attack/­create the attack
Billy found good support positions, always available to recycle when
on the left and playing some dangerous deep crosses into the box on
occasion.
Build the attack
Billy showed good composure under pressure, often playing the right
pass and showing a good range of passing on his left side. He only
misplaced two passes, but one was in a dangerous position. He also
showed an ability to s­ tep-​­in and break lines when appropriate. In the
Olympiakos game, it was his header, ­pick-​­up and calm pass (­under
pressure) to the right that started the ­counter-​­attack for the first goal.
Out of possession High press
Billy marshals his defence well, maintaining and policing the line depth
and communicating constantly. When in the high press, he moves
well in relation to the ball and is almost constantly in a good position
to respond to direct balls (­i.e., ­side-​­on body position, tracking the
opposition #9).
­M id-​­block
Billy showed a tendency to ­step-​­in aggressively to shut out passed
through the middle or into the opposition CF/­10. He misjudged this
a few times and was left exposed, with teammates having to cover
behind.
Low block
Here he showed excellent bravery and determination to win defensive
headers, block shots and organised the line well. He was occasionally
caught out in 1v1s, especially against Derby’s fast and strong CF,
who was able to ‘­pin and spin’ on Billy twice. He also struggled when
squared up 1v1, failing to stop two shots on goal.
­4 -​­Corner Billy looks like he is around peak growth (­upright and awkward in his
sensemaking movements), which may explain his aggression and perception of risk
(­what did you when attacking balls in midfield, and also his lack of mobility when in
notice that 1v1s. This needs to be confirmed, but if it is the case it may be worth
helps to explain waiting ­3 –​­6
the solutions months before reporting on him again.
reported on
above?)
Summary and Billy showed good bravery and leadership in these games, was calm
recommendation under pressure with the ball and determined in his ­low-​­block
defending. His positioning and concentration were always good, but
he was too aggressive in going to meet the ball on occasion and got
caught out. His 1v1 defending was the main weakness but his mobility
may improve with time.
Recommendation (­on this occasion): Monitor
(­­Recommend – ​­Monitor + – ​­Monitor – ​­Not recommend)
392 David Piggott and Bob Muir
­Table 23.2 Extracts of reports of the same player (­U21 #9) under the old and new systems

System Old New

In possession Movement was very good. Build the attack

Great pace and sharp in his From a high central position, he tended to
movement but didn’t quite either drift into space between lines to
come off for him. receive or make sharp i­ nside-​­out diagonal
Pace and reactions both ways runs between CDs and FBs. Early in
are excellent. He was a key the game the timing of these runs was
outlet over the top and in excellent, and he frequently received in
the channels as soon as they threatening positions in the final third,
won the ball but the quality protected the ball and won two free kicks in
into him wasn’t great. dangerous areas.
Out of As a striker he was isolated High press
possession and led the line well; his His team rarely attempted to press high up
desire to close down and the pitch, except when they went behind
defend was good. in the last 15 min. He occupied a central
position, loosely screening the ball to stop
penetration through the centre. Really this
was token pressure and he rarely pressed
from behind once the ball had been played
into midfield. When the team went behind
and (­another CF) came on to make a front
two, he closed down with much greater
intensity, forcing the ball back to the GK
who turned the ball over twice as a result.

The framework we developed (­which is still very much in use) offers a basis for
such consistent observation across a large team of professionals involved in the tal-
ent selection process. We offer this account as potential inspiration and illustration
for other national associations and clubs seeking to invest in the development of
scouts. It will take many years for such systems to mature and for predictions to be
scrutinised (­e.g. even in the case of the most precocious players, such as Jude Bell-
ingham, there is a 5­ -​­year gap between our initial report and his senior England se-
lection). Future evaluation work must, therefore, be planned and undertaken across
long periods of time (­i.e., ­5 –​­10 years, at least). Moreover, because of the complexity
of the decisions and d ­ ecision-​­making process, evaluation methodologies need to be
sensitive enough to unpick the m ­ ulti-​­layered mechanisms at play (­how sources of
information influence thinking) and the outcome patterns that emerge (­decisions
about selection) (­Pawson, 2013). Whilst the exploratory research focusing on the
practices and processes of soccer scouts has been useful, we would also argue that
future research needs to locate the activity of scouts in a much broader context.
Almost all professional clubs and major national associations generate and have
access to extensive multifaceted data on players, with scouting reports representing
just one vector among many.
 Modern approaches to scouting and recruitment 393
References
Baker, J., Wattie, N., & Schorer, J. (­2019). A proposed conceptualization of talent in sport: the
first step in a long and winding road. Psychology of Sport and Exercise, 43, ­27–​­33.
Bergkamp, T., Frencken, W., Neissen, S., Mejer, R., & den Hartigh, R. (­2021). How soc-
cer scouts identify talented players. European Journal of Sport Science. https://­doi.
org/­10.1080/­17461391.2021.1916081
Bergkamp, T., Nielssen, A., den Hartigh, R., Frencken, W., & Meijer, R. (­2019). Methodological
issues in soccer talent identification research. Sports Medicine, 49(­9), ­1317–​­1335.
Bush, M., Barnes, C., Archer, D., Hogg, B., & Bradley, P. (­2015). Evolution of match perfor-
mance parameters for various playing positions in the English premier league. Human Move-
ment Science, 39, ­1–​­11.
Calvin, M. (­2014). The Nowhere Men: The Unknown Story of Football’s True Talent Spotters.
London: Penguin Books.
Christiensen, M. (­2009). “­A n eye for talent”: talent identification and the “­practical sense” of
­top-​­level soccer coaches. Sociology of Sport Journal, 26, ­365–​­382.
Harper, D., Sandford, G., Clubb, J., Young, M., Taberner, M., Rhodes, D., Carling, C., & Keily,
J. (­2020). Elite football of 2030 will not be the same as that of 2020: what has evolved and what
needs to evolve? Scandinavian Journal of Medicine & Sport Science, 31, ­493–​­494.
Harvey, S., Pill, S., & Almond, L. (­2017). Old wine in new bottles: a response to claims that
teaching games of understanding was not developed as a theoretically based pedagogical
framework. Physical Education & Sport Pedagogy, 23(­2), 166–180.
Johnston, K., & Baker, J. (­2020). Waste reduction strategies: factors affecting talent wastage
and the efficacy of talent selection in sport. Frontiers in Psychology, 10(­2925), ­2 –​­11.
Jokuschies, N., Gut, V., & Conzelmann, A. (­2017). Systematising coaches’ ‘­eye for talent’: player
assessments based on expert coaches’ subjective talent criteria in t­op-​­level youth soccer.
International Journal of Sport Science & Coaching, 12(­5), ­565–​­576.
Klein, G. (­2013). Seeing What Others don’t: The Remarkable Ways We Gain Insights. New York:
Public Affairs.
Larkin, P., & O’Connor, D. (­2017). Talent identification and recruitment in youth soccer: re-
cruiters’ perceptions of the key attributes for player recruitment. PLoS ONE, 12(­4), e0175716.
Lund, S., & Sӧderstrӧm, T. (­2017). To see or not to see: talent identification in the Swedish foot-
ball association. Sociology of Sport Journal, 34, ­248–​­258.
Mann, D., & van Ginneken, P. (­2017). A ­ ge-​­ordered shirt numbering reduces the selection bias
associated with relative age effect. Journal of Sport Sciences, 35(­8), ­784–​­790.
Miller, P., Rowe, L., Cronin, C., & Bampouras, T. (­2012). Heoristic reasoning and the observer’s
view: the influence of example availability on ­ad-​­hoc frequency judgements in sport. Journal
of Applied Sport Psychology, 24, ­290–​­302.
Mitchell, S., Oslin, J., & Griffin, L. (­2013). Teaching Sports Concepts and Skills. Champaign, IL:
Human Kinetics.
Pawson, R. (­2013). The Science of Evaluation: A Realist Manifesto. London: Sage.
Piggott, D., & Jones, R. (­2020). The practical application of immersive g­ ames-​­based narratives,
in S. Pill (­Ed.), Perspectives on ­G ames-​­based Coaching. London: Routledge.
Reeves, M., Littlewood, M., McRobert, A., & Roberts, S. (­2018). The nature and function of
talent identification in ­junior-​­elite football in English category one academies. Soccer & Soci-
ety, 19(­8), ­1122–​­1134.
Suits, B. (­1978). The Grasshopper: Games, Life and Utopia. Ontario, CA: Broadview Press.
The FA. (­2010). The Future Game: The FA’s Guide for Young Player Development. London: The
FA.
394 David Piggott and Bob Muir
The FA. (­2021). The England DNA: How We Play. Burton: The FA. https://­thebootroom.thefa.
com/­resources/­­england-​­dna/­­how-­​­­we-​­play
Towlson, C., Cope, E., Perry, J., Court, D., & Levett, N. (­2019). Practitioners’ m
­ ulti-​­disciplinary
perspectives of soccer talent according to phase of development and playing position. Inter-
national Journal of Sport Science & Coaching, 14(­4), ­528–​­540.
Section F

Some Key Organizational

Roles at Clubs
24 Working as a director of sports
science or ­high-​­performance director
Tony Strudwick

Introduction
Soccer is played by 250 million people in more than 200 countries making it the world’s
most popular sport. The worldwide influence and daily interest attract e­ ver-​­increasing
attention and intelligent focus into the sport. Many academic institutions around the
world now offer programmes of study specifically related to soccer. In an applied set-
ting, a major shift has occurred towards scientific methods of preparing soccer players
for competition. Many soccer teams now routinely employ practitioners from the vari-
ous ­sub-​­disciplines of sports science with the aim of improving sporting performance.
Throughout the past few decades, the demand for soccer scientists and performance
directors has been growing because of the e­ ver-​­increasing focus in the soccer world
on achieving the best results possible. The establishment of advanced scientific sup-
port models is evidence that high performance is being taken seriously. Although the
field of sport management has been widely defined, the ­sub-​­field of managing ­h igh-​
p
­ erformance sports is relatively new and has emerged from elite sports (­Sotiriadou &
De Bosscher, 2018). A multitude of titles have been assigned to those practitioners
leading and managing ­h igh-​­performance departments, such as the Head of Medical
Services, Director of Performance, Human Performance Manager, and Head of Per-
formance. For the purpose of this chapter, the Director of Sports Science and ­High-​
P
­ erformance Director will be used to identify those individuals leading and managing
departments and performance processes.
Ultimately, the roles and functions of support staff have been examined more
closely, to the benefit of the soccer profession. The increase in ­qualification-​­led em-
ployment has led to an examination of the traditional role of the head coach and sup-
port team. To facilitate these changes, a new era of ­h igh-​­performance directors and
managers have evolved. These practitioners with a diverse range of skills are trained
and educated to think and work in a multidisciplinary environment. Moreover, these
practitioners have the relevant skills for appreciating the coaching process and its as-
sociated elements.
The key objective of this chapter is to explore the role of Director of Sports Science/­
H
­ igh-​­Performance Director and highlight some of the key issues involved in leading
and managing contemporary h ­ igh-​­performance when working at a professional club
or with a national team. This chapter also focuses on translating into practice the re-
quirements of leading and managing ­h igh-​­performance teams, with special reference
to the cultural and organisational structures pertinent to real working practices in
soccer.

DOI: 10.4324/9781003148418-30
398 Tony Strudwick
The rise of soccer science and sports medicine
­ n-​­field Soccer performance has always been the chief concern for all soccer clubs
O
throughout the professional era. The methods employed, however, have changed con-
siderably over the past few decades. Throughout the early professionalisation of the
sport, the players were mostly left in the charge of the trainer. Trainers were responsi-
ble for maintaining both discipline and physical fitness. Initially, besides having fitness
duties, the trainer provided ­day-­​­­to-​­day medical care and treated and managed player
injuries. Initially, ideas on what constituted training for soccer players were limited,
and the first generation of trainers was largely made up of professional athletes and
athletic trainers. From the 1960s, soccer players were becoming increasingly critical
of the medical treatment they received, and players began to seek second opinions
outside their clubs without permission. Although the image of the soccer trainer with
a bucket and sponge has been both mythologised and derided, the role needs to be
seen in context. Moreover, it does provide insight into the history of the relationship
between soccer and medicine, as well as the evolution of soccer science in the profes-
sionalisation of the game (­Carter, 2010).
Throughout the later stages of the 21st Century, soccer clubs appointed doctors,
physiotherapists, soft tissue therapists, fitness coaches, and sports scientists to max-
imise player preparation. Over these years, the trainer began to take on a more phys-
iotherapeutic role and medical support teams increased in numbers and complexity.
Demand was growing for greater support services with greater accountability amongst
support staff.
In 1992 the establishment of the English Premier League signalled a change in the
relationship between soccer and science. Greater intensity emerged as the commer-
cialisation of soccer increased. The value of players increased exponentially, as did
financial rewards for staying in the Premier League. As a result, these developments
necessitated a greater investment in medical and scientific facilities and resources.
In many ways, little had changed from the dawn of professional soccer in the early
1900s. Clubs had always invested in the welfare of their players, but the nature of the
process and organisational structure was shaped by the prevailing cultural c­ ontext –​
c­ ommercial, soccer, and social (­Carter, 2016).
Contemporary players have now been exposed to scientific approaches in prepara-
tion for competition. Certainly, examples of best practices can be seen in Elite English
soccer. Coaching practice that for many years was based largely on tradition, emu-
lation, and intuition is now giving way to an approach based on scientific evidence.
This shift has resulted in ­better-​­informed practitioners working with teams, stronger
links with scientific institutes, and more coaches willing to accept the changing role
of sports science in elite soccer. More importantly, it is against this backdrop, that
through the evolution of soccer science and increased professionalisation, we witness
the emergence of Directors of Sports Science and ­High-​­Performance Directors.

The role of the ­high-​­performance director

With the need to maximise individual and team performance, H ­ igh-​­Performance
Directors are required to manage and identify the key parameters that are required
for elite participation. ­High-​­performance sport operates in a ­fast-​­paced, complex en-
vironment and the skills required for successful practitioners are multifaceted and
 Working as a director of sports science 399
­Table 24.1 Some of the key responsibilities of a ­High-​­Performance Director

Responsibilities

Provide leadership and strategic vision to team functions, including medical services, sports
science, psychology, and performance analysis.
Manage all stakeholders involved in the delivery of the performance strategy; ensuring all
stakeholders clearly understand their roles and responsibilities and that all are delivering to
the required standard.
Maintain an effective, collaborative, and continuous relationship with the management team,
sharing and ­co-​­creating on best practice methods and research that can be deployed across
the organisation and partners.
Oversee the delivery of a m­ ulti-​­disciplinary team approach to the management of ­long-​­term
athletic development considering injury management, player load and development.
Ensure the performance trajectory of the players is positively impacted by contemporary
research and innovation initiatives.
Understand and manage risk/­compliance requirements; be an expert in compliance and
protocol, ensure that the department abides by regulations and activities in scope and is
always compliant.
Champion continuous process improvement; drive operational efficiency and effectiveness by
identifying opportunities for improvement in processes and ways of working, establishing
measurement and KPIs where relevant.
Set, deliver, and report to senior management on the strategic and operational plans and
budgets for the performance team.

multidisciplinary. To make sense of the requirements of the ­High-​­Performance Direc-

tor in a sporting context, it is perhaps useful to define the components of the role that
are relevant in shaping the performance environment. While there are many areas of
focus when delivering ­h igh-​­performance services, the key responsibilities of the Direc-
tor role are provided in ­Table 24.1.
Successful soccer performance is undoubtedly multidisciplinary in nature. ­High-​
P
­ erformance Directors need to be aware of the physiological, biomechanical, psycho-
logical, nutritional, medical, and other types of issues that can affect competition.
When all these factors work as an integrated system, excellence in ­h igh-​­performance
soccer is possible. Coaching is about ­problem-​­solving. Practitioners who are trained
to think critically about all aspects of performance will gain an advantage over
competitors.
If the role of the coach is to assimilate information and drive the coaching process,
then the role of the ­High-​­Performance Director is to lead a team to monitor, manage,
record, and deliver performance insights. Just as modern coaches need to be famil-
iar with the significant contributions that sports science can offer, H
­ igh-​­Performance
Directors need to be familiar with the complexities of the demands of soccer and the
appropriate methods of communicating with athletes, coaches, and stakeholders in-
volved in elite participation. While many factors need to be considered when working
as a Director of Sports Science or a ­High-​­Performance Director, there are four key ar-
eas that need to be appreciated and understood to shape the performance environment:

• ­High-​­Performance;
• Sports Science;
• Talent Development;
• Organisational Culture.
400 Tony Strudwick
High performance
­ igh-​­performance can be considered as producing results above and beyond standard
H
norms over a ­long-​­term. High performance is used to describe a product that is faster,
more efficient, and superior in functioning than other products. In a sporting context,
high performance is competition at the highest level of participation, where the em-
phasis is on winning and success. A h ­ igh-​­performance culture is a set of behaviours
and norms that leads an organisation to achieve superior results. In other words, it’s a
culture that drives a ­h igh-​­performance organisation. In a ­h igh-​­performance sporting
environment, organisations offer training in specialised facilities, coaching, and skill
development and transition to higher levels of competition (­Rees et al., 2016). In addi-
tion, athletes operating within a h ­ igh-​­performance environment are offered advanced
sports science support to maximise individual and team performance to achieve the
best results possible.
The intensive training and frequent competition in elite soccer induce a high degree
of stress upon the player. An analysis of the stress and injuries that may result is helpful
in identifying risk factors associated with ­soccer-​­related activities. In addition, players
must meet the requirements of the game with a demonstration of appropriate coping
strategies. It is, therefore, prudent for the H ­ igh-​­Performance Director to focus on the
‘­­High-​­Performance Status’ of individual participants so that appropriate strategies
can be implemented to maximise performance. In addition, key metrics for perfor-
mance can be established and used as evidence to demonstrate the impact of service.
The underlying philosophy behind ‘­­High-​­Performance Status’ is that coping strat-
egy and overall success is reflected in a player’s ability to sustain the load associated
with training and ­match-​­play at the highest level. Clearly, the athlete and the environ-
ment per se are critical to achieving sustained success. Coaches and athletes need to
understand the ‘­Performance v Cost/­Benefit’ profile of elite participation and how to
manage/­m itigate these risks on a team and individual basis through proactive moni-
toring and the implementation of preventative strategies.
In introducing this approach to monitoring high performance, it is important to
identify the objectives most critical to success. Moreover, it is important to identify the
critical few metrics to track high performance and alignment. ­High-​­performance sta-
tus factors along with metrics used to track these parameters are listed in ­Table 24.2.
These parameters can also be used as individual and team selection criteria and form
a basis for squad selection and rotation. Additionally, there is a need to look at the
performance reliability of players, which is based on the following equation:
 Match Availability × Percentage time on pitch 
Performance Reliability =  
 1000 
This metric has been introduced because it represents a player’s ability to not only
cope with the demands of training but also of ­h igh-​­performance games. That is, it
reflects how constitutional factors of the athlete interact with how teams employ the
player during matches.

Sport science
Sports science is a discipline that studies the application of scientific principles and
techniques and has the aim of improving sporting performance. The study of sports
 Working as a director of sports science 401
­Table 24.2 ­High-​­performance status of elite players

­High-​­performance factors How the factor is measured

Remain injury free Days missed through injury

Capable of sustaining ­h igh-​­p erformance ­Work-​­rate profiles during elite ­match-​­play
work rates based on objective match analysis data
Capable of playing 50 games per season Games ­played – ​­Percentage used during ­i n-​
­season competition
Window of opportunity (­­22–​­30 years old) Player ­age – ​­number of playing seasons in
professional league
Capable of playing a game every 4 days over Number of days per game over 5 game period
a ­5-​­game period (­90 min played)
Ability to demonstrate sound recovery on Objective markers as employed by sports
objective markers science department
Demonstrate seasonal match availability of See equation below*
90%
Demonstrate seasonal training availability See equation below**
of 85%

Where:
* Squad availability match = 1­ 00 – ((#
​­ of matches absent/­Total no of matches) * 100)
** Squad availability training = 1­ 00 – ((#
​­ of training sessions absent/­Total no of training sessions) * 100)

science traditionally incorporates areas of physiology, psychology, and biomechan-

ics but also includes other topics such as performance analysis and nutrition. Sports
science also helps practitioners understand the physical and psychological effects of
sports, thereby providing the best techniques for a sport and the most appropriate
methods of preventing injuries to an athlete involved in the performance of the sport.
Key areas of research in soccer include the effect of nutrition and training on perfor-
mance and recovery from participation, the effect of training volume on the immune
system, the biomechanics and motor control of elite sporting performance, talent
identification and development, cognition and muscle function, and motivation and
mental toughness.
The application of soccer science has a ­self-​­evident part to play in improving soccer
performance. Important features of the performance model, such as devising training
programmes, monitoring performance, and establishing preparation for competition,
are informed by such knowledge. The primary role of sports science in elite soccer is
to utilise scientific principles to maximise individual performance and player availa-
bility. Clearly, the role of the Director of Sports Science is to manage the delivery of
the key components of the sports science model.

Talent development
In sports research, the process of talent development is discussed with the purpose of
producing athletes that can attain a consistent ­world-​­class level of performance (­Li
et al., 2014). Although the area of talent identification and development has been a
subject of research for over 50 years, definitive definitions of talent have rarely been
offered (­Tranckle, 2004). In the literature, it is widely believed that the likelihood of
becoming an elite performer depends on the presence of innate gifts. Moreover, talent
is the expression of innate gifts and is influenced by a series of internal and external
developmental processes (­Gagné, 1985).
402 Tony Strudwick
Much of the contemporary research on talent development has focused on individ-
ual athletes and their ­m icro-​­environment (­Henriksen et al., 2010). Researchers have
emphasised either innate prerequisites (­talent detection and selection) for excellence or
the amount and quality of training required to reach the highest level of elite partici-
pation (­talent development). While talent, innate abilities, and chance are recognised
(­Gagné, 1998, 2005) as significant elements to excellence, there is limited evidence to
support how these areas interact with each other.
More recently, the psychological perspective has been developed in a new trend
regarding talent development environment models and a social perspective in un-
derstanding athletic talent (­Stambulova, 2009). The focus shifts from the individual
athlete per se to the environment itself. Martindale et al. (­2005) introduced the term
Talent Development Environment (­TDE). TDE refers to all aspects of the coaching/­
learning situation and focuses on the coaching context. Using this approach, Martin-
dale et al. (­2005) identified five properties of effective TDEs:

• ­Long-​­term aims and methods clearly identified;

• ­Wide-​­ranging coherent support and messages;
• Emphasis on appropriate development rather than early selection;
• Individualised and ongoing development;
• An integrated, holistic, and systematic development.

The emphasis becomes not on identifying individual talent, but rather on how best
to develop talent (­Ivarsson et al., 2014). Moreover, the focus is on the interaction be-
tween the individual athletes and their environment. Henriksen (­2010) has applied a
holistic approach to talent development, which also considers the ­macro-​­environment
(­organisational culture and sports systems). By applying a holistic approach to talent
development, it is easier to understand the challenges associated with it, such as re-
cruitment, retention, and transitions (­Henriksen, 2010).
It is against this backdrop of contemporary research that m ­ odern-​­
day H
­ igh-​
P
­ erformance Directors and Directors of Sports Science need to appreciate the key
facets of talent development when shaping the h ­ igh-​­performance environment. Given
the exponential growth of emerging departments associated with talent development
and sports performance, there will be tensions and challenges in managing and co-
ordinating the input of each area. The ­High-​­Performance Director must also recog-
nise that managing the ­co-​­existence of the ‘­talented’ athletes alongside other experts
across the various disciplines and departments is also a critical component of their
role (­Littlewood et al., 2018).

Organisational culture
According to Littlewood et al. (­2018), it is imperative that the figure leading and shap-
ing ­h igh-​­level performance must have an intimate knowledge and appreciation of the
organisational culture in which he/­she operates. Moreover, change is best achieved
through a process that involves attending to daily working practices and helping the
broader culture to evolve. To make sense of the influence of culture in a sporting set-
ting (­w ithin a developmental and performance environment) it is useful to understand
the culture and organisational structure that exist between groups of people or mem-
bers of a group.
 Working as a director of sports science 403
Sport participation in many countries cannot be appreciated aside from the Nation’s
culture, traditions, and values. Sport reflects national culture because it permeates
all levels of society. These cultural systems influence talent development, methods
of preparation, and organisational structures that form a durable template by which
ideas are transferred from one generation to the other. In seeking to ascertain how the
culture of a society may affect the development of methods of soccer preparation, we
need to recognise that culture itself is an extremely complex phenomenon.
Culture is typically referred to as a pattern of behaviours and basic assumptions
that are invented, discovered, or developed by a given group as it learns to cope with
its problems of external adaptation and internal integration (­Schein, 1991). At a more
visible level, culture describes ideas and images that are transferred from one gener-
ation or group to another. On a soccer level, we can assume that methods of player
preparation and daily interactions of stakeholders have become so deeply entrenched
in organisational structure that any attempt to challenge traditional practice is often
received with caution and resistance. Nonetheless, the increasing concern with finan-
cial profit and professionalisation has inevitably led to evolving methods of player
preparation and move away from overreliance on traditional methods.
A strong culture is one that is shared by all employees. However, one limitation of a
strong culture is the difficulty changing that culture. In an organisation where certain
values are widely shared, unlearning the old values and learning the new ones will be
challenging because employees (­and other key stakeholders) will need to adopt to new
ways of thinking. This is a critical role for the H
­ igh-​­Performance Director, where there
is a requirement to satisfy all the stakeholders within the business, while at the same
time navigate change management.

Building an organisational structure to facilitate high performance

­ igh-​­performance sport operates in a ­fast-​­paced, highly dynamic environment that is
H
influenced by the social, cultural, and economic conditions of the community in which
it operates (­Chelladurai, 2009). As such, managing the organisational structure of a
­High-​­performance team is a complex process shaped by several factors (­De Bosscher
et al., 2006).
Sports organisations use structures to determine relationships in the workplace. An
organisational structure is a system that outlines how certain activities are directed
to achieve the goals of an organisation. These activities can include rules, roles, and
responsibilities. The structure also determines how information flows between levels
within the company. There are a variety of structures to choose from, and it’s im-
portant to choose one that best fits the company’s needs. The structure can be both
horizontal and vertical in nature and it is the role of the H ­ igh-​­Performance Direc-
tor to characterise the dimensions of the performance support structure and levels of
­decision-​­making. When deciding on the most appropriate organisational structure to
deliver ­h igh-​­level performance, the following elements will impact on the structure:

• Levels of ­decision-​­making;
• Number of managers;
• Level of employee input;
• Flow of communication;
• Level of efficiency;
404 Tony Strudwick

Differences between horizontal and vertical structures

Vertical structures have clearly defined roles with specific responsibilities for
each person, reducing the level of employee autonomy. Horizontal structures
have less structure, often providing employees with equal opportunities. How-
ever, this may result in a lack of guidance or lead to internal conflict.

• Level of creativity;
• Amount of collaboration;
• Willingness to take risks.

The horizontal structure is related with the number of departments, divisions, and
­sub-​­divisions within the organisation and to the work broken down into narrow tasks
(­Slack, 1997). Sports organisations with these structures often have few managers, and
they allow employees to make decisions without needing manager approval. Provid-
ing employees with autonomy often helps employees feel empowered and motivated,
increasing their connection to the organisation and its goals. The relaxed structure of
horizontal organisational structures also often naturally encourages collaboration.
The vertical structure is related to the number of levels in a sports organisation.
Vertical organisational structure is a p ­ yramid-​­like ­top-​­down management structure.
These organisations have clearly defined roles with the highest level of leadership at
the top, followed by middle management than regular employees. D ­ ecision-​­making
often works from top to bottom, but work approval will work from bottom to top.
Vertical organisational structures define a clear chain of command. The highest
levels of managers make decisions about sales, marketing, customer service, and other
standards and communicate them to middle managers. Middle managers assign work
to employees and communicate processes and goals. Employees complete the work,
and the work goes through middle management and upper management for approval.
The first important step in gaining an advantage through sports science support is
to ensure the organisational structure and staffing are efficient. Traditionally, a soccer
team has a head coach and coaching staff, fitness or strength and conditioning coach,
sports scientist, physiotherapist, and medical doctor. All too often, this structure is
disjointed and has multiple avenues of coordination. Moreover, the head coach often
receives information referring to a player’s status from several sources, and this in-
formation is often clouded by personal and occupational bias (­Duncan & Strudwick,
2016). Over the past few years, there has been major growth in the support services
around professional soccer players, and this has led to the development of the ‘­Human
Performance Team’. While the Human Performance Team is constituted as a set of
people from different ­sub-​­disciplines of soccer science, the impact of the service pro-
vision is reliant on the organisational structure. A more contemporary model is shown
in ­Figure 24.1. The H ­ igh-​­Performance Director may have a medical, sports science,
physiotherapy or strength, and conditioning background and report directly to the
Head Coach and/­or Director of Soccer.
Given the complexity of modern soccer and the various ­sub-​­disciplines operating
within the ‘­Human Performance Team’, ­High-​­Performance Directors may consider de-
veloping a hybrid strategy that incorporates elements of both vertical and horizontal
 Working as a director of sports science 405

Director of Soccer

Head Coach

Head of High-Performance Head of Talent

Operations Director Recruitment

Head of Research Head of Sports Head of Analysis Head of Sports Head of Physical
Medicine Science Therapies

Physicians Surgeons Physiotherapists Conditioning Sports Nutritionist Psychologist

Coach Scientist

Assistants Assistants Assistants

Research Massage Podiatrist
Assistants Therapists

Assistants

­Figure 24.1 Example organisational model associated with the operation of a modern elite
soccer team.

organisational structures. The hybrid organisational structure establishes clear de-

partments related to specific topics with individual vertical structures. In this hybrid
structure, the performance team brings members together from each department to
collaborate. Here, each employee has vertical accountability to their specific depart-
ment and horizontal accountability to their teammates. For efficient delivery across
the Performance Team, rules, regulations, job descriptions, and procedures need to be
­well-​­defined.

The role of director of sports science

The application of scientific support models has a ­self-​­evident part to play in improv-
ing elite performance. Important features of the model such as devising training pro-
grammes, monitoring performance, and establishing preparation for competition, are
informed by such knowledge. The primary role of the Director of Sports Science is
to utilise scientific principles to maximise individual performance and player availa-
bility. Practitioners must effectively manipulate the training process to achieve these
objectives. Moreover, the dimensions of the training programme must be established,
and detailed planning carried out to positively influence both the coaching process
and the resultant player performance risk management.
An elite soccer player attempting to reach the highest level requires a systematic
approach to all areas of performance management. Such an approach can be achieved
by identifying critical component parts of the coaching process and the relation-
ships between the s­ ub-​­processes. There are several critical components that impact
on player performance management as detailed in F ­ igure 24.2. While many of the
406 Tony Strudwick

Data Management Performance Performance

Analysis Profiling

Nutrition Support Sports Science Training Prescription

Management Model

Promotion of Monitoring of Work Injury Prevention

Recovery Rates

­Figure 24.2 A typical sports science performance management model.

components overlap, successful implementation is dependent on a sound organisa-

tional support structure developed between players and staff. Critically, the Head of
Sports Science must have an appreciation of all the key components in the delivery of
­h igh-​­performance support.

Data management
Information is the fuel that drives the performance management process. Planning,
­decision-​­making, monitoring, and performance analysis all depend on the availability
of the necessary information. A critical concept for the Director of Sports Science is
distinguishing between which data are important and which are not. Data gathering
for the sake of it can be very expensive and futile unless it is used to drive action dur-
ing the coaching process. While technology on its own cannot guarantee success at
an elite level, time and effort focussed on developing robust analytical processes have
great potential. Only recently has data begun to transform the management of profes-
sional soccer.

Performance analysis
To gain a correct impression of the physiological loads imposed on soccer players
during competitive matches, observations must be made during real ­match-​­play. Per-
formance analysis entails determining w
­ ork-​­rate profiles of players within a team and
 Working as a director of sports science 407
classifying activities in terms of intensity, duration, and frequency (­Reilly, 1994). In
this way, an overall picture of the physiological demands of soccer can be gathered.
The application of performance analysis to soccer has enabled the objective recording
and interpretation of match events, describing the characteristic patterns of activity
in soccer. Improvement in performance is the central purpose of the coaching process
and a detailed knowledge at the behavioural level of performance is essential for al-
most all stages of the performance management model.

Performance profiling
To ensure that elite players are ­well-​­prepared, the Director of Sport Science should use
performance profiling as a means of providing information on current performance
status. A performance profile of a player provides a benchmark of the overall state
of his/her level of conditioning. A player’s level of conditioning may vary due to the
stage of the season, the effectiveness of the training programme, game frequency, or
the maturity status of the player. Quite simply, performance profiling should provide
information for analysis and subsequent action by both coach and player. To achieve
this end, assessment needs to be built into the training plan at regular and appropriate
intervals. In this way, performance profiling will assist the design and regulation of a
­h igh-​­performance programme.

Training prescription
In the preparation of elite players, it is important that the training programme is ­well-​
p
­ lanned. The training programme needs to be specific and objective, taking into con-
sideration the player’s potential and rate of development. Any training programme
adopted should encompass relevant experiences accumulated over the years together
with applied research findings. Such a programme needs to be versatile, enabling it
to be utilised as a model of training, being easily applied to individuals with their
own specific characteristics and goals. The consistency and knowledge of workloads
during each of the training categories means that two of the most important training
principles can be applied during fi ­ eld-​­based conditioning, namely, progression and
periodisation. Progression refers to gradually increasing the training load over time
as fitness gains are incurred. Periodisation can be defined as a logical, phasic method
of manipulating training variables to increase the potential for achieving specific per-
formance goals.

Injury prevention
In the preparation of elite athletes, the Director of Sports Science has a responsibility
to implement a comprehensive and planned training programme that allows for g­ ym-​
b
­ ased injury prevention strategies. The athlete must be trained in such a way that the
body will be prepared for optimum response to the physical demands of competition.
Strength training has been increasingly employed in the holistic management of con-
temporary soccer players. In simple terms, strength training involves increasing the
ability of the athlete to apply force. The ultimate objectives of strength training are to
develop the capacity to reproduce forceful bursts of energy and withstand the forces
of physical impact, landing, and deceleration. Following specific screening protocols
408 Tony Strudwick
for local muscles as well as joints and lower back/­p elvis, preventative ­g ym-​­based pro-
grammes in the form of core stability, balance, proprioception, muscular strength,
and power should be implemented to address the increasing issues of muscle strains in
contemporary elite soccer.

Monitoring of ­work-​­rates
To develop a successful training programme, the physical demands of training and
competition need to be fully understood. The physiological requirements of ­match-​
p
­ lay vary from match to match (­Gregson et al., 2010) and depend upon playing po-
sition, tactical role, and team success amongst other factors (­Bradley et al., 2009; Di
Salvo et al., 2009; Rampinini et al., 2007). Consequently, the subsequent volume and
intensity of training and/­or recovery should be individually prescribed according to
the players’ previous loadings and future requirements to optimise their readiness to
perform in the next match. A continual system of monitoring is essential to ensure the
correct decisions are made with regard to individual player requirements.

Promotion of recovery
A chronic problem in ­h igh-​­performance sport remains the continual risk of an imbal-
ance between the training, competition, and recovery components (­Budgett, 1990).
Successful training must involve overload while avoiding the combination of excessive
overload plus inadequate recovery (­Meeusen et al., 2006). Because of intense training
and competition, players may experience acute feelings of fatigue which temporar-
ily reduces functional capacity and performance. During the subsequent rest period,
positive adaptations may follow. This process of overcompensation should be consid-
ered as the foundation of all functional increases in athletic efficiency. However, if the
optimal balance between training stress and adequate recovery is miscalculated the
adaptation process will lessen, leading to overtraining.

Nutritional support
To maximise adaptations from training and enhance recovery after match play, it is
essential that players follow an effective individual nutritional support strategy. More-
over, a systematic approach to providing the appropriate ­nutritional-​­based strategies
will yield favourable results in terms of training adaptations, recovery, and match
performance.

Key challenges managing high performance at international level

The focus of international soccer is exclusively on elite performance. Therefore, a per-
formance support model needs to be w ­ ell-​­informed and deliver h
­ igh-​­level results. As a
practitioner working at this level, the critical areas of focus include:

• Ensure the team(­s) are physically prepared to compete successfully during major
tournaments;
• Maximise selection of players for every competitive game;
• Create concepts that reflect the Federation’s approach to training and preparation;
 Working as a director of sports science 409
­Table 24.3 Some key challenges at an international level of competition

Key challenges Factors

Environment Events played at environmental extremes

Nutrition Diverse range of individual nutritional requirements
Immunity Travel, exercise, and tournament stress
International fixtures Multiple fixtures during major tournaments
Tactics and systems of play Changing demands of international play
Contact time Reduced preparation time with players
Lines of communication Managing communication with clubs and players
Club v country priorities/­agendas Managing requirements of club and country
Individual player requirements Tailored training v generic team training
Individual player differences Managing players with different periodisation plans
Head coach communication Making sure head coach receives information
Load management Create an efficient strategy to manage load
Identifying player readiness/­freshness Need to quickly establish the status of players
Information sharing Ensuring close communication with clubs

• Facilitate high levels of motivation and organisation during training;

• Create a performance model that satisfies the needs of all stakeholders, including
players, coaches, and staff;
• Ensure close communication and liaison with clubs.

With countless variables influencing success at ­elite-​­level international ­match-​­play,

­ igh-​­performance practitioners must appreciate how their athletes will be challenged
h
during competition. International soccer presents a unique set of challenges and op-
portunities. These challenges must be appreciated, confronted, and quantified for soc-
cer success. An example of some of these challenges is presented in ­Table 24.3.
In addition to these challenges, practitioners need to have knowledge and under-
standing of the physical and physiological demands of participation in different en-
vironmental conditions, heat and altitude acclimation, optimisation of recovery
strategies, the impact of travelling across multiple time zones, and an appreciation of
dense fixtures during the international calendar.
The physical requirements at the international level vary from match to match,
depending on playing style, tactical organisation, and location of the match. Soccer
players at the international level are regularly called on to travel large distances to par-
ticipate in competitive games. Although international travel is routine for many elite
performers, it is not without issues for the travelling player, a circumstance that should
be recognised and managed by support staff. When journeys entail a ­2-​­to 3­ -​­hour time
zone transition and a short stay (­2 days), staying at home time may be feasible. Such an
approach is useful if the stay in the new time zone is 3 days or less and adjustment of
circadian rhythms is not essential. A European team that is to compete in the morning
in Japan or in the evening in the United States will require an adjustment of the body
clock because these timings would otherwise be too difficult to cope with.
The key is planning and advance preparation. By doing so, player health can be
maintained and negative influences on physical performance can be minimised. Play-
ers and teams that do not plan will approach international competitions with inade-
quate preparation and will be less likely to achieve a successful outcome.
The preparation and training programme must be w ­ ell-​­organised considering indi-
vidual differences, physiological capabilities, and diversity of periodisation templates
410 Tony Strudwick
athletes are exposed to at their respective clubs. A system of continual monitoring is
essential to ensure that all athletes perform the required volume, intensity, and fre-
quency of training. Training load should be prescribed to ensure optimal team prepa-
ration for the upcoming fixture, but also based on each individual athlete’s previous
training history and current physiological status. Careful planning between the coach
and sports scientist will allow the training process to be maximised reducing the risk
of injury occurrence or overtraining.
For coaches and h ­ igh-​­performance practitioners to make effective use of time avail-
able, a series of steps must be followed. First, the coach must appreciate the technical
and tactical elements of successful performance, including physiological considera-
tions and time on task. Second, the coach needs to translate this information into
­soccer-​­specific training drills. Third, the organisation, design and prescription of rel-
evant training methods must consider the major conditioning principles (­specificity,
overload, and recovery). The application of these principles in a planned manner is
the key to effective physiological preparation, enhanced motivation, and improved
execution of technical performance.
At an elite level of participation, the coach builds cooperation between sports sci-
entists and soccer players. Moreover, the coach with sports science guidance assimi-
lates information, analyses the effectiveness of the training plan, and constructs the
training sessions. Planning, ­decision-​­making, monitoring, and performance analysis
all depend on the availability of the necessary information. Prior to arrival at an in-
ternational training camp, H ­ igh-​­Performance Directors/­Directors of Sports Science
collaborate with host clubs to share data on athletes’ physiological status. This infor-
mation provides the platform to drive discussions and make informed decisions to
maximise individual and team preparation. Although situational variables such as
quality of opposition, game location, and congested fixture periods must be taken into
consideration, key performance insights may be identified.
When planning for international fixtures a ‘­Tactical Preparation’ methodology
is recommended to control training variables and maximise tactical input from the
coaching staff. This methodology will allow for multiple scenarios, diverse individual
management strategies and tactical planning. Some facets of a tactical preparation
methodology are listed below.

• All soccer training decisions are based on tactical preparation.

• There should be a direct relationship between practices and the tactical emphasis
of the upcoming fixture.
• Weekly training pattern with alternating loads and complexity to cope with re-
covery demands.
• Always combing tactical principles and physical components in training.
• Managing the physical components and tactical complexity to ensure the recovery
from previous sessions.
• Practices designed by manipulating constraints such as time, space, number of
players and rules.
• Practices designed so that their specific requirements (­tactical, physical, and men-
tal) are higher or lower than game.
• Recognising that the concept of periodisation is ­non-​­linear and an individual ap-
proach will be required.
• Adopting an agile approach to planning and ­decision-​­making where complexity
is embraced.
 Working as a director of sports science 411

Main
Sub Principles
Principles Extensive
Sub Sub Sub
Intensive Training
Day Off Principles Principles Principles
Training
Recovery Recovery Speed of Play Reaction

Match MD +1 MD +2 MD –4 MD –3 MD –2 MD –1 Match

Horizontal Alternation

­Figure 24.3 Model showing a potential periodisation strategy for player and team prepa-
ration for a international soccer team.

The Tactical Preparation methodology shares many of the concepts defined in The
Tactical Periodisation approach (­Oliveira, 2014), where a framework is provided to
organise training sessions to create ‘­actions’ that players expect during the next com-
petitive match. Here, ‘­principles’ and ‘­­sub-​­principles’ of the different phases of the
game are delivered to the players over different types of training sessions (­Intensive,
Extensive, Speed, and Reaction). This methodology does not separate any compo-
nent of the game model (­physical, technical, tactical, and psychological) and is de-
livered as an integrated approach to preparation. The consistency and knowledge of
workloads during each of the training sessions means that two important principles
can be applied, namely, the principle of specificity and the principle of horizontal
alternation.
The principle of specificity relates to training sessions designed to replicate situ-
ations of the game to improve the d ­ ecision-​­making of the players. The principle of
horizontal alternation relates to weekly training patterns with alternating loads and
complexity to cope with recovery demands. Moreover, it is necessary to develop levels
of play with an organisation by varying the complexity of the training throughout the
week. To achieve this end, it is necessary to horizontally alternate the type of domi-
nant contraction of the muscle, such as tension, duration, and speed. An example of
an international working week incorporating the principle of horizontal alternation is
presented in F
­ igure 24.3.
To optimise player freshness and maximise performance in competition, players
exposed to a Tactical Preparation approach are exposed to different stimuli daily,
thus avoiding monotony and/­or overwork. The inclusion of l­ow-​­intensity and re-
covery training will help achieve this aim. In practice, the weekly training plan is
dictated by several variables including, current physical status, load coming into
the training camp, number of games and individual differences. Therefore, a logical
approach is to include flexibility in the training plan and tailor weekly templates
to the specific requirements of the team and individual. But to follow some generic
guidelines.

Future directions and conclusions

We can assume that genuine endeavours are now being undertaken to improve coach
education, knowledge of soccer science and professionalisation. Organisational
and cultural factors that have previously conspired against a move towards ­h igh-​
­performance environments (­i.e., reluctance to embrace change, professionalisation,
412 Tony Strudwick
and the development of scientific framework) are now being overcome. Coaches and
players operating at an elite level understand the small increments in performance
standards that are possible at the highest level require training programmes that are
extensive in scale and need to be conducted at a high intensity. For this reason, the
Director of Sports Science or H ­ igh-​­Performance Director needs to have an enhanced
appreciation of the processes that are involved in the holistic management of elite
players.
At the elite level of soccer, the next decade will observe continued enhancement in
sports science innovation and player management. The exponential growth in tactical
development, player development, and the rise in technology to support high perfor-
mance will be fully explored. Elite soccer teams will move towards h ­ igh-​­performance
environments where the development of systematic performance models and increased
accountability will be commonplace. Innovations in player preparation are more chal-
lenging by the year and expectations go on rising. Therefore, player preparation must
be sharper and better informed. All in all, these factors call for superior sports science
support models and deeper insights, driven by empirical data, into issues relating to
the management of elite performance.
An enormous amount of data is now generated about a team’s performance on a
constant basis. Some coaches now have fi ­ rst-​­hand experience of how to use ‘­sports
analytics’ to improve player and team performance. In the future, ­h igh-​­performing
teams (­those that substantially outperform their competitors over the long term) will
turn to analytics as a competitive strategy. While technology on its own cannot turn
a soccer organisation into a high performer, time and effort focused on developing
robust analytical processes has great potential.
The key deliverable of the analytics process will be an increasing emphasis on using
data to make better decisions. A critical concept in the process of data collection is
distinguishing between which information/­data is important and which is not. Data
gathering for the sake of gathering data can be very expensive and futile unless it is
used to drive action during the coaching process. While technology on its own cannot
guarantee success at an elite level, time and effort focused on developing robust ana-
lytical processes has great potential.
There is no doubt that successful soccer performance is ­multi-​­disciplinary in na-
ture. The Director of Sports Science or H ­ igh-​­Performance Director will need to be
aware of the physiological, biomechanical, psychological, nutritional, medical, and
other issues that can impact on competition. When all these factors come together and
work as an integrated system, excellence in ­h igh-​­performance soccer is possible. Elite
sport is above all about p ­ roblem-​­solving. Practitioners who are trained to think criti-
cally about all aspects of performance and how they interact and influence each other
will be rewarded with success by gaining an advantage over competitors.

References
Bradley, P. S., Sheldon, W., Wooster, B., Olsen, P., Boanas, P., & Krustrup, P. (­2009). ­High-​
­i ntensity running in English FA premier league soccer matches. J Sports Sci, 27, ­159–​­168.
Budgett R. (­1990). Overtraining Syndrome. Br J Sports Med, 24 (­4), ­231–​­6.
Carter, N. (­2010). The rise and fall of the magic sponge: medicine and the transformation of the
football trainer: Social History Med, 23(­2), ­261–​­279.
Carter, N. (­ 2016). Evolution of soccer science. In Tony Strudwick (­ Ed.), Soccer Science
(­p­­p. ­3 –​­14). Champaign: Human Kinetics.
 Working as a director of sports science 413
Chelladurai, P. (­2009). Managing Organisations for Sport and Physical Activity: A Systems Per-
spective. Scottsdale, AZ: Holcomb Hathaway Publishers.
De Bosscher, V., De Knop, P., Van Bottenburg, M., & Shibli, S. (­2006). A conceptual framework
for analysing sports policy factors leading to international sporting success. European Sport
Management Quart, 6(­2), ­185–​­215.
Di Salvo, V., Gregson, W., Atkinson, G., Tordoff, P., & Drust, B. (­2009). Analysis of high inten-
sity activity in premier league soccer. Int J Sports Med, 30, ­205–​­212.
Duncan, C. & Strudwick, T. (­2016). National and cultural differences. In Tony Strudwick (­Ed.),
Soccer Science (­p­­p. ­15–​­36). Champaign: Human Kinetics.
Gagné, F. (­1985). Giftedness and talent: a ­re-​­examination of the definitions. Gifted Child Quart,
29, ­103–​­112.
Gagné, F. (­1998). A proposal for subcategories within the gifted or talented populations. Gifted
Child Quart, 42, ­87–​­95.
Gagné, F. (­2005). From gifts to talents: The DMGT as a developmental model. In R. J. Stern-
berg & J. E. Davidson (­Eds.), Conceptions of Giftedness (­2nd ed.), (­p­­p. ­98–​­119). New York:
Cambridge University Press.
Gregson, W., Drust, B., Atkinson, G., & Di Salvo, V. (­2010). ­Match-­​­­to-​­match variability of
­h igh-​­speed activities in premier league soccer. Int J Sports Med, 4, ­237–​­42.
Henriksen, K., Stambulova, N., & Roessler, K. K. (­2010). A holistic approach to athletic talent
development environments: A successful sailing milieu. Psychol Sport Exer, 11, ­212– ​­222.
Ivarsson, A., Stenling, A., Fallby, J., Johnson, U., Borg, E. & Johansson, G. (­2014). The predic-
tive ability of the talent development environment on youth elite football players’ w ­ ell-​­being:
a ­p erson-​­ centered approach. Psychol Sport Exer, 16, ­15–​­23.
Li, C., Wang, J. K. C. & Pyun, Y. D. (­2014). Talent development environmental factors in sport:
a review and taxonomic classification. Rev Taxon Classification, 66(­4), ­433–​­447.
Littlewood, M., Richardson, D. & Nesti, M. (­2018). Shaping the performance culture: the role
of the performance director. In Warren Gregson & Martin Littlewood (­Eds.), Science in Soc-
cer Translating Theory into Practice (­p­­p. ­3 –​­15). London: Bloomsbury Sport.
Martindale, J.J.R., Collins, D. & Daubney, J. (­2005). Talent development: a guide for practice
and research within sport. Quest, 57(­4), ­353–​­375.
Meeusen, M., Duclos, M., Gleeson, M., Rietjens, G., Steinacker, J., & Urhausen, A. (­2006). Pre-
vention, diagnosis and treatment of the overtraining syndrome. Eur J Sports Sci, 6(­1), ­1–​­14.
Oliveira, R. (­ 2014). Tactical Periodization: The Secrets of Soccer Most Effective Training
Methodology.
Rampinini, E., Coutts, A. J., Castagna, C., Sassi, R., & Impellizzeri, F. M. (­2007). Variation in
top level soccer match performance. Int J Sports Med, 28, ­1018–​­1024.
Rees, T., Hardy, L., Gullich, A., Abernathy, B., Cote, Core., Woodman, T., Montgomery,
H., Laing, S. & Warr, C. (­2 016). The Great British medalists project: a review of current
knowledge on the development of the world’s best sporting talent. Sports Med, 46(­8),
­1041–​­58.
Reilly, T. (­1994). Physiological aspects of soccer. Biol Sport, 11, ­3 –​­20.
Schein, E. (­ 1991). Organisational Culture and Leadership (­ 2nd Ed). San Francisco, CA:
­Jossey-​­ Bass.
Slack, T. (­1997). Understanding Sport Organizations: The Application of Organization
Theory. Champaign: Human Kinetics.
Sotiriadou, P. & De Bosscher, V. (­2018) Managing h ­ igh-​­performance sport: introduction to
past, present and future considerations, Eur Sport Manag Quart, 18:1, ­1–​­7.
Stambulova, N. (­2003). Symptoms of a c­ risis-​­transition: a grounded theory study. In N. Hass-
men (­Ed.), SIPF Yearbook 2003 (­p­­p. ­97–​­109). Orebro, Sweden: Orebro University Press.
Tranckle, P. (­2004). Understanding giftedness and talent in sport. The Coach, 21, ­61–​­73.
25 Working as a sporting director
Daniel Parnell, Rebecca Caplehorn, Kevin Thelwell,
Tony Asghar and Mark Batey

Introduction
The soccer industry has a problem with stability, helped little by ­Covid-​­19 (­Parnell et al.,
2020a). The approach of regularly dismissing head coaches and their entire backroom
staff, may bring rapid ­short-​­term results, but is not a paradigm regularly employed in
industries outside the sporting sphere. The high turnover of senior staff within the club
sporting hierarchy leads to a myriad of policy changes and inconsistency of strategy
and in culture (­Bridgewater, 2010; Kelly, 2017). This context has created an environment
of employment instability and vulnerability, which is, in turn, detrimental to organi-
sational performance and success (­Relvas et al., 2010; Gibson & Groom, 2018, 2019;
Roderick & Schumacker, 2017). Traditionally, this instability has created problems for
club owners who have often focused on delivering success on the pitch, and a ‘­win
on a Saturday’, rather than strategically protecting their investment. As owners have
clamoured for q ­ uick-​­fix solutions, entrenched in the ­short-​­term thinking and solutions,
rather than the ­medium-­​­­to-­​­­long-​­term horizon, a vicious circle of ­decision-​­making, in-
tensified by the risk and reward of success or failure, has created even greater insta-
bility and more Head Coach turnover (­Bridgewater, 2010; Gammelsæter, 2013; Kelly,
2017). One strategy considered and adopted by some clubs to address these issues has
been the introduction of a Sporting Director (­Parnell et al., 2018a).
In this chapter, we seek to examine the role of the Sporting Director in soccer. His-
torically, we can broadly categorise two main groups of clubs depending on where the
majority of power was congregated. Those clubs who were run mainly by the First
Team Manager, who generally had the final say on all aspects of the club and team, or
those clubs who were run by an Owner, President or Chief Executive who maintained
power for many aspects of how the club functioned, leaving the Head Coach to work
within the parameters he/­she was given. Yet, the ­ever-​­growing complexity and com-
mercialisation of the sport, increasing demands on performance for players, backroom
staff, consultants, and managers, has challenged this conventional leadership struc-
ture. It appears an important time to review the Sporting Director role and how this
role can help support the Head Coach and help deliver the goals of the organisation.

Defining a sporting director

As an emerging role within the soccer management landscape, there exists consid-
erable ambiguity regarding the title or definition of a Sporting Director. We use the
term Sporting Director in this chapter, but clubs seemingly use the title ‘­Director of

DOI: 10.4324/9781003148418-31
 Working as a sporting director 415
Football’, ‘­Technical Director’, ‘­Director of Football Operations’, and even ‘­Chief
Soccer Officer’ to describe individuals with strategic management responsibilities.
The inconsistency in terminology regarding the Sporting Director role has and will
continue to impede scholarly research into this area. For the purposes of clarity, and
in the absence of an existing definition, using descriptions from Parnell et al., (­2018a,
b) we propose that a Sporting Director may be defined as the individual with strategic
management responsibility for soccer operations.
­Figures 25.­1–​­25.3 provide representations of management structures that incorpo-
rate a Sporting Director. Typically, Sporting Directors adopt a position in between
that of the Head Coach and Chair/­Owner in the hierarchy (­­Figures 25.1 and 25.3),
but may in a flatter structure make up a management team alongside the Head Coach
(­­Figure 25.2). In some circumstances, the Sporting Director will report to a CEO
(­­Figure 25.1), at others directly to the board or owner. At ­h ighly-​­developed, elite clubs
with many sporting departments, there may be a clearer demarcation of management
responsibilities for the Sporting Director and Head Coach or heads of departments
(­­Figure 25.2) each with their own complex reporting structures. In smaller clubs, the

Chair/Owner

Governance
Board

CEO

Sporting Finance &

HR & Legal Marketing
Director Operations

Head Coach

Coaching

Performance
Analysis

Medical
Services

­Figure 25.1 A football management structure where the Sporting Director reports to a
CEO.
416 Daniel Parnell et al.

Chair/Owner

Governance Board

Chief Operating
Sporting Director Head Coach
Officer

Sports Science Performance Analysis Finance & Operations

Medical Services Coaching HR & Legal

Recruitment Marketing

­Figure 25.2 A football management structure where the Sporting Director, Head Coach,
and CEO report to the Governance Board/­Chair/­Owner.

hierarchy may be simplified with the Sporting Director taking a wide range of respon-
sibilities including player recruitment (­­Figure 25.3). In effect, the position taken by
the Sporting Director varies from club to club and will be impacted by such factors as
the size of the club, the scope and scale of the club’s administrative functions and the
existence of other technical roles (­e.g. Head of Recruitment) and sometimes the desires
of the owner or powerful stakeholders.
Given our proposed definition above, the Sporting Director is characterised as hav-
ing the direct responsibility of overseeing the core business pertaining to soccer op-
erations, and in some clubs, entails the responsibility for Head Coach recruitment,
­succession-​­planning, and dismissal (­Nissen, 2014; Parnell et al., 2021). In addition,
the Sporting Director as an architect or custodian of culture ensures the creation and
maintenance of a sustainable h­ igh-​­performance environment from the academy to the
first team (­Wagstaff & ­Burton-​­Wylie, 2018).
 Working as a sporting director 417

Chair/Owner

Governance Board

Chief Operating
Sporting Director
Officer

Head Coach Finance & Operations

Chief Scout HR & Legal

Academy Head Marketing

­Figure 25.3 A simplified football management structure where the Sporting Director
would take responsibility for player recruitment.

The rise of the sporting director role

Professional soccer (­and sport) has undergone dramatic changes over the past two dec-
ades. These changes have arisen primarily due to media rights, with most professional
clubs now operating as complex business institutions in dynamic pursuit of an ever
greater share of the significant monies that media rights provide (­Morrow & Howieson,
2014). The English Premier League (­EPL) has been at the forefront of these changes and
is embedded within a European and international marketplace of clubs, fans, spon-
sors, governing bodies, and partner commercial organisations. The European market
is thought to be worth ~£25 billion, with combined league revenues for the ‘­­Top-​­5’
leagues across Europe valued at ~£13 billion for the 17/­18 season (­Deloitte, 2019). Much
of this growth is due to the ­hyper-​­commercialisation and commodification of soccer
across Europe. At present, it is common for global investment funds, ­multi-​­national
conglomerates, sovereign wealth funds, and even royalties, to be part of ownership
structures and linked to club acquisition (­Parnell et al., 2020b). A complex stakeholder
environment within which a Sporting Director may expect to operate and negotiate.
During the past 30 years of the EPL, many factors in the soccer ecosystem have evolved.
Notably, the financial rewards and consequences of success or failure have intensified. At
418 Daniel Parnell et al.
the end of each EPL season, the bottom three teams are relegated to the division b ­ elow –​
T
­ he Championship. This relegation has significant negative financial ramifications on
the club’s income, including broadcast, matchday, and commercial revenue streams
(­Maguire, 2021). While the consequence of demotion is partially mitigated by the protec-
tion of ‘­parachute payments’ (­see Wilson et al., 2021), the chances of a prompt return to
the EPL are slim, despite the recent success of Norwich City FC, who were relegated from
the EPL to the Championship in 2019/­20, only to b ­ ounce-​­back immediately in the 2020/­21
season. Notably, given the focus of this chapter, Norwich City FC implemented a Sport-
ing Director model, recruiting Stuart Webber in 2017. The EPL has also seen an influx of
foreign ownership and majority of clubs in the EPL (­2021/­22) are ­foreign-​­owned. We have
also seen how the role of the contemporary manager (­or Head Coach) has considerably ex-
panded during this period (­Bridgewater, 2010; Kelly, 2017). Gone are the days of a kitman
and a handful of trusted coaches, to be replaced with a ­multi-​­layered ­high-​­performance
team of internal employees working alongside specialists, advisors, and analysts some-
times from external providers, the Sporting Director will expect to manage and influence
within and across formal and informal boundaries with diverse, skilled colleagues.
The implementation of a Sporting Director model has been commonplace in
Europe and is gaining popularity worldwide. Many senior leaders occupy these po-
sitions across Europe, including major clubs such as AFC Ajax, AS Roma, Atletico
Madrid, Barcelona, Bayern Munich, Borussia Dortmund, Inter Milan, Juventus, Lille
OSC, Paris ­Saint-​­Germain FC, PSV Eindhoven, RB Leipzig, and Real Madrid. Sport-
ing Directors can be found extensively in Major League Soccer and across the conti-
nent at clubs such as Club Bolivar in Bolivia and Guadalajara in Mexico. The United
­K ingdom-​­based Association of Sporting Directors caters for in excess of 500 mem-
bers from every continent (­see: https://­associationofsportingdirectors.com). There is
undoubtedly a rise in the popularity of Sporting Directors in soccer globally, much of
which remains under the radar with regard to research. Given the position and ­pre-​
­eminence of the English Premier League, and the reticence with which the role was
adopted, there has been a focus on the role in this context.
English clubs are often accused of being resistant to change and slow to adopt mod-
ern management methods. However, researchers have identified the multiple chal-
lenges of making the switch to the Sporting Director model, including hostility, and
distrust (­Kelly & Harris, 2010). Many head coaches harboured these feelings due to
what they perceived to be interference in their role, by owners and directors, all with
their own agenda (­Kelly, 2017) and none facing the pressure of losing their job if there
were to be a ‘­bad run’ of results. Therefore, and despite the challenges, many clubs
now seek strategies to best focus the talents of a Head Coach, who could easily be
subsumed by a vast array of responsibilities in the new complex, ­fi xture-​­congested,
highly contested, and commercial era of modern soccer. The Sporting Director model
seeks to minimise the Head Coach’s ­non-​­essential duties and find a more sensible and
parsimonious ‘­division of labour’ of leadership. While some have criticised clubs in
England for being slow in adopting the role, others have argued this is simply a re-
brand of an existing structure. Researchers have identified that perhaps Liverpool
FC, had an early version of the model, where Bob Paisley (­who became manager of
Liverpool in 1974) had some of the administrative duties previously undertaken by
Bill Shankly (­h is predecessor) given to Peter Robinson (­Liverpool FC club secretary).
Paisley was relieved of player contract duties, allowing him to focus on the ­day-­​­­to-​­day
management of the first team (­Lawrence, 2018). Lawrie McMenemy, Southampton FC
 Working as a sporting director 419
manager between 1973 and 1985 was asked to do a role similar to the Sporting Director
(­Lawrence, 2018). We could argue that one of the most successful managers in history,
Sir Alex Ferguson operated as a ­quasi-​­Sporting Director, fulfilling responsibilities as-
sociated with the role. As is often the case, the role may have existed long before it
became popularised and given a formal title.
A report considered the ‘­Technical Director’ (­which as we have discussed is a term
akin to the Sporting Director) role in England, compared and contrasted this to the
same role in European clubs (­Church, 2012). Church implied the role would become
more popular in England and outlined several reasons for this expected growth in
popularity. These reasons include: (­1) new ownership bringing in new working models;
(­2) a more ‘­­business-​­like’ approach by clubs, meaning the link between the technical
staff and the board will become increasingly vital; (­3) the Premier League’s Elite Per-
formance Plan (­EPPP) would cause a change to current staffing structures, and these
changes would need to be developed and managed; (­4) an increase in mandatory quali-
fications, professionalism, and accountability within clubs would also be a driver for the
uptake of the role; and (­5) it seems to be the modern trend for clubs to employ a Sporting
Director, and the likelihood is that other clubs will replicate this model for fear of being
‘­laggards’ in adopting innovative practices. Since the report, England has slowly shifted
its governance structures towards a Sporting Director model and Church maintains a
leadership position within The FA overseeing their flagship Level 5 Technical Directors
course. For example, in season 2016/­17 only 13 out of 20 EPL clubs had someone in a
similar role to a Sporting Director, however, in the 2021/­22 season, 17 out of 20 have
such appointments. Sporting Directors within clubs are becoming a mainstay, with
greater clarity now possible regarding their primary roles and responsibilities.

The roles and responsibilities of sporting directors

The initial appointment of a Sporting Director, by an owner or board, is often in the
pursuit of change, or a new (­or better) way of doing things. The Sporting Director
often includes an aspiration to give a club a ‘­way of doing things’, through a cohesive
and ­joined-​­up structure, a greater sense of stability and a ‘­­road-​­map’ to deliver upon a
­long-​­term strategy (­Parnell et al., 2018b). The Sporting Director is often someone who
has overall responsibility for the performance of various sporting departments within
a club. We have described this as someone who can deliver a strategic plan and oper-
ate as a custodian of the club. They often have responsibilities for the first team, the
academy, recruitment and scouting, sport science, and medical departments (­Parnell
et al., 2018a, 2021). The Sporting Director will often act as the intermediary between
the strategic apex of a club (­i.e., the board) and sporting departments (­Parnell et al.,
2018b). As a more ‘­permanent fixture’ within a club’s hierarchy, the Sporting Direc-
tor is instrumental in shaping the l­ong-​­term vision, strategy, and culture to support
sustainable high performance. They can act as a custodian of the ‘­way we do things
around here’ against the backdrop of (­relatively) regular changes to the Head Coach
and backroom staff.
The priorities of the Sporting Director may include supporting numerous assis-
tants across the first team and academy departments (­Parnell et al., 2018b). They are
also responsible for developing a positive working relationship with the owners and
Board, the recruitment of the best talent (­on and off the pitch) within budget (­Parnell
et al., 2021) and, developing and maintaining a ­club-​­wide philosophy to support its
420 Daniel Parnell et al.
sporting strategy. The Sporting Director is often renowned for recruitment practice
taking players in and out of the club (­Parnell et al., 2021), which is vital in the glo-
balised race for talent (­Bond et al., 2018, 2019). Recruitment of talent is undoubtedly
a key task, however, an overreliance on this capability may constrain the effectiveness
of introducing someone into the role. At present, little attention is given to the sup-
port the Sporting Director may give to medical and sports sciences, or the academy
­environment – ​­all of which can be critical for achieving ­short-​­and ­long-​­term sporting
objectives and ensuring a cohesive core of how ‘­we do things round here’ from top to
bottom.
Our intention is not to provide an exhaustive list or description, merely a nod to im-
portant areas of consideration. Sporting Directors should: know the football industry
(Renton, 1999); understand the context within which the business operates (­Renton,
1999); possess strategic awareness (­Renton, 1999); and a breadth of perspective, profes-
sional reputation, and expertise (­Ingley & Van der Walt, 2003); exercise interpersonal
and communicational skills (­Ingley & Van der Walt, 2003; Pye & Pettigrew, 2005; Rob-
erts et al., 2005); bring motivation and commitment (­Ingley & Van der Walt, 2003);
and the ability to question and challenge (­Roberts et al., 2005). As a consequence,
the recruitment of Sporting Directors raises considerations around their skill set and
capabilities.
The emergence of the Sporting Director role has been fraught with challenges. Like
any change or disruption is an innovation that changes the world (­or in our case, the
soccer industry) in such a way, that if successful organisations keep on doing what
they always did, they are likely to fail. As such, the Sporting Director often demands
a new organisational structure. In this respect, there are mixed views and practices
on whether a Sporting Director should sit on the board (­apex) of the club or elsewhere
(­for example, above the first team Head Coach, but below the board). Yet, when asked
Sporting Directors have stated:

“­A director needs to sit on the board. A director is a director and clubs need to
commit to that so you can do the job. I don’t understand why anyone would take
a [Sporting] Director role in title and not insist on being on the board.”…“­In a
football club, key decisions related to strategy are decided in the board room. If
you don’t sit round a table with the CEO and Director for Finance, how can you
possibly ensure your strategy is presented correctly, to influence decisions, to en-
sure you get the support you need? You can’t. You can’t really lead properly as a
Sporting Director without being on the board”.
(­See Parnell et al., 2018a, ­p. 162)

Although many Sporting Directors know the importance of sitting on the board of
the club, it is often negotiable as candidates seek opportunities in old organisations
who refuse to change and continue to face an uphill struggle despite their past suc-
cess. Architectural innovation refers to structural change to the organisation to em-
brace the innovation and is worth consideration (­Henderson & Clark, 1990). Yet, if
a club brings in a new strategy (­i.e., a Sporting Director), fitting this new innovation
into old structures offers very little scope for ­change – little
​­ influence, power, and
­resources – ​­the hierarchies remain intact. An existing board may see the introduction
of a Sporting Director as someone seeking to make a grab for power and challenge the
leadership’s ­decision-​­making status quo.
 Working as a sporting director 421
New change requires experimentation and the introduction of a Sporting Director
is a change that appears to require architectural innovation (­i.e., organisational and
structural change). This change will create consequences for clubs, people, power dy-
namics, resource division, and ­decision-​­making responsibilities. There has been much
experimentation on how this should work or be implemented (­or not) in any club at
any moment in time. This issue will remain a key item on the agenda for boards ex-
amining the Sporting Director model for implementation in what we can consider as
the current experimentation period. We have seen and can expect vast amounts of
trial and error. Some clubs may view an unsuccessful attempt to implement a Sporting
Director model as an indication to completely end their experimentation with the role.
This period of experimentation is fraught with challenges as boards are engaged with
the management of stakeholder expectations, politics, influence, and power dynamics.
However, we hope this experimentation leads to learning, improvements, and success.
This period will naturally come to an end as a dominant design emerges.

Successes associated with sporting directors in the role

Clubs have made progress on the journey of change with the introduction of different
Sporting Directors models. While we can accept that errors have been made by all in-
volved in the ­decision-​­making processes with respect to initiating this new role, there
has also been plenty of success. This is often unique to the club context as this can vary
from club to club based on ownership, governance, and organisational structure. The
following section provides the reader with two selections of successful people. It does
not serve to identify every successful Sporting Director, person or club, nor does ­non-​
­inclusion allude to unsuccessful practice. These examples serve to provide a road map
for the reader for further exploration and analysis.

Dan ­Ashworth – ​­Technical Director at Brighton Hove Albion FC

Dan Ashworth joined West Bromwich Albion (­WBA) originally to help develop the
academy ­structure – ​­later becoming Academy Director, where he formed a relation-
ship with the WBA Chairman Jeremy Peace. Within 3 years of joining WBA, Dan was
appointed Technical Director. Dan then moved to the English FA where he oversaw
the development of the ‘­England DNA’ strategy. During his time at the English FA, he
would see World Cup victories at U17 and U20 age groups, along with senior World
Cup ­semi-​­finals with both the men’s and women’s teams. Part of this success was de-
veloping an enhanced competitive games programme and teams that could compete
within these fixtures. Those who have worked with Dan regularly speak about his
management skills as being one of his biggest strengths. Dan is known for being in-
clusive and democratic in his ­decision-​­making. He described his role at Brighton as
being the hub in the centre of a ­wheel – ​­around him are the seven heads of department.
He described his job as connecting those seven areas and recruiting the right person
to lead the department and overseeing succession planning in the result that someone
leaves. Dan is committed to a development culture, getting the best out of people, and
helping them grow. This links to his inclusive approach, through allowing people to
express themselves and allowing the space to succeed. This role included ­non-​­playing
and playing talent. For example, there were ongoing discussions between Dan and
Graham Potter (­the first team Head Coach) to explore ways to improve their game,
422 Daniel Parnell et al.
the focus would be on internal players in their own system (­i.e., peripheral squad,
loan, and/­or academy players), rather than to look immediately outwards for playing
talent. Dan’s recruitment of Graham aligns both of their desires to develop people,
whether staff or players. Dan was naturally w ­ ell-​­placed to support talent pathways
within Brighton given his experience at WBA and The FA. However, he also has key
staff and quality people around him. For example, David Weir, a former player, as-
sistant manager of Rangers FC and Brentford FC as loan manager. David (­alongside
the other heads of departments) would work with Dan to deliver on the club’s strategy,
in this case, it may include achieving 30% of playing minutes attributed to academy
players in the English Premier League, alongside finishing in the top 10 places. There
is of course much more to say, to discuss and analyse, including Dan’s commitment
to the health and well-being of his staff and women’s game. Most recently, Dan joined
Newcastle United Football Club as their new Sporting Director. Dan is a leader and
one of the ‘go-to’ people within the inudstry.

­ onchi – ​­current Sporting Director at Sevilla FC and former sporting director

M
@ Roma FC
Monchi was a goalkeeper at Sevilla and spent most of his time as the number two
choice. When Sevilla was relegated from La Liga, Monchi was recruited as Sporting
Director to develop an elite scouting system and improve talent pathways from the
academy to the first team. During his time as Sporting Director of Sevilla, he oversaw
an incredible six Europa League trophies, along with a reputation for producing large
profits on undervalued talent who come to Sevilla and move on to some of Europe’s
top clubs. For example, Julio Baptista £1.5m to £15m, Dani Alves £435k to £27m, and
Ivan Rakitic £1.8m to £44m. Monchi believes in attention to detail rather than luck. He
views clubs that have opted for a Sporting Director model as being advantaged over
those that do not. Monchi describes his role as sitting between the Chairman, who
gives him the economic information, and the Head Coach, who outlines what he needs
with the first team, while also focusing on internal player development. He outlines
an ongoing tension between ­short-​­and ­long-​­term goals and the need to continue to
focus on player pathways. Monchi describes three pillars for success as having a united
direction, planning, and teamwork. During his 30 years at Sevilla, the two times he
experienced relegation was a result of internal division, as such its key to have a united
direction of work. Each club also needs a strategic and operational plan, to ensure
role clarity, and objections, which requires detailed planning. Finally, he believes
in the power of the collective and avoids individualism, as such teamwork is key for
successful organisations. Operationally, Monchi stays close to the players (­e.g., staff
and Head Coach), describing himself as a ‘­­locker-​­room’ Sporting Director, to know
the people, challenges, issues, and how he can help. Monchi utilises data analytics
(­i.e., big data, artificial intelligence, and machine learning) to inform his recruitment,
alongside an extensive professional scouting network. There is much more to discuss
on recruitment, but to close this short feature, here are the areas Monchi identifies as
important for Sporting Directors to consider:

• Do not avoid risk when making d ­ ecisions – it

​­ is impossible to do great things with-
out taking big risks;
• If you want to go fast, go alone, but if you want to go far, go together;
 Working as a sporting director 423
• Continual investment in personal development and do not be afraid of failure;
• Being able to adapt is the difference between success and failure.

Challenges that face sporting directors

A number of challenges impact the success of implementing a Sporting Director ap-
proach. The flexibility in the role title and lack of clarity with respect to the role can
create tensions internally and externally with stakeholders (­including fans and media),
which can influence the effectiveness of the club. The position of a Sporting Director
in a club’s hierarchy (­i.e., on the board or otherwise) impacts the influence and effec-
tiveness of anyone in the role. This is a relatively new role, and like any new innovation,
it takes time to find the best way to implement and change ways of doing things. There-
fore, managing existing hierarchies and power dynamics is key. This process must be
managed carefully when implementing a new Sporting Director, as this is undoubt-
edly a complex change. More broadly, there are a wide variety of challenges facing
Sporting Directors in practice that should inform continued professional development
and education programmes (­see T ­ able 25.1). The challenges pertain to the role and
responsibilities of a Sporting Director as we have reviewed in this chapter, in addition
to the myriad of macro issues that soccer organisations must adapt to. To ‘­bridge the
gap’ between the challenges faced and the skills required, we provide a suggestive set
of skills and competencies that Sporting Directors should look to d ­ evelop – and
​­ which
providers of formal and informal education should cater for.

Future directions and conclusions

There are a number of key considerations we have drawn from our analysis and ex-
perience. The title used for the Sporting Director role is flexible, but with definitional
clarity provided in this chapter, we hope to support focused and rigorous research in
this area. A Sporting Director may be defined as an individual with strategic manage-
ment responsibility for soccer operations.
The job role varies across clubs, and therefore the knowledge, expertise, and skill
required to perform the role may vary. Sporting Directors currently do not always
assume a b ­ oard-​­level position. Internal and external stakeholders do not appear to
fully understand the Sporting Director role and can lead to ambiguity both internally
and externally to the organisation. The role is new and innovation will take time and
involve trial and error. We are still learning the best ways for a Sporting Director to
maximise his/­her working relationship with the Head Coach and the wider network
of influential stakeholders. How best to support innovation and change in both op-
erations and cultures will remain an issue. The challenges facing Sporting Directors
are plenty, as such we need a shift in how we support Sporting Directors to prepare
for internal and external changes (­i.e., technology, social, media, data, and political).
If the Sporting Director role is to be successful, we need to think and work for organ-
isational structures that give those in the role the genuine position to influence. While
each club context is unique, this will likely result in a Sporting Director assuming a
­board-​­level position and influence. Once a dominant effective design is established
for the Sporting Director, the initial set of components will need to be refined and
elaborated, and progress takes the shape of improvements in the components within
the framework of a stable organisation. This process should allow clubs to focus on
424 Daniel Parnell et al.
Some challenges facing the Sporting Director in practice and the skills and
­Table 25.1 
competencies required to address them

Challenges Skills and competencies

The formulation and implementation of successful Strategic thinking

strategies Commercial acumen
Change and innovation management
Operations management skills
Leading ­h igh-​­performing teams comprised of Leadership and management skills
­h ighly-​­skilled, diverse professionals Change and innovation management
Building ­culture – ​­taking a leading role as a Leadership and management skills
‘­custodian of culture’ Change and innovation management
Strategic thinking
Ensuring good ­governance – ​­ethics, transparency, Commercial acumen
trust, and compliance Governance, legal and financial skills
Operations management skills
Managing and influencing across formal and Leadership and management skills
informal b­ oundaries – ​­including complex supply Commercial acumen
chains of ­specialists – e.g.,
​­ outsourcing Contract management
Strategic thinking
Building trust and influence in complex club Leadership and influencing skills
­h ierarchies – ​­navigating ‘­cultures of ownership’ Emotional intelligence
Talent identification and recruitment (­players Commercial acumen
and staff) including regulations, contracts, and Leadership and influencing skills
negotiation. Emotional intelligence
Data analytics (­to inform performance, talent ­Industry-​­specific data analytics skills
development and recruitment)
Industry regulations (­i.e., financial fair play, loan Commercial acumen
regulation changes) Governance, legal and financial skills
TV rights and resultant financial implications Commercial acumen
Health and ­well-​­being of staff and players Emotional intelligence
Human resource skills
Continued professional development, training, Emotional intelligence
qualifications and education for Sporting Human resource skills
Directors and all staff
Succession planning (­backroom staff) Strategic thinking
Leadership and management skills
Human resources skills
­Communication – ​­internal and external, fans, liaison Emotional intelligence
committees, and social media Communication skills
Digital and media skills
Emergent ­technology – ​­industry 4.0 or 4th industrial Strategic thinking
revolution (­world economic forum); e.g., how will Commercial acumen
blockchain and cryptocurrency effect transfers? Change and innovation management
Navigating the external environment (­i.e., Brexit, Strategic thinking
­COVID-​­19, climate change) Leadership and management skills
Commercial acumen
Change and innovation management
Operations management
Navigating a football club through complex societal Emotional intelligence
change (­for example: black lives matter, LGBTQ+, Leadership and management skills
national politics, religious observance) Strategic thinking
Commercial acumen
Change and innovation management
Governance, legal and financial skills
Horizon scanning to ensure prepared and ready for Strategic thinking
continued improved practice and innovation Leadership and management skills
Commercial acumen
 Working as a sporting director 425
continuous improvement, development, and p ­ rogress – ​­in the systems, people, and
­processes – ​­in line with the principles of total quality management. Ultimately, this
change will take time, there will be stumbles and there will be successes. The compo-
nents and practices associated with these successes must be acknowledged and shared
with key ­decision-​­makers and where possible implemented.
To further enhance the implementation of the role of Sporting Director within soc-
cer, additional work is required. This includes ensuring clearly defined role descriptors
for the Sporting Director role for employers and employees. Clubs need to position
the Sporting Director with an appropriate level of power and influence. This concep-
tual clarity will avoid role ambiguity. We require enhanced professional education
and qualifications to support those seeking to gain a Sporting Director role. In this
respect, we need to develop clear pathways for the recruitment and development of
future Sporting Directors. We require a distinct body of research to inform ­decision-​
­making and practice. For example, optimal Head Coach recruitment strategy, how to
best onboard a Head Coach, how to identify the ­best-​­fit between the club, Sporting
Director, and Head Coach, change preparation and management as a result of pro-
motion or relegation, and strategic alliances across clubs and ownership groups. The
collective work of formal and informal education bodies will be vital for the ongo-
ing professionalisation of sport and Sporting Directors. The unique Master of Sport
Directorship (­MSD) qualification at Manchester Metropolitan University provides a
formal executive qualification in this regard. Furthermore, the Association of Sport-
ing Directors is key to providing an independent and inclusive professional member-
ship body to provide continued support and guidance. Closing some of these gaps will
help ensure the growth and effectiveness of implementing a Sporting Director model
in clubs.

Acknowledgements
We would like to thank our colleagues at the Association of Sporting Directors for
their support with this research. Alongside our many colleagues in the industry who
have supported our work.

Disclosure statement
Daniel Parnell is CEO of the Association of Sporting Directors, Rebecca Caplehorn is
on the Technical Committee of the Association of Sporting Directors and Kevin Thel-
well is a member of the Association of Sporting Directors. Mark Batey is Programme
Leader of the Master of Sport Directorship (­MSD) at Manchester Metropolitan Uni-
versity, UK.

References
Bond, A. J., Widdop, P., & Chadwick, S. (­2018). Football’s emerging market trade network: ego
network approach to world systems theory. Managing Sport and Leisure, 23(­­1–​­2), ­70–​­91. doi:
10.1080/­23750472.2018.1481765.
Bond, A. J., Widdop, P., & Parnell, D. (­2019). Topological network properties of the Euro-
pean football loan system. European Sport Management Quarterly, ­ 2 0, 1–​­24. doi:10.108
0/­16184742.2019.1673460
Bridgewater, S. (­2010). Football Management. Basingstoke: Palgrave Macmillan.
426 Daniel Parnell et al.
Church, P. (­2012). Technical director report (­p­­p. ­70–​­98).
Deloitte. (­2019). Annual Review of Football Finance 2019. Deloitte Football Finance. Retrieved
from: https://­w ww2.deloitte.com/­uk/­en/­pages/­­sports-­​­­business-​­g roup/­articles/­­annual-­​­­review-­​
­­of-­​­­football-​­fi nance.html.
Gammelsæter, H. (­2013). Leadership succession and effectiveness in team sport. A critical re-
view of the coach succession literature. Sport, Business and Management: An International
Journal, 3(­4), ­285–​­296. doi: 10.1108/­­SBM-­​­­06–­​­­2013–​­0 015
Gibson, L., & Groom, R. (­2018). Ambiguity, manageability and the orchestration of organisa-
tional change: a case study of an English premier league academy manager. Sports Coaching
Review, 7(­1), ­23–​­44. doi: 10.1080/­21640629.2017.1317173
Gibson, L., & Groom, R. (­2019). The ­m icro-​­politics of organizational change in professional
youth football: towards an understanding of ‘­actions, strategies and professional interests’.
International Journal of Sports Science & Coaching, 14(­1), ­3 –​­14. doi: 10.1177/­1747954118766311
Henderson, R., & Clark, K. (­1990). Architectural innovation: the reconfiguration of existing
product technologies and the failure of established firms. Administrative Science Quarterly,
34(­1) 35. Doi: 10.2307/­2393549
Kelly, S. (­2017). The Role of the Professional Football Manager. Routledge: London.
Kelly, S., & Harris, J. (­2010). Managers, directors and trust in professional football. Sport in
Society, 13(­3), ­489–​­502. doi: 10.1080/­17430431003588150
Lawrence, I. (­2018). Football Club Management: Insights From the Field. Routledge: London.
Maguire, K. (­2021). The Price of Football Second Edition: Understanding Football Club Finance.
Agenda Publishing: London.
Morrow, S., & Howieson, B. (­2014). The new business of football: a study of current and
aspirant football club managers. Journal of Sport Management, 28(­5), ­515–​­528. doi:
10.1123/­jsm.­2013–​­0134
Nissen, R. (­2014). Playing the game: how football directors make sense of dismissing the coach.
International Journal Sport Management and Marketing, 15(­3/­4), ­214–​­231. doi: 10.1504/­IJSMM.
2014.072009
Parnell, D., Groom, R., Widdop, P., & Ward, S. (­2018a). The sporting director: exploring cur-
rent practice and challenges within elite football. In S. Chadwick, D. Parnell, D. Widdop, &
C. Anagnostopoulos (­Eds.), Routledge Handbook of Football Business and Management
(­p­­p. ­155–​­170). London: Routledge.
Parnell, D., Widdop, P., Groom, R., & Bond, A. (­2018b). The emergence of the sporting director
role in football and the potential of social network theory in future research. Managing Sport
and Leisure, 23(­­4 –​­6), ­242–​­254.
Parnell, D., Bond, A.J., Widdop, P., & Cockayne, B. (­2020b). Football worlds: business and net-
works during ­COVID-​­19. Soccer & Society, 22(­­1–​­2), ­19–​­26. Doi: 10.1080/­14660970.2020.1782719
Parnell, D., Widdop, P., Bond, A., & Wilson, R. (­2020a). ­COVID-​­19, networks and sport. Man-
aging Sport and Leisure, 2020, ­1–​­7. https://­w ww.tandfonline.com/­doi/­full/­10.1080/­23750472.
2020.1750100
Parnell, D., Bond, A.J., Widdop, P., Groom, R., & Cockayne, D. (­2021). Recruitment in
elite football: a network approach, European Sport Management Quarterly. https://­doi.
org/­10.1080/­16184742.2021.2011942
Pye, A., & Pettigrew, A. (­2005). Studying board context, process and dynamics: Some challenges
for the future. British Journal of Management, 16(­1), ­27–​­38. doi: 10.1111/­j.­1467–​­8551.2005.00445.x
Relvas, H., Littlewood, M., Nesti, M., Gilbourne, D., & Richardson, D. (­2010). Organizational
structures and working practices in elite European professional football clubs: understand-
ing the relationship between youth and professional domains. European Sport Management
Quarterly, 10(­2), ­165–​­187. doi: 10.1080/­16184740903559891
Renton, T. (­1999). Standards for the Board: Improving the Effectiveness of your Board. London:
Institute of Directors.
 Working as a sporting director 427
Roberts, J., McNulty, T., & Stiles, P. (­2005). Beyond agency conceptions of the work of the n­ on-​
­executive director; creating accountability in the boardroom. British Journal of Management,
16(­1), ­5 –​­26. doi: 10.1111/­j.­1467–​­8551.2005.00444.x
Roderick, M., & Schumacker, J. (­2017). ‘­The whole week comes down to the teamsheet’: a
footballer’s view of insecure work. Work, Employment and Society, 31(­1), ­166–​­174. doi:
10.1177/­0950017016672792
Wagstaff, C., & ­Burton-​­Wylie, S. (­2018). Organizational culture in sport: a conceptual, defini-
tional, and methodological review. Sport and Exercise Psychology Review, 14(­2), ­32–​­52.
Wilson, R., Plumley, D., Mondal, S., & Parnell, D. (­2021). Challenging parachute payments
and unmasking English football’s finances. Managing Sport and Leisure, 27, 93–98. Doi:
10.1080/­23750472.2020.1792745
Index

active recovery 95 electromyography 241–243

adaptive expertise 189 elite player performance plan 155
aerobic training 34, 39 emotions 115
anaerobic speed endurance training 42 expertise in coaching 183
anaerobic speed training 41 EXPERTS 147–148
anaerobic training 34, 36, 41
analysis: free kicks 280; open play 278; penalty factor analysis 281–283
kicks 280; set play 279 family 156–158
ASPIRE 147–148 fatigue 90–91, 257; transient 258
Female Athlete Triad 78
bio-banding 339–340 FIFA (11+) 7, 10, 11
biomechanics toolbar 243 financial fair play 155
fluid requirement 76
carbohydrates 67–74; in-game 71–72; post- formal learning 186–189
game 72; pre-match 71 future game problem 385
career transitions 168 future programmes 340–341
central tendency 315–316
challenge point hypothesis 148–149 game intelligence 124
coach-athlete relationship 158–160 game performance evaluation tool 131
coach development pathways 185 games-based approaches 149–150
cognitive function and heat 55 gastrointestinal tract infection 224
compression garments 99–100 gaze behaviours 125–129
concussion 215–218 GPS 253, 273, 299, 302
confidence 114–115 growth 329–332
constraints-led approach 149
contextual priors 130 heat acclimatation 59
cooling strategies 60 heat-related illness 55
Covid-19 231–232 high-performance director 398–399
creatine phosphate 37 high-speed running 255
cryotherapy 97–98 home advantage 113–114
cultural background 160–161 home grown players 160
cultural diversity 160 hyperthermia 7

data management 406 ill-being 170

decision-making 131–132 Index of Game Control 281
dehydration 76–78 Index of Offensive Behaviour 281
deliberate practice 147–148 infections 223
de-selection 371 infectious diseases 223–229
developmental pathways 141–145 informal learning 185–186
diagnosis of infectious diseases 229–230 injury 201–203; ankle 208–210; bone 212–214;
Director of Football Operations 415 cruciate ligament 204–208; epidemiology
Director of Sports Science 397 199; joint 203–210; knee 204; medial
430 Index
collateral ligament 208; meniscus 204; protein 74–75
mitigation 200; prevention 301–303, psychological momentum 112
264–265; screening 200, 246; tendon
210–212 rate limiters 149
international soccer 408–411 reading the game 125
isokinetic dynamometer 243–244 recovery 91; kinetics 24
isometric exercises 17, 21 recovery strategies 90
red zone 40
jumping performance 238–239; Sargent jump reflective practice 190
239; vertical jump 239 relative age 347–351; maturation biases 351–357
reliability 313–314
key performance indicators 277 repeated bout effects 20, 24, 93
repeated sprint training 256
load: external 293; internal 293 resistance training 15, 16
long-term athlete monitoring 303–304 retirement 175
LPS 253, 273
scanning 126–127
massage 96 scouts 382–384
match analysis 273 self-care 172
match day routines 5 simulation training 133–135
match demands 254–257 situational probabilities 130
maturation status 330–332, 347–351; skeletal age 330–331
fitness testing 339; injury 336–338; sleep 100–101
screening programme 332; training small-sided games 5
335–336 social identity 115
maximum voluntary contraction 243 social network analysis 283
menstrual cycle 57 socioeconomic background 161–162
mental health 168–174; literacy 173 sporting director 414
micronutrients 80–81 streamlining data 298–299
microstructure of practice 145–146 strength: assessment 243; training 9
monitoring training 44, 292–305 stretching 96; dynamic 6; exercises 6; static 6
muscle: biopsies 37; concentric contraction 11, supercompensation 23
245; damage 93; eccentric contraction 11, surrogate selector problem 387
245; lactate 38
myofascial release 96 tacit knowledge 365
tactical preparation approach 411
needs analysis 22 tactics 276
nutritional considerations 78–80; adolescent talent 363; development environment
players 79–80; female players 78 questionnaire 370; identification indicators
351–357; promotion programmes 370–375;
pattern recognition 129–130 recruiting framework 387–389
peak height velocity 330–331 tanner-whitehouse method 330
percentile rank 318–319 tapering 15
perceptual-cognitive skills 124 teaching games for understanding 149–150
performance analysis and coaching 274 time motion analyses 253
performance profiling 407 tolerance model 16
periodisation strategies 26
physical capabilities of players 36 upper respiratory tract infection 223–224
physical conditioning strategies 261
Player Insights team 382 vaccination 225–226
player monitoring and management 261, validity 313
263–264 video feedback 119
position specific match demands 257 virtual reality 133–135
Possession Effectiveness Index 281
post-activation: performance enhancement 4; warm up 3; active 4; passive 4
potentiation 4 wearable devices 295–296
pre-cooling 67–74 wellbeing 168–174