EUROPEAN JOURNAL OF SPORT SCIENCE

2022, VOL. 22, NO. 4, 600–609

https://doi.org/10.1080/17461391.2021.1887366

Processing visual information in elite junior soccer players: Effects of

chronological age and training experience on visual perception, attention, and
decision making
a,b
Stefanie Klatt and Nicholas J. Smeetonc
a
German Sport University Cologne, Institute of Exercise Training and Sport Informatics, Cologne, Germany; bInstitute of Sport Science,
University of Rostock, Rostock, Germany; cSport and Exercise Science and Sports Medicine Research and Enterprise Group, Welkin
Laboratories, University of Brighton, Eastbourne, UK

ABSTRACT KEYWORDS
Processing information in peripheral vision is an important perceptual-cognitive skill in team Feature recognition; object-
sports. The relative contribution of various perceptual-cognitive skills to expertise in sports detection; selection; team
throughout adolescence has not been investigated in detail yet. The current study examined sport; youth athletes
the effects of chronological age and training experience on perception, attention, and decision
making in young soccer players. Sixty-five elite youth players were required to judge different
game situations in a decision-making task involving both perceptual (object detection) and
attentional (postural feature recognition) skills to perceive player configurations in the visual
periphery. In general, performance decreased in the decision-making and feature-recognition
tasks with increasing use of peripheral visual field, but not in the object-detection task. Superior
performances were found for under 18-years-old players compared to under 16-years-old
players especially in their attentional skills. Higher training experience affected decision-making
and attentional performance. Overall, the findings provide insights and implications for training
perceptual-cognitive skills in team sports

Highlights
. Elite youth soccer players’ performance decreased in a soccer-specific decision-making and
feature-recognition tasks with increasing use of peripheral visual field, but not in an object-
detection task.
. Superior performances were found for under 18 years old players compared to under 16 years
old players especially in their attentional skills.
. Both chronological age and training experience influenced the recognition of postural feature
in peripheral vision, whereas player detection was unaffected.
. The ability to recognize postural features in peripheral vision is an important characteristic of
decision making in sports and requires a mature visual system, sufficient attentional capacity,
and may be developed through extended task-specific practice.

High-level sportspeople need to develop perceptual- Williams, Ford, Eccles, and Ward (2011) outlined
cognitive skills to be successful in team sports (Williams, important perceptual-cognitive processes of expert
Ward, & Smeeton, 2004). However, debate continues decision making that need to be understood. In order
about what these perceptual-cognitive characteristics to identify the processes underpinning anticipation,
of expert performance are (Broadbent, Causer, Williams, researchers should investigate the recognition and use
& Ford, 2015). The successful identification of these of task-relevant, postural information provided by the
characteristics is thought to be important for informing movements of teammates and opponents. Sub-
subsequent training programmes and developing sequently, researchers have tended to focus on the “pos-
future elite sportspeople (Hüttermann & Memmert, tural” information contained in the biological
2018; Otte, Millar, & Klatt, 2019; Williams & Ericsson, movements of opponents (Huys, Smeeton, Hodges,
2005). Beek, & Williams, 2008; Smeeton, Huys, & Jacobs,

CONTACT Stefanie Klatt s.klatt@dshs-koeln.de

Supplemental data for this article can be accessed at https://doi.org/10.1080/17461391.2021.1887366
© 2021 European College of Sport Science
 EUROPEAN JOURNAL OF SPORT SCIENCE 601

2013), with relatively little research on the perceptual- object recognition account of visual processing (Riesen-
cognitive processes that may be engaged when huber & Poggio, 1999), the process of stimulus detec-
making anticipation and pattern recognition judge- tion is seen as a more basic visual function than
ments (North & Williams, 2019). Huys et al. (2009) pro- stimulus recognition because the latter requires detec-
posed that information for anticipation was picked up tion of the stimulus and recognition of particular
globally, implying that attentional processes for antici- instances (i.e. postures) of stimuli (Verschae & Ruiz-
pation judgements were broader in experts than in del-Solar, 2015). Hüttermann et al. (2019) found that,
novices. whilst the test of the more basic object presence detec-
A detailed investigation has been undertaken by Hüt- tion led to a greater accuracy score than the test of
termann, Memmert, and Simons (2014) and it has been feature recognition (76% vs 46%), only the feature-rec-
shown that expert team players have an attentional ognition task performance was significantly greater in
focus 25% broader across the visual field than novices. the team sports players than the individual sports
The authors used the Attention-Window Task developed players (55% vs 36%), suggesting that object/feature
by Hüttermann, Memmert, Simons, and Bock (2013) recognition may be an important perceptual-cognitive
which has proved as a valid method to measure the process to be developed. In other words, the capability
size and shape of the attentional focus. By presenting to allocate visual attention to the periphery to pick up
two stimuli simultaneously with varying distances instances of postural orientation was a differentiating
between them in the visual periphery, it is possible to characteristic of team sport players, whereas perceiving
measure the ability to spread the focus of attention the presence of opponents was something that both
across visual space. groups of participants could do successfully. However,
There are different gaze strategies that can be used data using this group comparison approach does not
when various objects have to be perceived in the visual indicate how these skills might typically develop in
periphery. Fixations can be employed with the fovea skilled athletes.
used to process detailed information – however, this It is well known that perceptual and cognitive skills
strategy prevents the perception of multiple objects sim- account for much of the variance in soccer skills
ultaneously. In contrast, gaze can be fixed between per- between adult groups (Helsen & Starkes, 1999). Ward
ceptually relevant areas and information can be and Williams (2003) examined highly skilled 9 years to
processed concurrently using peripheral vision (Hütter- 17 years soccer players’ perceptual-cognitive skills in
mann, Memmert, & Liesner, 2014; Piras & Vickers, 2011). youth academies of English first division clubs and
As the latter fixation can be dynamically adapted novices from primary and secondary schools. The
(“visual pivots” or “gaze anchors”) – the approach of this study showed both a relationship between chronologi-
gaze strategy is that the gaze is fixed while attention is cal age and perceptual-cognitive skills in soccer-
distributed to various peripheral cues (Ripoll, Kerlirzin, unspecific tasks as well as differences between elite
Stein, & Reine, 1995). But regardless of the choice of and sub-elite players in soccer-specific tasks. But this
gaze strategy, it is self-apparent that restrictions of per- effect was no longer found with increases in chronologi-
ipheral vision limit athletes’ ability to identify other cal age. More precisely, older players altogether reacted
players or objects that are located in this part of their faster to peripheral stimuli than younger players, and
visual field. An effective decision-making strategy skill group differences were no longer found in players
requires the integration of the more salient visual older than those in the U15 age group. This result indi-
(central and peripheral) information available while less cates that the ability to detect stimuli in peripheral
salient sources of information should be ignored (Ryu, vision is no longer a differentiating characteristic by
Abernethy, Mann, Poolton, & Gorman, 2013). the age of 15, but greater task-specific experience in
More recently, Hüttermann, Ford, Williams, Varga, high-quality learning environments is important for per-
and Smeeton (2019) examined differences in decision- formance on sport-specific tasks and differentiates elite
making processes between team sports players and and sub-elite soccer players. However, the multidimen-
those that participated in individual sports. In order to sional battery of tests used by Ward and Williams
better understand the attentional and perceptual pro- (2003) could not provide evidence that performance
cesses underpinning their decision making, participants on those tests is causally related to on-field perform-
had to engage in a more basic measure of visual func- ance. Instead, higher test performances could have
tion by detecting the presence of opponent players as been linked back to experience rather than skilfulness
well as more complex processes of recognize the in the game. Overall, the relationship between the per-
running direction of teammates across a range of ceptual-cognitive skills and the athletes’ actual perform-
angles of the visual field. According to the hierarchical ance remained unclear in the described study.
602 S. KLATT AND N. J. SMEETON

In the current study, we aimed to examine percep- Participants

tual cognitive processes of elite junior soccer players.
In total, 65 young male soccer players aged 14–17 years
Participants performed a decision-making task that
(Mage = 15.63 years, SD = 0.96 years) participated in the
included a postural feature-recognition (attention-
study. Data from two additional participants were
based) and an object-detection (perception-based)
excluded due to technical problems and three more par-
task in each trial (see e.g. Klatt, Ford, & Smeeton,
ticipants had to cancel the testing because of longer-
2019, for research using the same task). The visual
term injuries.
focus of attention is typically allocated across a part
The players’ year of birth was used to determine their
of the visual field. Visual attention is a prerequisite for
chronological age. Because the sample included players
conscious recognition of information. In general,
born in two different years, it was examined whether this
people only consciously perceive those objects/events
one-year difference has an influence on perception,
onto which they direct their attention at a given time
attention, and decision-making processes. In general,
(Dehaene, Changeux, Naccache, Sackur, & Sergent,
the aim was to select a sample of players of whom it
2006). According to Hommel et al. (2019, p. 2289f)
could be assumed, based on the work of Crognale
“[…] attention is the set of cognitive/neural mechan-
(2002), among others, that the development of their
isms responsible for maximizing the efficient utilization
visual system is nearly completed.
of our limited capacities to process, store, and retrieve
At the time of data collection, the participants played
information”. When performing the object-detection
in two different youth leagues (under 18 years: U18, n =
task participants “only” need perceptual abilities,
33; under 16 years: U16, n = 32) – in the highest German
while for the postural feature-recognition task atten-
league of their age group respectively. The U18 players
tional skills are needed. It was predicted that chrono-
had an average age of 16.45 years (SD = 0.51 years) and
logical age and training experience (Ward & Williams,
the U16 players of 14.78 years (SD = 0.42 years), t(63) =
2003; Williams, Ward, Ward, & Smeeton, 2008) would
14.489, p < .001. While the U18 players participated in
affect young players’ performances. Specifically, it was
organized soccer for 9.62 years (SD = 1.68 years), the
predicted that differences in chronological age and
U16 players had played soccer in an organized club for
training experience would be found in the decision-
9.33 years (SD = 1.96 years), t(63) = 0.649, p = .519. In
making and postural feature-recognition task that
total, 15 U18 players indicated to have played soccer for
have been shown to differentiate skill groups, but not
more than 10 years and 18 players less than 10 years.
in the object-detection task that relies on more basic
There were also 15 players in the U16 group who had
visual function (Hüttermann et al., 2019). To explore
played for more than 10 years and 17 players less than
how age and experience related to the ability to
10 years. The U18 players reported to regularly practice
extract information in foveal and peripheral vision,
for 8.82 h (SD = 0.95 years) per week at the time of the
decision-making, postural feature-recognition, and
data collection, the U16 players were active on average
object-detection task performance scores were corre-
for 8.44 h (SD = 0.76 years) per week, t(63) = 1.781, p
lated with age and playing time in a club separately
= .08. All participants regularly participated in matches
across visual angle conditions.
during the weekends.
All participants reported normal or corrected-to-
normal vision (with either glasses or contact lenses) and
had not participated in any sensorimotor research
Methods
within the preceding six months. The study was approved
Sample size estimation by the ethics board of the leading university. Written
consent was obtained from all participants prior to
Based on previous research examining the attentional
testing according to the Declaration of Helsinki in 1975.
window and decision making in sport (Hüttermann
et al., 2019; Hüttermann, Smeeton, Ford, & Williams,
2019; Klatt & Smeeton, 2020), a minimum sample size
Materials
of 28 (per age group) was calculated using G*Power
(Faul, Erdfelder, Buchner, & Lang, 2009). This calculation Decision-making task. A decision-making task, which in
was based on the main effect of visual angle in these previous studies has already been used to analyse ath-
previous studies having a median effect size (η2) of letes’ decision making, attention, and perception (Hütter-
.623 and a 50% attenuation of this variable under train- mann et al., 2019; Hüttermann et al., 2019), was selected
ing experience and chronological age conditions being as testing method. After two practice trials, each player
predicted. completed 24 experimental trials. As can be seen in
 EUROPEAN JOURNAL OF SPORT SCIENCE 603

Figure 1. Sequence of events in one exemplary trial (modified from Hüttermann et al., 2019).

Figure 1, the test begins with the presentation of a Procedure

fixation cross for 1000 ms. Subsequently, two stimuli
All participants were tested individually in the labora-
are displayed, one at either side of the previously
tory. Before the test, participants provided personal
shown fixation cross. Teammates (white jerseys) and
information including information on their footballing
opponents (black jerseys) are used as stimulus material
experiences. Players were provided with information
and are presented, randomly varying each trial, at one
on the testing procedure in written form. Participants
of eight horizontal positions (10°, 20°, 30°, 40°, 50°, 60°,
were given the opportunity to ask questions in case of
70°, 80°) from the centre of the projection. In each trial,
any uncertainties. They stood approximately 1.40 m
two teammates are presented (white jerseys), one at
from a 2.80 × 2.20 m white projection screen (90° hori-
either side of the centre, who are randomly surrounded
zontal maximum visual angle × 76° vertical maximum
on either their right or left body side by zero, one, two,
angle) on which the task was presented. Overall,
or three opponents. While opponents always move in
testing took about 20 min per participant.
the direction opposite to teammates, the teammates
can move either towards the centre or towards the side
of the playing field (i.e. the centre or the side of the pro- Data analysis
jection). A still image of the respective game situation is
In line with previous research applying the same task (e.g.
presented to the participants for 300 ms. Subsequently,
Hüttermann et al., 2019; Hüttermann et al., 2019; Klatt &
the participants’ task is to put themselves in the position
Smeeton, 2020), we examined differences between the
of the player in possession of the ball, and to, within a
decision-making, the feature-recognition, and the
time limit of 4000 ms, make a decision on whether to
object-detection task performances using a four-way
pass or to keep the ball. However, the participant
ANOVA with task (decision-making, feature-recognition,
should only pass the ball if the respective teammate is
and object-detection task), and visual angle (10°, 20°,
not surrounded by any opponents and is facing
30°, 40°, 50°, 60°, 70°, 80°) as the within-subjects variables
towards him, that is, if the teammate is moving towards
and age (U16, U18) and playing time (under 10 years, over
the centre. The participant verbally communicates his
10 years) as the between-subjects variables.
decision (pass right, pass left, no pass) to the exper-
While the four-way ANOVA was performed in order to
imenter. After this, he is asked to indicate the exact
examine the relative differences in performance of the
running direction of both teammates, as part of the
subtasks (decision-making, feature-recognition, object-
feature-recognition task. Finally, the object-detection
detection task), we performed separate additional
task requires participants to indicate the number of
repeated-measures analyses of variance (ANOVAs) for
opponents that surround the teammate on either side
each of the three subtasks. We analysed accuracy rate
(cf. Klatt & Smeeton, 2020).
as the dependent variable, conducting an ANOVA with
604 S. KLATT AND N. J. SMEETON

visual angle (10°, 20°, 30°, 40°, 50°, 60°, 70°, 80°) as = .898, with no performance difference between the
repeated measures within-subjects factor and chrono- players of both age groups who had played soccer for
logical age (U16, U18) and playing experience (more more than 10 years, t(28) = 0.926, p = .362. Bonferroni
than 10 years, less than 10 years) as between-subjects corrected post hoc comparisons had an adjusted alpha
factors. For analyses in which the sphericity assumption of 0.025. The interaction between chronological age,
was violated, we reported the value of ε from the Green- training experience, and visual angle tended towards
house-Geisser correction. Bonferroni-corrected pairwise being significant, F(7, 427) = 1.995, p = .054, ηp 2 = .032.
comparisons were used to follow up significant main There was no other significant interaction effect (all p-
effects. To understand how performance on the values >.05).
decision-making, object-detection, and feature-recog-
nition tasks related to chronological age and playing
Object-detection task
experience in club environments across visual angles,
exploratory Pearson’s product moment correlation The total amount of correct responses in the object-
coefficients were calculated. detection task was 66.33% (SD = 22.34%) of trials. To
examine the identification rate of the number of
opponent players, we conducted a further ANOVA
Results
with the same factors as before. The ANOVA revealed
There was a main effect of task, F(1, 122) = 70.218, p neither a significant effect of visual angle, F(7,427) =
< .001, η 2 = .535, indicating that correct responses in 1.579, p = .140, nor of training experience, F(1, 61) =
the decision-making task (M = 89.21%, SD = 19.79%) 0.003, p = .955. However, there was an effect of
were higher than in the object-detection task (M = chronological age, F(1, 61) = 4.599, p = .036, η 2 = .070:
67.43%, SD = 30.97%), which in turn were higher than The U16 players (M = 59.90%, SD = 22.37%) performed
in the feature-recognition task (M = 56.02%, SD = worse than the U18 players (M = 72.57%, SD = 20.77%).
31.75%) (all ps < .001). The ANOVA also revealed a signifi- There was no significant interaction effect (all p-
cant four-way interaction effect between chronological values > .05).
age, training experience, visual angle, and task, F(14,
854) = 1.912, p < .05, η 2 = .030. In order to follow up on
Feature-recognition task
this significant interaction, task-wise separate three-
way ANOVAs were performed and results are presented In the feature-recognition task which required partici-
below. pants’ visual attentional skills, they achieved an
average score of 55.71% (SD = 17.31%). The ANOVA to
analyse the identification rate of the teammates’
Decision-making task
running directions showed again a significant main
The total amount of correct responses in the decision- effect of visual angle, F(7, 427) = 6.291, p < .001, η 2
making task was 89.10% (SD = 9.54%) of trials. The = .093, indicating that, in general, participants’ accuracy
ANOVA with participants’ accuracy rate in decision rate decreased with increasing angles between stimuli
making as dependent variable revealed a significant and became more variable (see Figure 4); Bonferroni cor-
main effect of visual angle, F(5.059,308.600) = 5.066, p rected follow-up pairwise comparisons showed specific
< .001, ηp 2 = .077, ε = .723 (Mauchly’s test of sphericity: differences between 20° and 70°, 30° and 70°, 20° and
χ 2(27) = 68.151, p < .001): In general, accuracy decreased 80° as well as 30° and 80° (p < .05). Furthermore, we
with increasing visual angles and became more variable found a significant effect of chronological age, F(1, 61)
(see Figure 2); Bonferroni-corrected follow-up pairwise = 6.199, p = .016, η 2 = .092: U18 players (M = 60.61%,
comparisons showed significant differences between SD = 15.52%) outperformed U16 players (M = 50.65%,
70° and 10°, 20°, 30°, and 60° conditions (p < .05). SD = 17.84%). In addition, these participants who
There was no significant effect of chronological age, F played soccer for more than 10 years in a club (M =
(1, 61) = 3.059, p = .085. But there was a significant 61.25%, SD = 17.13%) had greater feature recognition
effect of training experience, F(1, 61) = 4.544, p = .037, than those players who played soccer for less than 10
ηp 2 = .069. There was also a significant interaction years in a club (M = 50.95%, SD = 16.24%), F(1, 61) =
effect between chronological age and training experi- 6.849, p = .011, η 2 = .101. There was no significant inter-
ence, F(1, 61) = 6.981, p = .010, ηp 2 = .103 (see Figure 3): action effect (all p-values > .05), however, the interaction
The U18 players who had played soccer less than 10 between chronological age, training experience, and
years performed better than the U16 players who had visual angle tended towards being significant, F(7,
also played less than 10 years, t(33) = 2.654, p = .012, d 427) = 1.901, p = .068, ηp 2 = .030.
 EUROPEAN JOURNAL OF SPORT SCIENCE 605

Figure 2. Mean accuracy of responses (in percent) as a function of visual angles in the decision-making task. Error bars represent
standard deviations (*p < .05).

Exploratory analysis = .332), but not with playing time. Feature-recognition

performance correlated with age at 10° (r = .346) and
Correlations between task performances across the
50° (r = .303) and with playing time at 40° (r = .266).
visual angles and age and playing time are reported in
the Appendix (Supplementary file). Decision-making
performance across visual angles showed significant
positive relationships with 50° only for age (r = .267) Discussion
and playing time (r = .306), p < .05. Object-detection per- The aim of this study was to examine perceptual cogni-
formance correlated with age at 10° (r = .328) and 80° (r tive processes of elite junior soccer players. In line with

Figure 3. Effect of training experience on accuracy rate (in percent) in the decision-making task for U16 and U18 years players.
Symbols represent across-participants means, and error bars represent standard deviations (*p < .025).
606 S. KLATT AND N. J. SMEETON

Figure 4. Mean accuracy of responses (in percent) as a function of visual angles in the feature-recognition task. Error bars represent
standard deviations (*p < .05).

the predictions, a four-way interaction of chronological chronological age and training time effects were
age, training experience, visual angle, and task was approximately similar indicating both factors were simi-
found indicating that decision-making and feature-rec- larly important. However, there was also a relationship
ognition task performances depended on chronological between feature-recognition and chronological age at
age, training experience, and visual angle. However, in 10° indicating foveal vision as also being important.
the object-detection task, performance was only Foveal and peripheral effects were also found for the
different between U16 and U18 age groups. These relationship between chronological age and object
results indicate that recognizing task-relevant, postural detection. Typically, eye gaze methods have been used
information about teammates and opponents in the alongside spatial and temporal occlusion methods
peripheral vision is an important perceptual cognitive (Smeeton, Hüttermann, & Williams, 2019), but the eye
process in elite junior soccer players’ decision making. gaze method is only suitable for foveal information
It further suggests that task-relevant experience as well pick up and it is not possible to determine information
as chronological age are important for the development pick up from other areas of the visual field (Hüttermann,
of this skill. Noël, & Memmert, 2018). Using eye gaze methods to
The results from this study support and extend the understand how information is extracted from multiple
proposal that recognizing task-relevant, postural infor- player positions, North and Williams (2019) showed
mation is an important perceptual-cognitive process that expert soccer players spend more time fixating
present in athletes (Williams et al., 2011). Here, it is between forward players and the ball than novices.
shown that the skill of picking up peripheral information Using foveal vision, postural information as well as infor-
is important as well as picking up information in the mation concerning the relative position of them to other
fovea. The exploratory analysis showed significant players is used. It may be the case that peripheral and
relationships between training time and decision- foveal information pick up is used in combination to
making and feature-recognition performance at visual enable maximal use of the information (Murphy,
angles associated with peripheral vision (50° and 40°, Jackson, & Williams, 2019). In addition, it is shown here
respectively). No relationships between object-detection that postural information presented outside of foveal
and training time were found across any visual angles vision (visual angles beyond 10 degrees) can be picked
indicating training time was not associated with up in the periphery of a mature visual system. Given
object-detection. Relationships between decision that decision-making performance was superior in
making and feature-recognition and chronological age older players and those that had more experience
were also found at 50°. The effect sizes (r) for the playing at the elite level, it is argued that task-specific
 EUROPEAN JOURNAL OF SPORT SCIENCE 607

practice is an important mechanism through which this number of trials per angle was reduced in the current
decision-making process is developed (Ward & Williams, study. The main effect of visual angle across all tasks
2003). demonstrates reduced performance at larger visual
What advantage does picking up postural infor- angles and is consistent with previous studies (e.g. Hüt-
mation in peripheral vision have over saccading to pick termann et al., 2019; Hüttermann et al., 2019). However,
up information through foveal vision? Mann, Causer, future studies might reduce the number of visual angles
Nakamoto, and Runswick (2019) have reported on and test a larger number of trials per angle to more pre-
studies showing that it is faster to covertly switch cisely measure the visual angle threshold between
visual attention in the periphery rather than saccade to success and failure at the tasks. Moreover, although
the new information extraction location (Ryu, Aber- the task used represented a soccer field with soccer
nethy, Mann, & Poolton, 2015; Ryu, Mann, Abernethy, players, we cannot fully label the task as soccer-
& Poolton, 2016). It may also be an advantage to use a specific because players were not required to make
global information extraction approach (Huys et al., any soccer-specific movement responses. This response
2009; Woolley, Crowther, Doma, & Connor, 2015), method should be considered in future research. More-
because information extracted globally is more determi- over, it should be considered that decisions that have
nistic (Huys et al., 2008). A broad attentional window to be made in real soccer game situations are oftentimes
allows more players to be picked up (Hüttermann, more complex than the challenge to decide whether to
Helsen, Put, & Memmert, 2018; Hüttermann, Memmert, pass the ball to the left, to the right, or whether to
& Nerb, 2019) and thus, positions of other teammates control it/not pass at all. The further development of
and opponent players can be better assessed leading the design, e.g. through the presentation of more or
to an overall better decision making (Murphy et al., less teammates (i.e. manipulating crowding, see Rosen-
2019). holtz, 2016) and opponent players in game situations
The results reported here are broadly in line with pre- or through the presentation of dynamic stimuli,
vious studies into perceptual-cognitive processes in remains a challenge for future research. Furthermore, it
decision making in sport using the same task. The is currently unclear exactly how recognizing postural
four-way interaction showed that accuracy scores information is integrated with decision-making perform-
decreased in the postural feature-recognition and ance and what developmental or practice activities
decision-making tasks with increasing visual angles result in the acquisition of this important perceptual
between the peripheral stimuli, and that both older cognitive process of recognize postural information in
and more experienced players performed with greater the visual periphery. Ford et al. (2012) as well as Roca,
accuracy on these tasks. However, in contrast to these Williams, and Ford (2012) for example, already discussed
previous studies, this effect was not found in the the developmental activities that co-occur with superior
object-detection task, although performance on this anticipation and decision making in young athletes.
task was greater than in the feature-recognition task. Future research should be directed towards understand-
This can be explained by two differences with previous ing the features of the practice environment (Ford &
research. First, participants used in this study were all O’Connor, 2019) that allows this postural-feature recog-
elite soccer players with mature peripheral vision (Crog- nition skill to be developed and how this information is
nale, 2002) and, therefore, all participants were able to used during decision making (see Müller & Abernethy,
detect players in the periphery (Hüttermann et al., 2012, for a model in striking sports). Once this infor-
2014). Second, the stimuli in this study were presented mation is identified, it may be used to better inform
up to 80° of visual angle. While previous studies have training of decision-making skills (Broadbent et al.,
used a 210° immersive dome and presented the 2015). Moreover, intervention studies should be
stimuli up to visual angles of 160° (cf. Hüttermann planned to investigate causal links between changes in
et al., 2019; Hüttermann et al., 2019; Klatt et al., 2019; attentional and perceptual performances in youth ath-
Klatt & Smeeton, 2020), performance at the extremities letes during the development of expertise.
of peripheral vision was not examined here. It may be At 16–18 years old, most players have adopted a
the case that the interacting effects of chronological regular playing position (e.g. defender, midfielder,
age and playing time are found when a greater attacker) and have played in that role for at least a few
number of visual angles are examined in the object- years. Future research should examine the participants’
detection task. preferred playing position. It can be assumed that the
There are some limitations and considerations for position-specific perceptual-cognitive skills acquired
future research that need to be acknowledged. In might impact on the perception of and attention to
order to examine a larger number of visual angles, the information extracted from peripheral vision (e.g.
608 S. KLATT AND N. J. SMEETON

midfielders are usually required to scan all around them performance in the field: Future research directions.
due to the position on the pitch, whereas for central European Journal of Sport Science, 15, 322–331.
Crognale, M. A. (2002). Development, maturation, and aging of
defenders the play is typically in front of them). Further-
chromatic visual pathways: VEP results. Journal of Vision, 2,
more, the hours accumulated in different types of 438–450.
soccer-specific activities (e.g. practice, play, competition) Dehaene, S., Changeux, J., Naccache, L., Sackur, J., & Sergent, C.
has been shown to have an impact on perceptual-cogni- (2006). Conscious, preconscious and subliminal processing:
tive skills as well. This information should be collected in A testable taxonomy. Trends in Cognitive Sciences, 10, 204–
future studies providing practice history profiles of the 211.
Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical
participants, similar to the approach taken by Williams,
power analyses using G*Power 3.1: Tests for correlation and
Ward, Bell-Walker, and Ford (2012). regression analyses. Behavior Research Methods, 41, 1149–
Although we used football players presented on a 1160.
green football pitch in the current study, the design Ford, P. R., Carling, C., Garces, M., Marques, M., Miguel, C.,
differs from the behaviour being required in a real Farrant, A., … Salmela, J. H. (2012). The developmental
activities of elite soccer players aged under-16 years from
soccer game. It is most important that players select
Brazil, England, France, Ghana, Mexico, Portugal and
and execute the best decision for their team in every Sweden. Journal of Sports Sciences, 30, 1653–1663.
game situation. The current design required participants Ford, P. R., & O’Connor, D. (2019). Practice and sports activities
to make the right decision (i.e. where to pass the ball) in the acquisition of anticipation and decision making. In A.
and also to perceive various teammates and opponent M. Williams & R. C. Jackson (Eds.), Anticipation and decision
players simultaneously as all the information should be making in sport (pp. 267–285). London: Routledge.
Helsen, W. F., & Starkes, J. L. (1999). A multidimensional
brought together for each trial. Participants made the
approach to skilled perception and performance in sport.
correct decision (pass to the right/left side, no pass) in Applied Cognitive Psychology, 13, 1–27.
89% of trials. This high percentage indicated that even Hommel, B., Chapman, C., Cisek, P., Neyedli, H. F., Song, J.-H., &
though the players did not report all details correctly Welsh, T. (2019). No one knows what attention is. Attention,
(e.g. number of opponent players and running direction Perception & Psychophysics, 81, 228–2303.
Hüttermann, S., Ford, P. R., Williams, A. M., Varga, M., &
of the teammates), they were very often able to attend
Smeeton, N. J. (2019). Attention, perception, and action in
to the information enabling them to make the correct a simulated decision-making task. Journal of Sport and
decision. Possibly, they sometimes intuitively made the Exercise Psychology, 41, 230–241.
right decision without having seen all the necessary Hüttermann, S., Helsen, W. F., Put, K., & Memmert, D. (2018).
information. Does visual attention impact on decision-making in
In summary, perceptual cognitive processes in elite complex dynamic events? Journal of Sport and Exercise
Psychology, 40, 163–166.
junior soccer players were examined. It was found that
Hüttermann, S., & Memmert, D. (2018). Effects of lab- and field-
both chronological age and training experience based attentional training on athletes’ attention-window.
influenced the recognition of postural feature in periph- Psychology of Sport and Exercise, 38, 17–27.
eral vision, whereas player detection was unaffected. It is Hüttermann, S., Memmert, D., & Liesner, F. (2014). Finding the
concluded that the ability to recognize postural features happy medium: An analysis of gaze behavior strategies in a
representative task design of soccer penalties. Journal of
in peripheral vision is an important characteristic of
Applied Sport Psychology, 26, 172–181.
decision making in sports and requires a mature visual Hüttermann, S., Memmert, D., & Nerb, J. (2019). Individual
system, sufficient attentional capacity, and may be differences in attentional capability are linked to creative
developed through extended task-specific practice. decision making. Journal of Applied Social Psychology, 49,
159–167.
Hüttermann, S., Memmert, D., & Simons, D. J. (2014). The size
Disclosure statement and shape of the attentional “spotlight” varies with differ-
ences in sports expertise. Journal of Experimental
No potential conflict of interest was reported by the author(s). Psychology: Applied, 20, 147–157.
Hüttermann, S., Memmert, D., Simons, D. J., & Bock, O. (2013).
Fixation strategy influences the ability to focus attention
ORCID on two spatially separate objects. PLoS ONE, 8, e65673.
Stefanie Klatt http://orcid.org/0000-0002-2477-8699 Hüttermann, S., Noël, B., & Memmert, D. (2018). Eye tracking in
high-performance sports: Evaluation of its application in
expert athletes. International Journal of Computer Science
in Sport, 17, 182–203.
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