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Importance of Monitoring

Athlete monitoring is essential for optimizing performance and reducing injury

risk because it provides insights into an athlete’s physiological and biomechanical state.

This allows for tailored training programs, early detection of injury, fatigue, and

overtraining, and it allows for timely interventions to be put into place to prevent strain

and overuse injuries (Gabbett et al., 2017). Monitoring helps to balance training load and

recovery. This helps to minimize the risk of overtraining or undertraining and maximize

adaptations. Athlete monitoring also helps to reduce injury risk by tracking internal (for

example, heart rate and perceived exertion) and external (for example, distance covered

and accelerations) loads, monitoring systems identify patterns that may lead to injuries,

which allows for timely interventions. Although an athlete may track these things on their

own, they may not understand how to interpret them or how to use the data to improve

without a professional (like a coach) to help them. Regular monitoring also enhances

performance by providing insights into individual athlete responses to training. These

performance insights can then be used to make sure that training programs are

personalized and can help the athlete optimizer strength, endurance, and skill

development. As well as this, the data collected allows coaches to adjust training plans in

real-time, ensuring that athletes are prepared for competition without unnecessary

physical or psychological stress. Lastly, athlete monitoring helps to improve long-term

development. Tracking progress over time helps to design sustainable training programs

that support long-term performance gains while preventing burnout and injuries.

Athlete monitoring influences decision-making in training and competition by

providing real-time, individualized insights into an athlete’s physical and sometimes,

psychological state. One of the key ways in which it does this is by identifying fatigue

and readiness. Specifically using self-reporting methods, athletes can communicate their

perceived fatigue, muscle soreness, stress, and sleep quality, helping coaches adjust

training loads accordingly to optimize recovery and prevent overtraining (Saw et al.,

2015). Of course, this can also be done by a coach observing and monitoring data from

athletes as performance and energy levels tend to decrease when an athlete is overtrained.

Another key factor is that it allows for personalized training adjustments. Coaches can

use monitoring and self-reporting from athletes to tailor training programs based on how

athletes feel, ensuring that they have an adequate training load and stimulus to enhance

performance while reducing risk of injury. Next, monitoring helps to detect injury or

illness early as self-reported well-being can often indicate signs of an injury or illness,

allowing early intervention. Monitoring also helps to make decisions as to when an

athlete should be tapering and peaking. Monitoring can help coaches to determine

whether an athlete is in peak condition for competition or if modifications to training and

recovery are needed to maximize performance. Lastly, monitoring psychological and

emotional well-being can help coaches to make decisions to help manage anxiety and

prevent burnout, which both directly influence performance and an athletes’ readiness to

train and compete.

There are several challenges associated with athlete monitoring. Limitations

around time, expertise, and resources is one of them (Timmerman et al., 2024). Coaches

and support staff face constraints in terms of financial and human resources. A lack of

time to collect, analyze and interpret the data effectively is another issue as well as

limited expertise in understanding and applying these complex data-driven insights.

Athletes may also resist monitoring due to concerns about time, effort, and privacy.

Compliance with monitoring protocols is essential, however, it is challenging to maintain

for these reasons. Next, the reliability and validity of athlete monitoring tools may be a

concern. There could be difficulty in establishing objective thresholds for data

interpretation as well as an over-reliance on technology that could potentially distance

coaches from athletes. Logistical constraints are also a concern as identifying appropriate

times for monitoring is difficult, especially in a team sport setting. Lastly, balancing

subjective and objective data can be complicated. Combining data-driven insights with

personal feedback is necessary for effective monitoring, however, over-reliance on

numbers may overlook critical contextual factors affecting performance.

Tools and Techniques

Appropriate load monitoring can help to determine whether an athlete is adapting

to a training program adequately and minimize the risk of developing illness, injury, or

burnout. There are different tools and techniques used for athlete monitoring. External

load monitoring is where the work completed by an athlete is assessed, independent of

their internal psychological responses (Halson, 2014). Power output measuring devices

such as SRM in cycling can be used to continuously measure power output, providing

data on average and normalized power, speed, and accelerations. Time-motion analysis is

also used, predominantly in team sports, and movement patterns are evaluated as well as

distances covered, and times spent in various activity zones during training and

competition. Internal load monitoring is another way to monitor athletes. This method

evaluates the athlete’s physiological and psychological responses to training. Here,

techniques such as rating of perceived exertion (RPE), heart rate monitoring, blood
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lactate concentration, and training impulse (combining training duration and intensity to

quantify overall training load) are used. As well as these two main categories, other

monitoring tools can be effective. Assessing the rate at which heart rate returns to

baseline post-exercise can indicate an athlete’s fitness and fatigue levels. As well as this,

neuromuscular function tests and tests evaluating reaction time and cognitive function

can be beneficial. Analyzing blood markers can also provide insights into physiological

stress and recovery status. Finally, questionnaires and diaries where athletes can self-

report well-being, perceived fatigue, and sleep quality can help to monitor them.

These tools contribute to understanding athlete readiness and performance in

various ways. First, external load monitoring helps to measure the physical workload an

athlete undergoes during training or competition (Neupert et al., 2022). It also helps

coaches ensure that athletes are training at optimal intensities and volumes and helps to

detect overtraining risks by comparing workload trends over time. Internal load

monitoring allows one to evaluate how an athlete’s body responds to external loads and

helps identify excessive fatigue or undertraining by tracking physiological stress. Next,

neuromuscular function tests, such as jump tests, or sprint assessments, can detect muscle

fatigue and recovery status. This guides coaches in terms of adjustments to training laods

to optimize performance and prevent injury. Biochemical and hormonal assessments

provide insights into the body’s response to stress, inflammation, and recovery status, as

well as immune function. Lastly, Psychological and sleep monitoring allows coaches to

identify mental fatigue and recovery issues. This information also helps to ensure optimal

sleep and psychological readiness for peak performance.

There are both strengths and limitations associated with each monitoring tool.

External load monitoring, using tools like GPS, power meters, and time-motion analysis,

provides objective, quantifiable data on workload (Timmerman et al., 2024). It helps in

planning training loads and tracking physical demands which, in turn, helps to prevent

overtraining and optimize performance. Some limitations associated with these tools are

that they may not reflect individual physiological responses and the accuracy can vary

based on the device used. As well as this, they can have limited applicability to all sports,

especially those with irregular movement patterns. Internal load monitoring, such as

measuring heart rate, RPE, and blood lactate, can give insights into how an athlete’s body

is responding to training and can tell someone a lot about fatigue, recovery, and fitness

levels. Internal load monitoring data can also be integrated with external load data for a

comprehensive analysis. However, some of the variables measured, like heart rate, can be

influenced by external factors like stress or temperature and may require specialized

equipment like with blood lactate testing. Next, neuromuscular junction tests provide

insight into muscle fatigue and readiness, are quick and easy to implement in training,

and are useful for monitoring recovery and injury risk. Some limitations are that the

results can be influenced by motivation and technique, are not always indicative of

whole-body fatigue, and consistent testing protocols are required for accuracy.

Biochemical and hormonal assessments can be beneficial as they provide deep insights

into stress, recovery, and overall health, and can detect early signs of overtraining and

illness. However, these tests can be invasive and expensive and are not feasible for

frequent monitoring since they need to be analyzed in a laboratory. Along with this, the

results obtained may not provide immediate, actionable feedback. In terms of

psychological and sleep monitoring, in the form of questionnaires, for example, they can

be beneficial as they help to identify mental fatigue and psychological stress. They

provide insights into recovery and readiness and are relatively easy to implement and are

non-invasive. Nonetheless, these tools come with some limitations. One is that self-

reported data may be biased or inaccurate. Another is that sleep trackers may lack

precision in measuring sleep stages. Lastly, psychological metrics can be influenced by

external factors that are not related to training.

Fatigue Management

Fatigue management is a crucial aspect of athletic performance. It allows athletes

to optimize performance, enhance recovery, and promote long-term athletic health. As

well as this, it helps to prevent injuries and maximize training adaptations. The acute-to-

chronic workload ratio (ACWR) compares the recent training load (acute training load) to

the average workload over a longer period (chronic training load) to assess training

progression and injury risk (Maupin, 2020). It is calculated by dividing acute workload

by chronic workload. Acute workload often represents the workload accumulated over

one week, while chronic workload is often measured over four weeks. The rationale

behind the ACWR is rooted in the fitness-fatigue model, where acute workload reflects

the fatigue component and chronic workload represents the fitness component. The ratio

can be interpreted depending on the number calculated. If ACWR is between 0.8 and 1.3,

it is considered an optimal range, indicating a balanced workload. If ACWR is above 1.5,

it suggests a sudden spike in workload, which could increase the risk of injury. On the

other hand, if ACWR is below 0.8, it may indicate insufficient training, which can also

increase injury risk due to lack of preparedness.

By monitoring ACWR, coaches and sports scientists can identify when an

athlete’s acute workload significantly exceeds their chronic workload (Pinelli et al.,

2024). This indicates a spike that may lead to increased fatigue and heightened injury

risk. Maintaining an optimal ACWR range allows for progressive overload, enhancing

fitness while minimizing injury risk. In practice, this involves carefully planning training

sessions to ensure that increases in workload are gradual and within a range that the

athlete’s body can adapt to without unnecessary stress.

The acute-to-chronic workload ratio has been applied to various sports. One

example is in soccer. Tracking players’ weekly training loads, such as sprint distance,

high-intensity runs, and total workload, can help to identify spikes in intensity. In this

case, a club might monitor an athlete’s ACWR to ensure they gradually increase their

sprinting volume after returning from injury, avoiding sudden spikes that could lead to re-

injury. This helps to optimize training loads while minimizing overtraining and muscle

injuries. Another example is monitoring jump loads, accelerations, and decelerations over

training cycles in basketball. A team may use ACWR to limit the number of high-

intensity drills per week, ensuring that players do not exceed their chronic workload and

reducing the risk of stress fractures or ligament injuries. This can help to prevent

excessive fatigue and minimize the lower limb injuries common in basketball. One more

example is monitoring total mileage, track workout intensity, and session frequency in

track and field. A runner’s higher intensity track sessions are scheduled to ensure that

their ACWR stays in an optimal range, preventing injuries and allowing for adaptations

to occur, which lead to improved fitness.

Athlete monitoring is essential for optimizing performance and minimizing injury

risk by providing data-driven insights into training loads, recovery, and overall readiness.

Effective monitoring enables coaches and sports scientists to make informed decisions,

ensuring athletes train at appropriate intensities while avoiding overtraining. However,

challenges such as data accuracy, individual variability, and resource availability can

complicate monitoring efforts. Various tools and techniques, including heart rate

variability, rating of perceived exertion (RPE), force plates, and GPS tracking, offer

valuable insights into athlete readiness, each with its strengths and limitations. Among

these, the acute-to-chronic workload ratio (ACWR) is a key metric for managing fatigue,

as it helps track workload trends and identify potential injury risks. When applied across

sports like soccer, basketball, and track and field, ACWR allows for workload

adjustments that promote gradual adaptation and injury prevention. By integrating these

monitoring strategies, athletes can strike a balance between workload progression,

recovery, and performance optimization.

References

Gabbett, T. J., Nassis, G. P., Oetter, E., Pretorius, J., Johnston, N., Medina, D., Rodas, G.,

Saw, A. E., Main, L. C., & Gastin, P. B. (2015). Monitoring athletes through self-

report: factors influencing implementation. Journal of sports science &

medicine, 14(1), 137–146.

Halson S. L. (2014). Monitoring training load to understand fatigue in athletes. Sports

medicine (Auckland, N.Z.), 44 Suppl 2(Suppl 2), S139–S147.

https://doi.org/10.1007/s40279-014-0253-z

Maupin, D., Schram, B., Canetti, E., & Orr, R. (2020). The Relationship Between Acute:

Chronic Workload Ratios and Injury Risk in Sports: A Systematic Review. Open

access journal of sports medicine, 11, 51–75.

https://doi.org/10.2147/OAJSM.S231405

Myslinski, T., Howells, D., Beard, A., & Ryan, A. (2017). The athlete monitoring cycle:

a practical guide to interpreting and applying training monitoring data. British

journal of sports medicine, 51(20), 1451–1452. https://doi.org/10.1136/bjsports-

2016-097298

Neupert, E., Gupta, L., Holder, T., & Jobson, S. A. (2022). Athlete monitoring practices

in elite sport in the United Kingdom. Journal of Sports Sciences, 40(13), 1450–

1457. https://doi.org/10.1080/02640414.2022.2085435

Pinelli, S., Mandorino, M., Fantozzi, S., & Lacome, M. (2025). Exploring the relationship

between the acute:chronic workload ratio and running parameters in elite football

athletes. Applied Sciences, 15(3), 1659. https://doi.org/10.3390/app15031659

Timmerman, W., Abbiss, C., Lawler, N., Stanley, M., & Raynor, A. (2024). Athlete

monitoring perspectives of sports coaches and support staff: A scoping review.

International Journal of Sports Science & Coaching, 19. 1813-1832.

10.1177/17479541241247131.