Applying Acute:Chronic Workload Ratio

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Monitoring and managing training and match loads is critical to optimizing performance and preventing injury. Given the hectic, unconventional, and condensed schedule of many sports of the 2020-2021 season, managing player loads is going to be of utmost importance in getting players ready to play and keeping them healthy. Effective monitoring not only provides important feedback, but also assist in the planning and periodization of training. 

Today, athletes are exposed to increased training demands, condensed competition schedules, and shorter periods to rest and recover. This increased match congestion has been shown to increase injury rates among professional soccer players (Bengtsson et al., 2013). In recent years, training-load management and monitoring have been an area of increased attention. Evidence suggests that proper training-load management and prescription can reduce injury risk, as the majority of training-load related injuries are preventable. Monitoring protocols should address load management to improve performance, track readiness, and prevent injury. 

While monitoring the absolute load is important, it may be even more important to consider the rate of change in training load. The acute:chronic workload ratio (ACWR) has gained popularity due to its versatility and ability to calculate sudden changes in load.

What is the Acute:Chronic Workload Ratio?

The acute:chronic workload ratio (ACWR) can be used to understand athletes’ past and present fitness levels by comparing what they have done and what they have prepared for. Banister et al. suggested an athlete’s performance in response to training can be estimated from the difference between “fatigue” and “fitness” (Banister et al., 1975). The ideal “sweet spot” would maximize performance potential using an appropriate training load while limiting the negative consequences of training (injury, fatigue, overtraining, etc.). 

Acute workload is typically the workload performed by an athlete in one week. Acute workload represents the “fatigue” aspect of ACWR. 

Chronic workload is typically the four-week average acute workload. Chronic workload gives a representation of what an athlete has done and indicates the athlete’s “fitness.”

Comparing the acute training load to the chronic training load as a ratio can provide an index of athlete preparedness (Gabbett, 2016). If the acute training load is low (minimal fatigue) and the average chronic training load is high (the athlete has developed “fitness”), then the ACWR will be around 1 or less and the athlete will be well-prepared. When the acute load is higher (resulting in “fatigue”) and the average chronic training load is low (inadequate “fitness”), then the ACWR will be greater than 1 and the athlete may be in a fatigued state. 

Calculating ACWR

External or internal training-load measures can be used when determining ACWR. 

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External load is the external stimulus applied to an athlete using objectively measurable work during training or competition. Typical metrics include total distance, number of sprints, or weight lifted and can be measured using wearable technology. 

Internal load is the individual psychological or physiological response to external loads combined with other environmental or biological factors. This may include measures such as heart rate, RPE, or blood lactate concentrations. 

The ratio itself is calculated by dividing the acute workload (“fatigue”) by the chronic workload (“fitness”).

When calculating ACWR, it may be beneficial to include both internal and external training loads, as identical external training loads may result in considerably different internal responses. Whenever possible, monitoring training loads should be done on an individual basis and focus on the metrics that provide the most insight or are the most relevant for the individual or team. 

Importance of ACWR

ACWR and Injury Risk

Comparing acute and chronic loads as a ratio can serve as a snapshot of athlete preparedness. As stated previously, if the ACWR is around 1 or less, then the athlete should be in a well-prepared state. If the ACWR exceeds 1, then the athlete will be in a more fatigued state and could be at a greater risk of injury. Gabbett defined the following ranges and their meanings:

  • <0.80: under training and higher injury risk
  • 0.80-1.30: optimal workload and lowest relative injury risk
  • >1.50: overtraining “danger zone” and highest relative injury risk
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While these zones are helpful, each athlete may have a different “sweet spot.” Previous training history, injury history, and level of participation will have a large impact on their training-load tolerance and injury risk. Malone et al. found a “sweet spot” of 1.00-1.25 in professional soccer provided the lowest risk of injury (Malone et al., 2017). 

Injury Protection and High Chronic Loads

The ACWR can, for training planning and periodization, not just to monitor athletes from day-to-day. Studies have shown that appropriately planned and progressed training may protect against injuries and that athletes with higher chronic loads were more protected against injuries when they were exposed to higher acute training loads (Hulin et al., 2016). This study also found that players with a higher chronic workload were more resistant to injury than those with a low chronic workload. 

Bowen et al. recommend including progressive exposure to higher loads to improve players’ physical capacities while minimizing the risk of a rapid, excessive spike in training load (Bowen et al., 2020). In a similar study of elite youth soccer players, Bowen et al. found that high, excessive acute loads were related to greater injury risk, but progressive chronic exposure to higher workloads – accompanied by fluctuations to allow for adaptation and recovery – protected players from injury and developed physical capacity (Bowen et al., 2017). The increased fitness level associated with high chronic training loads allows for greater increases in training load from week-to-week without increasing the relative risk of injury (Malone et al., 2017). Further, players with higher aerobic capacity and chronic training load were more protected against rapid increases (spikes) in ACWR. 

Training-Load Spikes and Injury

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Analyzing training-load data and ACWR can provide insight into training-load progression and be a useful tool in changes in workload over time. Rapid and excessive increases in training load have been found to be responsible for a large percentage of non-contact soft tissue injuries (Bengtsson et al., 2013; Malone et al., 2017; Bowen et al., 2017; Bowen et al., 2020). 

Bowen et al. found that ACWR was more strongly associated with non-contact injury risk in English Premier League players than accumulated load alone. This indicates that the increase in load may be more responsible for injuries than work performed, as acute spikes were seen to produce the greatest non-contact injury risk (Bowen et al., 2020). Therefore, week-to-week changes in training load should be monitored to minimize injury risk. Ideal training-load increases should be around 10% (Malone et al., 2017). 

In soccer, injury risk may be phase dependent, with increased risk during the preseason even when absolute training load is similar (Malone et al., 2017). Given that chronic training load tends to be lower during the preseason period, rapid increases in acute workload may cause spikes that may expose athletes to potential injury.  This highlights the value of an appropriate off-season fitness program to maintain or improve the capacity of players as to reduce the risk of injury throughout the preseason period in which players may be more vulnerable to injury (Malone et al., 2017). 

Key Takeaways:

  • Monitoring and managing training and match loads is critical to optimizing performance and preventing injury.
  • The acute:chronic workload ratio (ACWR) can be used to understand athletes’ past and present fitness levels by comparing what they have done and what they have prepared for.
  • The ACWR “sweet spot” is around 0.80-1.30 which optimizes workload and has the lowest relative injury risk.
  • Rapid and excessive increases in training load have been found to be responsible for a large percentage of non-contact soft tissue injuries.
  • Athletes with higher chronic loads were more protected against injuries when they were exposed to higher acute training loads.

References:

Bengtsson H, Ekstrand J, Hägglund M. 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. 2013 Aug;47(12):743-7. doi: 10.1136/bjsports-2013-092383. PMID: 23851296.

Calvert, Thomas & Banister, Eric & Savage, Margaret & Bach, Tim. (1976). A Systems Model of the Effects of Training on Physical Performance. Systems, Man and Cybernetics, IEEE Transactions on. SMC-6. 94 – 102. 10.1109/TSMC.1976.5409179.

Gabbett TJ The training—injury prevention paradox: should athletes be training smarter and harder? British Journal of Sports Medicine 2016;50:273-280.

Malone, S., Owen, A., Newton, M., Mendes, B., Collins, K. and Gabbett, T., 2017. The acute: chronic workload ratio in relation to injury risk in professional soccer.Journal of Science and Medicine in Sport, 20(6), pp.561-565.

Bowen L, Gross AS, Gimpel M, et al Accumulated workloads and the acute:chronic workload ratio relate to injury risk in elite youth football players British Journal of Sports Medicine 2017;51:452-459.

Bowen L, Gross AS, Gimpel M, et al Spikes in acute:chronic workload ratio (ACWR) associated with a 5–7 times greater injury rate in English Premier League football players: a comprehensive 3-year study British Journal of Sports Medicine 2020;54:731-738.

Hulin, B., Gabbett, T., Lawson, D., Caputi, P. and Sampson, J., 2015. The acute: chronic workload ratio predicts injury: high chronic workload may decrease injury risk in elite rugby league players.British Journal of Sports Medicine, 50(4), pp.231-236.

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