How to use ACWR to optimize physical readiness, improve performance, and reduce injury risk.
Soligard et al. (2016) showed that poor training load prescription and management is a major risk factor for injury. It is believed that these training load-related injuries are avoidable. As a result, there has been huge growth in training load monitoring in recent years, with coaches aiming to improve training load prescription and management during competition with the ultimate goal of optimizing physical readiness, improving performance, and reducing injury risk. One useful tool used by coaches in recent years is Acute:Chronic Workload Ratio (ACWR).
What is ACWR?
ACWR compares an athlete’s short-term (acute) training load and long-term (chronic) training load to provide coaches with a snapshot of an athlete’s training load history. In other words, it examines the relationship between what they have done to build up a level of fitness (chronic), and their level of fatigue (acute).
ACWR can be used to:
- Gauge an athlete’s physical readiness
- Flag an athlete’s risk of injury
- Manage training load and improve training periodisation
Metrics used to calculate ACWR
ACWR can be calculated from a wide variety of external and internal loads including:
- External Loads / Total Distance, Total Weight Lifted, Power Output
- Internal Loads / Total Training Load (sRPE), Heart Rate, Blood Lactate
For the purposes of this article and the examples given, we will use sRPE.
There are two methods that can be used to calculate ACWR:
- Rolling Average Model / treats each workload in the time period as equal.
- Exponentially Weighted Moving Average Model / puts greater emphasis on the most recent loads by applying a decreasing weighting for older workloads.
For the purposes of this article and the examples given, we will use the Rolling Average Model.
Calculating Acute Workload
Acute workload is typically calculated as the total training load performed in a training week (7 days).
To calculate acute workload, you would first calculate the sRPE of each individual activity during the training week by multiplying the duration in minutes of the activity, by the RPE (1-10). Then all of these values are added together to give you the acute workload, or total weekly training load.
|Day 1 / Gym||60||7||420|
|Day 2 / Pitch Training||75||8||600|
|Day 3 / Rest||0||0||0|
|Day 4 / Pitch Training||70||5||350|
|Day 5 / Rest||0||0||0|
|Day 6 / Match||80||8||640|
|Day 7 / Rest||0||0||0|
Calculating Chronic Workload
Chronic workload is typically calculated as the average weekly training load across a period of 4-weeks, however some coaches may choose to use a shorter 3-week window.
To calculate the chronic workload first you must calculate the weekly training load for each of the 4-weeks in the period as described above. You then calculate the average weekly training load for the time period which is your chronic workload.
|Weekly Training Load|
|Chronic Training Load||1,905|
The Acute:Chronic Workload Ratio (ACWR) is calculated by dividing the acute (short-term) workload by the chronic (long-term) workload. For example, 2,010/1,905 = 1.06
Interpreting ACWR data
To explain it in simple terms, it is preferable to have a high chronic workload, so the athlete is well-prepared, with an acute workload that is similar or slightly less than the chronic workload so that the athlete is not experiencing fatigue.
As shown in the graph below, Gabbett (2016) suggests that there is a sweet spot for reducing injury risk of between 0.8 and 1.3, however, and that below an ACWR of 0.8 that injury risk begins to increase again due to undertraining.
He presents the following ranges:
|< 0.8||Undertraining, higher relative injury risk|
|0.8 to 1.3||Sweet-spot – the lowest risk of injury|
|> 1.5||Danger zone – overtraining, highest injury risk|
Ranges are not absolute
It’s very important to clarify that these ranges are not absolute and can vary from sport to sport, and from athlete to athlete, as multiple studies have shown. Factors that should be taken into account include the athlete’s training age, stage of development, injury history, and others to give you an understanding of the individual and what their personal thresholds are.
The risks of poorly managed training load
Studies have been carried out in a number of sports including AFL (Murray et al., 2016), Rugby (Hulin et al., 2015), Soccer (Malone et al., 2017), and GAA (Malone et al., 2017). The majority of findings suggest that there is a relationship between ACWR and injury risk. As ACWR increases so too does an athlete’s risk of injury.
Studies have shown that sudden increases in training load are associated with an increase in injuries. Piggott et al. (2009) showed that an athlete’s risk of injury was relatively low at below 10% when training load increased by no more than 5-10% on the previous week. However, when the increase in training load was greater than 15%, the athletes’ injury risk jumped to between 21% and 49%.
Using ACWR to decrease injury risk
ACWR is a tool that can be used to safely manage progressions in training loads to minimize injury risk. It can be applied to program schedules or retrospective data and will flag any sudden training load increases so that coaches can make the necessary interventions to reduce injuries and optimize performance.
By monitoring Acute and Chronic workloads, coaches can also maximize performance by ensuring their athletes have been exposed to sufficient training loads to prepare them for competition while ensuring they are not fatigued going into competition and can peak when it counts.
Research has shown that poor training load prescription and management is a risk factor for injury. ACWR is one of the tools at a coach’s disposal as they try to minimize injury risk, maximize athlete readiness, and improve performance.
Monitoring ACWR can provide coaches with the insights they need to safely manage progressions in training loads, while maintaining a balance between their long-term and short-term training loads, so that their athletes are sufficiently prepared for the stresses of competition, without suffering from fatigue. Ensuring that they’re ready to perform when it counts.
- Soligard, T., Schwellnus, M., Alonso, J., Bahr, R., Clarsen, B., Dijkstra, H., Gabbett, T., Gleeson, M., Hägglund, M., Hutchinson, M., Janse van Rensburg, C., Khan, K., Meeusen, R., Orchard, J., Pluim, B., Raftery, M., Budgett, R. and Engebretsen, L., 2016. How much is too much? (Part 1) International Olympic Committee consensus statement on load in sport and risk of injury.British Journal of Sports Medicine, 50(17), pp.1030-1041. http://bjsm.bmj.com/content/50/17/1030
- Gabbett, T., 2016. The training—injury prevention paradox: should athletes be training smarter and harder?.British Journal of Sports Medicine, 50(5), pp.273-280. https://bjsm.bmj.com/content/50/5/273
- Murray, N., Gabbett, T., Townshend, A., Hulin, B. and McLellan, C., 2016. Individual and combined effects of acute and chronic running loads on injury risk in elite Australian footballers. Scandinavian Journal of Medicine & Science in Sports, 27(9), pp.990-998. https://pubmed.ncbi.nlm.nih.gov/27418064/
- 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. http://bjsm.bmj.com/content/early/2015/10/28/bjsports-2015-094817.short
- 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. https://pubmed.ncbi.nlm.nih.gov/27856198/
- Malone, S., Roe, M., Doran, D., Gabbett, T. and Collins, K., 2017. Protection Against Spikes in Workload with Aerobic Fitness and Playing Experience: The Role of the Acute: Chronic Workload Ratio on Injury Risk in Elite Gaelic Football. International Journal of Sports Physiology and Performance, 12(3), pp.393-401. https://pubmed.ncbi.nlm.nih.gov/27400233/
- Piggott, B., Newton, M. J., & McGuigan, M. R., 2009. The relationship between training load and incidence of injury and illness over a pre-season at an Australian football league club. Journal of Australian Strength and Conditioning, 17(3), pp. 4-17. http://researchonline.nd.edu.au/health_article/61/
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