About this Research Topic
The scientific monitoring of athletes’ workload is fundamental to determine and understand the individual physiological and biological responses and adaptations to training. Moreover, monitoring may also help to assess fatigue and the associated need for recovery in different situations. This again may help to minimize the risk of illness and injury. However, monitoring requires accurate measurement of sport-related and common everyday activities of an athlete such as performance, physiological responses, emotional well-being, symptoms of illness, and injuries. As a lower injury rates are associated with increased team sport performance, sport scientists and medical staff should regularly and accurately evaluate athletes’ injury risk with this measures to evaluate readiness to train and competition, as well as appropriate recovery.
Based on the early work of Banister and Calvert, Gabbett and colleagues introduced the concept of the acute:chronic workload ratio (ACWR) to model the relationship between changes in load and how these changes are related to injury risk. In the past two years, there has been growing interest in the use of ACWR to monitor athletes’ injury risk in different team sports. In general, this ratio is computed over a 28 days period and describes the ratio between the workload accumulated during the last seven days (i.e., acute training load) relative to the mean (chronic) workload over the previous three to six weeks. Athletes’ physical fitness may develop well if the chronic load is progressively increased to high levels while the acute load remains low (i.e. ACWR range between 0.8-1.3). Conversely, the athlete is considered not well-prepared and likely at an increased risk of injury if acute loads exceed chronic loads (i.e. ACWR exceeds 1.5). Thus, this model seems to consider the positive and negative effects of measured loads during training and competition for prevention of acute and more particularly overuse injuries.
Both internal (heart rate, session-rate of perceived exertion [Session-RPE] x duration) and external (fitness performance, tracking variables using for example Global Positioning Systems [GPS] such as running speed, acceleration variables) measures of loads during training and competition are frequently used to calculate ACWR. However, no physiological or biological markers have been used to validate ACWR. This ratio may present many benefits for sport scientists and/or medical staff when monitoring athletes. Indeed, it has recently been recommended as a useful method to identify injury risk. Moreover, this model has been validated in several sports such as Australian football, cricket and rugby. However, while it seems a viable mechanism for the monitoring of injury risk, the validity of the ACWR has recently been questioned, with several flaws being detected. Consequently, further research is needed to determine the underlying physiological mechanisms of ACWR and if it really constitutes a superior approach for injury risk and performance prediction in different sports.
Based on the early work of Banister and Calvert, Gabbett and colleagues introduced the concept of the acute:chronic workload ratio (ACWR) to model the relationship between changes in load and how these changes are related to injury risk. In the past two years, there has been growing interest in the use of ACWR to monitor athletes’ injury risk in different team sports. In general, this ratio is computed over a 28 days period and describes the ratio between the workload accumulated during the last seven days (i.e., acute training load) relative to the mean (chronic) workload over the previous three to six weeks. Athletes’ physical fitness may develop well if the chronic load is progressively increased to high levels while the acute load remains low (i.e. ACWR range between 0.8-1.3). Conversely, the athlete is considered not well-prepared and likely at an increased risk of injury if acute loads exceed chronic loads (i.e. ACWR exceeds 1.5). Thus, this model seems to consider the positive and negative effects of measured loads during training and competition for prevention of acute and more particularly overuse injuries.
Both internal (heart rate, session-rate of perceived exertion [Session-RPE] x duration) and external (fitness performance, tracking variables using for example Global Positioning Systems [GPS] such as running speed, acceleration variables) measures of loads during training and competition are frequently used to calculate ACWR. However, no physiological or biological markers have been used to validate ACWR. This ratio may present many benefits for sport scientists and/or medical staff when monitoring athletes. Indeed, it has recently been recommended as a useful method to identify injury risk. Moreover, this model has been validated in several sports such as Australian football, cricket and rugby. However, while it seems a viable mechanism for the monitoring of injury risk, the validity of the ACWR has recently been questioned, with several flaws being detected. Consequently, further research is needed to determine the underlying physiological mechanisms of ACWR and if it really constitutes a superior approach for injury risk and performance prediction in different sports.
Keywords: Exercise, Training load, Monitoring, Injury, Recovery, Physical Fitness, Adaptation.
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