Editorial: Acute: Chronic Workload Ratio: Is There Scientific Evidence?

Abstract

The scientific monitoring of athletes is fundamental to determine and understand the individual biological responses to training (Halson, 2014). In elite sports, it is crucial to regularly monitor training and performance to detect biopositive or negative responses that can be used to effectively program training according to the needs of each athlete (Bourdon et al., 2017). Moreover, workload monitoring can also help to assess fatigue and indicate the need for recovery in different physically demanding situations to ultimately avoid injuries (Halson, 2014). As there is evidence that lower injury rates are associated with higher team sport performances (Eirale et al., 2013), sport scientists and medical staff should regularly and accurately evaluate athletes' injury risk using workload measures (Halson, 2014). Based on Banister et al. (1975) fitness and fatigue model, Gabbett et al. (2016) introduced the concept of the acute:chronic workload ratio (ACWR) with acute workload hypothetically representing the fatigue component and chronic workload the fitness component of Banister's model (Figure 1). ACWR allows individualized performance development and injury prevention using the relation between acute to chronic workload data. For this purpose, internal (e.g., heart rate, session-rate of perceived exertion [sRPE] × duration) and external (e.g., performance measures, tracking variables such as running speed and/or acceleration using Global Positioning Systems [GPS]) load measures should be collected to compute ACWR during training and competition (Malone et al., 2017). It has previously been recommended to determine the ratio between acute (training load accumulated during the last 7 days) and chronic (mean training load over the previous 3 to 6 weeks) workloads (Gabbett et al., 2016; Gabbett and Whiteley, 2017). The underlying rationale is that athletes' physical fitness develops adequately if the chronic load progressively increases to high levels while the acute load remains below, similar to, or slightly above the chronic workload (i.e., ACWR range between 0.8 and 1.3). Conversely, the athlete is considered not well-prepared and likely at an increased risk of sustaining acute or overuse injuries if the acute workload exceeds the chronic load (i.e., ACWR ≥ 1.5) (Malone et al., 2017; Windt and Gabbett, 2017). Open in a separate window Figure 1 Conceptual model for developing athlete monitoring systems according to the fitness-fatigue model using the acute: chronic workload (ACWR) approach and internal/external workload measures. While the fitness component is comparable to chronic workload (e.g., 28 days rolling average workload), fatigue is comparable to acute workload (e.g., 7 days rolling average workload) (adapted from Coutts et al., 2018).