Better way to determine the acute:chronic workload ratio?

Williams, Seán; West, Stephen W; Cross, Matthew; Stokes, Keith

doi:10.1136/bjsports-2016-096589

Cited by 127 publications

(157 citation statements)

References 7 publications

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“…27,40 This analytical approach has recently been reported to identify injury risk in a variety of athletes. 27,54,55 However, while interesting for monitoring injury risk, the validity of the ACWR has recently been questioned 56,57 as the rolling average fails to account for the decaying nature of fitness and fatigue effects over time, and therefore it may not accurately represent variations in the manner in which loads are accumulated. An alternative method is to use an exponentially weighted moving average 58 for the calculation of acute and chronic loads, which assigns a decreasing weighting to compensate for the latency effects of loads.…”

Section: Analyzing Training-load Datamentioning

confidence: 99%

“…An alternative method is to use an exponentially weighted moving average 58 for the calculation of acute and chronic loads, which assigns a decreasing weighting to compensate for the latency effects of loads. 57 Further research is, however, required to determine if this new model provides a superior approach for predicting performance and/or injury.…”

Section: Analyzing Training-load Datamentioning

confidence: 99%

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Monitoring Athlete Training Loads: Consensus Statement

Bourdon¹,

Cardinale²,

Murray³

et al. 2017

International Journal of Sports Physiology and Performance

725

735

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Monitoring the load placed on athletes in both training and competition has become a very hot topic in sport science. Both scientists and coaches routinely monitor training loads using multidisciplinary approaches, and the pursuit of the best methodologies to capture and interpret data has produced an exponential increase in empirical and applied research. Indeed, the field has developed with such speed in recent years that it has given rise to industries aimed at developing new and novel paradigms to allow us to precisely quantify the internal and external loads placed on athletes and to help protect them from injury and ill health. In February 2016, a conference on "Monitoring Athlete Training Loads-The Hows and the Whys" was convened in Doha, Qatar, which brought together experts from around the world to share their applied research and contemporary practices in this rapidly growing field and also to investigate where it may branch to in the future. This consensus statement brings together the key findings and recommendations from this conference in a shared conceptual framework for use by coaches, sport-science and -medicine staff, and other related professionals who have an interest in monitoring athlete training loads and serves to provide an outline on what athlete-load monitoring is and how it is being applied in research and practice, why load monitoring is important and what the underlying rationale and prospective goals of monitoring are, and where athlete-load monitoring is heading in the future.

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Section: Analyzing Training-load Datamentioning

confidence: 99%

Section: Analyzing Training-load Datamentioning

confidence: 99%

Monitoring Athlete Training Loads: Consensus Statement

Bourdon¹,

Cardinale²,

Murray³

et al. 2017

International Journal of Sports Physiology and Performance

725

735

View full text Add to dashboard Cite

show abstract

“…Recently, Williams et al 18 proposed the use of ‘exponentially weighted moving averages (EWMA)’19 as a new method to calculate acute and chronic loads to address the decaying nature of fitness and fatigue. This method assigns a decreasing weighting to each older load value, thereby giving more weighting to the recent load undertaken by the athlete.…”

Section: Introductionmentioning

confidence: 99%

Calculating acute:chronic workload ratios using exponentially weighted moving averages provides a more sensitive indicator of injury likelihood than rolling averages

Gabbett²,

et al. 2016

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“…Hypotheses are theories that are evidence-driven. In a recent insightful British Journal of Sports Medicine letter, Williams et al 8 hypothesised that when determining injury risk, an exponentially weighted moving average (EWMA) offered a ‘ better ’ approach to calculating the acute:chronic workload ratio (ACWR) than rolling averages (RA). Their findings did indeed show that the two methods were different.…”

Section: The Cyclical Continuum Of Evidencementioning

confidence: 99%