Literature DB >> 32502973

Acute:Chronic Workload Ratio: Conceptual Issues and Fundamental Pitfalls.

Franco M Impellizzeri, Matthew S Tenan, Tom Kempton, Andrew Novak, Aaron J Coutts.   

Abstract

The number of studies examining associations between training load and injury has increased exponentially. As a result, many new measures of exposure and training-load-based prognostic factors have been created. The acute:chronic workload ratio (ACWR) is the most popular. However, when recommending the manipulation of a prognostic factor in order to alter the likelihood of an event, one assumes a causal effect. This introduces a series of additional conceptual and methodological considerations that are problematic and should be considered. Because no studies have even tried to estimate causal effects properly, manipulating ACWR in practical settings in order to change injury rates remains a conjecture and an overinterpretation of the available data. Furthermore, there are known issues with the use of ratio data and unrecognized assumptions that negatively affect the ACWR metric for use as a causal prognostic factor. ACWR use in practical settings can lead to inappropriate recommendations, because its causal relation to injury has not been established, it is an inaccurate metric (failing to normalize the numerator by the denominator even when uncoupled), it has a lack of background rationale to support its causal role, it is an ambiguous metric, and it is not consistently and unidirectionally related to injury risk.
Conclusion: There is no evidence supporting the use of ACWR in training-load-management systems or for training recommendations aimed at reducing injury risk. The statistical properties of the ratio make the ACWR an inaccurate metric and complicate its interpretation for practical applications. In addition, it adds noise and creates statistical artifacts.

Keywords:  critical analysis; injuries; training load; training principles

Year:  2020        PMID: 32502973     DOI: 10.1123/ijspp.2019-0864

Source DB:  PubMed          Journal:  Int J Sports Physiol Perform        ISSN: 1555-0265            Impact factor:   4.010


  15 in total

1.  Training Load, Heart Rate Variability, Direct Current Potential and Elite Long Jump Performance Prior and during the 2016 Olympic Games.

Authors:  Joseph Coyne; Aaron Coutts; Robert Newton; G Gregory Haff
Journal:  J Sports Sci Med       Date:  2021-06-15       Impact factor: 2.988

2.  Training Load and Its Role in Injury Prevention, Part 2: Conceptual and Methodologic Pitfalls.

Authors:  Franco M Impellizzeri; Alan McCall; Patrick Ward; Luke Bornn; Aaron J Coutts
Journal:  J Athl Train       Date:  2020-09-01       Impact factor: 2.860

3.  Chronic Workload, Subjective Arm Health, and Throwing Injury in High School Baseball Players: 3-Year Retrospective Pilot Study.

Authors:  Sameer Mehta; Sisi Tang; Chamith Rajapakse; Scott Juzwak; Brittany Dowling
Journal:  Sports Health       Date:  2021-11-15       Impact factor: 3.843

4.  Comparison of Measurements of External Load between Professional Soccer Players.

Authors:  Roghayyeh Gholizadeh; Hadi Nobari; Lotfali Bolboli; Marefat Siahkouhian; João Paulo Brito
Journal:  Healthcare (Basel)       Date:  2022-06-15

5.  Not straightforward: modelling non-linearity in training load and injury research.

Authors:  Lena Kristin Bache-Mathiesen; Thor Einar Andersen; Torstein Dalen-Lorentsen; Benjamin Clarsen; Morten Wang Fagerland
Journal:  BMJ Open Sport Exerc Med       Date:  2021-08-06

Review 6.  Training Load Monitoring Considerations for Female Gaelic Team Sports: From Theory to Practice.

Authors:  John D Duggan; Jeremy A Moody; Paul J Byrne; Stephen-Mark Cooper; Lisa Ryan
Journal:  Sports (Basel)       Date:  2021-06-05

7.  External Training Load and the Association With Back Pain in Competitive Adolescent Tennis Players: Results From the SMASH Cohort Study.

Authors:  Fredrik Johansson; Tim Gabbett; Per Svedmark; Eva Skillgate
Journal:  Sports Health       Date:  2021-10-25       Impact factor: 3.843

8.  Association Between Spikes in External Training Load and Shoulder Injuries in Competitive Adolescent Tennis Players: The SMASH Cohort Study.

Authors:  Fredrik Johansson; Ann Cools; Tim Gabbett; Jaime Fernandez-Fernandez; Eva Skillgate
Journal:  Sports Health       Date:  2021-10-25       Impact factor: 3.843

Review 9.  A Narrative Review for a Machine Learning Application in Sports: An Example Based on Injury Forecasting in Soccer.

Authors:  Alessio Rossi; Luca Pappalardo; Paolo Cintia
Journal:  Sports (Basel)       Date:  2021-12-24

10.  Facilitators and barriers for implementation of a load management intervention in football.

Authors:  Torstein Dalen-Lorentsen; Andreas Ranvik; John Bjørneboe; Benjamin Clarsen; Thor Einar Andersen
Journal:  BMJ Open Sport Exerc Med       Date:  2021-06-22
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