What Role Do Chronic Workloads Play in the Acute to Chronic Workload Ratio? Time to Dismiss ACWR and Its Underlying Theory

Abstract

Aim

The aim of this study was to examine the associations between the injury risk and the acute (AL) to chronic (CL) workload ratio (ACWR) by substituting the original CL with contrived values to assess the role of CL (i.e., the presence and implications of statistical artefacts).

Methods

Using previously published data, we generated a contrived ACWR by dividing the AL by fixed and randomly generated CLs, and we compared these results to real data. We also reproduced previously reported subgroup analyses, including dichotomising players’ data above and below the median CL. Our analyses follow the same, previously published modelling approach.

Results

The analyses with original data showed effects compatible with higher injury risk for ACWR only (odd ratios, OR: 2.45, 95% CI 1.28–4.71). However, we observed similar effects by dividing AL by the “contrived” fixed and randomly generated CLs: OR 1.95 (1.18–3.52) dividing by 1510 (average CL); and OR ranging from 1.16 to 2.07, using random CL 1.53 (mean). Random ACWRs reduced the variance relative to the original AL and further inflated the ORs (mean OR 1.89, from 1.42 to 2.70). ACWR causes artificial reclassification of players compared to AL alone. Finally, neither ACWR nor AL alone confer a meaningful predictive advantage to an intercept-only model, even within the training sample (c-statistic 0.574/0.544 vs. 0.5 in both ACWR/AL and intercept-only models, respectively).

Discussion

ACWR is a rescaling of the explanatory variable (AL, numerator), in turn magnifying its effect estimates and decreasing its variance despite conferring no predictive advantage. Other ratio-related transformations (e.g., reducing the variance of the explanatory variable and unjustified reclassifications) further inflate the OR of AL alone with injury risk. These results also disprove the etiological theory behind this ratio and its components. We suggest ACWR be dismissed as a framework and model, and in line with this, injury frameworks, recommendations, and consensus be updated to reflect the lack of predictive value of and statistical artefacts inherent in ACWR models.

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Acknowledgements

The Authors would like to thank Lorenzo Lolli for the suggestions, Marco Riggio for the support in the data extraction and preparation, and Ermanno Rampinini for the reuse of data.

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Correspondence to Franco M. Impellizzeri.

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The Authors affirm that they have no financial affiliation (including research funding) or involvement with any commercial organization that has a direct financial interest in any matter included in this manuscript.

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Data cannot be shared since there is no permission from the team owning the data, but sharing of a synthetic dataset may be considered upon request.

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This study was conducted reanalysing previously published data with the permission of the authors and the management of the team.

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We declared that all the authors made substantial contributions to the manuscript: conception, acquisition, interpretation of data, drafted the work, revised it critically for important intellectual content, approved the version to be published, and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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The original article has been updated: Due to Table 2 update.

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Impellizzeri, F.M., Woodcock, S., Coutts, A.J. et al. What Role Do Chronic Workloads Play in the Acute to Chronic Workload Ratio? Time to Dismiss ACWR and Its Underlying Theory. Sports Med 51, 581–592 (2021). https://doi.org/10.1007/s40279-020-01378-6

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