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

Impellizzeri, FM; Woodcock, S; Coutts, AJ; Fanchini, M; McCall, A; Vigotsky, AD

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

Impellizzeri, FM Woodcock, S

Coutts, AJ Fanchini, M McCall, A Vigotsky, AD

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Publisher:: ADIS INT LTD
Publication Type:: Journal Article
Citation:: Sports medicine (Auckland, N.Z.), 2020, 8, (10)
Issue Date:: 2020-12-17

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Field	Value	Language
dc.contributor.author	Impellizzeri, FM
dc.contributor.author	Woodcock, S https://orcid.org/0000-0003-4903-3164
dc.contributor.author	Coutts, AJ
dc.contributor.author	Fanchini, M
dc.contributor.author	McCall, A
dc.contributor.author	Vigotsky, AD
dc.date.accessioned	2021-01-07T04:12:10Z
dc.date.available	2020-10-23
dc.date.available	2021-01-07T04:12:10Z
dc.date.issued	2020-12-17
dc.identifier.citation	Sports medicine (Auckland, N.Z.), 2020, 8, (10)
dc.identifier.issn	0112-1642
dc.identifier.issn	1179-2035
dc.identifier.uri	http://hdl.handle.net/10453/145169
dc.description.abstract	<h4>Aim</h4>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).<h4>Methods</h4>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.<h4>Results</h4>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).<h4>Discussion</h4>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.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	ADIS INT LTD
dc.relation.ispartof	Sports medicine (Auckland, N.Z.)
dc.relation.isbasedon	10.1136/bmjopen-2018-022626
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject	0913 Mechanical Engineering, 1106 Human Movement and Sports Sciences, 1302 Curriculum and Pedagogy
dc.subject.classification	Sport Sciences
dc.title	What Role Do Chronic Workloads Play in the Acute to Chronic Workload Ratio? Time to Dismiss ACWR and Its Underlying Theory.
dc.type	Journal Article
utslib.citation.volume	8
utslib.location.activity	New Zealand
utslib.for	0913 Mechanical Engineering
utslib.for	1106 Human Movement and Sports Sciences
utslib.for	1302 Curriculum and Pedagogy
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Health
utslib.copyright.status	closed_access	*
dc.date.updated	2021-01-07T04:12:02Z
pubs.issue	10
pubs.publication-status	Published
pubs.volume	8
utslib.citation.issue	10

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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http://hdl.handle.net/10453/145169