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dc.contributor.authorHunter, Ben
dc.contributor.authorMeyler, Samuel
dc.contributor.authorMuniz, Daniel
dc.date.accessioned2022-08-26T15:30:03Z
dc.date.available2022-08-26T15:30:03Z
dc.date.issued2022-07-01
dc.identifier.citationHunter , B , Meyler , S & Muniz , D 2022 , ' Commentary on Viewpoint: Using V̇O2max as a marker of training status in athletes - can we do better? ' , Journal of Applied Physiology , vol. 133 , no. 1 , pp. 156-157 . https://doi.org/10.1152/japplphysiol.00224.2022
dc.identifier.issn8750-7587
dc.identifier.otherPURE: 28047766
dc.identifier.otherPURE UUID: 47270d58-b111-42c8-abcb-2e4db42b1e0d
dc.identifier.otherScopus: 85134426717
dc.identifier.otherORCID: /0000-0002-6748-9870/work/117949589
dc.identifier.otherORCID: /0000-0003-4190-4543/work/117949689
dc.identifier.urihttp://hdl.handle.net/2299/25741
dc.description© 2022 the American Physiological Society. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1152/japplphysiol.00224.2022
dc.description.abstractTo the editor: Podlogar et al. (1) have presented a compelling argument for using the critical intensity as an alternative method of classifying athletes. It was concluded that the critical intensity best represents the culmination of several physiological capabilities while being a strong predictor of performance. We agree that laboratory-based determination of critical intensity can be costly and time-consuming (2). However, field-based testing can be used to determine the critical intensity, which broadens the potential application of monitoring athletes in the field. Furthermore, we would like to posit that reasonable estimates of critical power (CP) and critical speed (CS) can also be derived from habitual training data. Karsten et al. (3) demonstrated that CP estimates derived from training data in cyclists showed high levels of agreement with estimates derived from laboratory testing. Smyth and Muniz-Pumares (4) showed that CS can be determined using training data in a large group of marathon runners. Importantly, these estimations were strong predictors of marathon performance. Further to training data, the use of historical best performances of elite runners demonstrates another promising avenue in which athletes may be stratified (5). Although this approach may be useful in applied conditions or athlete classification, caution should be exercised when using it for research where more accurate estimations are desirable. To summarize, the use of training data to estimate CS or CP could permit the classification of athletes. In addition, such an approach permits remote alteration of training interventions in response to changes in training status over time.en
dc.format.extent2
dc.language.isoeng
dc.relation.ispartofJournal of Applied Physiology
dc.titleCommentary on Viewpoint: Using V̇O2max as a marker of training status in athletes - can we do better?en
dc.contributor.institutionDepartment of Psychology, Sport and Geography
dc.contributor.institutionSchool of Life and Medical Sciences
dc.contributor.institutionCentre for Research in Psychology and Sport Sciences
dc.contributor.institutionSport, Health and Exercise
dc.contributor.institutionAdaptive Physiology and Functional Nutrition
dc.contributor.institutionHealth and Wellbeing
dc.description.statusPeer reviewed
dc.date.embargoedUntil2023-07-12
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85134426717&partnerID=8YFLogxK
rioxxterms.versionAM
rioxxterms.versionofrecordhttps://doi.org/10.1152/japplphysiol.00224.2022
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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