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Using Field Based Data to Model Sprint Track Cycling Performance

Cycling performance models are used to study rider and sport characteristics to better understand performance determinants and optimise competition outcomes. Performance requirements cover the demands of competition a cyclist may encounter, whilst rider attributes are physical, technical and psychol...

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Autores principales: Ferguson, Hamish A., Harnish, Chris, Chase, J. Geoffrey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7966696/
https://www.ncbi.nlm.nih.gov/pubmed/33725208
http://dx.doi.org/10.1186/s40798-021-00310-0
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author Ferguson, Hamish A.
Harnish, Chris
Chase, J. Geoffrey
author_facet Ferguson, Hamish A.
Harnish, Chris
Chase, J. Geoffrey
author_sort Ferguson, Hamish A.
collection PubMed
description Cycling performance models are used to study rider and sport characteristics to better understand performance determinants and optimise competition outcomes. Performance requirements cover the demands of competition a cyclist may encounter, whilst rider attributes are physical, technical and psychological characteristics contributing to performance. Several current models of endurance-cycling enhance understanding of performance in road cycling and track endurance, relying on a supply and demand perspective. However, they have yet to be developed for sprint-cycling, with current athlete preparation, instead relying on measures of peak-power, speed and strength to assess performance and guide training. Peak-power models do not adequately explain the demands of actual competition in events over 15-60 s, let alone, in World-Championship sprint cycling events comprising several rounds to medal finals. Whilst there are no descriptive studies of track-sprint cycling events, we present data from physiological interventions using track cycling and repeated sprint exercise research in multiple sports, to elucidate the demands of performance requiring several maximal sprints over a competition. This review will show physiological and power meter data, illustrating the role of all energy pathways in sprint performance. This understanding highlights the need to focus on the capacity required for a given race and over an event, and therefore the recovery needed for each subsequent race, within and between races, and how optimal pacing can be used to enhance performance. We propose a shift in sprint-cyclist preparation away from training just for peak power, to a more comprehensive model of the actual event demands.
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spelling pubmed-79666962021-04-01 Using Field Based Data to Model Sprint Track Cycling Performance Ferguson, Hamish A. Harnish, Chris Chase, J. Geoffrey Sports Med Open Review Article Cycling performance models are used to study rider and sport characteristics to better understand performance determinants and optimise competition outcomes. Performance requirements cover the demands of competition a cyclist may encounter, whilst rider attributes are physical, technical and psychological characteristics contributing to performance. Several current models of endurance-cycling enhance understanding of performance in road cycling and track endurance, relying on a supply and demand perspective. However, they have yet to be developed for sprint-cycling, with current athlete preparation, instead relying on measures of peak-power, speed and strength to assess performance and guide training. Peak-power models do not adequately explain the demands of actual competition in events over 15-60 s, let alone, in World-Championship sprint cycling events comprising several rounds to medal finals. Whilst there are no descriptive studies of track-sprint cycling events, we present data from physiological interventions using track cycling and repeated sprint exercise research in multiple sports, to elucidate the demands of performance requiring several maximal sprints over a competition. This review will show physiological and power meter data, illustrating the role of all energy pathways in sprint performance. This understanding highlights the need to focus on the capacity required for a given race and over an event, and therefore the recovery needed for each subsequent race, within and between races, and how optimal pacing can be used to enhance performance. We propose a shift in sprint-cyclist preparation away from training just for peak power, to a more comprehensive model of the actual event demands. Springer International Publishing 2021-03-16 /pmc/articles/PMC7966696/ /pubmed/33725208 http://dx.doi.org/10.1186/s40798-021-00310-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Review Article
Ferguson, Hamish A.
Harnish, Chris
Chase, J. Geoffrey
Using Field Based Data to Model Sprint Track Cycling Performance
title Using Field Based Data to Model Sprint Track Cycling Performance
title_full Using Field Based Data to Model Sprint Track Cycling Performance
title_fullStr Using Field Based Data to Model Sprint Track Cycling Performance
title_full_unstemmed Using Field Based Data to Model Sprint Track Cycling Performance
title_short Using Field Based Data to Model Sprint Track Cycling Performance
title_sort using field based data to model sprint track cycling performance
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7966696/
https://www.ncbi.nlm.nih.gov/pubmed/33725208
http://dx.doi.org/10.1186/s40798-021-00310-0
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