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Wolverhampton Intellectual Repository and E-Theses > School of Sport, Performing Arts and Leisure > Research Centre for Sport, Exercise and Performance > Sport Performance > Scaling maximal oxygen uptake to predict cycling time-trial performance in the field: a non-linear approach.

Please use this identifier to cite or link to this item: http://hdl.handle.net/2436/7755
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Title: Scaling maximal oxygen uptake to predict cycling time-trial performance in the field: a non-linear approach.
Authors: Nevill, Alan M.
Jobson, Simon A.
Palmer, G.S.
Olds, Tim
Citation: European Journal of Applied Physiology, 94(5-6): 705-710
Publisher: Springer Berlin / Heidelberg
Issue Date: 2005
URI: http://hdl.handle.net/2436/7755
DOI: 10.1007/s00421-005-1321-8
PubMed ID: 15906080
Additional Links: http://www.springerlink.com/content/j863561v70228548/
Abstract: The purpose of the present article is to identify the most appropriate method of scaling VO2max for differences in body mass when assessing the energy cost of time-trial cycling. The data from three time-trial cycling studies were analysed (N = 79) using a proportional power-function ANCOVA model. The maximum oxygen uptake-to-mass ratio found to predict cycling speed was VO2max(m)(-0.32) precisely the same as that derived by Swain for sub-maximal cycling speeds (10, 15 and 20 mph). The analysis was also able to confirm a proportional curvilinear association between cycling speed and energy cost, given by (VO2max(m)(-0.32))0.41. The model predicts, for example, that for a male cyclist (72 kg) to increase his average speed from 30 km h(-1) to 35 km h(-1), he would require an increase in VO2max from 2.36 l min(-1) to 3.44 l min(-1), an increase of 1.08 l min(-1). In contrast, for the cyclist to increase his mean speed from 40 km h(-1) to 45 km h(-1), he would require a greater increase in VO2max from 4.77 l min(-1) to 6.36 l min(-1), i.e. an increase of 1.59 l min(-1). The model is also able to accommodate other determinants of time-trial cycling, e.g. the benefit of cycling with a side wind (5% faster) compared with facing a predominately head/tail wind (P<0.05). Future research could explore whether the same scaling approach could be applied to, for example, alternative measures of recording power output to improve the prediction of time-trial cycling performance.
Type: Article
Language: en
Keywords: Power output
Allometric modelling
Cycling
Body mass
Wind resistance
Performance measurement
Sports Medicine
ISSN: 1439-6319
Appears in Collections: Sport, Exercise and Health Research Group
Sport Performance
Learning and Teaching in Sport, Exercise and Performance

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