Scaling maximal oxygen uptake to predict cycling time-trial performance in the field: a non-linear approach.

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.