ArticleEuropean journal of applied physiology2006
Optimal power-to-mass ratios when predicting flat and hill-climbing time-trial cycling.
Article in European journal of applied physiology, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Exercise and Fat: A Primer.Sports medicine - open · 2026Review
- Optimal body mass normalization of power output for accurate prediction of estimated cycling performance over complex time-trial courses.Frontiers in sports and active living · 2025Article
- Optimal [Formula: see text] ratio for predicting 15 km performance among elite male cross-country skiers.Open access journal of sports medicine · 2015Article
- Oxygen uptake at different intensities and sub-techniques predicts sprint performance in elite male cross-country skiers.European journal of applied physiology · 2014Article
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Authors and funding
4 authors.
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Abstract
The purpose of this article was to establish whether previously reported oxygen-to-mass ratios, used to predict flat and hill-climbing cycling performance, extend to similar power-to-mass ratios incorporating other, often quick and convenient measures of power output recorded in the laboratory [maximum aerobic power (W(MAP)), power output at ventilatory threshold (W(VT)) and average power output (W(AVG)) maintained during a 1 h performance test]. A proportional allometric model was used to predict the optimal power-to-mass ratios associated with cycling speeds during flat and hill-climbing cycling. The optimal models predicting flat time-trial cycling speeds were found to be (W(MAP)m(-0.48))(0.54), (W(VT)m(-0.48))(0.46) and (W(AVG)m(-0.34))(0.58) that explained 69.3, 59.1 and 96.3% of the variance in cycling speeds, respectively. Cross-validation results suggest that, in conjunction with body mass, W(MAP) can provide an accurate and independent prediction of time-trial cycling, explaining 94.6% of the variance in cycling speeds with the standard deviation about the regression line, s=0.686 km h(-1). Based on these models, there is evidence to support that previously reported VO2-to-mass ratios associated with flat cycling speed extend to other laboratory-recorded measures of power output (i.e. Wm(-0.32)). However, the power-function exponents (0.54, 0.46 and 0.58) would appear to conflict with the assumption that the cyclists' speeds should be proportional to the cube root (0.33) of power demand/expended, a finding that could be explained by other confounding variables such as bicycle geometry, tractional resistance and/or the presence of a tailwind. The models predicting 6 and 12% hill-climbing cycling speeds were found to be proportional to (W(MAP)m(-0.91))(0.66), revealing a mass exponent, 0.91, that also supports previous research.
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