The aim of this study was 1) to validate the 0.5 body-mass exponent for maximal. oxygen uptake [Formula: see text] as the optimal predictor of performance in a 15 km classical-technique skiing competition among elite male cross-country skiers and 2) to evaluate the influence of distance covered on the body-mass exponent for [Formula: see text] among elite male skiers. Twenty-four elite male skiers (age: 21.4±3.3 years [mean ± standard deviation]) completed an incremental treadmill roller-skiing test to determine their [Formula: see text]. Performance data were collected from a 15 km classical-technique cross-country skiing competition performed on a 5 km course. Power-function modeling (ie, an allometric scaling approach) was used to establish the optimal body-mass exponent for [Formula: see text] to predict the skiing performance. The optimal power-function models were found to be [Formula: see text] and [Formula: see text], which explained 69% and 81% of the variance in skiing speed, respectively. All the variables contributed to the models. Based on the validation results, it may be recommended that [Formula: see text] divided by the square root of body mass (mL · min(-1) · kg(-0.5)) should be used when elite male skiers' performance capability in 15 km classical-technique races is evaluated. Moreover, the body-mass exponent for [Formula: see text] was demonstrated to be influenced by the distance covered, indicating that heavier skiers have a more pronounced positive pacing profile (ie, race speed gradually decreasing throughout the race) compared to that of lighter skiers.
Keywords: allometric scaling; cross-country skiing; maximal oxygen uptake; pacing.