ArticleOpen access journal of sports medicine2015
Optimal [Formula: see text] ratio for predicting 15 km performance among elite male cross-country skiers.
Article in Open access journal of sports medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Running Assessed Maximal Oxygen Uptake Increases with Participant Classification Framework Tier in Overall Cross-Country Skiing Performance: A Systematic Review with Meta-regressions.Sports medicine - open · 2026Pooled it
- Micro-pacing and performance determinants in skiathlon: linking speed profiles, sub-technique selection, and cycle characteristics.BMC sports science, medicine & rehabilitation · 2026Article
- Pacing and predictors of performance during cross-country skiing races: A systematic review.Journal of sport and health science · 2018Article
- The influence of sex, age, and race experience on pacing profiles during the 90 km Vasaloppet ski race.Open access journal of sports medicine · 2016Article
- Aerobic power and lean mass are indicators of competitive sprint performance among elite female cross-country skiers.Open access journal of sports medicine · 2016Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
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