Abstract
Background
Previous research in cross-country skiing (XCS), frequently emphasises the importance of maximal oxygen uptake (VO2Max) and individual studies have correlated XCS performance with VO2Max. However, meta-regression analyses with multiple studies have not previously been conducted.
Objective
The aim of this study was to conduct meta-analyses of VO2Max data, in relation to XCS performance using retrospective participant classification framework (PCF) scoring.
Methods
Electronic databases were searched, up to November 2024, using Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. Data were extracted from the included studies (n = 78), with participant groups separated by exercise mode and sex, and retrospectively scored using the PCF. Random effects meta-regressions with sub-grouping were conducted, to calculate pooled mean values by PCF tier, standard error, and 95% confidence intervals.
Results
Sufficient data were only present for inferential analysis of running based protocols. VO2Max values generally increased with PCF tier in males and females for both absolute (Male: R2 = 0.80; Female: R2 = 0.66) and relative to total body mass values (Male: R2 = 0.41; Female: R2 = 0.69).
Conclusion
Performance prediction is multifaceted, particularly within XCS where numerous physiological parameters are compounded by multiple skiing techniques. These findings emphasise the importance of VO2Max in XCS to develop performance across the participation spectrum. Even within ‘elite’ athletes, this remains true, possibly reflecting a lack of homogeneity of VO2Max values within this sub-population. The values presented within this study may represent useful benchmark values for talent identification and performance development purposes.
Previous research in cross-country skiing (XCS), frequently emphasises the importance of maximal oxygen uptake (VO2Max) and individual studies have correlated XCS performance with VO2Max. However, meta-regression analyses with multiple studies have not previously been conducted.
Objective
The aim of this study was to conduct meta-analyses of VO2Max data, in relation to XCS performance using retrospective participant classification framework (PCF) scoring.
Methods
Electronic databases were searched, up to November 2024, using Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. Data were extracted from the included studies (n = 78), with participant groups separated by exercise mode and sex, and retrospectively scored using the PCF. Random effects meta-regressions with sub-grouping were conducted, to calculate pooled mean values by PCF tier, standard error, and 95% confidence intervals.
Results
Sufficient data were only present for inferential analysis of running based protocols. VO2Max values generally increased with PCF tier in males and females for both absolute (Male: R2 = 0.80; Female: R2 = 0.66) and relative to total body mass values (Male: R2 = 0.41; Female: R2 = 0.69).
Conclusion
Performance prediction is multifaceted, particularly within XCS where numerous physiological parameters are compounded by multiple skiing techniques. These findings emphasise the importance of VO2Max in XCS to develop performance across the participation spectrum. Even within ‘elite’ athletes, this remains true, possibly reflecting a lack of homogeneity of VO2Max values within this sub-population. The values presented within this study may represent useful benchmark values for talent identification and performance development purposes.
| Original language | English |
|---|---|
| Article number | 66 |
| Number of pages | 41 |
| Journal | Sports Medicine - Open |
| Volume | 12 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 9 Jun 2026 |
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