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Associations Between Laboratory-Based Performance Indicators and On-Snow Competitive Success in Elite Cross-Country
Elias Bucher1,2, Jon P Wehrlin1, Severin Trösch3
1Section for Elite Sport, Swiss Federal Institute of Sport Magglingen, Magglingen, Switzerland.
Purpose:
This study examined the associations between laboratory-based performance indicators and competitive success in elite cross-country skiing, considering sex- and age-related differences over a 15-year period.
Methods:
A total of 106 Swiss National Team cross-country skiers (62 males and 44 females) underwent standardized physiological testing including 24-minute double-poling treadmill time-trial performance (24-minute DP), maximal oxygen uptake (V˙O2max), performance at the second lactate threshold, hemoglobin mass, 1-minute skating treadmill time-trial performance (Sprint1-min), squat jump peak power, and fat-free mass. Competitive performance was assessed using International Ski Federation (FIS) points in distance (FISDist) and sprint (FISSpr) events. Mixed-effects models analyzed the predictive strength of test variables, incorporating sex and age interactions.
Results:
Twenty-four-minute DP and relative V˙O2max explained 42% of the variance in FISDist, while Sprint1-min (66%), squat jump, and absolute V˙O2max (both 50%) were the strongest predictors of FISSpr. Improvements in 24-minute DP, second lactate threshold, and Sprint1-min had a greater impact on reducing FIS points in females, whereas relative and absolute V˙O2max, hemoglobin mass, squat jump, and fat-free mass showed similar predictive relationships across sexes. Age moderated these associations, with younger athletes experiencing greater reductions in FIS points per unit increase in test performance.
Conclusions:
This study highlights the importance of a comprehensive performance assessment in elite cross-country skiing that integrates ski-specific time trials, physiological capacity, strength, and body composition. The findings indicate that the relevance of laboratory-based performance indicators varies by sex and career stage, underscoring the need for longitudinal, age-aware interpretation when relating test outcomes to on-snow performance.
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Coefficient of Correlation
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...