Using Multivariate Data Analysis to Project Performance in Biathletes and Cross-Country Skiers

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Thomas W. Jones Swedish Winter Sports Research Centre, Mid Sweden University, Östersund, Sweden

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Hampus P. Lindblom Swedish Winter Sports Research Centre, Mid Sweden University, Östersund, Sweden

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Marko S. Laaksonen Swedish Winter Sports Research Centre, Mid Sweden University, Östersund, Sweden

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Kerry McGawley Swedish Winter Sports Research Centre, Mid Sweden University, Östersund, Sweden

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Purpose: To determine whether competitive performance, as defined by International Biathlon Union (IBU) and International Ski Federation (FIS) points in biathlon and cross-country (XC) skiing, respectively, can be projected using a combination of anthropometric and physiological metrics. Shooting accuracy was also included in the biathlon models. Methods: Data were analyzed using multivariate methods from 45 (23 female and 22 male) biathletes and 202 (86 female and 116 male) XC skiers who were all members of senior national teams, national development teams, or ski-university or high school invite-only programs (age range: 16–36 y). Anthropometric and physiological characteristics were assessed via dual-energy X-ray absorptiometry and incremental roller-ski treadmill tests, respectively. Shooting accuracy was assessed via an outdoor standardized testing protocol. Results: Valid projective models were identified for female biathletes’ IBU points (R2 = .80/Q2 = .65) and female XC skiers’ FIS distance (R2 = .81/Q2 = .74) and sprint (R2 = .81/Q2 = .70) points. No valid models were identified for the men. The most important variables for the projection of IBU points were shooting accuracy, speeds at blood lactate concentrations of 4 and 2 mmol·L−1, peak aerobic power, and lean mass. The most important variables for the projection of FIS distance and sprint points were speeds at blood lactate concentrations of 4 and 2 mmol·L−1 and peak aerobic power. Conclusions: This study highlights the relative importance of specific anthropometric, physiological, and shooting-accuracy metrics in female biathletes and XC skiers. The data can help to identify the specific metrics that should be targeted when monitoring athletes’ progression and designing training plans.

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