Prediction of cross-country ski season performance based on a linear regression model of laboratory roller ski capacity and VO2max test - Naef, N.; Steiner, T.; Müller, B.; Wehrlin, J. P. (14th annual Congress of the European College of Sport Science, Oslo/Norway, June 24-27, 2009, Book of Abstracts, 2009)
Cross-country (XC) ski-specific testing is used to support elite athletes regarding their training control as well as to predict performance of competitive ski season (Alsobrook & Heil, 2009, Staib et al., 2000). The purpose of this study was to investigate the relationship between the results of two different laboratory preseason roller ski tests and the XC ski performance of the following season as well as its predictability with a linear regression model. Methods: In October 2008, 14 male XC skiers of the Swiss National U20 (n=5), U23 (n=2) and Elite (n=7) Distance Ski Team completed two laboratory roller ski tests on a large motor-driven treadmill. Athletes performed a maximal diagonal stride test to measure VO2max. 24 hours later they carried out a maximal double poling capacity test with self selected speed during three stages of eight minutes (5 min at 3° inclination and 3 min at 5° inclination) to establish maximal possible distance. XC ski season performance was ranked by the 4th XC ski distance International Ski Federation (FIS) points list 2008/2009. Spearmen correlation analyses and multiple linear regression models were applied. Results: Athletes achieved a mean total distance of 5299.3 ± 460.5m, a VO2max of 77.4 ± 4.6 ml/min/kg and mean FIS Points of 59.7 ± 44.1 (range = 1.2 - 130.5). There was a negative correlation between distance and FIS points as well as VO2max and FIS points (r = - 0.832; p < 0.001 and r = - 0.510; p = 0.062, respectively). Age was significantly correlated to FIS points (r2 = - 0.638; p = 0.014). The best linear regression model to predict FIS points was: FIS points = - 0.069 * distance [m] - 2.897 * VO2max [ml/min/kg] + 650.95 with a mean residual of 15.6 ± 9.2 points. Correlation between XC ski performance and the linear regression model was significantly (r2 = 0.790, p < 0.001). Discussion and Conclusion These findings suggest that distance achieved during the capacity test and VO2max are important determinants of the following XC ski season performance. Our linear regression model based on a ski-specific laboratory test is highly correlated with seasonal performance (FIS). We suggest that this model is a useful tool to predict XC ski performance of the following winter season, in spite of the long time frame and possible confounding factors (health problems, ski preparation, race tactic, etc).