INTRODUCTION: While aerobic capacity tends to decline after the age of 30-35 years of age, endurance performance ability can remain elevated well into an athlete's 40's for high-skill requiring sports such as cross-country skiing. The present study investigated the use of a regression modelling technique to describe the age-related declines in ski performance, as well as for adjusting cross-country ski race times for the overall age-related decline in race performance. METHOD: Publicly available race finish data (age, gender, finishing time and overall place) for the Boulder Mountain Tour (32 km; Sun Valley, ID, USA) were used for these analyses. Data from nine of the last 10 years (2000-2010) included 8,011 finishers of which 5065 were men and 2946 were women. Race times for each year were first separately screened for outliers (i.e., >2.5xSEE) after regressing on age for each gender. Once identified, outliers were removed from the data pool and all subsequent analyses. Standard step-forward multiple regression procedures (P-value to enter =0.05) were applied to the screened data from all nine races (n=5515; 18-83 years of age range). Potential predictor variables included gender (G) (0 = women, 1 = men), age (A) (linear model), age and age2 (quadratic model), a cluster of eight dummy-coded variables that identified the nine separate races (Race ID), as well as interactions amongst these variables. Overall model a-level was set at 0.01. RESULTS & DISCUSSION: The final equation included gender, the quadratic age model, and the cluster of Race ID variables. When solved for a single year's data, such as 2010, the final model was as follows: Race Time (mins) = 94.896-13.05xG+0.046xA+0.00723xA2 (R2=0.50). Thus, men tended to ski an average of 13 mins faster than women regardless of age while the age-related decline in performance accelerated after the age of 40 years (Figure 1A). Before adjusting for age, the actual first place men and women were 21-33 years of age. After the adjustment for age (Figure 1B) and then recalculating the finish places, the top age-adjusted men and women finishers were 39-65 years of age. CONCLUSION: Both age- and gender-related influences on performance can be modelled from mass start cross-country ski race data. Further, this modelling strategy may be used to adjust race finish times to identify the best skiers regardless of age.
© Copyright 2010 Book of Abstracts. 5th International Congress on Science and Skiing, Dec. 14 - 19, 2010, St. Christoph am Arlberg. Veröffentlicht von University of Salzburg, Interfakultärer Fachbereich Sport- und Bewegungswissenschaft/USI. Alle Rechte vorbehalten.