Skip Navigation LinksHome > May 2011 - Volume 25 - Issue 5 > Personal Best Time and Training Volume, Not Anthropometry, i...
Journal of Strength & Conditioning Research:
doi: 10.1519/JSC.0b013e3181d85ac4
Original Research

Personal Best Time and Training Volume, Not Anthropometry, is Related to Race Performance in the ‘Swiss Bike Masters’ Mountain Bike Ultramarathon

Knechtle, Beat1,2; Knechtle, Patrizia1; Rosemann, Thomas2; Senn, Oliver2

Collapse Box


Knechtle, B, Knechtle, P, Rosemann, T, and Senn, O. Personal best time and training volume, not anthropometry, is related to race performance in the ‘Swiss Bike Masters’ mountain bike ultramarathon. J Strength Cond Res 25(5): 1312-1317, 2011-We investigated in 73 male ultraendurance mountain bikers, with (mean and SD) age 39.1 (8.6) years, weight 74.4 (8.3) kg, height 1.78 (0.07) m, and a body mass index of 23.3 (1.9) kg·m−2, whether variables of anthropometry, training, or prerace experience were associated with race time using bi and multivariate analysis. Our investigation was conducted at the “Swiss Bike Masters,” which covers a distance of 120 km and an altitude of 5,000 m. In the bivariate analysis, body mass index (r = 0.29), circumference of upper arm (r = 0.28), sum of upper body skinfolds (r = 0.38), sum of lower body skinfolds (r = 0.25), sum of 8 skinfolds (r = 0.36), percent body fat (r = 0.41), total cycling kilometers per year (r = −0.47), yearly volume in both mountain bike (r = −0.33) and road cycling (r = −0.52), number of training units per week (r = −0.48), distance per unit in road cycling (r = −0.33), average speed during training in road cycling (r = −0.33), and personal best time in the “Swiss Bike Masters”(r = 0.67) were related to race time. In the multiple linear regression analysis, personal best time in the “Swiss Bike Masters” (p = 0.000), total yearly cycling kilometers (p = 0.004), and yearly training kilometers in road cycling (p = 0.017) were related to race time. When the personal best time was the dependent variable in a separate regression model, total yearly cycling kilometers (p = 0.002) remained the single predictor variable. We concluded that finishing a particular mountain bike ultramarathon does not seem to require a special anthropometry but rather a specific skill and experience for this selective kind of race coupled with a high training volume. For practical use, we concluded that successful athletes in a mountain bike ultramarathon, in a special environment and using sophisticated equipment, need prerace experience coupled with high training volume, rather than any special anthropometry.

© 2011 National Strength and Conditioning Association



Article Tools


Article Level Metrics

Search for Similar Articles
You may search for similar articles that contain these same keywords or you may modify the keyword list to augment your search.