Personal best time and training volume, not anthropometry, is related to race performance in the ‘Swiss Bike Masters’ mountain bike ultramarathon

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Deutscher übersetzter Titel:Persönliche Bestzeit und Trainingsumfang, nicht die Anthropometrie, stehen in Bezug zur Rennleistung beim ‚Swiss Bike Masters’ Mountainbike-Ultramarathon
Autor:Knechtle, Beat; Knechtle, Patrizia; Rosemann, Thomas; Senn, Oliver
Erschienen in:Journal of strength and conditioning research
Veröffentlicht:25 (2011), 5, S. 1312-1317, Lit.
Format: Literatur (SPOLIT)
Publikationstyp: Zeitschriftenartikel
Medienart: Gedruckte Ressource
Sprache:Englisch
ISSN:1064-8011, 1533-4287
DOI:10.1519/JSC.0b013e3181d85ac4
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Erfassungsnummer:PU201106005428
Quelle:BISp

Abstract

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. Verf.-Referat