Gäbler, M, Prieske, O, Elferink-Gemser, MT, Hortobágyi, T, Warnke, T, and Granacher, U. Measures of physical fitness improve prediction of kayak and canoe sprint performance in young kayakers and canoeists. J Strength Cond Res 37(6): 1264-1270, 2023-Markers of talent selection and predictors of performance in canoe and kayak sprint are not yet well defined. We aimed to determine the combination of variables (i.e., demographic, anthropometric, and physical fitness) that most accurately predicts sprint performance (i.e., 500- and 2000-m race time) in semielite, young kayakers and canoeists ( n = 39, age 13 year, 10F). The level of significance was set at p < 0.05. Linear regression analyses identified boat type (i.e., kayak or canoe), skeletal muscle mass, and average power during a 2-minute bench pull test, normalized to body mass, as predictors of 2000-m race time (R 22000 m = 0.69, Akaike information criterion [AIC] = 425) and together with vertical jump height, as predictors of 500-m race time (R 2500 m = 0.87, AIC = 255). This was an improvement over models containing solely demographic variables (R 2500 m = 0.66, AIC = 293; R 22000 m = 0.44, AIC = 446) and over models containing demographic and anthropometric variables (R 2500m = 0.79, AIC = 277; R 22000 m = 0.56, AIC = 437). Race time showed the strongest semipartial correlations with the 2-minute bench pull test (0.7 ≤ r ≤ 0.9). Adding physical fitness data (i.e., 2-minute bench pull test) to demographic and anthropometric data improves the prediction accuracy of race times in young kayak and canoe athletes. The characteristics of physical fitness tests should resemble as much as possible the biomechanical (e.g., prime movers) and metabolic (e.g., duration) demands of the sport.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1519/JSC.0000000000004055 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!