A Single Set of Biomechanical Variables Cannot Predict Jump Performance Across Various Jumping Tasks
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[1] Duke University
Duke University
Township of Durham, Estados Unidos
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- Localización: Journal of strength and conditioning research: the research journal of the NSCA, ISSN 1064-8011, Vol. 29, Nº. 2, 2015, págs. 396-407
- Idioma: inglés
- Texto completo no disponible (Saber más ...)
- Dialnet Métricas: 1 Cita
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Resumen
Vertical jump performance is related to high-level function in athletics. The purpose of this study was to determine whether a single set of biomechanical variables exist that can predict vertical jump height during multiple jumping strategies: single foot jump, drop jump, and countermovement jump. Three-dimensional mechanics were collected during the 3 different jumping tasks in 50 recreational male athletes. Three successful trials were analyzed for each jump type. Testing order was randomized to minimize fatigue effects, and the dominant limb was used for analysis. All discrete variables were correlated to jump height and the 10 variables that had the strongest correlation were inserted into a linear regression model to identify what variables predicted maximum jump height. No single set of variables that predicted jump height existed across all 3 jumping tasks. One foot jump height was predicted by peak knee power, peak hip extension moment, peak knee extension velocity, and the percentage of the trial when peak knee flexion velocity occurred (r2 = 0.58). Countermovement jump height was predicted by peak hip power, ankle range of motion, and knee range of motion (r2 = 0.65). Drop jump height was predicted by the peak vertical ground reaction force and the percentage of the trial when the peak hip velocity occurred (r2 = 0.37). A single set of variables was not identified that could predict jump performance across different types of jumping tasks; therefore, additional interventional investigations are needed to better understand how to alter and improve jump performance.
