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A single set of biomechanical variables cannot predict jump performance across various jumping tasks.
J Strength Cond Res. 2015 Feb; 29(2):396-407.JS

Abstract

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 (r = 0.58). Countermovement jump height was predicted by peak hip power, ankle range of motion, and knee range of motion (r = 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 (r = 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.

Authors+Show Affiliations

1Michael W. Krzyzewski Human Performance Research Laboratory, Department of Orthopaedic Surgery; 2Division of Physical Therapy, Department of Community and Family Medicine, Orthopaedic Surgery; and 3Department of Orthopaedic Surgery, Duke University, Durham, North Carolina.No affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

25436626

Citation

Johnston, Lucas A., et al. "A Single Set of Biomechanical Variables Cannot Predict Jump Performance Across Various Jumping Tasks." Journal of Strength and Conditioning Research, vol. 29, no. 2, 2015, pp. 396-407.
Johnston LA, Butler RJ, Sparling TL, et al. A single set of biomechanical variables cannot predict jump performance across various jumping tasks. J Strength Cond Res. 2015;29(2):396-407.
Johnston, L. A., Butler, R. J., Sparling, T. L., & Queen, R. M. (2015). A single set of biomechanical variables cannot predict jump performance across various jumping tasks. Journal of Strength and Conditioning Research, 29(2), 396-407. https://doi.org/10.1519/JSC.0000000000000779
Johnston LA, et al. A Single Set of Biomechanical Variables Cannot Predict Jump Performance Across Various Jumping Tasks. J Strength Cond Res. 2015;29(2):396-407. PubMed PMID: 25436626.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - A single set of biomechanical variables cannot predict jump performance across various jumping tasks. AU - Johnston,Lucas A, AU - Butler,Robert J, AU - Sparling,Tawnee L, AU - Queen,Robin M, PY - 2014/12/2/entrez PY - 2014/12/2/pubmed PY - 2016/1/12/medline SP - 396 EP - 407 JF - Journal of strength and conditioning research JO - J Strength Cond Res VL - 29 IS - 2 N2 - 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 (r = 0.58). Countermovement jump height was predicted by peak hip power, ankle range of motion, and knee range of motion (r = 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 (r = 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. SN - 1533-4287 UR - https://www.unboundmedicine.com/medline/citation/25436626/A_single_set_of_biomechanical_variables_cannot_predict_jump_performance_across_various_jumping_tasks_ DB - PRIME DP - Unbound Medicine ER -