Examining isokinetic knee peak torque and time to peak torque as predictors of vertical jump height in division I men’s basketball players

C Caroline Westwood A Arakua Welbeck C Carolyn Killelea P Peter Howard M Mallory Faherty D Daniel Le (Department of Proteomic and Genomic Technologies, Genentech) R Ryan Zerega C Charles R. Reiter T Timothy C. Sell

Abstract

The vertical jump (VJ) is one of the most important movements for basketball athletes and therefore determining modifiable predictors of the VJ would aid substantially in crafting more effective training regimens. The purpose of this study was to determine if isokinetic quadriceps strength and torque predict VJ height and which characteristics and testing speed is the strongest predictor of VJ height. Fifteen subjects (age: 18.5 ± 1.0 years, height: 195.9 ± 6.9 cm, weight: 96.2 ± 13.7 kg) from a single Division I men’s basketball team were recruited for this study. All participants performed a standing vertical jump with arm-swing to assess their maximum VJ height. Participants also completed an isokinetic knee extension strength protocol that included testing at multiple speeds. Pearson and Spearman tests found no significant correlation between jump height and peak torque at any of the speeds. Regression analysis showed a statistically significant relationship between time to peak torque at 300°/s and VJ height (R2 =  0.23, p =  0.04). These findings suggest that in a population of elite basketball players, the knee’s ability to rapidly generate torque likely plays a greater role in VJ performance than its ability to generate high magnitude of torque. This presents a potential benefit of explosive training regimens such as plyometrics for maximization of jump performance.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 20, Issue 4
Published April 01, 2025
Pages e0303701
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (9)

C

Caroline Westwood

A

Arakua Welbeck

C

Carolyn Killelea

P

Peter Howard

M

Mallory Faherty

D

Daniel Le

Department of Proteomic and Genomic Technologies, Genentech

R

Ryan Zerega

C

Charles R. Reiter

T

Timothy C. Sell