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Regression Models of Sprint, Vertical Jump, and Change of Direction Performance

Swinton, Paul A.1; Lloyd, Ray2; Keogh, Justin W.L.3,4; Agouris, Ioannis1; Stewart, Arthur D.5

Journal of Strength & Conditioning Research: July 2014 - Volume 28 - Issue 7 - p 1839–1848
doi: 10.1519/JSC.0000000000000348
Original Research

Abstract: Swinton, PA, Lloyd, R, Keogh, JWL, Agouris, I, and Stewart, AD. Regression models of sprint, vertical jump, and change of direction performance. J Strength Cond Res 28(7): 1839–1848, 2014—It was the aim of the present study to expand on previous correlation analyses that have attempted to identify factors that influence performance of jumping, sprinting, and changing direction. This was achieved by using a regression approach to obtain linear models that combined anthropometric, strength, and other biomechanical variables. Thirty rugby union players participated in the study (age: 24.2 ± 3.9 years; stature: 181.2 ± 6.6 cm; mass: 94.2 ± 11.1 kg). The athletes' ability to sprint, jump, and change direction was assessed using a 30-m sprint, vertical jump, and 505 agility test, respectively. Regression variables were collected during maximum strength tests (1 repetition maximum [1RM] deadlift and squat) and performance of fast velocity resistance exercises (deadlift and jump squat) using submaximum loads (10–70% 1RM). Force, velocity, power, and rate of force development (RFD) values were measured during fast velocity exercises with the greatest values produced across loads selected for further analysis. Anthropometric data, including lengths, widths, and girths were collected using a 3-dimensional body scanner. Potential regression variables were first identified using correlation analyses. Suitable variables were then regressed using a best subsets approach. Three factor models generally provided the most appropriate balance between explained variance and model complexity. Adjusted R2 values of 0.86, 0.82, and 0.67 were obtained for sprint, jump, and change of direction performance, respectively. Anthropometric measurements did not feature in any of the top models because of their strong association with body mass. For each performance measure, variance was best explained by relative maximum strength. Improvements in models were then obtained by including velocity and power values for jumping and sprinting performance, and by including RFD values for change of direction performance.

1School of Health Sciences, Robert Gordon University, Aberdeen, United Kingdom;

2School of Social and Health Sciences, University of Abertay, Dundee, United Kingdom;

3Sport Performance Research Institute New Zealand, School of Sport and Recreation, Auckland University of Technology, Auckland, New Zealand;

4Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Australia; and

5Centre for Obesity Research and Epidemiology, Robert Gordon University, Aberdeen, United Kingdom

Address correspondence to Dr. Paul A. Swinton,

Copyright © 2014 by the National Strength & Conditioning Association.