On discretising continuous data for subgroup analysis in baseball pitching and alternative analytical methodologies

• Published in: Sports biomechanics pp. 1 - 12
• Main Authors: Giordano, Kevin A, Wasserberger, Kyle W
• Format: Journal Article
• Language: English
• Published: England 09.07.2024
• Subjects: t-test; Categorisation; regression; dichotomisation
• ISSN: 1476-3141; 1752-6116; 1752-6116
• DOI: 10.1080/14763141.2024.2377219

There is a plethora of research attempting to contrast high- and low-velocity pitchers to identify traits to target for increasing velocity. However, pitch velocity exists on a continuum. Therefore, our purpose is to display the analytical discrepancies between creating velocity subgroups and leaving velocity as a continuous variable by examining the influence of ball velocity on elbow valgus torque. Motion capture data for 1315 actively competing pitchers were retrospectively extracted from a private database. We compared three analytic methods: (1) linear regression of valgus torque on ball velocity, (2) t-test between low- and high-velocity groups formed by a median split, and (3) t-test between very low- and very high-velocity groups formed by upper and lower velocity quartiles. Linear regression indicates ball velocity influenced valgus torque (  < 0.001, R  = 0.280). Median splitting reduced the predictability of ball velocity on valgus torque (  < 0.001, R  = 0.180). Conversely, extreme group splitting artificially inflated the effect size (  < 0.001, R  = 0.347). We recommend sports biomechanics researchers not discretise a continuous variable to form subgroups for analysis because (1) it distorts the relationship between the variables of interest and (2) a regression equation can be used to estimate the dependent variable at any value of the independent variable, not just the group means.