Classification of Soccer and Basketball Players’ Jumping Performance Characteristics: A Logistic Regression Approach

Abstract

This study aimed to examine countermovement jump (CMJ) kinetic data using logistic regression, in order to distinguish sports-related mechanical profiles. Eighty-one professional basketball and soccer athletes participated, each performing three CMJs on a force platform. Inferential parametric and nonparametric statistics were performed to explore group differences. Binary logistic regression was used to model the response variable (soccer or not soccer). Statistical significance (p < 0.05) was reached for differences between groups in maximum braking rate of force development (RFDDmax, U79 = 1035), mean braking rate of force development (RFDDavg, U79 = 1038), propulsive impulse (IMPU, t79 = 2.375), minimum value of vertical displacement for center of mass (SBCMmin, t79 = 3.135), and time difference (% of impulse time; ΔΤ) between the peak value of maximum force value (FUmax) and SBCMmin (U79 = 1188). Logistic regression showed that RFDDavg, impulse during the downward phase (IMPD), IMPU, and ΔΤ were all significant predictors. The model showed that soccer group membership could be strongly related to IMPU, with the odds ratio being 6.48 times higher from the basketball group, whereas RFDDavg, IMPD, and ΔΤ were related to basketball group. The results imply that soccer players execute CMJ differently compared to basketball players, exhibiting increased countermovement depth and impulse generation during the propulsive phase.