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

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 (RFD_Dmax, U₇₉ = 1035), mean braking rate of force development (RFD_Davg, U₇₉ = 1038), propulsive impulse (IMP_U, t₇₉ = 2.375), minimum value of vertical displacement for center of mass (S_BCMmin, t₇₉ = 3.135), and time difference (% of impulse time; Δ_Τ) between the peak value of maximum force value (F_Umax) and S_BCMmin (U₇₉ = 1188). Logistic regression showed that RFD_Davg, impulse during the downward phase (IMP_D), IMP_U, and Δ_Τ were all significant predictors. The model showed that soccer group membership could be strongly related to IMP_U, with the odds ratio being 6.48 times higher from the basketball group, whereas RFD_Davg, IMP_D, and Δ_Τ 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.