Cluster-based identification of movement patterns in bilateral and unilateral drop jump tasks: insights into the performance-injury conflict.

Abstract

Stiff landing mechanics has been associated with increased anterior cruciate ligament (ACL) injury risk, yet it may optimise jump performance, creating a theoretical performance-injury conflict. This study examined movement patterns, their consistency, and performance during two-leg drop vertical jumps (DVJ) and single-leg drop vertical jumps (SDVJ). Forty-six healthy adults completed 3D motion analysis of DVJ from 30 cm and SDVJ from 15 cm, along with isokinetic knee torque testing. Ten ACL injury-related biomechanical variables were analysed using principal component analysis and hierarchical clustering. Clustering based on movement mechanics revealed three patterns: high-stiffness (shorter contact time, reduced joint flexion, greater joint moments and vertical GRF), medium-stiffness, and soft-stiffness (longer contact time, deeper flexion, lowest moments and GRF). Jump height did not differ between clusters, and 46% of participants changed pattern between tasks. Isokinetic knee extensor torque differed between the high- and soft-stiffness groups only in SDVJ, with greater values in the high-stiffness group. A separate performance-based classification (median split) revealed large differences in jump height-up to twofold-yet no difference in peak vertical GRF. These findings highlight the need for task-specific assessments that consider both discrete metrics and propulsive force production when identifying at-risk athletes while preserving performance potential.