Hierarchical Movement-Pattern Deficits During Drop Jump Predict Injury Risk in Football Players: A LESS-Based Prospective Cohort Study

Purpose: To determine whether specific movement-pattern deficits and their hierarchical interaction during drop jump (DJ) tasks can predict injury occurrence in football players using a LESS-based observational screening approach. Methods: Seventy-two male football players (age: 21.4 ± 3.2 years; height: 178.2 ± 6.4 cm; body mass: 73.5 ± 7.1 kg) completed a standardised DJ assessment during the pre-season period. Movement quality was evaluated using a modified Landing Error Scoring System (LESS)-based observational protocol including six biomechanical domains related to lower-limb and trunk control. The occurrence of non-contact lower-limb injuries resulting in time loss was prospectively monitored throughout the competitive season. Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were performed to identify independent predictors of injury and evaluate model discrimination. Additionally, a Classification and Regression Tree (CART) model was implemented to identify hierarchical movement-based injury-risk profiles. Results: Eighteen players (25%) sustained at least one time-loss injury during the observation period. Injured players demonstrated significantly higher composite movement-error scores compared with non-injured players (6.1 ± 1.8 vs. 4.3 ± 1.5; p = 0.01). Dynamic knee valgus (OR = 2.84; 95% CI: 1.32–6.12; p = 0.008) and trunk control deficits (OR = 2.17; 95% CI: 1.08–4.36; p = 0.030) emerged as independent predictors of injury risk. The logistic regression model demonstrated acceptable discriminative capacity (AUC = 0.74; sensitivity = 0.72; specificity = 0.67). CART analysis identified three hierarchical movement-risk profiles: low risk (predicted probability < 0.15), moderate risk (0.15–0.40), and high risk (>0.40). Players exhibiting combined dynamic knee valgus and trunk control deficits demonstrated the highest injury probability. Conclusions: The present findings support the use of movement-pattern profiling during DJ tasks as a practical and clinically interpretable strategy for injury-risk stratification in football players. Rather than relying exclusively on composite movement-error scores, the interaction between dynamic knee valgus and trunk control deficits appears to represent a distinct neuromuscular risk phenotype associated with elevated injury probability. Integrating observational movement screening with hierarchical risk modelling may contribute to the development of more individualised injury-prevention strategies in football.