FUNCTIONAL MOVEMENT SCREENING AND PERFORMANCE POTENTIAL IN TENNIS

Introduction. The objective of the study was to identify the relationship between Functional Movement Screening (FMS) scores and tennis-specific performance indicators, including dynamic balance, agility, and serve accuracy, among young competitive male tennis players. Materials and Methods. Thirty young competitive male tennis players (mean age 21.34 ± 2.11 years) from the Institute Gymkhana Tennis Club, Indian Institute of Technology Madras (IIT Madras), Chennai, India, participated in the study. Functional movement quality was assessed using the Functional Movement Screen (FMS), while dynamic balance, agility, and serve accuracy were evaluated using the Y-Balance Test, T-Test, and tennis serve accuracy test, respectively. Pearson’s product-moment correlation analysis was used to determine the associations between FMS scores and tennis-specific performance indicators, while multiple linear regression analysis was performed to examine the predictive contribution of FMS scores. Data were analysed using IBM SPSS Statistics Version 20, with statistical significance set at p ≤ 0.05. Results. The participants demonstrated a mean FMS score of 15.87 ± 2.26, Y-Balance composite score of 93.52 ± 4.67%, agility time of 9.71 ± 0.63 s, and serve accuracy of 76.43 ± 8.71%. FMS scores showed a significant positive correlation with dynamic balance (r = 0.612, p < 0.001) and serve accuracy (r = 0.487, p < 0.001), while a significant negative correlation was observed with agility time (r = −0.574, p < 0.001). The regression analysis demonstrated that FMS scores significantly predicted dynamic balance (β = 0.612, R² = 0.374, p < 0.001), accounting for 37.4% of the variance. FMS scores also significantly predicted agility performance (β = −0.574, R² = 0.329, p < 0.001), explaining 32.9% of the variance in agility time. Furthermore, FMS scores significantly predicted serve accuracy (β = 0.487, R² = 0.237, p < 0.001), accounting for 23.7% of its variance. The correlation effect sizes were large for the relationships between FMS and dynamic balance (r = 0.612) and FMS and agility (r = −0.574), while the association between FMS and serve accuracy was moderate (r = 0.487). Conclusions. Higher FMS scores were significantly associated with better dynamic balance, faster agility performance, and greater serve accuracy among young competitive tennis players. FMS scores demonstrated significant predictive relationships with all three performance indicators, with the strongest explanatory contribution observed for dynamic balance and agility. Functional movement assessment may therefore be useful as part of the regular physical evaluation and athlete development process in tennis. However, the cross-sectional design does not permit causal inference, and longitudinal studies are required to determine whether improvements in functional movement quality directly enhance tennis performance.