INTRODUCTION: Body composition is critical in athletic performance, influencing metrics such as jump height and force production. Variations in body composition, such as increased lean tissue mass and reduced fat mass, have been identified as strong predictors of superior jump performance due to their positive effects on power-to-weight ratios and reduced injury risk (MacDonald et al., 2013). Lean mass is strongly correlated with improved jump performance, as greater lean mass enhances muscle cross-sectional area and, consequently, the force and power generated during physical activities like countermovement jumps (CMJ) (Stephenson et al., 2015). Low body fat percentages are generally associated with higher agility, power, and vertical jump height, making them desirable characteristics in volleyball athletes. (Acar & Eler, 2019). PURPOSE: This study sought to evaluate correlations between body composition variables and jump performance in NCAA Division I volleyball players. Specifically, we examined lean mass, fat mass, bone mineral density (BMD), and lower limb asymmetries. METHODS: Forty-one female volleyball players (age: 20.1 ± 1.6 years, weight: 70.9 ± 9.8 kg, height: 175.3 ± 8.3 cm) underwent body composition assessment using DXA to measure lean mass, fat mass, and BMD. Jump performance metrics were evaluated using the DARI® Motion Analysis System, including vertical jump peak power, rate of force development (RFD), and unilateral jump performance. Pearson`s correlation coefficients were used to analyze the relationships, with significance set at p < 0.05. RESULTS: Lean mass showed a strong positive correlation with vertical jump peak power and rate of force development (RFD) (r = 0.72 ± 0.08, p < 0.001), while bone mineral density (BMD) demonstrated a moderate positive correlation with RFD (r = 0.47 ± 0.12, p = 0.002). Fat mass was negatively correlated with vertical jump height and peak power (r = -0.33 ± 0.09, p = 0.017). Furthermore, asymmetries in lean mass and BMD between legs reduced unilateral performance efficiency by 10-15% on average (p < 0.05). CONCLUSION: Lean mass was the strongest predictor of jump performance, emphasizing the importance of resistance training to enhance lower-body muscle development. Fat mass negatively impacted performance, underscoring the need to manage non-functional weight. Although BMD plays a moderate role, it supports better force generation. Correcting leg asymmetries could further improve unilateral jump efficiency. These findings highlight the value of tailored training programs focusing on body composition to optimize performance.
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