Abstract
In sports such as soccer, which require sudden directional changes and single-leg stability, postural balance is a key determinant of performance. Insufficient knowledge regarding how balance levels influence directional changes and their potential relationship with injury risk remains a relevant practical problem in soccer. However, balance is often evaluated using single composite scores, while the relationships between directional postural deviations and central stability remain underexplored. Addressing this gap may improve the understanding of direction-specific balance demands in athletes. This study examined the associations between four-directional postural deviations and central stability obtained from a controlled dynamic single-leg postural stability test, and their relationships with lower extremity muscle strength and anthropometric characteristics. The applied methodology, incorporating anthropometric characteristics, was used to better approach this problem. A total of 95 male soccer players participated. Before interpretation, it is noted that lateral–medial and anterior–posterior deviation pairs are computed as proportional distributions by the device software; therefore, their strong inverse correlations (ρ = − 1.00) reflect mathematical dependency rather than biomechanical opposition. Significant correlations were observed between height and both body weight (ρ = 0.68) and lower extremity muscle strength (ρ = 0.51). Height was positively associated with lateral postural deviation (ρ = 0.30). Central stability was positively associated with height (ρ = 0.50) and demonstrated moderate directional relationships with lateral (ρ = 0.44) and medial deviation (ρ = − 0.44) (p < .01). In contrast, body weight and relative lower extremity strength showed weak or borderline associations with directional postural deviations. These findings suggest that postural control in soccer players exhibits directional organization influenced by anthropometric characteristics, indicating that individualized balance training approaches may be beneficial, particularly for optimizing direction-specific performance, while causal inferences cannot be made due to the cross-sectional design.