Integrating trunk endurance, dynamic stability, and in-game performance analysis in youth elite basketball players.

Abstract

Background: Physical preparation in basketball is essential but often limited by training time and prior focus on tactical and technical skills. While postural stability is known to assist injury prevention and performance, its specific impact on game-related performance remains unclear. With the development of motion analysis systems, the numerical values of external and internal loads measured during matches have become measurable. This study aimed to examine the relationship between postural stability and game-related performance and introduce a method for visualizing key competencies.

Method: Twenty-three U16 female basketball players (age = 15.22 ± 0.82 years, mass = 66.3 ± 8.85 kg, high = 174.0 ± 8.2 cm) participated from the Hungarian first league. Postural stability was assessed via plank test and one minute dynamic standing balance tests, while game-related performance was monitored through match-derived internal and external load values measured by WIMU PRO™ System, alongside statistical data derived from the official box scores. After the postural stability measurements, we monitored an official basketball match, which was conducted according to official International Basketball Association (FIBA) rules. For clear and comprehensive presentation, we combined the game-related performance indicators using Principal Component Analysis (PCA).

Results: A moderate correlation (0.5 < r < 0.8, p < 0.05) was found between the game-related performance and postural stability variables. However, plank test indicators showed no significant correlations with game-related performance variables, except for bad throws (r = 0.56, p = 0.037), the postural error (PE), a variable reflecting compensatory movement during fatigue in the plank test, correlated with balance indicators (r = 0.63, p = 0.014). Mediolateral balance control correlated with explosive game-related performace metrics, including maximum acceleration (r = -0.65, p = 0.01), deceleration (r = 0.56, p = 0.035), and steals (r = -0.52, p = 0.05). PCA proved effective in creating game competency scores, enabling a graphical representation of game-related performance.

Conclusion: Findings suggest that trunk endurance alone was not directly related to game-related performance, while dynamic balance metrics showed moderate correlations. The PE values provide deeper insights into the balance-trunk stability relation. The dynamic balance test could support player monitoring, and the PCA based method facilitates player profiling.