A Multi-Block Multivariate Analysis to Explore the Influence of the Somatic Maturation in Youth Basketball

The aim of this study was to examine the influence of somatic maturation in anthropometric, physical, and game-related variables in youth basketball age groups under-13 (U-13) and under-15 (U-15). One-hundred and eighty-five basketball players performed anthropometrical and physical tests during a non-official youth basketball tournament. Predicted maturity offset (MO) and game-related variables were also analyzed. Cluster analysis was used to analyze the between-maturation status differences in all parameters in each age group. Also, regularized generalized canonical correlation analysis (RGCCA) was used to assess relative contributions of maturational, physical, and game-related variables within each age group. Based on MO, two different clusters were identified within each age category. Greater differences in MO were identified among U-13 clusters than among U-15 clusters. No significant differences were observed between clusters in terms of physical and game-related variables. High correlations between maturational, physical, and game-related variables (i.e., points scored, field goals attempted, and rebounds) were found for boys. In girls, different trends in terms of correlations were observed. The strongest association between blocks was observed between physical tests and game-related variables in all age categories, except for U-15 girls. Knowing and identifying performance profiles according to biological age is of upmost importance since it allows the coach to create challenging situations adjusted to the individual's needs.

Automated summary

This study aimed to examine the influence of somatic maturation on anthropometric, physical, and game-related variables in youth basketball players under-13 and under-15 age groups. Through cluster analysis, differences in maturation status within each age group were identified, with higher correlations between physical tests and game-related variables in all age categories except for U-15 girls. Understanding performance profiles based on biological age is crucial for coaches to provide tailored training for individual needs.