Arede Jorge, Oliveira Irene, Ángel Gomez Miguel-Angel, Leite Nuno
Research Centre in Sports Sciences, Health Sciences and Human Development, Vila Real, Portugal.
Department of Mathematics, University of Trás-os-Montes and Alto Douro, Vila Real, Portugal.
Front Psychol. 2021 Feb 1;12:602576. doi: 10.3389/fpsyg.2021.602576. eCollection 2021.
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.
本研究旨在探讨身体成熟度对13岁以下（U-13）和15岁以下（U-15）青少年篮球年龄组人体测量学、身体和比赛相关变量的影响。185名篮球运动员在一场非官方青少年篮球锦标赛期间进行了人体测量和体能测试。还分析了预测成熟偏移（MO）和比赛相关变量。聚类分析用于分析每个年龄组所有参数在成熟状态之间的差异。此外，正则化广义典型相关分析（RGCCA）用于评估每个年龄组内成熟、身体和比赛相关变量的相对贡献。基于MO，在每个年龄类别中识别出两个不同的聚类。U-13聚类之间的MO差异比U-15聚类之间的差异更大。在身体和比赛相关变量方面，聚类之间未观察到显著差异。在男孩中，成熟、身体和比赛相关变量（即得分、投篮次数和篮板）之间存在高度相关性。在女孩中，观察到了不同的相关趋势。除U-15女孩外，在所有年龄组中，封盖在体能测试和比赛相关变量之间的关联最为强烈。根据生物年龄了解和识别表现特征至关重要，因为这使教练能够创造符合个人需求的具有挑战性的情境。
