School of Heath Sciences, Robert Gordon University, Aberdeen, UK.
Eur J Sport Sci. 2021 Aug;21(8):1101-1110. doi: 10.1080/17461391.2020.1808079. Epub 2020 Sep 4.
The purpose of this long-term retrospective analysis was to determine whether anthropometric and physical performance data could predict success in elite youth Scottish soccer players. Stature, body mass, sprint, jump and aerobic performance were collected from 512 players (U10 to U17) across a 10-year period. Players participated in an average of four profiling sessions (range: 1-14) and up to a maximum of three per year (August, December, and May) with standardisation applied to the surface, test order, time and protocols. One hundred players were awarded professional contracts. Associations between variables were quantified with mixed-effects linear models. Prediction was assessed with least absolute shrinkage and selection operator (LASSO) regression developed on a training set (2/3 data) and tested with proportion of error on a leave-out (1/3 data) test set. Confidence intervals were obtained through bootstrap LASSO samples. A strong relative age bias was identified with 50% of successful players born in the first quarter of the year. Successful players were on average taller and performed better in sprint and jump tests ( < 0.05). However, effects were small and even when variables were combined, proportion of errors identified were similar to random guessing (0.45[95%CI:0.41-0.49]). The results indicate that whilst successful players as youths demonstrate on average distinct anthropometric and physical profiles, these differences are unlikely to provide a reliable source to predict success within an already talented group. Practitioners should use data collected to guide exercise prescription but be aware of its substantive limitations in predicting success in isolation.
本长期回顾性分析的目的是确定人体测量学和身体表现数据是否可预测精英青年苏格兰足球运动员的成功。从 10 年间的 512 名(U10 至 U17 年龄组)球员中收集了身高、体重、冲刺、跳跃和有氧表现数据。球员平均参加了 4 次(范围为 1 至 14 次)个人资料分析,每年最多可达 3 次(8 月、12 月和 5 月),并对表面、测试顺序、时间和方案进行了标准化。有 100 名球员获得了职业合同。使用混合效应线性模型量化变量之间的关联。使用训练集(2/3 的数据)上开发的最小绝对收缩和选择运算符(LASSO)回归以及在保留(1/3 的数据)测试集上进行的误差比例测试来评估预测。置信区间通过引导 LASSO 样本获得。研究发现存在较强的相对年龄偏差,50%的成功球员出生在第一季度。成功的球员平均身高更高,在冲刺和跳跃测试中表现更好(<0.05)。但是,效果很小,即使将变量组合在一起,确定的错误比例也与随机猜测相似(0.45[95%CI:0.41-0.49])。结果表明,尽管年轻时期的成功球员平均表现出明显的人体测量和身体特征,但这些差异不太可能为预测已经有天赋的群体中的成功提供可靠的依据。从业者应使用收集的数据来指导运动处方,但要意识到其在单独预测成功方面存在实质性的局限性。