De Larochelambert Quentin, Barlier Kilian, Hamri Imad, Difernand Audrey, Sedeaud Adrien, Toussaint Jean François, Antero Juliana, Louis Pierre-Yves, Coulmy Nicolas
Institut de Mathématiques de Bourgogne, UMR 5584 CNRS, Université Bourgogne Franche-Comté, Dijon, France.
Institut de Recherche bioMédicale et d'Epidémiologie du Sport, EA7329, INSEP, Université de Paris, Paris, France.
Front Physiol. 2023 Jan 5;13:1082072. doi: 10.3389/fphys.2022.1082072. eCollection 2022.
Estimating the potential of alpine skiers is an unresolved question, especially because of the complexity of sports performance. We developed a potential estimation model based solely on the evolution of performance as a function of age. A bayesian mixed model allowed to estimate the potential curve and the age at peak performance for the population (24.81 ± 0.2) and for each individual as the uncertainty around this curve. With Gaussian mixtures, we identified among all the estimates four types of curves, clustered according to the performance level and the progression per age. Relying on the uncertainty calculated on the progression curve the model created also allow to estimate a score and an uncertainty associated with each cluster for all individuals. The results allows to: i) describe and explain the relationship between age and performance in alpine skiing from a species point of view (at 0.87%) and ii) to provide to sport staffs the estimation of the potential of each individual and her/his typology of progression to better detect sports potential. The entire methodology is based on age and performance data, but the progression identified may depend on parameters specific to alpine skiing.
评估高山滑雪运动员的潜力是一个尚未解决的问题，尤其是由于运动表现的复杂性。我们开发了一个仅基于表现随年龄变化的潜在估计模型。贝叶斯混合模型能够估计总体（24.81±0.2）以及每个个体的潜在曲线和最佳表现年龄，同时考虑到围绕该曲线的不确定性。通过高斯混合模型，我们在所有估计值中识别出四种类型的曲线，这些曲线根据表现水平和年龄增长情况进行聚类。基于在进展曲线上计算出的不确定性，该模型还能为所有个体估计一个分数以及与每个聚类相关的不确定性。结果能够：i）从物种角度（准确率为0.87%）描述和解释高山滑雪中年龄与表现之间的关系；ii）为体育工作人员提供每个个体的潜力估计及其进步类型，以便更好地发现运动潜力。整个方法基于年龄和表现数据，但所确定的进步情况可能取决于高山滑雪特有的参数。
