Feb. 21, 2024, 5:42 a.m. | Shinpei Nakamura-Sakai, Laura Forastiere, Brian Macdonald

cs.LG updates on arXiv.org arxiv.org

arXiv:2402.12400v1 Announce Type: cross
Abstract: In the realm of competitive sports, understanding the performance dynamics of athletes, represented by the age curve (showing progression, peak, and decline), is vital. Our research introduces a novel framework for quantifying age-specific treatment effects, enhancing the granularity of performance trajectory analysis. Firstly, we propose a methodology for estimating the age curve using game-level data, diverging from traditional season-level data approaches, and tackling its inherent complexities with a meta-learner framework that leverages advanced machine learning …

abstract age application arxiv athletes cs.lg dynamics effects framework management nba novel peak performance research sports stat.ap strategies treatment type understanding vital

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