Machine Learning in Sports Identifying Potential Archers - Muazu Musa, Rabiu; Taha, Zahari; P.P.Abdul Majeed, Anwar; Abdullah, Mohamad Razali; SpringerLink (Online service) (Singapore : Springer Nature Singapore : Imprint: Springer, 2019)
This brief highlights the association of different performance variables that influences archery performance and the employment of different machine learning algorithms in the identification of potential archers. The sport of archery is often associated with a myriad of performance indicators namely bio-physiological, psychological, anthropometric as well as physical fitness. Traditionally, the determination of potential archers is carried out by means of conventional statistical techniques. Nonetheless, such methods often fall short in associating non-linear relationships between the variables. This book explores the notion of machine learning that is capable of mitigating the aforesaid issue. This book is valuable for coaches and managers in identifying potential archers during talent identification programs.
Introduction -- Bio-physiological indicators in evaluating archery performance -- Psychological variables in ascertaining potential archers -- Anthropometry correlation to archery performance -- Physical fitness parameters in the identification of high potential archers -- Concluding remarks.
Keywords: Computational intelligence; Sports sciences; Computer simulation; Sports -- Psychological aspects; Biomedical engineering; Social sciences -- Data processing; Computational Intelligence; Sport Science; Computer Modelling; Sport Psychology; Biomedical Engineering and Bioengineering; Computer Application in Social and Behavioral Sciences