Machine Learning in Sports Identifying Potential Archers /

• Κύριοι συγγραφείς: Muazu Musa, Rabiu (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Taha, Zahari (http://id.loc.gov/vocabulary/relators/aut), P.P.Abdul Majeed, Anwar (http://id.loc.gov/vocabulary/relators/aut), Abdullah, Mohamad Razali (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: SpringerBriefs in Applied Sciences and Technology,
• Θέματα: Computational intelligence.; Sports.; Computer simulation.; Sports-Psychological aspects.; Biomedical engineering.; Application software.; Computational Intelligence.; Sport.; Simulation and Modeling.; Sport Psychology.; Biomedical Engineering and Bioengineering.; Computer Appl. in Social and Behavioral Sciences.
• Φυσική περιγραφή: XII, 45 p. 11 illus. in color. online resource.
• ISBN: 9789811325922
• ISSN: 2191-530X
• DOI: 10.1007/978-981-13-2592-2

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.