SpringerBriefs in Applied Sciences and Technology: Identifying Potential Archers

Muazu Musa, Rabiu; Taha, Zahari; P.P.Abdul Majeed, Anwar; Abdullah, Mohamad Razali

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.​

Details

Published by: Springer

Publication Date: 2018-09-27

Format: Paperback

ISBN-13: 9789811325915

DOI: 10.1007/978-981-13-2592-2

Dimensions: 235cm x155cm

Pages: 45