Abstract
Sport analytics allows sport teams and organizations to improve performance and associated business decisions. There is an increasing demand for sport analytics, in part connected to the emergence of Big Data, resulting in a new discipline in the sport industry. Business models related to sport analytics offer the opportunity to analyze the performance of athletes, teams, clubs, and sport organizations. The burgeoning yet competitive objectives based on sport analytics explain, to a degree, why it is rare to find algorithms, predictive models, and other statistical methods and analyses being carried out in the public domain. This chapter first outlines topical views of the developing field of sport analytics that suggest that its application is based on organizational self-interest, resulting in a degree of obfuscation that may limit the pursuit of knowledge. Countering these opinions, however, is evidence pointing to sport analytics becoming more mainstream and a domain of shared knowledge. The chapter provides a non-exhaustive literature review, including sections addressing statistical elements, performance optimization, theoretical frameworks, and the application of sport analytics, followed by some overall observations. Within that context, recent developments in the sport industry demonstrate that sport analytics is more than alchemy.
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