Statistics in Sports is a growing field in Statistics, specially in North America, that provides specialized methodology for collecting and analyzing sports data in order to make decisions for successful planning and implementation of new strategies. Prior to the twenty-first century, decision making in sports was primarily based on the information acquired by observation. This has changed with technological advances, mainly related to data acquisition and the availability of personal computing.
The term “sports analytics” has been more popular than the term, “Statistics in sports”, perhaps due to the fact that the expertise is borrowed from different fields such as Statistics, Computer Science, Management, and the Health Sciences. Therefore, sports analytics is broadly described as the process of data management, predictive model implementation, and the use of information systems for decision making to gain a competitive advantage on the field of play (Alamar and Mehrotra 2011). There are many areas where sports analytics have been implemented. For example, sports teams use statistical analysis to evaluate players in order to determine the best game strategy. Sports associations develop rankings of players and teams, evaluate existing rules and study the feasibility of introducing new rules. Sports health professionals use statistical methods to understand players’ physical and mental conditions.
The discipline of Statistics has recognized that sport is rich in data, and that interesting statistical problems arise in sport. Two of the early sports papers in prominent Statistics journals that are familiar to us are by Elderton (1945) and Wood (1945). Both of these papers concern the distribution of running scoring in Test cricket. With the understanding of a need to foster the development of statistics and its applications in sports, the American Statistical Association (ASA) initiated a separate section for “Statistics in Sports”(SIS) in 1992. It promotes publications devoted to statistical theory and methodology and their application to statistics in sports. The SIS section also promotes meetings devoted to sports analytics, provides career guidance, data resources and online sports statistics forums.
(This post is written based on the Introduction of my PhD thesis,"Sports Analytics", which can be found online from Simon Fraser University (SFU) Library)
