Sports analytics

Sports analytics are collections of relevant historical statistics that can provide a competitive advantage to a team or individual by helping to inform players, coaches and other staff and help facilitate decision-making both during and prior to sporting events. The term "sports analytics" was popularized in mainstream sports culture following the release of the 2011 film Moneyball. In this film, Oakland Athletics general manager Billy Beane (played by Brad Pitt) relies heavily on the use of baseball analytics to build a competitive team on a minimal budget, building upon and extending the established practice of Sabermetrics.

There are two key aspects of sports analytics—on-field and off-field analytics. On-field analytics deals with improving the on-field performance of teams and players, including questions such as "which player on the Red Sox contributed most to the team's offense?" or "who is the best wing player in the NBA?", etc. Off-field analytics deals with the business side of sports. Off-field analytics focuses on helping a sport organization or body surface patterns and insights through data that would help increase ticket and merchandise sales, improve fan engagement, etc. Off-field analytics essentially uses data to help rights-holders make decisions that would lead to higher growth and increased profitability.[1]

As technology has advanced over the last number of years, data collection has become more in-depth and can be conducted with relative ease. Advancements in data collection have allowed for sports analytics to grow as well, leading to the development of advanced statistics and machine learning,[2] as well as sport specific technologies that allow for things like game simulations to be conducted by teams prior to play, improve fan acquisition and marketing strategies, and even understand the impact of sponsorship on each team as well as its fans.[3]

Another significant impact sports analytics has had on professional sports is in relation to sports betting. In-depth sports analytics has taken sports gambling to new levels; whether it be fantasy sports leagues or nightly wagers, bettors now have more information at their disposal to help aid decision making than ever before. A number of companies and webpages have been developed to help provide fans with up-to-date information for their betting needs.[3]

  1. ^ Ray, Sugato (June 22, 2017). "The Evolution and Future of Analytics in Sport". Proem Sports | Sports Analytics | Singapore & India. Retrieved August 5, 2018.
  2. ^ Soto Valero, C. (1 December 2016). "Predicting Win–loss outcomes in MLB regular season games – A comparative study using data mining methods". International Journal of Computer Science in Sport. 15 (2): 91–112. doi:10.1515/ijcss-2016-0007.
  3. ^ a b "How Data Analytics Helps Coaches in Planning". WorkInSports. August 21, 2017. Retrieved August 5, 2018.

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