How baseball data can help teams build winners

Sports analytics are collections of relevant historical statistics that help players, coaches, and staff make decisions, both on and off the field. These lessons answer how baseball data can help teams build winners. They trace how data informs decisions about players and on-field strategy.

2 articles, 1 video, 1 book · about 31 min of reading and viewing

The reading path

1. Read
   sports analytics · Wikipedia · 20 min read

   In baseball analytics, batting average is one of the most commonly discussed statistics and is determined by dividing a player's hits by their at bats. The NHL kept statistics since its inception but adopted analytics-based decision making relatively recently. The Toronto Maple Leafs hired assistant general manager Kyle Dubas, who had a largely analytical background, in 2014.

2. Read
   Athlytics: Data Mining and Machine Learning for Sports Analytics · sites.pitt.edu · 3 min read

   Sports analytics gained traction as franchises adopted data mining and machine learning, partly because early investors enjoyed huge success and a competitive advantage. The Oakland Athletics' success with analytics was popularized by the best-seller "Moneyball."

3. Watch
   

   2.3.2 Sports Analytics - Video 1: The Story of Moneyball · YouTube · 8 min watch

   The video covers how sports analytics changed baseball, as part of MIT 15.071 The Analytics Edge, Spring 2017, taught by Dimitris Bertsimas.

4. Book
   

   Moneyball: The Art of Winning an Unfair Game · Bookshop.org

   Moneyball by Michael Lewis describes the Oakland Athletics' use of sabermetrics to assemble a competitive baseball team on a small budget, and statistical analysis indicating that on-base percentage and slugging percentage are better measures of batting.

Book links are Bookshop.org affiliate links. Curiate may earn a commission on purchases, at no extra cost to you — Bookshop.org also gives a share to independent bookshops.