Sports analytics: How 'Moneyball' meets big data (gallery)

Sports analytics: How 'Moneyball' meets big data (gallery)

Summary: Bill James and Billy Beane have led the way for sports teams to make strategic decisions based on analyzing data rather than watching the actual games or players.

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  • WAR

    Billy Beane changed the face of baseball by using new statistics, such as on-base percentage and slugging average, as a better indication of a player's vaue than traditional baseball measurements — batting average, stolen bases, and RBI. An even newer analysis of a baseball player's value is called WAR (wins above replacement) which attempts to indicate how much a player contributes to his team. One major leaguer who stands out is Atlanta Braves outfielder Jason Heyward. His three-year WAR rating is the sixth highest for outfielders under 22 since 1961.

    For more read:  ESPN Stats and Info. There are a lot of interesting blogs on the site. The Atlanta Braves analysis is third on the list.

    Photo: Wikipedia

  • Injury list

    The English Rugby Union's frequent champion Leicester Tigers are using IBM's predictive analytics software to assess injury risks and then deliver training programs for players at risk. The Tigers are hoping analytics can keep players on the field longer.

    IBM has developed software which is designed to measure fatigue levels and game intensity. The Tigers will also crunch physical and biological data from its 45 players. In addition, the Tigers plan to use big data to measure psychological factors such as stress levels, social issues and environmental stress.

    IBM's software will also be used to gauge the performance for its under-19 academy feeder teams and choose players accordingly.

    Caption: Larry Dignan

    Photo: Wikipedia

  • Kevin Mongeon is the principal owner at The Sports Analytics Institute and shows how sports analytics can impact on winning and losing in his blog, "More Hockey Data"? Unlike baseball where specific actions show measureable results, hockey is played in a continous flow making the game more difficult to put into an analysis on paper.

    Mongeon says additional data is needed to discover a statistical path to a winning season. He needs statistical models that can examine a player's abilities even under different scenerios.

    Photo: Wikipedia

     

Topics: Big Data, Data Management

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