How Big Data Fails To Make Big Plays In Sports

Ever since Moneyball, the sports intelligentsia have rushed to find ways to implement Big Data to maximize the performance of their teams. From soccer to baseball, data is heralded as the key to winning games and, ultimately, trophies.

Except that it isn’t. Not completely, anyway. The more data we collect, the harder it is to filter signal from noise, according to renowned statistician Nate Silver. One sport where this truth recently became evident is cricket.

Cricket, unfamiliar to most Americans, is popular throughout the former British Empire. England recently suffered a humiliating defeat to Australia, losing 5-0. While The Daily Telegraph lists five reasons England lost, there really is only one reason: England cricket coach Andy Flowers relied too much on Big Data. After the release of Moneyball in 2011, Flowers turned slavishly to data to determine who to play and how to play.

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