Scorecasting: Freakanomics for the sports world

A movement has been growing in the sports world in the last few decades: the use of lots of data in order to make decisions. Some of this data goes against “conventional wisdom” such as ideas of whether players can be “clutch” (some good stuff on which NBA players you would want to take the final shot with the game on the line) and what should actually be valued in free agents (MLB’s shift toward statistics like on-base percentage over home runs and RBIs).

A new book, Scorecasting, tackles a number of sports issue from a quantitative perspective. Read an interview (including a few examples from the book) with one of the authors here.

It will be interesting to see just how mainstream these sorts of ideas become. Does the average sports fan, or even the average sports broadcaster, want to rely on these kinds of data as opposed to their intuition or their feeling? Numbers may provide a better explanation – but numbers have all sorts of perceptions tied to them including the idea that people are just twisting the data to fit their explanation and that numbers about sports are developed by geeks who can’t play sports (or something along these lines).

I, for one, would like to have more quantitative data available to me when watching sports. Information like the batting average of a batter for particular parts of the plate (usually split into nine segments) or on a particular count would be useful. The data might seem overwhelming but ultimately, I think it helps people see the patterns underlying their favorite sport. For example, a home run hit on an 0-2 count in the 9th inning to win the game is impressive in its own right. But to know how rarely home runs are hit on the 0-2, even more so for some batters, adds to the feat.

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