Petti: How MLB teams can get the most out of analytics

From SABR member Bill Petti at The Hardball Times on January 27, 2015:

Statistics and numbers have always permeated baseball. From its earliest days, observers of the sport have attempted to catalog the performance of the game in various ways using numbers. Those efforts have evolved from merely trying to describe or recreate the game numerically to understanding, explaining and predicting performance on the field. We can safely say that the transition to an era where virtually every front office looks to data and advanced analytical methods for some kind of advantage (or, at the very least, to keep up with the competition) is complete. Whether it is a department of one or an army of analysts, every major league team has individuals focused on collecting and statistically analyzing data about player performance.

A decade ago, when only a handful of teams were serious about gaining an advantage through thoughtful analysis data, it was easy to see how the few could identify and exploit market inefficiencies. But in a world where everyone is on the prowl for these inefficiencies—small and large market teams, alike, leveraging largely the same data sources—is there really any advantage left for teams to gain from data? Or has it become mere tables stakes; there may not be marginal gains from the practice, but opting out means putting your team at a structural disadvantage?

I would argue that there are still marginal gains to be made, and there are data that suggest the same. Ben Baumer and Andrew Zimbalist looked at whether the competitive balance across major league baseball had improved since the growth and spread of analytics. Interestingly, they found that whatever tightening of competitiveness had been achieved was likely more a function of changes to revenue sharing. So even if all teams are leveraging data today, they aren’t all getting the same return from it.

Data can be powerful, but it would be a mistake to assume that simply having data will bring about an advantage, or even the same advantage. Data alone can’t improve performance. Moving from data to insight to change is no easy task, and teams have to overcome plenty of barriers along the way.

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Originally published: January 27, 2015. Last Updated: January 27, 2015.