bigdatabadcalls

It is Opening Day for the St. Louis Cardinals and since KellyMitchell is headquartered in St. Louis, we thought we’d share this Big Data study that reveals why some umpires make bad calls. The study finds that umpires sometimes favor pitchers based on home field, All-Star status, race, and reputation. The better the pitcher, the more often their pitches are favored and pitchers labeled as wild are given less confidence. This subconscious benefit of the doubt is what leaves some batters, like Matt Holiday, shaking their heads.

“After analyzing more than 700,000 pitches thrown during the 2008 and 2009 seasons, we found that umpires frequently made errors behind the plate — about 14 percent of non-swinging pitches were called erroneously,” according to King and Kim.

The difference Big Data makes for this report is that it not only gives us the number of bad calls made, but tells us why they are more likely to occur.

“It’s that what you expect is what you see. We expect good All-star pitchers to throw more accurately.  We also expect that a pitcher who is way ahead in the count will throw a waste pitch and that on the 3-0, he’ll put it over the plate.  My guess is that umpires share these expectations. The difference is that the umps can turn their expectations into self-fulfilling prophecies,” says Livingston.

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