An Unhealthy Over-Analysis of the Unhealthy Over-Analysis of Baseball

There I was, minding my own business and doing my best to avoid my family, when what to my wandering eyes did appear but a Twitter timeline filled with reports of poorly-placed fear. I really should know better at this point, as there are some things you’re better off avoiding. I mean, why would you willingly volunteer to have your panties twisted into an uncomfortable knot? Just the same, I pressed forward into what I knew would most assuredly leave me with a significant literary wedgie.

And so, dander already up, I clicked the link and fell headlong into rabbit hole. When I emerged, I was what the soul-sucking millennial scourge might call mad online. The Unhealthy Over-Analysis of Major League Baseball, the title tsk-tsked with pearl-clutching self-righteousness. Already indignant over this indignation, I dove deeper and got dirtier.

The quasi-intellectual baseball mind in me was offended by the egregious misunderstanding of statistical application, while the pedantic jerk in me was tearing his hair out over the (lack of) editing. But I don’t want to make this about the All Out Sports Network site that hosted the article, nor do I want to go after author Len Nunes, whose only other piece for the outlet passively advocates for guys like Sammy Sosa and Mark McGwire to get more consideration for the Hall of Fame.

Actually, I really do want to go after the author for believing that we use BABIP in the same manner as batting average or for cautioning stat-heads against using a single metric to evaluate player performance. Just to be clear, batting average on balls in play is not a measure of a hitter’s actual performance, but of how lucky or unlucky he may be. BABIP and BA should be used together so as to understand whether the latter is being artificially suppressed or inflated by the former.

Nunes doesn’t seem to understand that though.

When it comes to regular batting average, the explanation of batting average is common sense. The formula is simply hits divided by the number of at-bats. If a batter is hitting .250, that translates to going 1 out of 4 at the plate during a “typical game”. According to, there were 116 qualified players that hit .250 and only 20 of those managed to maintain a .300 clip.

Your formula for BABIP is –> (Hits minus homers) divided by (at-bats minus strikeouts and home runs plus sacrifice flys). There is a 499-word explanation of how to correctly use BABIP on FanGraphs. A .300 BABIP is considered the league norm.

Why is this over-analysis? If your favorite player is hitting .300, you are happy. If your favorite player is DJ LeMahieu, you already know you are getting a boatload of singles (138) and not much power (5 HR). At the same time, if your favorite player is Cespedes, then you know you are getting a power-hitter (35 HR) and you are hoping that there are runners on base when he jacks one out of the ballpark.

In his bumbling attempt to chastise those who lean heavily on metrics, the author does shine a light on problems that exist when it comes to the evaluation of baseball. While it’s true that it is incredibly foolish to deny completely the human side of the game, turning a blind eye to advanced metrics is equally damning.

If you’ve ever been to the eye doctor, you’ve no doubt had to look through a phoropter, a device used to measure refractive error. The doctor turns dials and asks if your vision is clearer with number one or number two, with A or B. But you know what? Sometimes the answer is not one or the other. It’s no different with baseball.

There’s an even deeper issue here though, and that is the ignorance that leads the casting of stones or the drawing of lines in the sand and clay. My issue is not with someone’s preference for either the eye test (in terms of baseball again this time) or the soulless rows of esoteric numbers that populate the pages of sites like FanGraphs, but on the insistence that one must swear allegiance to one camp or the other. You can’t just say “fWAR!” or “F WAR!” It’s not that simple.

Where scouts were once the primary means through which organizations evaluated players, teams are now devoting hundreds of thousands of dollars to proprietary computer systems. That doesn’t mean, though, that the 20-80 scale is irrelevant in the face of millions of lines of code. Baseball was, is, and always will be a mental game, and that’s not something you can decipher with a spreadsheet. Baseball was, is, and always will be a numbers game, and that’s not something you can explain with adjectives.

Pitcher wins might not matter, but team wins do. As we learn more about how to better measure performance through statistical analysis, it’s necessary to filter that data through human eyes. Personality will always play a role in the percentages. To remain willfully ignorant of either side of the equation is an affront to the game and those who love it. When it comes to scouts and stats, it just seems that we’d all be a lot better off to shake hands than to shake our fists.

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