Competing religions of baseball

There are two seemingly unrelated stories that I’d like to take a moment to compare in order to make a point.

In the world of economics, public policy, and how not to format a spreadsheet, word has come out that a seminal paper arguing that high debt-to-GDP rates are bad for economic growth was based on bad data after the two professors who ran the study made an error in Excel.

Meanwhile, in the world of amusing-but-not-important baseball news, MLB Network’s Brian Kenny ripped into White Sox broadcaster Hawk Harrelson for blaspheming sabermetrics.

The way in which we interpret data is important. For years prior to the Moneyball revolution (which has definitely been related to the success of Nate Silver and Big Data’s popularity), people within the sports stats community were begging for somebody to pay attention to their numbers, and they had a darn good point. Good hypotheses based on solid evidence were ignored for traditional theory in a way that seemed fraternal and anti-scientific.

Since then, statistical analysis certainly has gained ground in front offices and with the greater fan base, but too often it’s presented, much like a lot of modern economic theory, as science.

A lot of blame here is on the media, which like to create false dichotomies to masquerade conversation as conflict. No example of this is better than MLB Network’s over-the-top commercial featuring Kenny and Harold Reynolds, with the former serving as the God of Logic and the latter as the God of Wisdom in an eternal battle to decide who should bat fifth for the Mariners.

The commercial begins with Kenny doing his best Will Hunting impression. (And if we’re gonna get all super nerdy, the best he can mutter is something about OPS? C’mon.) He then looks squarely into the camera and states resolutely, “Stats tell the truth,” which befuddles me. The truth … about what? Reynolds plays opposite as the old-timey baseball coach who learned the game on the diamond, not from a textbook.

This all really started with Michael Lewis’ over-dramatization of the front office divide between scouts and stats guys in Oakland, but it’s been taken to a whole other, dare I say, religious level. On one side is Sabermetrics, represented as a branch of science grounded in Enlightenment values and unyielding objectivity. On the other side is Scouting/Feeling/Traditionalism, represented as dealing with strategy, keen observation, and insightful instinct as a result of experience.

I talked to a random guy about baseball before this season started, and when I attempted to rebut his argument that the Mets would have the worst outfield in the history of baseball, he shook his head, looked at me solemnly and said, “Sabermetrics says so.” I guess I had two options: I could agree with him and trust the numbers or reject the numbers and trust faith. Sabermetrics said so, so I really had no other choice.

In the big data revolution, it’s always important to remember that there are no panaceas. Statistical analysis is a social science, not a physical one. The best anyone can do with a spreadsheet is test some thoughts and get results that mean the thoughts may be true after all. Nerdy 20s-something-looking kids with glasses are not the modern oracles. They’re just using a different tool.

*Note: for another good take that overlaps with this topic, check out Jack Moore’s article

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  1. Brad Johnson said...

    What an excellent sentence:

    The best anyone can do with a spreadsheet is test some thoughts and get results that mean the thoughts may be true after all.

  2. SonOfDaveRoberts said...

    Jim, you forgot to mention that they all live in their parents’ basement, have acne and have never been on a date.

  3. ettin said...

    “I could agree with him and trust the numbers or reject the numbers and trust faith.”

    This is where I firmly disagree with you. You aren’t trusting in “faith” you are trusting in what you have seen with your own two eyes, scouting reports, etc. “Faith” is a belief in some intangible entity that has no root in the physical world.

    Sabermetrics hasn’t (and probably never will) identified a player’s mental makeup, grit, determination, etc. and thus it is up to scouts, staff psychologists, and coaches to identify players that have the right attitude to play professional baseball. There is a mental part to this game that is very difficult to quantify but can be observed with regular interaction.

    Also, the pot shot at nerdy 20-somethings is so cliche. There are excellent sabermetrically-inclinded General Managers in the game such as Dipoto and Luhnow who certainly aren’t 20-something looking kids with glasses. I’m certainly not. Leave the labels out please.

  4. Jim said...

    I just wish the sabrmaticians wouldn’t try to cram their numbers, INCLUDING THE ALL-IMPORTANT DECIMALS, down our throats.  I am a long absent returning reader to THT this off-season but now I pick and choose the articles I read.  If they start out with the Godly wisdom of some metric, I hit the back button.  They are probably good articles and mean well, but they just holler at you to either believe in sabrmetrics totally or go watch football (or worse yet, movies).  I doubt true sabrmaticians watch baseball for the nuances and beauty, they are too busy plugging another stat into their spreadsheet.  Some writers on this site included.

  5. Bill Petti said...

    I am confused what point you are trying to make by saying that analysis of baseball is a social science and not a physical one. If it is to draw a distinction between causal and probabilistic analysis it isn’t exactly right—plenty of physical phenomenon are governed by probabilistic relationships. If it is to say that our predictions in the social world are less reliable than in the physical world that may be a bit better, but there are certainly areas where social prediction can outpace physical.

  6. Pat Andriola said...

    Bill, it’s the latter. I’m confused where social prediction outpaces the physical (maybe on the extremes, like that MAD theory is more reliable than string theory, or something like that). The point is that social science mimics the physical science, hypothesis—-> controlled experimentation and the like, but the results are usually not as conclusive.

  7. Bill Petti said...

    Well, quantum mechanics is an area that is highly unpredictable—or, I should say, more aptly characterized by probability than strict predictability. Weather and other highly complex, interdependent physical systems have significant challenges from a prediction standpoint, whereas I can reasonably predict the behavior of a consumer or employee based on some specific attitudinal metrics, etc.

    I guess my larger point is I don’t like the physical/social dichotomy (admittedly, personal preference). I’d rather think about the nature of the system—e.g. is it more cloud-like or clock-like? What’s the level of interdependence with other systems? How many variables and what is the volatility of those variables? What is the specific time horizon over which we are trying to predict an outcome?—and whether it has a structure which lends itself to more or less reliable predictions.

    And I totally admit that being a social scientist makes me overly sensitive to this wink

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