Regular readers of this blog are familiar with the pinch-hitter syndrome: People whose job it is to do just one thing are not always so good at that one thing. I first encountered this when noting the many silly errors introduced into my books by well-meaning copy-editors with too much time on their hands. As I wrote a few years ago:
This is a funny thing. A copy editor is a professional editor. All they do (or, at least, much of what they do) is edit, so how is it that they do such a bad job compared to a statistician, for whom writing is only a small part of the job description?
The answer certainly isn’t that I’m so wonderful. Non-copy-editor colleagues can go through anything I write and find lots of typos, grammatical errors, confusing passages, and flat-out mistakes.
No, the problem comes with the copy editor, and I think it’s an example of the pinch-hitter syndrome. The pinch-hitter is the guy who sits on the bench and then comes up to bat, often in a key moment of a close game. When I was a kid, I always thought that pinch hitters must be the best sluggers in baseball, because all they do (well, almost all) is hit. But of course this isn’t the case–the best hitters play outfield, or first base, or third base, or whatever. If the pinch hitter were really good, he’d be a starter. So, Kirk Gibson in the 1988 World Series notwithstanding, pinch hitters are generally not the best hitters.
There must be some general social-science principle here, about generalists and specialists, roles in an organization, etc?
This idea was recently picked up by a real-life baseball statistician–Eric Seidman of Baseball Prospectus–who writes:
I wanted to talk to you about the pinch-hitter theory you presented, as I’ve noticed it in an abundance of situations as well.
When I read your theory it made perfect sense, although a slight modification is needed, namely in that it makes more sense as a relief-pitcher theory. In sabermetrics, we have found that pitchers perform better as relievers than they do as starters. In fact, if a starter becomes a reliever, you can expect him to lop about 1.4 runs off of his ERA and vice-versa, simply by virtue of facing batters more often. When you get to facing the batting order the 2nd and 3rd time through, relievers are almost always better options because they are fresh. Their talent levels are nowhere near those of the starters–otherwise, they would BE starters–but in that particular situation, their fresh “eyes” as it pertains to this metaphor are much more effective.
For another example, when working on my book Bridging the Statistical Gap, I found that my editor would make great changes but would miss a lot of ancillary things that I would notice upon delving back in after a week away from it. Applying that to the relief pitcher idea, the editor was still more talented when it came to editing, but his being “in too deep”, the equivalent of facing the opposing batting order a few times, made my fresh eyes a bit more accurate.
I’m wondering if you have seen this written about in other areas, as it really intrigues me as a line of study, applying psychological concepts as well as those in statistics.
These are interesting thoughts–first, the idea of applying to relief pitchers, and, second, the “fresh eyes” idea, which is more adds some subtlety to the concept. I’m still not quite sure what he’s saying about the pitchers, though: Is he saying that because relief pitchers come in with fresh arms, they can throw harder, or is he saying that, because hitters see starters over and over again, they can improve their swing as the game goes on, whereas when the reliever comes in, the hitters are starting afresh?
Beyond this, I’m interested in Seidman’s larger question, about whether this is a more general psychological/sociological phenomenon. Do any social scientists out there have any thoughts?
P.S. I seem to recall Bill James disparaging the ERA statistic–he felt that “unearned” runs count too, and they don’t happen by accident. So I’m surprised that the Baseball Prospectus people use ERA rather than RA. Is it just because ERA is what we’re all familiar with, so the professional baseball statisticians want to talk our language? Or is ERA actually more useful than I thought?