6:18 pm ET
Aug 9, 2011


When Outfielders Pitch, Laugh and Learn

    • This article draws the wrong conclusion from the data it cites by hiding a lot in misleading phrases such as "about average" and "about the same percentage". For example, looking at the McCracken link on the pitching of position players, he finds that BABIP is .020 higher for position players who are pitching than for actual pitchers. McCracken and Bialik might choose to call this "about the same", but it is not. An extra 20 points in batting average (or On Base Percentage if you prefer) is a huge difference - roughly the difference between an average hitting team and a great hitting team. And the fact that there is this big difference goes to undercut the entire BABIP argument that except for HRs, Ks, and BBs, hitting and pitching is essentially random. They are not, and this data in fact nicely demonstrates that - even if the author fails to appreciate the high significance of this difference.

    • Jeffrey, thanks for the comment. I disagree that 20 points, or two percentage points, of batting average is a big difference, especially over as small a sample size as McCracken used -- even though he was looking at 61 years of data, there were only 313 innings, which is a little over one season for a single starting pitcher. And the same starting pitcher can see opponents' batting average on balls in play vary by at least that much over more innings. Take CC Sabathia (he's on my mind since I wrote about him Monday). From 2007 to 2008, Sabathia was outstanding, compiling a 2.95 ERA over 494 innings. Yet opposing batters hit safely on 30.7% of balls in play, for a BABIP of .307 -- higher even that the nonpitchers in McCracken's sample. Over the next two seasons, Sabathia remained top-notch, with a 3.27 ERA in 467.2 innings. Yet his BABIP declined to .281. That's a difference of 26 points, over more innings -- for the same pitcher. (All stats via Baseball Reference.) 20 points isn't much, particularly since logic would suggest nonpitchers would be much, much worse at forcing batters who hit the ball in play into outs than professional pitchers are.

    • Thanks for your reply Carl, but I am going to have to respectively disagree with you here. Let me give you some back of the envelope calculations to make my point.

      First, as far a statistical significance goes, yes the McCracken sample is too small to clearly distinguish luck from skill here. That said, a .020 difference in BABIP for a sample of his size falls just short of a 2 standard deviations difference here, which means that this difference is almost statistically significant at a 5% confidence level (I will spare you the quick calculation unless you ask for it). This low statistical power, however, is not an indication that BABIP is random, but is rather simply a reflection that his sample is too small to clearly distinguish important differences. (And we haven't even gotten into the fact that when the game has reached a point that the left fielder is pitching, it is likely that the many of the hitters are subs.)

      Turning to the more interesting question, I think you are simply wrong in dismissing a .020 difference as essentially meaningless. Look at it this way: McCracken finds that when pitching, his position players have a collective ERA of a rotten 6.51. I would estimate that this is an ERA somewhere around 2.5 higher than pitchers over the same time period. But a .020 difference in extra batting average allowed will translate, on average, to roughly about an extra 1.00 in a pitcher's ERA. So this extra .020 in BABIP, which you dismiss as meaningless, explains approximately 40% (1.00/2.50) of the poor performance of the position players on the mound. The remaining 60% would of course be due to the pieces pulled out of BABIP - a high walk rate, poor Ks, and lots of HRs.

      The bottom line is this. While McCracken's sample is too small to conclude anything clearly, the point estimates from his sample suggest that a little bit less than half of the underperformance of position players when pitching is due to variation in BABIP, with the remainder coming from the factors not included in BABIP. If you want to argue that it is a bit surprising that over half of the underperformance is due to high walks, low Ks, and extra HRs, on that I will agree. But when you argue, as BABIP enthusiasts do, that almost none of the underperformance is coming from hits "falling in", and that BABIP is essentially random, that is simply a false conclusion to draw from the data presented here.

      Yes, over a small sample, BABIP, like almost all baseball statistics, can vary a lot by chance. And yes, a .020 difference does sound small, but such a difference in fact does translate into a huge difference on the field, and by McCracken's own data presented here, does explain almost half of the underperformance of position players when they take the mound.

    • Thanks for the reply. What's your source on this? "But a .020 difference in extra batting average allowed will translate, on average, to roughly about an extra 1.00 in a pitcher’s ERA." That sounds high. In any case I think that overstates the effect of a .020 difference in batting average on balls in play, which isn't equivalent to batting average, because strikeouts and home runs also are factors that feed into batting average. In fact if you remove home runs than you probably get a much smaller effect than one run of pitcher ERA.

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