http://www.fangraphs.com/graphs.aspx?playerid=1101&position=OF&page=7&type=full

Who has never been below .300 in his life and was at almost .400 last year, as compared to, say, John McDonald (the worst hitter I can think of, being from Toronto):

http://www.fangraphs.com/graphs.aspx?playerid=395&position=3BSS&page=7&type=full

It’s true that the league average BABIP is consistent from one year to the next, but that’s like saying that the league AVG is consistent. It doesn’t mean that nobody has the ability to be consistently better or worse.

Of course that’s true within reason. Something as way off as a BABIP of 0.063 is certainly a sign of at least some bad luck (as is going 4-43 if you’re not legally blind).

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I don’t know whether he has been hitting into the shift or not.

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You can’t throw away a “scant” four ground balls when he’d only had 49 balls in play at that point. That’s over 8% of his BIP.

How about the fact that 57% of his balls in play hadn’t even left the infield? Does that account for anything?

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My point about the other stats is that we actually *have* looked at them. You might disagree with my conclusions, but your characterization of my methods is inaccurate—I certainly didn’t go into this looking only at David’s BABIP. I looked at a lot of other numbers, and the only number that looked like a preposterous outlier was, yes, his batting average on balls in play. Just because I ultimately decided those other numbers were enough within the norm that they alone couldn’t account for a sub-.100 batting average doesn’t mean I didn’t give them a careful evaluation. I didn’t throw them out because of small sample size—I threw them out because considering that the sample size is so small, a slightly higher GB% translates to a scant handful of batted balls.

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The BABIP in Mo Vaughn’s last four years (when his knee was becoming a serious problem) is a lot lower than in his prime.

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My argument is that Papi’s crappy BABIP is a fluke due to small sample size. So on my end, the small sample size is actually working *with* my argument, not against it. You say that people misuse BABIP as a be-all-end-all stat, but I don’t think anyone has done that in this particular discussion. We’ve talked about GB%, LD%, K rate, BB rate, IF/F%….

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1) He’s a known case that we can work backwards from. We know that his knee issues affected his play later in his career. So we can look at his stats and see a pattern for that kind of hitter.

2) He’s very similar to David Ortiz.

If we’re going to argue small sample size here then there can’t be a double standard. If I can’t include Mo Vaugn’s 79 ABs in a list of his BABIP, then Sarah can’t write an article analyzing a player’s BABIP in mid-April. We can’t have it both ways.

My general point is that people misuse BABIP as an end-all-be-all stat. Under-290=Unlucky Over-300=Lucky. Clearly not. If injury is a possibility, you have to look at that too.

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As for the specifics, Ortiz has (through yesterday’s game) come to the plate 81 times. If he had a line drive percentage of say 17% (what he had last season) then he would have roughly 6 more line drives, or about 4.5 more hits.

So, yeah, his low BABIP is a function partly of luck, partly line drive percentage, and partly a sample size issue.

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