John McDonald and the One Weird Trick for Projecting BABIP

Infielder John McDonald announced his retirement on Wednesday, having recorded at least some manner of major-league playing time in each of the past 16 seasons.

McDonald’s defensive reputation was excellent almost till the end — and the numbers support that narrative. In more than 4000 innings at shortstop, McDonald saved about 19 runs, or about six runs per every 150 games. At second base, he was (unsurprisingly) better, saving roughly 16 runs per every 150 games at that position.

Offensively, his track record was decidedly less impressive. In 2651 plate appearances, McDonald slashed just .233/.273/.323, producing a 56 wRC+. Not poor enough, that, to prevent him from having a legitimate major-league career. That said, McDonald was sort of a human case study designed to test how little offense a team would tolerate from an elite defender.

What’s notable about McDonald’s offensive performance is that, of the two metrics which most directly inform batting average — that is, strikeout rate and BABIP — McDonald constantly posted above-average figures by one of them. Between 1999 and 2014, the league-average strikeout rate was 17.2%. Over that same interval, McDonald produced a 14.3% strikeout rate. Maybe not quite a standard deviation better than the mean, that, but still solidly above average. The trouble for McDonald was his batted-ball outcomes. Over those same 2651 plate appearances — more than an adequate sample for such a thing to become reliable — he produced just a .264 BABIP, rendering him something like a 30 on the 20-80 scale by this particular measure. The frequency with which he made contact, in other words, was never adequate enough to compensate for his lack of power on contact.

McDonald’s curious batting profile has some value for its capacity to provide a better understanding not only of current players — but, perhaps more intriguingly, for prospects. For, inspecting his batted-ball profile, one finds that McDonald consistently produced infield-fly-ball rates (IFFB%) above — which is to say, worse than — league average. Even more relevant to this line of inquiry, McDonald’s IFFB rates were also high relative to all his batted balls. Indeed, both inuition and Steve Saude (writing for Community blog in 2012) tell us that, if IFFB% offers some clues as to a hitter’s BABIP, then IFFB as a percentage of all batted balls offers even more in that way.

Regard, for example, this graph, which plots BABIP vs. IFFB% for all players who recorded more than 5000 plate appearances between 2002 and -14:

IFFB%

And now regard this second graph, which plots BABIP vs. IFFB per Batted Ball for that same population:

IFFB per Batted Ball

The correlation is considerably stronger in the latter instance — and continues to grow stronger in larger samples, too, as the table below illustrates (again, using the sample of hitters from 2002 to -14).

Min PA Obs. r^2
1000 685 0.40
2000 438 0.50
3000 275 0.49
4000 173 0.54
5000 92 0.50
6000 43 0.56
7000 21 0.70
8000 7 0.77

While there are certainly calculators that exist and which offer more sophisticated means by which to estimate a player’s “true talent BABIP,” as it were, it’s striking the degree to which a player’s infield-fly profile reveals his likely BABIPs. This is advantageous, as well, as fly-ball and pop-up rates become reliable in about just 20% of the plate appearances as does BABIP.

As for McDonald himself, one finds that he produced infield flys on 5.8% of his batted balls — a figure which would equate roughly to a .270 BABIP. His career mark, again, was a .264 BABIP.

Finally, for the benefit of the reader, here’s a reference table featuring rough equivalencies between IFFB per batted ball and BABIP:

Grade IFFB/BIP BABIP
20 7.25% .250
30 6.00% .268
40 4.75% .285
50 3.50% .300
60 2.25% .315
70 1.00% .330
80 0.00% .345





Carson Cistulli has published a book of aphorisms called Spirited Ejaculations of a New Enthusiast.

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Only Glove, No Love
9 years ago

Adam Everett: BABIP .275 IFFB% 17.1%

Same same? Better? Worse?