BABIP Laggers, xBABIP and Fantasy Rebound Candidates

by Eno Sarris //

We’ve quoted Russell Carlton’s study about the benchmarks when different statistics become significant plenty of times here. In that study, he basically asked how long it took for a statistic to reliably predict itself in one season. Given a batter’s batting average, for example, how many plate appearances does it take until that average predicts his future in-season batting average to a 70% reliability? The answer, in this case, is never. Batting average is one of the most volatile statistics in baseball, and subsequently we’re always chasing those hits in fantasy play.

While batting average itself doesn’t normalize quickly, there are some interesting quirks in the component pieces. For example, line drive rate becomes significant within 40 plate appearances. In other words, the poor-line-drive-hitting players do actually have something to worry about in the early going. While BABIP doesn’t become significant over one season, one of the main components of BABIP - line drive rate – steadies rather quickly.

It follows that players with poor BABIPs are not created equally. A player with a poor line drive rate (the average line drive rate is around 19%) may end the season with a poor BABIP, and therefore a poor batting average. That makes our mission clear. Let’s take a look at the 10 worst BABIPs in the majors, courtesy of FanGraphs. Not surprisingly, the list is filled with under-achievers.
BABIPLaggers.jpg
It’s nice how quickly you can get a sense of which of these players is more ready for a rebound in batting average than the rest. For example, Carlos Quentin may have something to worry about. He’s just not centering the ball, and with a poor line drive this year as well as over his career (15.7%), he may actually end up being a guy with power and poor batting averages once we look back on his full career. That’s another way of seeing how misleading batting average can be – even though we are more than 1500 plate appearances into Quentin’s career, there’s a non-zero chance that he’s better than his .248 career batting average so far. On the other hand, this spider graph from the Bloomberg Sports Fantasy Tools might actually show us who he really is.

QuentinGrab.jpgThere are other names on that list that pop out as ready to bust out. We’ve heard a million times how Mark Teixeira is just a slow starter, he’s got an average line drive rate, and for some reason nearly 80% of his balls in play are becoming outs. That shouldn’t continue, nor should Casey Kotchman continue to be this unlucky on balls in play.

You can use a player’s batted ball profile – their groundballs, flyballs, line drives – and their speed – measured by stolen bases for now – to predict what their BABIP should be. This stat, often called xBABIP, does a good job of pointing out which players are ready for the rebound as well. Here’s the original article, by Peter Bendix and Chris Dutton, that also included an xBABIP calculator.

BABIPxBABIP.jpgCheck out the same 10 players from above, with their batting average, BABIP and xBABIP as columns. Players with the highest xBABIPs on this list suffer from the worst luck and are therefore the best bets for improved batting averages in the future. 

So there you have it. Feel good about Nick Johnson, Teixeira and Kotchman, and worry a little about Quentin and Aramis Ramirez in particular. BABIP is always a useful tool when looking at slumping batting averages, but xBABIP and its component stats help us complete the picture.


Statistics updated through 5/9/10. For more on players with slumping batting averages, check out 
Bloomberg Sports Fantasy Tools.

1 Comment

This doesn’t make me feel good about Aaron Hill’s struggles. His early season LD% is only 9%. I’ve been optimistic since his BABIP is only .200, but this article tells me that I reallyshould have drafted Pedroia instead of Hill. D’oh.

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