The Luckiest BABIPers

Last summer, Jeff Zimmerman updated the xBABIP formula and provided a spreadsheet calculator to perform the dirty work. So with a month of the season in the books, let’s take a look at the hitter’s who have outperformed their xBABIP marks the most. It would be easy to simply sort by BABIP and note that the .400+ guys won’t maintain that pace, but it’s very possible that their batted ball profile supports a BABIP above .350. You wouldn’t know that without the calculator.

Player Career BABIP 2013 BABIP xBABIP Diff
Lance Berkman 0.317 0.370 0.232 0.138
Chris Johnson 0.354 0.458 0.324 0.134
Torii Hunter 0.309 0.438 0.319 0.119
Carlos Santana 0.280 0.431 0.320 0.111
Alex Gordon 0.327 0.414 0.311 0.103

I was shocked to see Lance Berkman‘s name atop the list with an xBABIP of just .232. I had to immediately check his player page to see if it made any logical sense, since I thought there was at least the possibility I entered the numbers incorrectly. But alas, it is not a mistake after all. His line drive rate is just 14%, which is perhaps the most significant driver of a hitter’s xBABIP. Aside from hitting far too few line drives, he has hit pop-ups at an inflated 19% rate. To complete the trifecta, his fly ball rate is at a career high of 46%. So not enough liners and too many fly balls and pop-ups? Who does he think he is, Mike Moustakas? While there’s no telling how long he’ll remain healthy and on the field, I’d chalk this up to early season random variation. Hitting third in the Texas lineup is a prime spot and he should continue to earn value in even shallower mixed leagues. But of course, that batting average is going to dive below .300 sooner or later.

Ohhh Chris Johnson, the man who strings together a whole bunch of singles and fools fantasy owners into thinking he’s worth picking up “while he’s hot”. The xBABIP tells us that he does deserve a better than league average mark, and that’s supported by a high line drive rate and nary a pop up. He has also maintained high marks in the past. But c’mon folks, the balls have been falling in, but they won’t continue to at this pace, and once they stop, he’ll go right back to being worthless in all the leagues he was added in. And then of course, Fredi Gonzalez, who would probably be that fantasy owner who makes 300 transactions every season based on hot and cold streaks, is going to bench Johnson in favor of Juan Francisco. On the positive side though, he’s striking out at the lowest frequency of his career. Unfortunately, he’s swinging and missing just as often, so don’t expect the improved contact rate to last.

Last season, Torii Hunter drank the BABIP juice and posted a .389 mark that easily set a new career high. That hid the fact that both his power and stolen base attempts were his lowest since 2000. Well, he’s up to his new tricks again, hitting even more line drives than he did last year when he posted the highest rate of his career. Perhaps he realizes he no longer possesses the power from his younger years and has instead changed his approach to emphasize line drives instead of fly balls that would simply find outfield gloves. It makes sense and that’s what the stats are telling us. Of course, that only suggests that he should be able to beat his career BABIP mark of .309, but another mark above .350 is asking for too much in all likelihood.

All that had been missing from Carlos Santana‘s potential to finish the season as the top fantasy catcher was good BABIP skills. In two and a quarter seasons, he has never exceeded a .278 BABIP, which has held down his batting average, despite pretty strong contact rates for a hitter with his power. The only real difference in his batted ball profile this season is that he has yet to hit a pop up. Obviously, that won’t continue, so he’s just been making solid contact over this first month. Santana has been a pretty strong pull hitter throughout his career, which hurts a hitter’s BABIP potential. I thought maybe he has been going to the opposite field more frequently this season that would explain some of the BABIP improvement, but that hasn’t been the case. Since his previous season BABIP marks were all below league average, he’s definitely the type of hitter to gamble on for a random BABIP spike.

Alex Gordon has been a line drive machine in recent years, while posting pop-up rates below the league average. With his power and speed, that’s a perfect combination that would result in a high BABIP. This year his line drive rate is down, but so is his pop-up rate. His ground ball rate is also at a career high. All together, it probably leads to a slightly lower xBABIP because of the LD%. Gordon has posted BABIP marks in the mid-.350 range the past two seasons, so his fall may not be as far as some of the others.

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Mike Podhorzer produces player projections using his own forecasting system and is the author of the eBook Projecting X: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. His projections helped him win the inaugural 2013 Tout Wars mixed draft league. He also sells beautiful photos through his online gallery, Pod's Pics. Follow Mike on Twitter @MikePodhorzer and contact him via email.

19 Responses to “The Luckiest BABIPers”

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  1. JT Grace says:

    “Fredi Gonzalez, who would probably be that fantasy owner who makes 300 transactions every season based on hot and cold streaks”

    LOL!! Sad, but true.

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    • Jim says:

      I make 300 (or more) transactions each season, but that’s because I only hold relievers and stream starters. Lots of top notch closers and setup guys means I always win in rate categories and saves, and by only streaming pitchers playing against strikeout prone offenses, I can stay competitive in K’s. But it does mean 5+ transactions a day.

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  2. ryan says:

    Would be great if u could post the top 20 or 25 luckiest and unluckiest.

    Looking at dumping victorino for moss, cain, or nava.
    scoring weighted based upon r/rbi/ and tb/bb, small bonus for sb.
    Gardner, mclouth, and parra also available.

    Thanks guys!

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    • wynams says:

      seconded … I would be more interested in the top unluckiest.

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      • Mike says:

        That would be nice. in the meantime, you might try sorting players by line drive %, then look at GB/FB ratios, HR/FB and the IFFB rate to get an idea of who has been unlucky. Seems like Konerko, Pierzynski, Keppinger, Beltran, Iannetta, and LaRoche might be unluckiest so far.

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  3. Hey I just need to ride out Chris Johnson a little longer until Aramis comes back for me. Keep BABIPing it up!

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  4. mymaus says:

    I know this could be a stupid question — any reason why xBABIP and BABIP-xBABIP can’t be reported on player pages and leaders lists?

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  5. Wobatus says:

    Johnson’s career wRC+ is 103. He obviously can hit liners, he just K’s a lot otherwise, doesn’t walk and has meh power, but he’s a tolerable depth guy in fantasy. Last year he was at 108. I know wRC+ isn’t a category in most leagues. But where he really kills you in real life is fielding. That’s not an issue in fantasy.

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  6. Urban Shocker says:

    Mike I have a question-and let me preface this by saying I’m all about looking for an edge, even with the usual sample size grain of salt.

    But why is UZR reported with a million caveats, & yet there are no such disclaimers on (hitters!) xBABIP, which I believe has a similarly low correlation? Maybe I’m doing a bit of apples and oranges, as one is an expected rate, but I’m sure you get my point. I suppose I’m an xBABIP apostate :)

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    • I’m not sure what you’re saying. A similarly low correlation to what? xBABIP is just a formula that is supposed to estimate BABIP, just like SIERA or xFIP. Based on the skills the player has shown, this is what his BABIP, or ERA, should be.

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      • Urban Shocker says:

        There’s not a correlation shown in the Zimmerman article you reference, but slash12′s previous xBABIP had a correlation of .3 Pretty low right?

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      • I don’t see a .3 correlation referenced anywhere in slash12′s article. However, he does say he calculated a .44 r-squared in the comments, which is about a .66 correlation. That’s not amazing or anything, but pretty good.

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      • Urban Shocker says:

        well of course SB nation is acting up and I can’t get to the comments now, and perhaps I remembered it wrong. Certainly a .66 merits consideration, but then again, that was based on only a 2 years sample, and I think that bugs me too.

        Thanks for jumping into the comments!

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  7. Corey says:

    Are there any trends in Babip over/under performers? Would indicate something wrong with the model if people who have one thing in common tend to overperform their xbabip or underperform it. More importantly it would enhance collective knowledge of what drives babips. In particular I wonder about extreme rates, might people who hit extreme rates of say line drives badly over-perform their xbabip? If so that would indicate that maybe the model needs a squared term or something. I also wonder if home runs might actually have a relationship to babip as an indicator of how hard the batter is hitting the ball. Have you looked at extra base hit percentage for example? Even though home runs formulaicly have no relationship to babip they might be theoretically related.

    From your article it seems like this might be the case, you say “Alex Gordan has been a line drive machine,” and “Carlos Santana has yet to hit a popup,” Torii Hunter is “hitting even more line drives than last year,” Chris Johnson’s is “supported by a high line drive rate and nary a popup,”

    Other than that most of these guys are outside the range of reasonable expectations in general, the only one on your list who your writeup suggests shouldn’t be hitting for a high babip is Berkman. As a Berkman owner this makes me sad, but I wonder if there are intervening variables here or non-linear effects to be explored.

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    • The formula isn’t perfect, as it excludes lots of variables that I know should factor in. So there will be outliers. But it’s the best formula we have that I’m aware of and does a good enough job for the majority of the hitter population.

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  8. The Humber Games says:

    Interesting that Marte doesn’t show up here, as most analysts seem to think he’s doomed for regression with his .410+ babip.

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