De-Lucker X: The Final 2012 Numbers

Remember when the Playstation 2 came out, and then Sony released a newer, smaller version of the original Playstation, called the PSone? After that, people started calling the original Playstation console the PSX, or Playstation X. Today, we are going back to the original console version of the De-Lucker, so grab your nearest mint copy of Final Fantasy VII and buckle in!

Why DLX?

FanGraphs recently re-did how we calculate wOBA for all the players. In an effort to give base-running its own stand-alone category and run/win value, we reduced wOBA to a hitting-only metric and took out SB and CS. That’s where the problem with the De-Lucker 2.0.

DL 2.0 used the Fielding Independent wOBA formula, which includes stolen bases. In order to keep things parallel, we now must revert back to the Should Hit formula — essentially:

0.09 + 1.74(HR%) + 0.39(BB%) – 0.26(K%) + 0.68(BABIP)

The De-Lucker part comes in when we plop an xBABIP in the place of yonder true BABIP. Jeff Zimmerman and Robert Boden (slash12) have been working on and promoting what I believe is the best xBABIP formula out there, so let us once again use that.

Beneath the jump: More caveats! All sorts of data! Downloadable Excel spreadsheets! Fewer video game references!

De-Lucker X!

(Note: Minimum 100 PA, presently filtered to show only 300 PA or more.)


We cannot use DLX for purely forecasting measures. It is a regression-based and backwards-looking tool. DLX says, “This player would have had this wOBA given this (predicted) BABIP.” If the player dramatically changes his strikeout or walks rate (uncommon), if his home run rate was unusual for a season (pretty common), or if the inputs to his BABIP were crazy town banana pants, then his DLX will probably look a lot different than his 2013 wOBA.

For example, this is what happens when we compare the predictive powers of DLX with basically the bare minimum of anything else:

Click to embiggen this puppy; lest you break your eyes.

What does that tell us? That (1) DLX is reflective, not forcastive. When predicting a 2012 wOBA, it was more predictive to look at a player’s raw 2011 wOBA than his 2012 DLX. Also, (2) the MLB is volatile. Without delving much further into the generally unhelpful exercise of testing DLX’s predictive powers, we can conclude a hitter’s statistics — as well as his playing time — are highly volatile.

Lastly, (3) I believe much of the variation comes from a player’s fluctuation in home run rates as well as the normally-expected BABIP fluctuations. ‘Twere I some database boffin, I would present to you DLX rates wherein we use a player’s career HR/PA numbers, not their sub-optimal single-season home run rates. But here we are: You, stuck with sub-optimal me, and me, stuck with passive you.

So Why Even Look at DLX?

A fair question! The preceding caveats mean to dissuade the reader from just looking at the data and saying, “Whoopie! Player X is going to be such a huge fantasy sleeper for me next year! Bradley said so!”

I certainly did not! In fact, what I am merely presenting is a piece of the puzzle. When you see Player X with some crazy colorful cells up there, step two is to find out why. DLX says Adam Dunn under-performed by almost 50 wOBA points. Now ask why. (“Why?”) Because Boden’s xBABIP formula says he had the peripheral numbers of .317 BABIP — but in all likelihood, an age 32 Dunn may finally be slow enough that he will never crest above a .300 BABIP again.

Likewise, fellas like Elliot Johnson and Munenori Kawasaki — both players I love — may not be worthy of their xBABIPs on the simple merit of being bench players whose hitting talents might get overestimated in a regression to the MLB’s mean.

That told, DLX offers a great conclusion to all the once-vague arguments, such as:

“If Dee Gordon‘s BABIP would just come up to his minor league BABIP, he would be a great hitter.”

Eh, probably not. (Hey, a .299 DLX is not terrible for a shortstop, but in no way objectively “great.”)

“If Mike Trout‘s BABIP goes down to a normal level, he won’t be nearly as good a hitter.”

Nope. (Still a .403 DLX after 20 point BABIP drop. Home run rate? That’s a different inquiry…)

James Loney‘s bad numbers in 2011 were almost entirely BABIP-fueled.”

It appears that way. (A .325 DLX puts his just about on track for his career norm.)

Justin Ruggiano is just a product of good luck and good timing.”

Not so! (He could drop 80 points of BABIP and still have a strong .347 wOBA — assuming all other rates hold.)

Now YOU think of your strawmen, and then prove them wrong. It’s almost like fun!

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Bradley writes for FanGraphs and The Hardball Times. Follow him on Twitter @BradleyWoodrum.

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3 years 6 months ago

“Justin Ruggiano is just a product of good luck and good timing.”

Not so! (He could drop 80 points of BABIP and still have a strong .347 wOBA — assuming all other rates hold.)

I certainly hope he does well, but you look at some of his stats and it screams regression. 13.5 SwStrk %! 26.3 K%!! .401 BABIP!! I was just wondering how far it would go. A .347 wOBA, tossed in with ~20 SBs is pretty good in our current run environment. He could be a sneaky pickup, and with the Marlins I would think he can get a full season load of PAs. It is the Marlins though, so who know. Justin already told me “he got this.”–mlb.html

3 years 6 months ago

It looks like about 80% of the players were “unlucky” last year. Shouldn’t the difference be centered around zero if luck is random?