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FIP for Hitters? Defense Independent Offense
Posted By Matt Klaassen On February 23, 2010 @ 1:56 pm In Daily Graphings,Research | 29 Comments
While writing on the “three true outcomes” (walk, strikeout, and home run) leaders and trailers from 2007-2009, I was reminded of a toy idea that I’d had earlier to create something like FIP (Fielding Independent Pitching), using the same basic components, except for hitters. I finally got around to doing it recently, and the results were interesting. I’m not saying this is any more than a junk stat. But it might be interesting, who knows?
* You want real sabermetric research? Read Matthew Carruth, Dave Allen, or one of the many other intelligent researches writers here and elsewhere. Trying to waste time at work? You came to the right place. Tom Tango may have created wOBA and FIP, but this a stat that gives me joy.
The basic formula for FIP is ((HR*13+(BB+HBP-IBB)*3-K*2)/IP) + 3.2, where “3.2″ is a season/league specific factor to put the league FIP on the same scale as the league ERA. To make it suitable for hitters, I made a couple of minor modifications: 1) I scaled it to RA rather than ERA. The RA scale for the 2009 MLB was 3.52. 2) For IP I used outs made by the hitter (divided by 3 to get on the IP scale): AB-H+SF+SH+GIDP (I left out CS because I want to deal with the pitcher/hitter matchup). Ladies and gentleman, I present the formula for Defense Independent Offense, or DIO:
((HR*13+(BB+HBP-IBB)*3-K*2)/(Outs/3)) + 3.52.
Who (among qualifying hitters) led the league in DIO for 2009? Remember that for hitters, a higher number will be better.
So far, so good, those are some great hitters. Here are the trailers:
Some of these names — Betancorut, Winn, Bonifacio — aren’t surprising. But what about Michael Bourn, for example? Didn’t he have a decent season at the plate in 2009? Hold on to that thought.
Just as a player’s wOBA can be compared with league wOBA to give up the player’s runs created above average (wRAA), we can compare a players DIO with the league’s runs per game (4.61 in 2009) to produce a DRAA: =(DIO-lgR/G)*(Outs/27).* Here are the 2009 leaders in DRAA and with their wRAA figures for sake of comparison.
* One can also calculate absolute runs created (wRC) with DIO * (Outs/27).
1. Albert Pujols 69.9 DRAA, 69.7 wRAA
2. Prince Fielder 65.6 DRAA, 54.9 wRAA
3. Adrian Gonzalez 62.2 DRAA, 41.5 wRAA
4. Mark Teixeira 53.5 DRAA, 42.9 wRAA
5. Adam Dunn 53.2 DRAA, 35.9 wRAA
The Pujols figures are almost dead-on, and given the crudeness of DIO, Fielder and Teixeira aren’t that far off, but Gonzalez and Dunn seem to be quite overrated by DIO-Runs. The general “in the neighborhood-ness” isn’t that surprising, given that FIP (and thus DIO) are based on linear weights of the relevant events, and wOBA is just linear weights expressed as a rate stat. But what about the discrepancies? Does the perhaps mean we should be rethinking wOBA/wRAA in favor of my awesome new offensive metric, or at least use it more prominently, just as FIP is generally favored (around here) over ERA?
In a word: no. Going back to the origins of DIPS-theory, pitchers generally have little control over balls in play, and thus DIPS, FIP, tRA, etc. are attempts to remove the defense-dependent elements from pitcher evaluation. However, while BABIP generally has less year-to-year correlation for hitters than, say, walk rate, it does correlate far better than for pitchers. That is why traditional linear weights (like wRAA) are preferable for hitters. DIO systematically underrates hitters like Michael Bourn not only because it ignores steals, but because it assumes that the players contributions on balls in play are league-average, whereas Bourn’s contributions in those areas are well-above average. DIO’s also badly underrates hitters like Joe Mauer (40.5 DRAA vs. 54.9 wRAA in 2009) and Ichiro Suzuki (-2.2 DRAA vs. 22.6 wRAA), as well as overrating (still very good) hitters like Adrian Gonzalez and Adam Dunn.
DIO has interesting aspects. It highlights how many good hitters get most of their value from hitting home runs and walking, for example. There is also much to be said for using a rate stat baselined against outs rather than PA (I wouldn’t go so far as to make the mistake of generating a DIO-based Offensive Winning Percentage, although it was tempting). For me, it was worth it just to walk through and see how well the stat did in ranking hitters. Most of all, it was a good reminder of the difference in BABIP as a skill relative to pitchers and hitters. Without reminders like these, I’d be left on my own, like a rainbow in the dark.
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