Archive for FIP

Way out in the National League West, the much-mocked Barry Zito and the much-debated Trevor Cahill are both off to good starts. Both players got their starts with the Oakland As before moving the to National League. Of more interest is that both players have, at different times, been held up as examples of pitchers for whom DIPS stats like FIP are inadequate. Without getting into lengthy discussions of each pitcher or the whole debate about DIPS (of which FIP is just one variety), let’s take a look at Zito and Cahill’s early-season performances with a glance at their past performances and see if there is anything of interest.

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Episode Eleven
In which the panel tries its luck.

Headlines
FIP for Hitters?: A Summary
The Problem with PrOPS
A New Metric: Regressed wOBA
… and other hits of tomorrow!

Featuring
Matthew Carruth
Matt Klaassen

Finally, you can subscribe to the podcast via iTunes or other feeder things.

Audio on the flip-flop.

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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.

1. Albert Pujols, 9.18
2. Prince Fielder, 8.66
3. Adrian Gonzalez, 8.55
4. Alex Rodriguez 8.32
5. Carlos Pena 8.31
6. Adam Dunn, 8.11

So far, so good, those are some great hitters. Here are the trailers:

150. Yuniesky Betancourt, 4.26
151. Michael Bourn, 4.12
152. Randy Winn, 4.03
153. Cristian Guzman, 3.92
154. Emilio Bonifacio, 3.73

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.

The goal of an ideal bullpen is to relieve the starting pitcher and effectively shut the opposition down to the point that they stand no chance of coming back. We hear so often the idea that playoff spots are won and lost in the bullpen, and from reading numerous blogs, one might think that 26 of the 30 major league teams have “the worst bullpen in baseball.” In my eyes, the best type of reliever is one who limits his walks, gives up as few home runs as possible, and strikes out as many batters as he can. These are the controllable skills for a pitcher, or, in other words, game outcomes that have nothing to do with the defense. Which bullpen comes closest to this ideal reliever? Well, with the update to the team pages here at Fangraphs, we now have the capability to check.

For starters, which relief corps posted the best strikeout rates? The Cubs (8.68), Yankees (8.66), and Dodgers (8.62) vastly stood out from the rest in this category. The impressive Rays bullpen came in fourth place at 8.03, narrowly ahead of the Reds at 7.97. At the bottom of the league were the Pirates (6.45), Orioles (6.80), Tigers (6.83), Rangers (6.85), and Cardinals (6.87). The Cardinals may have stuck around for a while in the playoff picture, but their season was not as statistically sound as the results would indicate. And I don’t think anyone will argue that the Pirates, Orioles, and Rangers have very poor pitching staffs, or that the Tigers were an all-around disappointment this season.

When we move to walks, we see that the Dodgers (3.22) once again find themselves in the top five, at the number one spot, but their “colleagues” are different. The DBacks come in second at 3.24, followed by the Twins at 3.26, White Sox at 3.31, and Indians at 3.33, meaning that the bullpens that struck out plenty of batters were not too tremendous at limiting walks. At the bottom of the heap we once again find the Orioles, Rangers, Pirates, and Tigers, with the Mariners now mixed in. See any trend emerging?

Moving to K/BB ratio, we get a mixture of the K/9 and BB/9 leaders, as the Dodgers (2.68) lead the Cubs (2.57) and Yankees (2.46), with the White Sox (2.38) and Diamondbacks (2.32) rounding out the top five. Guess who is at the bottom? Yes, the Orioles, Tigers, Pirates, Rangers, and new-found friend the Mariners. The Orioles bullpen had an ugly 1.40 K/BB. The Mariners at least registered a K/9 above 7.0, they just had issues limiting walks.

How about home runs? The Phillies, whose bullpen has been lauded for the entire season, finally break into the top five, finishing first with a 0.69 HR/9. Led by Brad Lidge and his unsustainable 3.9% HR/FB, the Phils narrowly edged the Blue Jays (0.70), the familiar Dodgers (0.73), and the Mariners and Athletics (0.78 each). When we put it all together, in the form of FIP, the ERA equivalent of controllable skills, the Dodgers led by a wide margin over all others at 3.47.

The Yankees, Phillies, and Blue Jays then ranged from 3.82-3.85. Controllable skills are not the only measure of success, but they are very important, and nobody realistically came close to the Dodgers in 2008. The Blue Jays did have a big ERA and FIP differential, as they posted the lowest bullpen WHIP at 1.25 and highest bullpen LOB rate at 79.8%. Their FIP of 3.85 suggests their 2.94 ERA was a bit lower than expected, but elite relievers are known for being able to consistently post high strand rates, low BABIPs, and other luck-based indicators that tend to normalize for starters. Based on these results, it seems the best controllable skills in the NL belong to the Dodgers bullpen, while the Yankees and Blue Jays topped the junior circuit.

A conundrum is loosely defined as anything that puzzles… so it makes perfect sense to use the term when describing the anomaly present in the ERA and FIPs of both Carlos Zambrano and Jeremy Bonderman. We’ve written about pitchers either outperforming their FIP or failing to live up to it plenty of times here, but, in probing the last three calendar years feature recently instituted on the leaders page, it appears that things tend to even out a bit. Except, of course, with regards to Zambrano and Bonderman.

Sixty starting pitchers qualified for inclusion over the last three calendar years and they produced the following averages:

ERA-FIP: 0.12
BABIP: .303
LOB: 71.8%
K/BB: 2.48
HR/9: 0.98

One standard deviation of the ERA-FIP is 0.28, meaning we can expect about 2/3 of the data to fall within the -0.16 to 0.40 range; additionally, 95% of the data can be expected to fall within the -0.44 to 0.68 range. Of the group of sixty pitchers, just two fell beyond the 95% confidence interval: Carlos Zambrano at -0.53 and Jeremy Bonderman at 0.83.

Now, one potential reason that someone like Zambrano consistently posts better ERAs than his FIP would suggest could deal with his BABIP: the average BABIP of this group in this span is .303 and Zambrano comes in at .273, a full thirty points lower. On the other end of the spectrum, Bonderman comes in at .325, over twenty points higher. In fact, when looking at the eighteen pitchers who fell beyond one standard deviation of the ERA-FIP mean, the nine higher than 0.40 ranged from .297-.332 in BABIP while those below -0.16 ranged between .269-.309.

I actually discovered whilst writing this post that a question regarding Zambrano outperforming his FIP was posed in the Inside the Book mailbag, to which MGL mentioned the possibility of him posting a lower than average BABIP after concluding that it is definitely possible for certain pitchers to post certain types of BABIPs. This is definitely the case. As MGL also noted in the mailbag, “FIP is a very good at eliminating the noise in BABIP, which allows us to get a better estimate of a pitcher’s run prevention skill, in the short run. In the long run, ERA, RA or ERC is MUCH better because it captures the differences in BABIP skill among pitchers, as well as the other things I mentioned above that contribute to a pitcher’s run prevention skill but are not addressed at all in FIP (like WP rate).”

So, one reason these two guys are constantly posting ERAs much better or worse than their FIP would suggest could be that they have posted above or below average BABIPs with enough regularity to show they have some type of control over it; in that regard, their ERA would be a better indicator of run prevention. Then again, they might not have control over their BABIP and this could all even out, but it would seem that this is a very likely cause at this juncture.