Searching the Diamonds of SIERA Leone
I'm just going to get this out of the way: I've been thinking of that corny title ever since SIERA was unveiled last week and it was one of the driving forces in me penning this post. I'm a sucker for cheesy titles that reference over-hyped hip-hop artists.
Baseball Prospectus recently rolled out their new pitching metric called Skill Interactive Earned Run Average or SIERA for short. Matt Swartz and Eric Seidman set out to improve on some of the perceived short-comings of FIP. The new stat was deconstructed by Tom Tango on his blog a couple of times (if you click that link, beware: a lot of math that is over my head) and Cubs Stats has kept track of the week-long series that B-Pro was running last week. The early consensus seems to be that it is marginally better than using FIP (or xFIP).
What I'm going to do is use the handy little SIERA calculator that Cubs Stats built and take a gander at the Tigers pitching staff in 2009 through the lens of xFIP and SIERA after the jump.
Before we dive into this, just a bit more back round of SIERA. They listed six major things they are improving on versus FIP:
1. Allows for the fact that a high ground-ball rate is more useful to pitchers who walk more batters, due to the potential that double plays wipe away runners.
2. Allows for the fact that a low fly-ball rate (and therefore, a low HR rate) is less useful to pitchers who strike out a lot of batters (e.g. Johan Santana's FIP tends to be higher than his ERA because the former treats all HR the same, even though Santana’s skill set portends this bombs allowed will usually be solo shots).
3. Allows for the fact that adding strikeouts is more useful when you don't strike out many guys to begin with, since more runners get stranded.
4. Allows for the fact that adding ground balls is more useful when you already allow a lot of ground balls because there are frequently runners on first.
5. Corrects for the fact that QERA used GB/BIP instead of GB/PA (e.g. Joel Pineiro is all contact, so increasing his ground-ball rate means more ground balls than if Oliver Perez had done it, given he's not a high contact guy).
6. Corrects for the fact that FIP and xFIP use IP as a denominator which means that luck on balls in play changes one's FIP.
For this project, I'm going to be limiting the sample to Tigers hurlers that threw at least 40 innings in 2009 for Detroit. That leaves us with Brandon Lyon, Justin Verlander, Edwin Jackson, Ryan Perry, Rick Porcello, Bobby Seay, Zach Miner, Fernando Rodney, Nate Robertson, Armando Galarraga, and Jarrod Washburn. I'll even throw in Max Scherzer, free of charge.
SIERA vs. xFIP
First, we'll start off with The Winners. This is a group of the pitchers above who SIERA likes a lot more than xFIP.
| Name | SIERA | xFIP | SIERA-xFIP |
|---|---|---|---|
| Bobby Seay | 4.10 | 4.72 | -0.62 |
| Justin Verlander | 2.67 | 3.26 | -0.59 |
Verlander and Seay get big jumps by SIERA. Verlander was dominant by xFIP measurements, but when you expand on the formula and give JV a Johan Santana-like fix -- Santana's FIP's are usually higher than his ERA's because FIP treats all homers the same. Guys like Santana who strikeout a very high number of hitters normally don't have many people on base which leads to more solo bombs -- it shows just how dominant Verlander was last year. Fun fact: Verlander gave up 271 fly balls in 2009. He struck out 269 batters. That is absurd.
Seay continues to be an effective reliever and will be again this year. Whether that is in Motown or not remains to be seen.
The Middle Pack are all pitchers with a difference between SIERA and xFIP of 0 to -0.49 runs.
| Name | SIERA | xFIP | SIERA-xFIP |
|---|---|---|---|
| Ryan Perry | 4.15 | 4.53 | -0.38 |
| Nate Robertson | 5.01 | 5.37 | -0.36 |
| Max Scherzer | 3.53 | 3.88 | -0.35 |
| Edwin Jackson | 4.17 | 4.39 | -0.22 |
| Brandon Lyon | 4.09 | 4.24 | -0.15 |
| Fernando Rodney | 4.28 | 4.42 | -0.14 |
| Jarrod Washburn | 5.38 | 5.44 | -0.06 |
| Armando Galarraga | 4.98 | 5.02 | -0.04 |
Perry, Robertson, and Scherzer all get healthy bumps. All of these guys sported a 1:1 ground ball:fly ball ratio last year -- except for Robertson and Washburn who had 1 and 3 more fly balls than grounders, respectively.
The Loser Pack are the remaining pitchers who are rated better by xFIP than SIERA.
| Name | SIERA | xFIP | SIERA-xFIP |
|---|---|---|---|
| Zach Miner | 4.94 | 4.86 | 0.08 |
| Rick Porcello | 4.59 | 4.32 | 0.27 |
Unfortunately for us Miner Proponents over the years, SIERA didn't smile to kindly on swing man. SIERA gives more room for ground ball machines like Miner and Porcello (that's the theory), but they just K'd so few guys last year while not exactly suppressing walks. They had K:BB ratios of 1.41 (Miner) and 1.71 (Porcello). Outside of getting guys to beat the ball into the ground, they really didn't do much else. I'd expect a bit of a shift for Porcello in 2010, though. I think his arsenal is just too good to not get his breaking ball and good change-up to generate more whiffs this year.
What do we conclude from this? Well, SIERA is a stat that is more complicated than FIP or xFIP. What you do gain is that it allows more leeway for guys who strikeout around the league average number of hitters but are great at getting the worm-burners. It isn't light years ahead of xFIP, so feel free to continue to use FIP if you'd like -- I'm probably going to. However, for some guys like Verlander or Johan Santana -- and other guys who strikeout a large number of hitters, don't walk many, and aren't ground ball aficionados -- SIERA looks to be better at properly weighting their talents in a pitching metric.
You can look at and download my spreadsheet on Google Docs (File -> Download As -> what ever format you'd like). It includes each pitchers tERA as well -- however, these are not extracted from Fangraphs. I used xFIP (or a regressed version of FIP), so I felt it only right to use the regressed version of tRA called tRA*. I got this data from Stat Corner. To convert tRA* to tERA, you must multiply by 0.92 because roughly 92% of all runs scored are earned runs. tRA* is measuring a pitchers total runs allowed (hence the tRA acronym) and not just earned runs. This puts it on the same scale as SIERA and xFIP.
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Very very cool
I won’t be spouting SIERA as the gospel now, but it’s always nice to have another quality metric out there to push the boundaries and get better analysis.
Seeing how highly Scherzer is valued in each of those metrics gives me so much hope (my goodness he’s so much better than Edwin Jackson), let’s pray that he can stay healthy.
Upon closer reading, I see it's more of a Kanye reference
Still, all publicity is good publicity I guess, even if it originates w/ Kanye and before that a Leo DiCaprio movie.
I would've went with Siera Madre
but that’s just because I’ve been reading about the Cuban Revolution lately.
Anywho, I’ll be keeping an eye on these numbers. I’d like to see how they compare to xFIP and all of that over the last 5 years or so.
Sounds interesting
once my head stops spinning! lol.
I’ve been skeptical of BABIP being used to indicate a luck factor in a pitcher’s ERA. Some pitchers are just better ground ball pitchers, so they’ll necessarily tend to have a lower BABIP, because more grounders result in outs than line drives. BABIP is not an irrelevant stat, but I think that drawing an automatic conclusion that a pitcher with a below league average BABIP is just lucky, is a faulty conclusion.
SIERA will take a little getting used to, but it looks like an interesting metric.
Backwards
groundball pitchers would have a higher BABiP. More groundballs eventually become base hits. A higher % of fly balls are turned into outs (or HR, thus removing the “in play” part)
It's really not nearly as consistent as all that.
Top 7 GB/FB ratio players BABIP
Joel Pinero .293
Derek Lowe .330
Jason Marquis .291
Ricky Romero .325
Chris Carpenter .272
Rick Porcello .281
Ubaldo Jiminez .290
Bottom 7 GB/FB ratio players BABIP
Jered Weaver .288
Ted Lilly .270
Scott Baker .287
Jeremy Guthrie .294
Johan Santana .296
Justin Verlander .328
Aaron Harang .339
As you can see, even with the most extreme players on either side, the BABIPs are all over the charts. The correlation between GB/FB pitchers and BABIP is a pretty weak one. BABIP has a great deal more to do with defense and luck then it does with being a ground ball or fly ball pitcher.
Thanks, Chris
I was thinking more in terms of not giving up so many line drives, which result in the highest percentage of hits allowed by comparison with either fly balls or ground balls. I think there is a skill in being able to induce either ground balls or getting the hitter to pop one up, as opposed to getting tagged. All BIP are not created equal. In addition, a pitcher that gives up a higher number of BB’s can compensate for that by inducing more ground balls, particularly if he doesn’t have to worry as much about giving up the gopher ball.
Selection bias
If you take pitchers with a GB% > 50 (of which there were 15 who qualified for the ERA title), their average BABiP is .302. For pitchers with a GB% < 40 (16 who qualified for the ERA title), their average BABiP is .289.
Or if you want to look at it the other way, the top 20 pitchers based on FB% (ERA qualifiers only) had an average BABiP of .286 and the bottom 20 in FB% had an average BABiP of .301.
I chose the tops and bottoms simply because they are the best examples
as you get further down, things simply get muddied by the fact that these are no longer extreme fly ball or groundball pitchers. It’s simply more difficult to tell where the BABIP is coming from. We can choose arbitrary cutoffs until the cows come home, but the most extreme cases show us that there just isn’t the direct correlation you’re implying. In 30 pitchers, .013 simply isn’t that statistically significant when we’re dealing with something where defense has such a major effect.
Also, simply looking at Porcello vs Verlander, since everyone is intimately familiar with the Tigers
Is the reason for the extreme differences not obvious? On a team with a very good infield defense and a fairly bad outfield defense the fly ball pitcher has a lousy BABIP while the groundball pitcher has a good one. Seems pretty straightforward to me. Your theory is a sound one, certainly. But it seems apparently that the quality of the defense where the balls are going has a great deal more to do with their BABIPs then does simply where the balls go.
Defense obviously plays a part in BABiP
but when you take everything into account league-wide, ground balls turn into hits more often than fly balls. That’s all I was getting at. Naturally, the Royals pitchers will give up more hits through the left side of the infield (Yuni factor) than Rockies pitchers (Tulo factor). But I haven’t seen any ground ball home runs yet.
What you say is true, of course
but the trouble with generalizations like that is that every pitcher, no matter who, gives up quite a few ground balls over the course of a season. The sort of pitcher for whom inducing the ground ball is not a skill they possess is going to give up a very, very different ground ball than a so-called “ground ball pitcher.” In general, absolutely, the ground ball will produce a hit more often then the fly ball. That’s a simple matter of physics. It’s easier to make a play with 10 seconds then in a split second. But I still don’t think that says anything about the BABIP of a groundball specialist. They’re simply creating a very different kind of ground ball.

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