clock menu more-arrow no yes

Filed under:

Searching the Diamonds of SIERA Leone

New, comments

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.