I’ve long been a critic of the save statistic, and I don’t need to rehash why it’s the scourge of the baseball world, but relief pitching is still an important part of the game and we often struggle to properly measure it. Won/Loss record and saves tell you nothing about a player’s individual skill, especially not relievers, and even things like ERA don’t do a lot of good because relievers aren’t charged for runners they let in belonging to another pitcher and can get charged with runs allowed by the pitchers who come after.
Strikeouts, walks, and homeruns allowed (the basis of FIP) are good measurements, but FIP inherently strips away context. And context does matter for relief pitchers. It’s an elite reliever’s job to come in and strand runners, so strikeouts are good and homeruns are bad, but sequencing is really important and it matters a lot when they get outs and when they allow baserunners.
In a sense, FIP and similar statistics are good, but they aren’t perfect because they’re context neutral and we might want some context in reliever stats. Win Probability Added (WPA) is a typical way to fix this, but this feels too context dependent for me. WAR is always a nice combination of these kinds of measures, but WAR is a counting stat so how much a reliever is used matters a lot, and relievers are often used incorrectly.
My point here is not that I can come up with something better, but rather that I want to try to add something. I always look at reliever stats and find logical holes more often than with position players and starters. I want a reliever stat that measures context, considers the peripheral numbers, and also understands the luck involved. I didn’t find one out there that satisfied me, so I went to work inventing one.
I’ll say this. This isn’t perfect and I want to improve it. Flaws you may find in the method should not cause you to discount it, but rather to add to the discussion. This is a first crack. I hope you find it useful.
So first, I started with a question: What is the job of a relief pitcher? Here was my answer:
- Strand runners
- Don’t allow baserunners
- If you allow baserunners, don’t let them score.
With that outlined, I went to work thinking about how to measure each and came up with the following statistic that I will call SOEFA, pronounced like “sofa.” It stands for Strand On-base ERA FIP Average and should be thought of as a way to measure relievers from your sofa. Yes, I have a whimsical side.
It has four components, let’s walk through them.
First is Strand Rate+, which I calculated as what percent better or worse a reliever is from league average at stranding runners. League average is 70%, so if you strand 100% of your inherited runners, your Strand Rate+ is .43 because you are 43% better than league average.
Second, is your Expected OBP+ or xOBP+ which is your opponents on base percentage calculated as a percentage deviation from league average just like SR+, except that I regress your hits allowed based on league average BABIP because sometimes batters get lucky hits.
Third, is my version or ERA+, which is just like normal ERA- except I scale mine to zero instead of 100 like the major stat sites and invert it. Same principles regarding deviation from average applies. FIP+ is exactly the same, except I use FIP-. These numbers are park adjusted.
To combine them, I add SR+ to xOBP+ and then add ERA+ to get eSOEFA. I then repeat the same process and replace ERA+ with FIP+ to get fSOEFA. A pitcher’s SOEFA score is the average between the two.
The output gives you a number that sets league average at zero and ranges technically from negative infinity to about 2.5, but generally speaking you won’t see a reliever fall below -2.5. Basically it’s a -3 to 3 scale that puts good relievers on the plus side and bad ones on the negative side.
Additionally, at my discretion, relievers who have inherited fewer than five baserunners during the season (this number will likely be fluid based on where we are in the season) are given a league average SR+ so that if you don’t ever inherit runners you aren’t unfairly punished because you are not given sufficient opportunity to strand them or you are not given credit for an awesome strand rate if you strand the only runner you inherit.
I’m pretty happy with the first round of results. The first run of results came from stats entering June 25th and it generally lines up with my impression of the best performing relief pitchers in baseball. I have no idea if this stat is predictive or how long it takes to stabilize. Right now, it correlates with ERA and FIP at -.73 and -.75 despite the fact that each is only 1/6 of the input and the R squared is around .6 using it to predict FIP, if those kinds of things interest you.
It’s experimental. It’s meant to be fun and maybe helpful.
A word of note is that Fangraphs and B-R seem to use different cutoffs for which relievers “qualify,” so this output may be missing a few relievers. I’m sorry about that. The great thing about this statistic is that I can easily produce the number for any reliever in baseball in less than two minutes. If you want to know how a reliever measures up or how a reliever did during a given season, just ask and I can provide the number based on a handy program I wrote. Hit me on Twitter @NeilWeinberg44 and I’d be happy to provide the SOEFA for any reliever.
Thanks for reading and I welcome any feedback. Who knows, maybe this will work.
Below are the SOEFA for the vast majority of qualifying relievers up through 6/24/13. If you want to know the SOEFA of a reliever not on this list or would like an update score, please let me know.
|3||Junichi Tazawa||Red Sox||0.92|
|10||Jesse Crain||White Sox||0.83|
|12||Brett Cecil||Blue Jays||0.79|
|18||Koji Uehara||Red Sox||0.7|
|21||Casey Janssen||Blue Jays||0.64|
|38||Addison Reed||White Sox||0.46|
|48||Andrew Miller||Red Sox||0.4|
|65||Nate Jones||White Sox||0.26|
|72||Matt Thornton||White Sox||0.19|
|73||Steve Delabar||Blue Jays||0.18|
|82||Matt Lindstrom||White Sox||0.14|
|99||Aaron Loup||Blue Jays||0.03|
|103||Dane de la Rosa||Angels||-0.02|
|130||Clayton Mortensen||Red Sox||-0.4|
|133||Esmil Rogers||Blue Jays||-0.5|