The Short and Simple SIERA Primer

We’ve had our five part series introducing everyone to FanGraphs’ newest stat, SIERA. Now, how about we simplify things and explain SIERA in 500 words?

The following is taken from the new FanGraphs Library page on SIERA, so it will always be available here whenever needed.


Skill-Interactive ERA (SIERA) is the newest in a long line of ERA-estimators. Like its predecessors FIP and xFIP, SIERA attempts to answer the question: what is the underlying skill level of this pitcher? Is this pitcher likely to be successful going forward or not? Based on their past results, how should we expect them to perform in the future?

But while FIP and xFIP largely ignore balls in play — they focus on strikeouts, walks, and homeruns instead — SIERA adds in complexity in an attempt to more accurately model what makes a pitcher successful. SIERA doesn’t ignore balls in play, but attempts to explain why certain pitchers are more successful at limiting hits and preventing runs. This is the strength of SIERA; while it is only slightly more predictive than xFIP, SIERA tells us more about the how and why of pitching.

Here’s what SIERA tells us:

Strikeouts are good…even better than FIP suggests. High strikeout pitchers generate weaker contact, which means they allow fewer hits (AKA have lower BABIPs) and have lower homerun rates. The same can be said of relievers, as they enter the game for a short period of time and pitch with more intensity.

Also, high strikeout pitchers can increase their groundball rate in double play situations. Situational pitching is a skill for pitchers with dominant stuff.

Walks are bad…but not that bad if you don’t allow many of them. Walks don’t hurt low-walk pitcher nearly as much as they hurt other pitchers, since low-walk pitchers can limit further baserunners. Similarly, if a pitcher allows a large amount of baserunners, they are more likely to allow a high percentage of those baserunners to score.

Balls in play are complicated. In general, groundballs go for hits more often than flyballs (although they don’t result in extra base hits as often). But the higher a pitcher’s groundball rate, the easier it is for their defense to turn those ground balls into outs. In other words, a pitcher with a 55% groundball rate will have a lower BABIP on grounders than a pitcher with a 45% groundball rate. And if a pitcher walks a large number of batters and also has a high groundball rate, their double-play rate will be higher as well.

As for flyballs, pitchers with a high flyball rate will have a lower Homerun Per Flyball rate than other pitchers.


If I had to explain SIERA concisely to a friend, it’d probably sound a little something like this:

If you want to know how well a pitcher is likely to perform in the future, SIERA is the stat for you. At the moment, it’s the most accurate stat for predicting a pitcher’s future ERA, and it’s also the best at modeling the complexity of pitching.

But for all its complexity, the theory behind SIERA is intuitive and easy to understand. For example, SIERA assumes that strikeouts are good, walks are bad, high strikeout pitchers induce weaker contact, wild pitchers allow more baserunners to score, and extreme groundball pitchers are better at generating easy-to-field groundballs.

SIERA is a fun new tool, and I can’t wait to see it in action. Have at it, world!

For even more information on SIERA, see its FanGraphs Library page.

We hoped you liked reading The Short and Simple SIERA Primer by Steve Slowinski!

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Steve is the editor-in-chief of DRaysBay and the keeper of the FanGraphs Library. You can follow him on Twitter at @steveslow.

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Nice summary. But to be picky, SIERA doesn’t “assume” any of those things you mentioned in your last paragraph; those are CONCLUSIONS from regression results.

Unfortunately, the initial reaction from the “traditional” saber community has been, not surprisingly, fairly negative — statistical regressions appear to be too complicated for them, so their natural reaction is to simply label it as math gobbledy-gook. Too bad for them.

And by the way, why doesn’t the Pitching Leaders Dashboard tab include SIERA so we can compare it directly against FIP, xFIP and ERA? Instead, you’ve stuck it on the Advanced tab and it’s a PITA to flip back and forth to see how a given pitcher compares between SIERA and the others.

Otherwise, great work!

Mr. Cthulu
Mr. Cthulu

“Unfortunately, the initial reaction from the “traditional” saber community has been, not surprisingly, fairly negative — statistical regressions appear to be too complicated for them, so their natural reaction is to simply label it as math gobbledy-gook. Too bad for them.”

Well, that was an easy way to address all the legitimate questions and concerns raised by other Saber authors. It’s so much easier to just tear down a straw man.