If you want to measure how many runs a pitcher has given up, ERA is your statistic.

If you want to measure how well a pitcher has actually pitched then FIP, xFIP or SIERA may be better.

And understanding the difference between those ideas is what this post is about.

The most commonly used measure for how a pitcher has performed is Wins and Losses. But those statistics really don’t directly measure how the pitcher pitched, rather they measure how well the team played overall — including defense and hitting — on the day that pitcher pitched.

If you wanted to isolate the role of the pitcher, look at the Total Runs a pitcher gave up. Yet Total Runs is still substantially dependent on fielding performance. It’s widely accepted that pitchers shouldn’t be accountable for runs scoring due to the fielding errors of their teammates.

A further refinement in isolating the pitcher’s contribution is to rely on the official scorer to determine errors and then judge runs as “earned” or “unearned.” Assigning only earned runs to a pitcher is the basis of the statistic we know as Earned Run Average (ERA). We typically cite ERA and not Total Runs because we want to limit the credit/blame of the pitcher to only what he controls.

While ERA is an improvement over Total Runs, it still depends on many things out of the pitcher’s control and is a relatively crude measure of how well the pitcher has actually pitched. Fielding isn’t just about errors, it’s about range and arm strength. So ERA depends on the quality of your fielders (and the whims of the official scorer).

ERA also depends on the competency of the bullpen, as many “earned” runs allowed are actually inherited runners scored off of relief pitchers. For example, Mike Leake was charged with two earned runs when Logan Ondrusek allowed inherited runners to score against the Cardinals. If Sam LeCure comes in instead of Ondrusek, that might significantly affect Leake’s ERA. There’s a wide variability for bullpen performance between teams and even from night to night on the same team.

ERA also depends on how lucky or unlucky a pitcher is on balls batted into play. Research has shown that pitchers have little control over what happens to a ball that is put in play.

Finally, ERA depends on the luck of random sequencing. Suppose Pitcher A gives up a single, walk and home run, in that order. He’d have given up three earned runs. Suppose Pitcher B gave up a home run, single then walk. That sequencing would have produced only one earned run. Did Pitcher A perform three times worse than Pitcher B? Because that’s what his ERA would indicate.

ERA measures the actual “earned” runs a pitcher is assigned, but it depends on many variables that a pitcher can’t control. Fortunately, lots of smart people have come up with more refined and accurate measures that further isolate how a pitcher has actually performed.

One of which is FIP.

FIP stands for Fielding Independent Pitching. FIP is calculated by counting the number of home runs, strikeouts, walks and hit batters the pitcher actually allows and plugs those numbers into a formula.Ã‚Â A constant term (3.2) is added so the resulting number is scaled to ERA for the sake of familiarity and comparability.

The argument for FIP over ERA is that it better isolates what the pitcher controls — not his shortstop’s range, not the official scorer’s ruling, not the relief pitcher’s ability to throw strikes, not whether bloops fall in for hits etc.

Studies have shown that FIP is a better predictor of a pitcher’s future ERA than the pitcher’s current or past ERAs. That’s an important sentence to process. If you want to measure how many runs the pitcher has *already* given up, use ERA. If you want to predict how many runs a pitcher will give up *in the future*, FIP is better.

FIP is just one of the alternatives to ERA.

xFIP (Expected FIP) uses the concept of FIP as a starting point, but normalizes home runs across luck and stadiums. FIP uses a hard count of how many home runs a pitcher actually gives up. xFIP estimates how many a pitcher *should* give up assuming normal luck. It’s based on the notion that a pitcher only controls how many fly balls he surrenders, and that home runs are a fairly constant percentage of all fly balls (HR/FB) over time. [On the other hand, some pitchers, like Mike Leake, have seemed to be more prone to home runs, even when taking into account how many fly balls they give up.] xFIP has been proven to be a better ERA predictor than FIP.

SIERA (skill-interactive ERA) adds more nuance yet to FIP. It accounts for the fact that all balls in play are not the same. For example, ground balls are turned into outs at a higher rate than line drives but at a lower rate than fly balls. It also turns out that pitchers with more strikeouts generally have lower HR/FB, so it’s a refinement on xFIP. Pitchers with more strikeouts also tend to have lower BABIP and more double plays per ground ball. SIERA has been proven to be a better predictor of ERA than either FIP or xFIP.

Of course, you should never look at just one measure of how a pitcher performs. FIP, xFIP and SIERA are just a few of the most common sabermetric attempts to further refine measurement of pitcher performance. If you want to know how a *team* did, look at Wins, Runs and ERA. If you want to look at how the *pitcher*, in isolation, performed and will perform, look at FIP, xFIP and SIERA.

Here are the up-to-date 2013 numbers for the Reds’ starting rotation:

[table id=34 /]