ERA- / FIP- / xFIP-

ERA Minus, FIP Minus, and xFIP Minus are the pitching version of OPS+ and wRC+ and are a simple way to tell how well a player performed in relation to league average. All of these statistics have a similar scale, where 100 is league average and each point above or below 100 represents a percent above or below league average. However, as lower is better for (almost) all pitching stats, a lower ERA- or FIP- is better.

To learn about ERA, FIP, or xFIP specifically, please visit their respective Library pages. ERA-, FIP-, and xFIP- are the park and league adjusted versions of each of those statistics. In other words, a pitcher with an 80 ERA- had a park adjusted ERA that was 20 percentage points better than their league’s (AL or NL) ERA for that season.

Calculation:

Calculating ERA-, FIP-, or xFIP- is very easy as long as you have three pieces of information: your player’s ERA, FIP, or xFIP, their team’s park factor, and the league average (AL or NL) ERA, FIP, or xFIP for that time period. Once you have those, the formula looks like this, shown with ERA. The calculations are identical for FIP and xFIP.

ERA Minus = 100*((ERA + (ERA – ERA*(PF/100)) )/ AL or NL ERA)

In 2014, Clayton Kershaw had a 1.77 ERA, a home park factor of 96, and the NL ERA was 3.66. So we do the following calculation:

50 = 100*(1.77 + (1.77 – 1.77*(96/100)))/ 3.66

Please note that our listed park factors are rounded so there may be a few occasions in which your calculation is off by one point as a result. Otherwise, you simply take the player’s ERA, adjust it for their home park, divide by league average, and multiply by 100 (just for presentation) to return the ERA-.

Why ERA-/FIP-/xFIP-:

Using a park and league adjusted version of your favorite pitching statistic is very useful for two reasons. First, park adjustments are important because the 30 MLB parks are different enough that you would expect run scoring to vary based only on the dimensions, altitude, and weather even if the players made the same pitches and same swings. The results aren’t dramatic outside of Coors Field, but shifting the baseline by 5 or 10 percent is meaningful when comparing players. Simply put, it’s more difficult to prevent runs in Yankee Stadium than it is at Tropicana Field so we should adjust a player’s numbers accordingly. A 3.00 ERA at Yankee Stadium is more impressive than one at the Trop and ERA- allows us to quantify that difference.

Second, adjusting for league average is important for two reasons. You certainly want to make some sort of correction for the fact run scoring is higher in the AL than the NL, but you also want to scale ERA to league average so that you can compare players during different eras. By dividing by the league specific ERA, you are able to do both. As a result, a 95 ERA- in 2014 and a 95 ERA- in 2000 both communicate that the pitcher was 5 percent better than league average during that season, even though league average ERA was very different between those two seasons.

For example, a 4.00 ERA in 2000 was pretty good but a 4.00 ERA in 2014 would be below average. ERA- allows you to compare those two seasons because without it, you might be left to assume they were roughly equivalent when they were not.

How to Use ERA-/FIP-/xFIP-:

Using ERA-/FIP-/xFIP- is a snap. Since you already know how to use each one of those statistics on their own, the only thing you need to know about using the “minus” stats is that league average for that year and league is always set to 100 and that every point below 100 means the pitcher is that many percentage points better than league average in that particular stat, after accounting for the player’s home park.

For example, an 87 ERA- is 13 percentage points better than the league average ERA for that year and league once you account for the park. A 110 ERA- is 10 percentage points worse than the league average ERA for that year and league once you account for the park.

Essentially, the only reason to use regular ERA instead of ERA- is for ease of communication or if you actually want to observe the differences created by the run environments. Many people understand what a 3.50 ERA means, but telling someone a player has a 96 ERA- may be a bit more confusing. If you have a good internal sense of league average for that season and how the parks affect run scoring, using ERA in conversation will do the trick. But if you want to make detailed comparisons across players (i.e. Player X is better than Player Y because his ERA is better), you want to make sure you’re using the park and league adjustments.

Context:

League average for ERA-, FIP-, and xFIP- is always set to 100 for each league, but the specific distribution will bounce around from season to season. The following, however, is a good rule of thumb based on starting pitchers. Relievers will have lower values on average just like when dealing with ERA or FIP.

Rating	ERA-/FIP-/xFIP-
Excellent	70
Great	80
Above Average	90
Average	100
Below Average	110
Poor	115
Awful	125

Things to Remember:

● ERA-, FIP-, and xFIP- are park and league adjusted. They control for home park and your specific league’s average ERA, FIP, or xFIP.

● League average is always set to 100.

● Every point above or below 100 is a one percentage point deviation from average during that year.

● Park Factors are estimates, which means that they will not always influence every pitcher the same way. Also, particular pitchers might be more or less influenced by their home park than average, so there is some inherent uncertainty in ERA- because the park factors are imperfect. For example, a 3.00 ERA in the NL in 2014 is an 86 ERA- with a 95 park factor, an 84 ERA- with a 98 park factor, and an 80 ERA- with a 102 park factor. If a park factor is dramatically wrong, the influence is still only within five or so percent.

Links for Further Reading:

The Minus Stats – FanGraphs

ERA-, FIP-, xFIP- – FanGraphs

Esoteric Ramblings about + – Walk Like A Sabermetrician