We here at Innings Pitched, know that ** understanding sabermetrics can be a difficult task**. Statistics, numbers, volumes of data, and acronyms. Who knows what they all mean or how to calculate them.

Well you are in luck, *because we do.*

The **Sabermetrics Glossary **will be a never-ending series that defines the terms, shows the reader (you), how to calculate the values, and describes how you should analyze each statistical measure.

** Earned Run Average (ERA) **

Henry Chadwick, a statistician and writer, was concerned that the win-loss record did not provide an adequate benchmark to measure the quality of a starting pitching. The earned run average (ERA) was born.

* A slight digression here, but Chadwick invented the ERA out of fear that the win-loss record inadequately portrayed the effectiveness of a starting pitcher. He did so in the late 19th century. So why do many writers, or fans today, still utilize the win-loss record to justify how effective a pitcher is? A little food for thought. *

The statistic was a mainstream staple in the early 20th century when relief pitchers became a more prominent fixture.

The ERA is defined as the mean of earned runs given up by a pitcher per nine innings pitched.

Effectively, an earned run is any run that was charged to the pitcher that did not score as a result of an error by the defense.

So, what makes a decent ERA, does it differ for starters versus relievers?

ERA, while useful, has many limitations. What do you expect from a statistic generated a 100+ years ago?

** Limitations of ERA **

ERA depends on factors that are outside the baseball pitcher’s control such as:

- Poor defense that has limited range or poor fielding percentage
- Bad luck with batting average on ball in play (BABIP)
- Controversial or borderline umpiring (balls and strikes)
- Controversial calls from the scorer (borderline errors, called as hits)

ERA is also very subjective. If one baseball stadium has a left field wall that is 310 feet from home-plate and another has one that is 340 feet from home-plate, how can you compare? A baseball hit 315 feet at the first stadium would be an earned run and would be an out at the second stadium. Apples to oranges.

Luckily, sabermetric aficionados have developed measures to counteract this noise. ERA-, FIP, and xFIP.

**What is ERA-?**

ERA- (pronounced, ERA minus) accounts for the park factor.

The park factor (PF) accommodates the sizes, dimensions, layouts and peculiarities of each park, effectively stripping these variables from the conventional ERA.

ERA- is placed on the following metric scale.

Based on the above image, 100 ERA – is considered league average, 70 ERA- is excellent, and 125 ERA- is awful.

If ERA- accounts for park factors, how do we account for BABIP?

** What is FIP?**

FIP, or fielding independent pitching, removes all defensive metrics from the equation and assumes that the batting average on balls in play (BABIP) mirrors the league average. FIP essentially ensures that only metrics that are within the pitcher’s control, statistically contribute (i.e. strikeouts, balls, homeruns).

BABIP fluctuates year to year. Sometimes balls find gaps that had not in past seasons, think lazy bloopers or balls are hit directly at people due to shifts. These anomalies average out across all pitchers in the league and results in an average of approximately .300 for BABIP (slight fluctuations year-to-year). Bad luck can increase this number or great defense that covers substantial ground can decrease the number. FIP removes this measure, isolating actions that are within a baseball pitcher’s control.

The FIP Constant is a mathematical value that allows the data to be regressed to statistical value that is analyzed on the same theoretical scale as ERA.

Now there is also FIP- (pronounced FIP minus), that removes park factors similar to ERA-. We will not go into detail here, but the ranges are identical to ERA-, and provides the user with a more easily understood scale.

** What is xFIP?**

Expected Fielding Independent Pitching or xFIP is similar to fielding independent pitching (FIP). However, the statistic is regressed, effectively replacing a baseball pitcher’s home run total with an estimate of how many homeruns they should have allowed. This is completed by correlating the homeruns given up by an equivalent league average home run/fly ball percentage.

The reason for this, is that homerun rates are unstable year to year and often subject to environmental conditions outside the pitcher’s control.

Now there is also xFIP- (pronounced expected FIP minus), that removes park factors similar to ERA-. We will not go into detail here, but the ranges are identical to ERA-, and provides the user with a more easily understood scale.

** How to Use ERA, FIP, xFIP **

We, here at Innings Pitched , review earned run average, fielding independent pitching, and expected fielding independent pitcher for all our sabermetric reviews.

We generally start with ERA and take a quick look at ERA-. This way we can see how an individual park affects the stat-line. We then look at FIP and see if the pitcher just had bad luck with BABIP or an atrocious defense. Finally, we look at xFIP to see if the baseball pitcher has given statistically unrealistic amounts of homeruns. Each statistic measure helps paint the picture of effectiveness for each baseball pitcher.

Have questions? Of course you do, because I always do. Sound off in the comments below or reach out to us on Twitter **@InningsPitched**