One of the best predictors of Earned Run Average (ERA), Expected Fielding Independent Pitching (xFIP) uses a pitcher's Fielding Independent Pitching (FIP) and Home Run to Fly Ball (HR/FB) rate to provide an estimate of what the pitcher's ERA should have been with neutral defense, luck, and opponent quality.
Many people, including myself, believe that the quality of a pitcher can essentially be derived from a few basic statistics, specifically Strikeouts per Nine Innings (K/9), Walks per Nine Innings (BB/9), Hit by Pitches per Nine Innings (HPB/9), and Home Runs per Nine Innings (HR/9). The rest is up to the defense. Because these statistics are the only things a pitcher can control, it is unfair to penalize a pitcher for having a poor defense behind him, which is exactly what many more common pitching statistics like ERA do.
Does a pitcher really control all of those aforementioned statistics? At first glance, you may think so, but consider that home runs are still batted balls. The best power hitters in the league are the hitters that are able to hit lots of home runs without sacrificing their batting average by constantly flying out. As a result, the best power hitters almost always sport high HR/FB rates. The worst hitters, therefore, have low HR/FB rates.
This is the major reason why a pitcher's HR/FB rate is almost entirely random, and the variation of the statistic prevents pitchers from maintaining a steady rate from season to season. In order to compensate for this statistical noise, xFIP was created, normalizing a pitcher's HR/FB rate to the league average. This adjustment has made xFIP the best predictor of future ERA among the statistics available to the public, even surpassing actual projection systems like Steamer, ZIPS, and PECOTA.
Unfortunately, almost all minor league batted ball data is unavailable to the public, making it impossible to quantify HR/FB rate for minor league pitchers. Indeed, the only statistic available is Ground Out to Air Out (GO/AO) ratio. This has made it difficult to distinguish true minor league pitching talent from fluke seasons caused by irregular HR/FB rates.
For major league players, these two categories are easily distinguishable. For example, in 2012, Oakland A's pitcher Jarrod Parker had a 3.47 ERA and a 3.43 FIP, on the basis of a 6.8% HR/FB rate and 0.55 HR/9. The low HR/FB rate was clearly unsustainable, and as expected in 2013 his HR/FB rate jumped to a more reasonable 10.5%, right around major league average. As a result, his HR/9 hiked to a staggering 1.14 home runs per nine innings, causing his ERA and FIP to elevate to unimpressive values of 3.97 and 4.40, respectively.
If Jarrod Parker happened to be a minor league pitcher, we would have been unaware of his unsustainable HR/FB rate, and would have falsely characterized him as a talented pitcher capable of a 3.43 ERA (based on his FIP). In reality, with xFIP and HR/FB rates available for major league pitchers, any person familiar with saber-metrics could have told you following the 2012 season that Parker's 2012 was a fluke, and that he is more of a 3.97 ERA pitcher than a 3.43 ERA pitcher just by looking at his xFIP.
A little more than half a run in ERA may seen insignificant, but Parker was worth 2.2 WAR more in 2012 than in 2013 despite similar peripherals. That is the difference between an All-Star and a borderline major league pitcher.
Clearly, a statistic similar to xFIP is necessary in order to determine the true talent levels of minor league pitchers. With GO/AO being the only available batted ball statistic available for minor league pitchers, this seems like a difficult task.
It is common knowledge, however, that pitchers who induce more ground balls also allow fewer home runs. What is not clear is whether the relationship between GO/AO ratio and HR/9 is significant enough to form a new ERA predictor for minor league pitchers.
In Part 2, we will find out whether or not this statistic, MiLB xFIP, is indeed possible. Is there really a correlation between GO/AO ratio and HR/9?