Ask a sabermetrician what his or her favorite statistics are that measure the quality of a pitcher and xFIP is bound to be a frequent answer. So what is xFIP and why do statisticians prefer it over a more widely accepted statistic like ERA?
xFIP, or expected fielding independent pitching, estimates a pitcher's performance based solely on events within his control - strikeouts, walks, hit-by-pitches, and flyballs allowed. FIP, or fielding independent pitching, attempts to do a similar calculation, but xFIP goes a step further by lowering a pitcher's HR/FB rate to the league average due to the general year-to-year volatility in the HR/FB metric. The scale of xFIP is similar to ERA, so many people (mistakenly) use the two interchangeably and often completely replace ERA with xFIP as a way to better understand a pitcher's performance without other factors like defense, luck, or sequencing.
The problem with relying on xFIP as the sole measurement of a pitcher's performance is similar to the flaws in using BABIP as the sole measurement of a hitter. Despite the high variability in pitcher's HR/FB rates each year, most pitchers still have a certain level of control over that metric. That means that immediately setting HR/FB rate back to league average can and will understate or overstate a pitcher's skills, depending on the pitcher's level of control over his home run rates.
As a result, there are several statistics that are useful to see alongside ERA vs xFIP to better understand how "earned" his HR/FB rate actually was. These stats include Brls/PA%, park factors and Hard%, while looking at statistics like BABIP and LOB% in conjunction with the others also helps better paint a picture of how "earned" a pitcher's ERA actually was.
Unfortunately, 2020 is a truly awful season to solely use to measure pitching performances because of the small sample size. As a result, the data below is from June 13, 2019 through the end of 2020 season. Why this strange date range? Primarily because it's the largest range available where any starting pitcher started 32 games - in fact, it included three pitchers who started 32 games.
Below is a dashboard sorted by the pitchers with the largest disparities between his ERA and xFIP. Catch Lou Blasi and myself this Sunday on SiriusXM Fantasy Sports Radio as we breakdown these pitchers in more detail!