What is xFIP?

So far on our journey of learning about advanced pitching metrics, we have learned about the flaws of Earned Run Average, and why Fielding Independent Pitching might be a more useful tool for predicting future performance. 

Now, it’s time to take it a step further by diving into Expected Fielding Independent Pitching, otherwise known as xFIP.

xFIP Explained

We know that Fielding Independent Pitching is a measurement of a pitcher’s ability to influence the three true outcomes – home runs, strikeouts, and walks. FIP takes out the random nature of balls put in play and leaves us with a more accurate indicator of how many runs a pitcher should have given up.

But – there is still one problem. In the same way that pitchers of varying skill levels have limited control over whether balls in play land for hits or outs, they similarly have limited control over whether fly balls become home runs.

This is the main methodology behind xFIP—another member of the Defense Independent Pitching Statistics category. While xFIP still accounts for the same three true outcomes, it normalizes a pitcher’s home run per fly ball percentage, which is written as HR/FB%.

HR per FB% for individual pitchers tends to regress to the league average over time. League home run to fly ball rates show more predictable trend lines, usually between 10% on the low end to 15% on the high-end year over year, but as far as individual pitchers are concerned this number can vary greatly.

By using the league average HR per FB% in its calculation, it makes sense to remove the variability and further isolate the skills that pitchers have the most control over—their ability to get strikeouts and limit walks.

 xFIP is calculated using the following equation:

xFIP = ((13 * (Fly balls * lg avg HR / FB%)) + (3 * (BB+HBP)) – (2*K)) / IP + constant

Summary

xFIP differs from FIP by using league average HR per FB% to remove the variability that might throw off our analysis of a pitcher’s performance in a given year. Using this metric, we focus on elements that a pitcher can control to better analyze their skillset. It’s important to understand the reasoning behind how and why we use each of these advanced metrics so we can use them in conjunction with one another.