# Staturday: The FIPs

So far this offseason, we have covered the basics and offensive stats. If you missed any or want to take a look at them again, you can find them all __here.__ Today we jump onto the mound and break down the different pitching stats starting with FIP and xFIP.

FIP stands for Fielding Independent Pitching, and looks at results only a pitcher can control. What can a pitcher control? Strikeouts, walks, homers, and hit-by-pitches. If a pitcher gives up a ground ball does that ball go right to the shortstop or does it find a hole? FIP does not care. The formula for FIP is:

And here is the equation for FIP Constant:

Hopefully all of these different equations are starting to look familiar because they share many of the same properties. We see that different variables are weighted differently (homers are worse than walks because they always score runs), and many times they take into account some sort of league average.

The FIP constant is a value added at the end to put FIP on the same scale as ERA. The lower the FIP score, the better the pitcher just like ERA.

xFIP stands for Expected Fielding Independent Pitching and it is calculated exactly like FIP except for the home run element. Let's look at the equation for xFIP.

We see here that instead of home runs given up, xFIP looks at the number of fly balls a pitcher gave up and multiplies it with the league average for home runs to fly balls given up. The reason for this is that sometimes a pitcher has a bad year, or a great year. xFIP tries to remove the flukiness of the season.

Let's take a look at some Cubs pitchers to see how these numbers are used and for context, league average HR/FB was 15.3%.

Four of the Cubs starters from last year are returning, and three of them had below league average HR/FB ratios. Comparing the ERAs to the FIP, we see that Quintana was almost a full run better in FIP than his ERA suggesting he was unlucky either with the Cubs defense, balls finding holes, or just the sequence of events. Looking at his xFIP he still should have had an ERA almost half a run better than the 4.80 he posted.

One more interesting guy to look at is Yu. He had a HR/FB ratio almost 8% higher than league average. xFIP is saying that if we took the league average number, his ERA would have been closer to 3.40 than the almost 4.00 he had. But we cannot just solely rely on xFIP to point to Yu being that kind of pitcher next season. Looking at his career average for HR/FB, we find that it is 13.9% which is a little bit better than league average for this past season. That almost falls in line with the league average over the same number of seasons (2012-2019). With that knowledge and the results of xFIP, I think it is fair to say that Yu should finish the 2020 season closer to the 3.40 ERA instead of the 4.00 ERA we saw in 2019.

Next week we will look at ERA- and SIERA.