Pittsburgh Pirates: Sabermetric Sunday xFIP

There are few, if any, teams in the Major Leagues as sabermetric savvy as the Pittsburgh Pirates. So, here at Rum Bunter we are going to education the masses with sabermetric Sundays.

Last week, I began my sabermetric Sunday series here at Rum Bunter. I started with taking a look at FIP, and why I believe it is the best stat to evaluate pitchers on. This Sunday, we will take a look at what I believe is the second best stat to evaluate pitchers on.

What stat is that you ask? Well, that is xFIP of course. Why is this a good stat to evaluate pitchers on? Why do teams such as the Pittsburgh Pirates use it? Well, read on to find out more!

Expected fielding independent pitching, or xFIP, is a stat that judges a pitcher’s expected run prevention independent of the performance of their defense. xFIP is based on at bats that end in results that do not involve the defense. Strike outs, walks, hit by pitches, and fly balls all go into determining a pitcher’s xFIP.

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The biggest difference between FIP and xFIP is that xFIP eliminates the amount of home runs allowed. This is because home run rate usually fluctuates over time, and the amount of home runs allowed by a pitcher could depend largely on the ballpark they are pitching in. This is something the Pittsburgh Pirates have seen this year with left-handed starter Jon Niese.

Through his first 64 innings pitched as a Pittsburgh Pirate Jon Niese has allowed 12 home runs. However, seven of them came in hitter friendly ballparks in Colorado, Arizona, and Cincinnati. As a result, Niese’s xFIP (4.27) is better than his ERA (4.36) this season.

How is xFIP calculated? Here’s how: (13*(fly balls*league average home run rate/fly ball percentage)+(3*(BB+HBP))-(2*K)/innings pitched+the constant (3.10). Got all of that? If not, checkout FanGraphs’ sabermetric library where they have nice diagrams and such.

The reason league average home run rate is used instead of the amount of home runs the pitcher has allowed is to eliminate the randomness that is involved with pitching in the Major Leagues. This ties in with Jon Niese having allowed seven of his 12 home runs in three hitter friendly ballparks. Think about, there are a lot of fly balls that Pittsburgh Pirates pitchers allow at PNC Park that are routine outs that end up eight rows deep at Great American Smallpark, I mean Ballpark, in Cincinnati.

So why use xFIP? Because, like FIP, xFIP is a better indication of how a pitcher has pitched and is a better indication of future performance than ERA is. FIP removes defense, luck, and sequencing from a pitcher’s results. xFIP takes it a step further and also removes the randomness, such as ballpark affect, that pitcher’s encounter. This is why Major League teams that are sabermetric savvy, aka smart, such as the Pittsburgh Pirates put a lot of stock into xFIP.

xFIP is a good indicator of a pitcher that is due for regression, either positive or negative, to the norm. Once again we’ll use Jon Niese as our example. Niese has pitched extremely well his past five starts, but even before that when his ERA was well over five his xFIP remained in the mid-fours.

This was a sign that Niese was due for some positive regression and that he was pitching better than his ERA. It also showed that Niese’s biggest problem was that he was giving up too many home runs, and now that he is pitching in ballparks where the ball does not fly out as if it was shot out of a cannon his home run rate has dropped to normal and his ERA has dropped as well.

Personally, I still prefer FIP over xFIP when evaluating a pitcher’s performance to date. However, in my opinion, xFIP is a better indicator of future performance because it eliminates the randomness of which ballparks a pitcher has pitched in.

That will do it for this week’s sabermetric’s lesson. I hope everyone learned something new about xFIP today, and that everyone now better understands xFIP and how to use it. If you have any questions, post them in the comments section below.