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FIP/xFIP: Using Sabermetrics for 2023 Fantasy Baseball

Julio Urias - Fantasy Baseball Rankings, MLB Injury News, DFS and Betting Picks

Rick Lucks breaks down how to use FIP and xFIP to identify pitching sleepers and busts as his 2023 series on making sabermetrics more accessible for fantasy baseball managers continues.

While we've only examined how to evaluate hitters using advanced stats thus far, sabermetrics are at least as useful for pitchers. The first advanced pitching stat most fantasy managers encounter is FIP. FIP stands for Fielding Independent Pitching and attempts to measure a pitcher's actual skill instead of the effects of luck or his supporting cast. According to the DIPS theory, pitchers control only Ks, BBs, and home runs allowed. Therefore, Ks, walks, and dingers are the only inputs used to determine the number.

Sometimes xFIP is cited instead of FIP. The "x" stands for expected, and the stat is rooted in the fact that HR/FB varies for pitchers just as much as hitters. While FIP uses a player's actual homers allowed, xFIP charges him with a league-average amount of homers based on his fly balls allowed. Some pitchers are consistently more or less homer-prone than average, but studies show xFIP is a more reliable predictor of future ERA than regular FIP.

For fantasy purposes, it is sufficient to understand the three primary inputs listed above and the fact that both stats are on the ERA scale. That means that if a FIP or xFIP would be a good ERA, it is a strong number. The math is perfect, meaning that the league average FIP, xFIP, and ERA are identical (3.97 last year). Both FIP and xFIP are displayed on the right-hand side of the first table for pitcher pages on FanGraphs, so it is very accessible.

Be sure to check all of our fantasy baseball draft tools and resources:

 

How to Use FIP and xFIP

This predictive nature of FIP and xFIP is the reason fantasy managers should care about them. Both metrics predict future ERA more reliably than ERA itself, making them a good go-to stat to determine if an early breakout may be for real or if a struggling superstar is likely to rebound. All things being equal, it is generally expected that a pitcher's ERA will regress toward his current FIP and xFIP over the long season or across seasons.

For example, Julio Urias of the Dodgers enjoyed a career year in 2022 with a 2.16 ERA. Unfortunately, both his 3.71 FIP and 3.81 xFIP were slightly above-average as opposed to ace material. Instead, his ERA was the result of some combination of luck and his supporting cast, meaning that the fantasy community shouldn't draft him in 2023 expecting a straight repeat of his 2022 success.

Certain types of pitchers may consistently defy FIP. The first is knuckleball guys, who have challenged DIPS theory since its introduction. Sadly, nobody really threw a knuckleball in 2022, nor are any knucklers expected to make a fantasy impact in 2023.

The other type is simply called a "FIP-beater" that manages to control contact against him to the point that he outperforms his peripheral stats.  Kyle Hendricks had an amazing stretch of doing this from 2016-2020. In 2016, his 2.13 ERA was backed by just a 3.20 FIP and 3.59 xFIP. In 2017, his 3.03 ERA was backed by a 3.88 FIP and 3.76 xFIP.  In 2018, a 3.44 ERA was backed by a 3.78 FIP and 3.87 xFIP. 2019 saw a 3.46 ERA with 3.61 FIP and 4.26 xFIP, and the shortened 2020 season saw a 2.88 ERA with a 3.55 FIP and 3.78 xFIP.

Using sabermetrics, you would have expected significant regression in each of these years only to be proven wrong. However, his ERA was consistently trending upward outside of the COVID season. The house of cards came crashing down in 2021 when Hendricks posted a 4.77 ERA against uninspiring FIP (4.89) and xFIP (4.61) marks. Those banking on a return to form were disappointed last season as Hendricks posted a 4.80 ERA backed by a 4.82 FIP and 4.46 xFIP.

These "FIP-beaters" tend to lose it suddenly, with Johnny Cueto and Matt Cain also among the many who turned from fantasy assets to duds overnight. Pitchers like this rarely make good fantasy investments. Strikeouts are a key component of FIP, so pitchers who defy it are often lacking in a common fantasy category. Why risk a poor ERA for a two-category upside? There is an ongoing debate in the sabermetric community though, so this author's word is not gospel on the subject.

 

What Are SIERA and xERA?

SIERA stands for Skill-Interactive ERA and attempts to measure a pitcher's true talent more accurately than FIP and xFIP. It is marginally more accurate than xFIP, but its increased complexity may not be worth it. The stat assumes that ground ball pitchers will have a lower BABIP on grounders than other pitchers, while fly ball pitchers will have lower HR/FB marks. It is also adjusted for the overall run-scoring environment and a pitcher's home park.

That may sound good, but remember that those adjustments won't affect your fantasy team's bottom line. German Marquez posted a bad 4.95 ERA for the Rockies last year, but his SIERA was only 4.27 in part to correct for Coors Field. Obviously, pitching at Coors will not improve your ERA, so you can't count on Marquez regressing to his SIERA given his home park. SIERA is also not on the ERA scale, with a league average of 3.88 to the 3.97 of the other metrics last season.

A Statcast metric called xERA (Expected ERA) does what SIERA tries to do but better, incorporating Statcast contact quality metrics such as average launch angle instead of SIERA's broad assumptions. It's also on the ERA scale. Marquez had a 4.49 xERA last season, suggesting that he deserved something better than his actual ERA while still acknowledging the realities of pitching at Coors.

 

Conclusion

To conclude, FIP and xFIP are metrics that try to determine the ERA a given pitcher deserves based only on the outcomes he actually controls: Ks, BBs, and home runs allowed. While FIP uses the pitcher's actual homers allowed, xFIP regresses it to the league average figure. Both metrics are on the ERA scale and may be used to predict future ERA with more accuracy than ERA alone. Meanwhile, xERA is a useful metric for the Statcast-inclined.



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