Targeting Starting Pitchers Based on xFIP/FIP Differentials

Eno Sarris said not to look at HR rate. He said it and I’m going to listen. However, FIP and xFIP are not HR rates, and I’m going to look at that. Too often we assume that others know, or we actually know, what a statistic represents. We hear it, we think it, we know it. But, take a moment with me to reinvigorate our understanding of these two very important statistics.

FIP gives us an idea of how a pitcher performs regardless of who is playing defense behind him. It accounts for strikeouts, walks, hit by pitches, and home runs allowed. FIP gives us a better understanding of how a pitcher is performing than ERA. xFIP tells us all the same but accounts for the volatility of the HR rate. Quoting from our very own FanGraphs glossary, xFIP is:

calculated in the same way as FIP, except it replaces a pitcher’s home run total with an estimate of how many home runs they should have allowed given the number of fly balls they surrendered while assuming a league average home run to fly ball percentage (between 9 and 10% depending on the year).

If we take the difference between the two (xFIP-FIP) we will be able to see who is underperforming or overperforming. We can see who has fallen prey to the HR rate bad luck that Sarris told us not to look at, and who has been straddling the line between a warning track fly ball and an official dinger. Here are the top 10, most negative xFIP/FIP differentials among all qualified starting pitchers this season:

 

Starters with Negative xFIP/FIP Differentials
Name K/9 BB/9 HR/FB FIP xFIP Diff
David Peterson 10.73 2.96 35.7% 4.51 2.85 -1.66
Kenta Maeda 8.79 2.20 25.9% 5.27 3.76 -1.51
Mike Foltynewicz 8.37 2.16 21.4% 5.57 4.28 -1.29
Luis Castillo 7.28 2.43 23.8% 4.69 3.75 -0.94
Lucas Giolito 12.03 3.82 21.4% 4.25 3.32 -0.93
Bruce Zimmermann 6.60 3.00 19.4% 5.88 4.96 -0.92
Antonio Senzatela 5.46 2.73 20.8% 5.20 4.44 -0.76
Yusei Kikuchi 7.92 3.23 20.8% 4.64 3.90 -0.74
Adam Wainwright 9.70 2.36 18.8% 4.27 3.65 -0.62
Adrian Houser 6.16 3.23 21.1% 4.51 3.91 -0.60
*Among qualified starters.

 

What we have here, in a nutshell, are pitchers who have given up home runs and the announcer said, “In any other park that would have been an out.” So, perhaps these pitchers are frustrating current owners and could be trade targets. But certainly, a few of them are on the wire, just waiting for a claim. Here are a few to note:

  1. #Don’tDropMaeda. His high HR/FB rate has juiced the FIP as he’s been serving up meatballs with freshly grated parmesan. Both his changeup (17.6%) and his slider (32.7%) have a CSW below where he’s finished each season in his career, but Monday night’s showing was very promising that he is, at least, on the track to get it dialed in. 
  2. Bruce Zimmerman (excuse me a second while I start an Ottoneu bid auction) is an arm to keep an eye on along with Antonio Senzatela as interesting options to start when on the road. Though it’s a low sample size, Zimmerman’s HR splits are already favoring the road. 
  3. Don’t sleep on David Peterson. His CSW is up from 27.7% in 2020 to 30.8% in 2021 and he is rostered at only 8.8% in ESPN leagues. 

There are two sides to every coin and this side shows us who is getting lucky. The announcers say, “Well, he got lucky there as that ball just barely missed making it out on a windy night here in…” It may be time to sell high or to at least curb your expectations on these qualified pitchers with high differentials:

 

Starters with Positive xFIP/FIP Differentials
Name K/9 BB/9 HR/FB FIP xFIP Diff
Matthew Boyd 6.06 1.77 2.1% 2.97 4.98 2.01
Kyle Gibson 7.29 2.97 0.0% 2.57 3.95 1.38
Nathan Eovaldi 8.31 1.82 0.0% 2.13 3.50 1.37
Gerrit Cole 14.81 0.72 2.9% 0.48 1.78 1.30
Ryan Yarbrough 7.02 1.62 5.4% 3.14 4.32 1.18
Carlos Martinez 4.95 2.23 5.1% 3.80 4.98 1.18
Danny Duffy 10.20 2.70 6.1% 2.61 3.69 1.08
José Urquidy 7.15 2.12 8.0% 3.84 4.91 1.07
Matt Harvey 6.39 2.61 6.1% 3.50 4.54 1.04
Taijuan Walker 9.00 5.00 4.5% 3.37 4.33 0.96
*Among qualified starters.
  1. I will admit to riding the Boyd train and toot, toot, tooting all the way into the station. Every night I see the check next to his name is a night I’m expecting a bad start. But, it hasn’t really happened yet. Four-seamer, changeup, slider with a very low HR/FB rate in cold Detroit means…what? Well, it means this is not sustainable. But, Boyd’s HR/FB rate spiked in 2020 and has come back down to start 2021. If he can find his slider again and sustain his changeup success (CSW currently sits a 34.7%) he may just be a rotation mainstay in deep leagues. 
  2. People have been high on Kyle Gibson, Danny Duffy, and Jose Urquidy, and why not? They have been performing. But, their xFIP would suggest that they have been getting lucky on fly balls so far this season and now could be a great opportunity to use them in a trade to fill a need.
  3. It is kind of amazing to see Gerrit Cole on this list given how great he’s been so far this season. Carmen Ciardiello recently analyzed his start to 2021 and how it’s been overlooked due to panic in the Big Apple. But, don’t forget about Ben Clemens’ piece last summer, making note of Cole’s increased hard-hit rate in 2020 (37.1%.) He is currently giving up fly balls at a 47.3% rate (4th among qualified starters), along with a hard-hit rate similar to 2020 at 33.3%. #Don’tDropCole, obviously, but don’t be surprised when the long ball starts to bite him a bit. 

Expected and actual differentials can be interesting to analyze throughout the season, but don’t let it be the only thing you look at when deciding to drop or claim. One fly ball on a cold and overcast day in April could easily be a nacho-smattering home run in July. Just be sure you’re on the right side of the aisle when hot cheese goes flying through the air.





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pchphxmember
1 year ago

FIP and xFIP are great descriptive metrics!