WAR Update: Catcher Framing!

Update: An earlier bug that impacted updated pitcher WAR has now been resolved. The pitcher tables below have been updated to reflect that. Thanks to everyone who pointed out the issue!

I’m very pleased to announce that FanGraphs has finally added catcher framing data to the site, with full thanks to Jared Cross, who you may know as the co-creator of the Steamer projections. We’ve also incorporated catcher framing into WAR.

Including catcher framing in WAR has been a topic of internal debate at FanGraphs for the past half-decade. The problem has never been with the inclusion of framing numbers on the catcher side of things. That’s a fairly simple addition. The problem has always been what to do with the pitchers. For instance, the 2011 Brewers were some 40 runs above average in catcher framing. When you add those 40 runs to catchers, do you subtract 40 runs from pitchers? As it turns out, you do, but those runs are not attributed equally to each pitcher:

2011 Brewers Starting Rotation
Player IP Catcher Framing Framing per 9
Randy Wolf 212.1 -0.45 -0.02
Yovani Gallardo 207.1 7.79 0.34
Shaun Marcum 200.2 7.47 0.34
Zack Greinke 171.2 5.95 0.31
Chris Narveson 161.2 5.12 0.29
Positive framing numbers for pitchers indicate a pitcher was helped by the catcher’s framing ability; negative numbers indicate a pitcher was hindered by the catcher’s framing ability.

While most of the pitchers on the 2011 Brewers benefited from Jonathan Lucroy’s otherworldly framing, Randy Wolf was stuck with George Kottaras most of the time. In this instance, the entire Brewers pitching staff, with the exception of Randy Wolf, was a little bit worse once catcher framing is taken into account than their previous, non-catcher framing inclusive WAR would indicate.

Exactly how do you add catcher framing to WAR you ask?

For catchers, you take the catcher framing runs above average, divide by the runs to wins converter, and add it to your existing WAR total.

WAR = (Batting + Base Running + Fielding + Catcher Framing + Replacement Level) / Runs to Wins

On the pitcher side, we adjust FIP by the catcher framing runs above average per 9 innings. If Zack Greinke’s 2011 FIP was 3.00, and he was helped to the extent of 0.31 framing runs per 9 innings, we now use 3.31 in the WAR calculation instead of the original 3.00 FIP. We also adjust the pitcher’s dynamic runs to wins converter. In Greinke’s case, this would increase his personal run environment and also increase the runs to wins converter.

WAR = (((League FIP – (FIP + Catcher Framing / 9)) / Dynamic Runs to Wins Converter + Replacement Level) * IP / 9) * Game Start Leverage / 2

The RA9-WAR calculation has been adjusted in the exact same way.

Let’s take a look at how the inclusion of catcher framing has changed things:

Largest Career WAR Increases (2008 – 2018)
Player Catcher Framing Old WAR New WAR Difference
Brian McCann 181.9 30.4 49.2 18.8
Russell Martin 165.6 29.5 46.7 17.2
Yadier Molina 151.6 34.8 50.5 15.7
Jose Molina 140.4 0.6 15.2 14.6
Jonathan Lucroy 126.8 22.6 36.2 13.6
Miguel Montero 127.0 15.6 28.9 13.3
Yasmani Grandal 119.6 15.1 27.6 12.5
Buster Posey 118.0 38.7 51.1 12.4
Tyler Flowers 89.4 8.6 17.8 9.2
David Ross 80.7 10.0 18.3 8.4
Ryan Hanigan 79.2 8.8 17.1 8.3
Martin Maldonado 69.2 4.6 11.7 7.2
Jeff Mathis 69.1 -1.1 6.0 7.1
Chris Stewart 66.2 2.9 10.0 7.1
Mike Zunino 49.5 7.7 13.0 5.3
Hank Conger 48.1 1.7 6.9 5.2
Rene Rivera 48.1 3.9 9.1 5.1
Largest Career WAR Decreases (2008 – 2018)
Player Catcher Framing Old WAR New WAR Difference
Ryan Doumit -156.6 5.7 -10.4 -16.1
Gerald Laird -109.1 4.0 -7.2 -11.2
Nick Hundley -90.7 11.3 1.9 -9.4
Chris Iannetta -89.5 17.7 8.3 -9.3
Kurt Suzuki -86.1 18.1 9.0 -9.1
Carlos Santana -78.6 14.7 6.4 -8.3
Salvador Perez -79.9 17.8 9.5 -8.3
A.J. Ellis -77.1 8.2 0.1 -8.1
Carlos Ruiz -68.9 21.2 14.0 -7.3
Dioner Navarro -65.4 5.6 -1.2 -6.8
Lou Marson -57.6 2.5 -3.5 -6.0
Welington Castillo -52.1 13.2 7.6 -5.6
John Buck -52.4 7.2 1.7 -5.6
John Jaso -51.9 8.0 2.5 -5.5
Rob Johnson -48.4 -1.5 -6.5 -5.0
Robinson Chirinos -47.7 8.3 3.4 -5.0
Largest Single Season WAR Increases (2008 – 2018)
Player Season Catcher Framing Old WAR New WAR Difference
Jonathan Lucroy 2011 42.4 1.4 5.9 4.5
Brian McCann 2008 37.5 5.1 8.9 3.7
Brian McCann 2011 34.1 3.8 7.4 3.6
Jonathan Lucroy 2013 31.8 3.4 6.8 3.4
Jonathan Lucroy 2010 32.4 0.6 4.0 3.4
Jose Molina 2008 32.1 0.4 3.6 3.2
Tyler Flowers 2017 31.9 2.4 5.6 3.2
Brian McCann 2009 31.6 3.7 6.9 3.2
Jose Molina 2012 27.1 0.8 3.6 2.8
Buster Posey 2012 27.0 7.5 10.4 2.8
Yadier Molina 2010 27.2 2.2 5.1 2.8
Russell Martin 2011 26.6 2.5 5.3 2.8
Russell Martin 2008 28.1 4.8 7.6 2.8
Brian McCann 2012 26.4 1.5 4.2 2.8
Buster Posey 2016 26.7 3.8 6.5 2.7
Jonathan Lucroy 2012 26.1 3.4 6.2 2.7
Y Grandal 2016 25.7 2.8 5.5 2.6
Miguel Montero 2014 23.8 1.1 3.7 2.6
Hank Conger 2014 22.9 0.3 2.8 2.5
Mike Zunino 2014 22.8 1.7 4.2 2.5
Largest Single Season WAR Decreases (2008 – 2018)
Player Season Catcher Framing Old WAR New WAR Difference
Ryan Doumit 2008 -57.8 2.9 -2.8 -5.8
J Saltalamacchia 2014 -31.8 1.5 -2.0 -3.5
Gerald Laird 2009 -32.3 1.6 -1.6 -3.2
Carlos Santana 2011 -30.3 3.4 0.2 -3.2
Carlos Santana 2012 -27.6 3.0 0.1 -2.9
Chris Iannetta 2008 -26.6 3.1 0.5 -2.7
Jorge Posada 2010 -24.2 1.5 -1.0 -2.5
Kurt Suzuki 2014 -22.8 1.9 -0.6 -2.5
Ryan Doumit 2009 -24.6 0.6 -1.9 -2.5
Chris Iannetta 2013 -22.8 1.9 -0.5 -2.5
Dioner Navarro 2014 -22.0 2.0 -0.4 -2.4
Gerald Laird 2008 -23.9 1.4 -1.0 -2.4
Ryan Doumit 2012 -22.2 1.0 -1.4 -2.3
Dioner Navarro 2008 -22.6 1.9 -0.3 -2.3
Miguel Olivo 2011 -21.2 0.2 -2.0 -2.2
Jonathan Lucroy 2017 -22.1 1.1 -1.1 -2.2
Lou Marson 2011 -20.4 1.0 -1.2 -2.2
Lou Marson 2010 -20.3 0.5 -1.6 -2.1
Rob Johnson 2009 -20.8 -0.1 -2.2 -2.1
Dioner Navarro 2016 -20.2 -0.2 -2.3 -2.1
Wilin Rosario 2012 -19.5 1.2 -0.8 -2.0
John Buck 2010 -19.1 2.8 0.8 -2.0
W Castillo 2013 -18.3 3.2 1.2 -2.0

And the Pitchers, where the differences are considerably smaller:

Largest Pitcher WAR Increases (2008 – 2018)
Player Framing Old War New War Difference
Felix Hernandez -23.3 42.7 45.4 2.7
Justin Masterson -20.7 14.2 16.4 2.2
Jason Vargas -21.0 12.9 15.0 2.1
Justin Verlander -17.6 57.0 59.0 2.0
Ricky Nolasco -12.4 23.6 25.0 1.4
Mike Pelfrey -13.6 11.8 13.2 1.4
Kevin Correia -12.3 5.5 6.8 1.2
Cole Hamels -11.1 41.4 42.6 1.2
Anibal Sanchez -11.7 25.7 27.0 1.2
Zach Duke -12.4 8.3 9.5 1.2
Ubaldo Jimenez -10.8 26.6 27.8 1.1
Ian Snell -11.9 1.6 2.7 1.1
Derek Holland -10.5 13.2 14.3 1.1
Danny Duffy -10.2 11.7 12.8 1.1
Luke Hochevar -10.1 8.0 9.1 1.0
Paul Maholm -10.2 11.4 12.4 1.0
Edwin Jackson -10.1 16.1 17.2 1.0
Jeff Karstens -9.6 3.2 4.2 1.0
Roberto Hernandez -9.7 4.2 5.1 1.0
Largest Pitcher WAR Decreases (2008 – 2018)
Player Framing Old War New War Difference
Yovani Gallardo 25.6 21.3 18.4 -2.9
Bronson Arroyo 28.6 8.9 6.1 -2.8
Madison Bumgarner 23.4 30.7 28.0 -2.7
Tim Hudson 24.5 14.5 12.0 -2.6
Kyle Lohse 21.7 14.9 12.6 -2.3
Adam Wainwright 18.6 35.3 33.2 -2.1
Jair Jurrjens 19.2 9.7 7.7 -2.0
Derek Lowe 19.0 12.4 10.5 -2.0
Ryan Vogelsong 18.4 5.8 3.9 -1.9
Tommy Hanson 17.2 9.5 7.6 -1.8
Johnny Cueto 16.9 29.5 27.7 -1.8
Marco Estrada 16.6 13.3 11.6 -1.7
Matt Cain 15.7 21.1 19.4 -1.7
Ian Kennedy 14.7 16.3 14.6 -1.6
CC Sabathia 14.7 40.3 38.7 -1.6
Zack Greinke 13.8 50.7 49.1 -1.6

Now you know everything there is to know about how we added catcher framing to WAR. Please note the following:

  • Catcher Framing (abbreviated as FRM) is available on the leaderboards and player pages in the fielding sections.
  • WAR has been updated with catcher framing data everywhere WAR is available on the site.
  • Catcher Framing data is available in batter and pitcher sections of the leaderboard as a custom stat.
  • Fielding (the WAR component) now includes Catcher Framing runs above average.
  • Steamer projections and depth chart projections both include projected catcher framing for catchers and pitchers.





David Appelman is the creator of FanGraphs.

136 Comments
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Bryzmember
5 years ago

A lot of these differences are stark, though we can understand a little better why Jeff Mathis is always a hot commodity. Also, I found it a little amusing that Kevin Correia and Mike Pelfrey were in the “biggest losers” table, and one of their catchers in 2013 with the Twins was none other than Ryan Doumit (he only caught 43 games, but still, it’s a fun coincidence).

formerly matt w
5 years ago
Reply to  Bryz

There’s something more than coincidence here. Paul Maholm, Ian Snell, and Zach Duke are also among the biggest losers, and they were the pitchers with the most innings for the Pirates in 2008, when Doumit had a -55 Def score. Jeff Karstens was also a Doumit-era Pirate pitcher. Correia was also a teammate of Doumit in 2011.

This seems weird–if Doumit is getting a huge downward WAR adjustment, and the pitchers are also getting a downward WAR adjustment, where is that WAR going?

FrodoBeck
5 years ago

The law of conservation of mass and WAR is at stake here.

CousinNicky
5 years ago

The randomness is what is bothering me with this. How are Lucroy and McCann going from greatest single season framer to below average in just a couple seasons?

hearthebeard
5 years ago
Reply to  CousinNicky

Just on speculation – I would say that Umpires do not like to be manipulated. I read something on Fangraphs I believe about how umpires have begun to squeeze catchers with great framing reputations. That doesn’t change the value they earned the years before, just means there might be a sweet spot of framing value before the umpire community pushes back.

sadtrombonemember
5 years ago
Reply to  CousinNicky

To be fair, other metrics have identified the same thing with Lucroy. And catching is so hard on the body; it makes sense that if something about your body changes, the subtlety of framing may be lost.

jdtTXmember
5 years ago
Reply to  sadtrombone

The article a couple of years ago examining how low Lucroy was squatting before and after his framing metrics changed was really good and made sense. Those extra couple of inches made a significant difference.

Jon
5 years ago
Reply to  CousinNicky

Another guess: maybe framing isn’t as much of a repeatable skill as we’d like to think. In other words, the same way that one pitcher will lead the league in BABIP one year and be below average the next.

dl80
5 years ago
Reply to  Jon

It’s also possible that catcher may be especially good at framing certain pitches (say, fastballs) but not others (say sliders). Or sliders in the zone are ok but they struggle with sliders low and away to lefties. As pitch mix changes year to year, framing value probably does also.

teufelshuffle
5 years ago
Reply to  Jon

It also could be a repeatable skill, but physically demanding and subject to decline the same way bat speed is. In that way it would not be random, but not constant either.

tung_twista
5 years ago
Reply to  CousinNicky

It is similar with defense stats.
There is a lot of randomness along with actual skill.
If you looked at wrc+ on a monthly basis, you’d observe “best hitters” turning into pumpkins.
The problem is teasing the skill part out.

However, there is additional concern here because the volatility of defensive stats can be explained by “sample size”. Yet, framing opportunities seem like it should be a much larger size so it is not satisfactory.

Another point that has been brought up is as framing became the stat du jour, teams/catchers started actively working on it and were able to pick it up pretty quickly so the average increased. (There was a fangraphs article about this phenomenon)

Individually, these don’t seem sufficient but all of them combined might be able to explain it. Having said that, I will still look at framing with several pinches of salt.

jonvanderlugtmember
5 years ago
Reply to  CousinNicky

Jeff wrote a piece on this a while back. As more and more teams become hip to framing, the framing skill of the average catcher rises. Lucroy and McCann could have still been the same talent-wise, but the rest of the league caught up.

Savin Hillbillymember
5 years ago

formerly matt w, maybe I’m confused, but aren’t the pitchers you mention getting *upward* adjustments, not downward? I’m seeing them in the “Largest Pitcher WAR Increases” table, where their history as Doumit’s teammates makes perfect sense.

johansantana17
5 years ago

You are correct. formerly matt w is the one who is confused.