How Bad Could a Pitch-Framer Possibly Be?
Thursday afternoon I spent a few minutes talking about pitch-framing with Michael Baumann and Ben Lindbergh. I was on their podcast for a segment to talk about my entry in this year’s Hardball Times Annual, and in the course of the conversation, Ryan Doumit’s name came up. As a big-leaguer, Doumit mostly stayed under the radar, but pitch-framing research exposed his crippling weakness. The numbers made him look bad. Not just bad-bad. Not just run-of-the-mill bad. Extremely bad. Extraordinarily bad. Doumit, as a receiver in 2008, is charged with -63 runs at Baseball Prospectus.
It wasn’t a one-year fluke. For his career, Doumit’s framing was worth almost -200 runs. If you look at his FanGraphs page, you see 8.2 career WAR. Fine role player, average bat. Add in framing, though, and he plummets to a WAR of nearly -12. Doumit goes from being useful to toxic. All because of something we couldn’t even measure a decade ago.
You’d be justified in wondering whether these numbers are accurate. I have trouble believing in them myself. That’s just so, so much value given away. However, allow me to offer this evidence. Doumit caught more than 4,000 innings. Other catchers on his teams caught twice as much. When Doumit was catching, the pitchers allowed 5.34 runs per nine innings. When someone else was catching, the pitchers allowed 4.90 runs per nine innings. That difference, over Doumit’s innings total: 213 runs. Something bad was happening there.
I’ve gone off course. I’m not here to pick on Ryan Doumit. He earned salaries totaling more than $22 million. He did it! But thinking about Doumit made me wonder. How bad could a pitch-framer possibly be? What would be the lower bound? I can’t give you a realistic answer, but I can give you estimates.
You need to imagine someone very bad. What does a good pitch-framer do? A good pitch-framer maximizes strikes, both in the zone and out of it. It follows that a bad pitch-framer minimizes strikes, both in the zone and out of it. Ryan Doumit cost his pitchers strikes. He gave up strikes over the plate, and he failed to steal many strikes off of it. I imagine he had problems with both posture and technique. I don’t know. He’s done playing, so I’ll leave him be.
Here’s what bad framing can look like. It’s not that these guys are necessarily bad framers, but they can have instances of bad framing, just like Joey Votto can take the occasional bad swing.
Imagine a guy who’s constantly giving up could-be strikes. Look, I don’t know why it’s happening. I don’t know what his deal is. I don’t know who he’s mad at. I don’t know why he’s playing so much! In this hypothetical, he’s playing very much. He’s getting a full season’s worth of action. We have a (1) very bad pitch-framer, who (2) catches most of the games. Let’s say he’s catching for the Cubs. It doesn’t actually matter which team he’s assigned to, but the Cubs could stand to be taken down a notch.
Here is the core of our analysis:
That’s just taken from here. This shows you the league-average called-strike rates, for 2016. There’s not much more we need. I’ll be using a constant run value of 0.14 runs per pitch. That’s derived from good research, and even though constants tend to break down at extremes — and even though this is an extreme imagined scenario — I’m just trying to get us into the ballpark. Let’s see where the math takes us.
Another assumption is that our catcher is receiving pitches with an average location distribution. So, the same distribution as shown above. It’s worth noting that not every taken pitch is a borderline pitch. Nearly 40% of pitches wound up in areas with a 0% called-strike rate. The framer’s lack of talent doesn’t matter there. We can begin with the most extreme case imaginable. Our catcher doesn’t receive a single called strike. Not one! Not even on pitches down the middle. Running all that math, and adjusting for playing time, we’d get a framing value of about -400 runs, compared to average. This would be costing a few runs every single game.
A protest: Even this extreme hypothetical is impossible to imagine. Umpires are still going to call strikes on those pitches down the gut. So let’s give our framer full strike credit for pitches thrown to zones with a called-strike rate of 100%. Now the framer’s value shows up at -350 runs.
We can extend that a little, if we want to. Let’s be nice. Why cut it off at the 100% threshold? Let’s set a new threshold at 95%. Those are all still pretty much pitches over the middle. We’ll give our framer credit for an average performance on pitches within those zones. Still no strikes anywhere else. The value sits around -225 runs.
For the final adjustment, let’s move that threshold one more time, to 90%. Our framer gets credit for average performance on all pitches thrown within zones with a called-strike rate of at least 90%. Those are mostly gimme pitches. Once again, no strikes elsewhere. Now our calculated value settles around -200 runs. That’s 200 runs worse than the average receiver, over the equivalent of regular playing time.
That’s like -20 wins. Now, if you wanted to calculate WAR, you’d have to fold in runs for the replacement-level adjustment. And our framer would get credit for a positive positional adjustment, since catchers get a big boost there. Because this guy is a catcher, he’s probably not much of a baserunner. Nothing to be done there. And just as a hitter, Barry Bonds topped out at +117 runs, compared to average, in 2001. If our guy hit like the best version of Barry Bonds, he’d still be by far the worst player around. He’d still be a handful of games worse than replacement, although given the offense, and given that pitch-framing can be subtle, one wonders how much fans would actually hate him. I bet they’d really hate the umpires.
Anyhow, now we have an idea of the lower boundary. It’s pretty far down there. It’s so much worse than even Ryan Doumit. Thank you for joining me for whatever this was.
Jeff made Lookout Landing a thing, but he does not still write there about the Mariners. He does write here, sometimes about the Mariners, but usually not.

Would Barry Bonds have been -20 war as a catcher, tho?
Maybe he’d just stand up and hold out four fingers to every single batter, figuring if it works for him while he’s at the plate…
To restate the obvious: It’s thought provoking that the catcher is the only player with a rate stat that gets applied to such a large number of events in a season. To not have a counting stat like WAR for pitch framing until pretty recently obviously concealed the small leverage*frequent event behind one of human’s best-known cognitive biases (relative scale). I’ll look for more candidates for that in non-baseball life today. Thanks!
WOW if there was ever a case for robo umps, this is it.
People keep talking about fairly minor inaccuracies in enforcing the rulebook as reason to mechanize the game. I respect and love that the game is a long, large-sample season with rates and metrics built into its DNA. However, the human element is what attracted me to the game in the first place. It’s cerebral. The pitcher is doing his best to beat the batter. He does that by changing speeds, timing, location, and movement. The game is at it’s best when both parties have to try to get in the other guy’s head to come out on top. Same goes for the players and umps. You have to adjust to the ump’s zone (is it pear shaped? Scootched outside? Low?) You can play with the ump as well. Fool him into calling a strike here and there, or a ball here and there. More strikes often leads to more borderline calls. Fewer strikes means fewer calls. Ted Williams made it known that he had the best eye in the majors, and it got to the point where umps would hesitate to call borderline strikes to disagree with him. “90% of the game is half mental.” deploying robots eats at that 45%(?), even if it yields more “accurate” results.
Ryan “no mitt” Doumit was an interesting topic in Travis Sawchik’s Big Data Baseball. Very good read for anybody interested.
I played catcher for years and I always tried to work on pitch framing. That being said, I think a lot of this recent fixation on it is a bit misguided. Kind of like base stealing stats being attributed mostly to catchers.
For instance, I don’t know anybody that thought Javy Lopez was a particularly great defensive catcher. I bet if you ran his “pitch framing” stats for his career, they look pretty good. How much of that is attributed to catching 100 games per season for the three of the best “corner painters” of all time. Give me the worst butcher in the league and let him catch Greg Maddux in his prime. I bet he has more called strikes than average.
Seems to me that could be measured (and likely IS) by comparing Greg Maddux’s called strike rates with other cathers to that when he was throwing to Javy Lopez … or Javy’s called strike rates when catching Maddux to that when he was catching other pitchers.
You are absolutely correct that pitcher identity plays a big role. It’s a hell of a lot easier to catch Kyle Hendricks than it would be to catch, say, Daniel Cabrera or early-career Aaron Sanchez. The numbers at Baseball Prospectus, though, attempt to adjust for that very thing. I can’t promise they do a perfect job, but it’s not being ignored.
FWIW, Lopez rarely caught Maddux — 72 times, and just 23 in their last 6 years as teammates. After 1996, Greg always had a “personal catcher” like Eddie Perez, Henry Blanco, Paul Bako, etc.
Scary thought: This doesn’t even account for the chaining of a good pitcher tiring earlier because they had to throw more pitches to get outs, forcing more and worse pitchers from the bullpen into the game. The season-long byproduct of that fatigue is equally horrifying.
I guess it raises the question of whether the Pirates’ pitchers performed increasingly worse relative to league average (or their projections) as the seasons went on while Ryan Doumit was the primary catcher.
Can’t be any worse than having Dee H. Gordon as your primary catcher….
I wonder how many people get this. It was so long ago.
What about a catcher so big that the umpire can’t see around them at all?
“Okay, so just turn around after the pitch so I can see where it left a bruise on your chest, and I’ll determine if that spot was in the strike zone or not…”
“When Doumit was catching, the pitchers allowed 5.34 runs per nine innings. When someone else was catching, the pitchers allowed 4.90 runs per nine innings. That difference, over Doumit’s innings total: 213 runs. Something bad was happening there.”
Suppose the backup catcher usually catches the #4/#5 starters, and the starting catcher catches the #1, #2, #3 (and sometimes #4) starters.
Something to think about.
The pirates’ pitching staffs those years were so bad, it probably didn’t matter.
Are umpire tendancies at all factored into a catcher’s borderline called strike percent?
I think it’s a neat stat. However, your catcher not only has to frame it good, but you then have to hope that your pitcher puts it in the right place AND the umpire has to call it in the right spot. All this within what……….a split second? Amazing game. Talk about quick thinking, whew. Still, I think this is a job for robots or drones going forward, in turns of in game measurement.
Objection, this piece makes not a single reference to the Casey Stengelism about needing a catcher, please rewrite
This makes me wonder about things like 1B scoops, Javy Baez quick tags, etc. Those parts of the game people still quantify as “probably not that important.” No one would’ve guessed pitch framing could have this much impact before the data was studied
Just some very quick spitballing:
Runner on 2nd, 0 out: 1.13 expected runs
Bases empty, 1 out: 0.26 expected runs
A caught stealing could be seen to be worth 0.87 runs in that scenario.
Obviously the math would be more complicated to include all base/out states, but this is actually the most value you could get from a CS. And, we wouldn’t want to assign 100% of that run value to just the tagger – a vast majority would go to the pitcher & catcher. In other words, 0.87 runs serves as something of an extremely generous ceiling for the value of a tag applied.
Pitch framing ranges from -20 to +20 runs / season
Baserunning ranges from -10 to +10 runs / season
For tagging to be in the same vicinity as baserunning, you’d need to give Javy Baez full credit for every tag and expect that he has 10 tags per season that your average tagger wouldn’t convert.
Teams averaged about 33 caught-stealings each. You’d have to think that Javy Baez could bring a team to 43 caught stealings single-handedly.
I don’t honestly know what to conclude from this. I thought I’d get somewhere that said “it’s nifty but not really valuable” and maybe that’s true, but honestly I’d not be shocked if Javy’s tagging saves 5 runs / year over your average 2B.
1. “Thank you for joining me for whatever this was,” is a great way to end anything.
2. Since pitch framing has been a thing in my brain, what I’ve noticed is it often has to do with losing strikes due to moving the glove after the catch. We focus a lot on the pullback into the zone, but I think there’s more value available in the receipt that shows you exactly where the pitch was.
In his book, Jason Kendall, the former catcher opined that pulling the ball back was poor receiving and that umpires would punish a catcher for cheating too hard. According to him it was more important to get your wrist/glove in a position where you could freeze the ball at impact. As opposed to trying to catch it with your glove moving back into the strike zone to an obvious degree. Getting your glove deflected out of the zone by a pitch is definitely a no-no.
In that future where Jeff Sullivan has shuffled off this mortal coil, the epitaph I imagine on his tombstone:
The cStrike% chart shows a huge zone discrepancy between the two sides of the plate. Whats the explanation?
I believe it’s the LHB strike zone, I think there are more outside strikes called for LHBs than for RHBs.