The State and Future of Pitch-Framing Research

Defensive metrics couldn't reach a consensus on Jason Varitek's final seasons (via Eric Kilby).

Defensive metrics couldn’t reach a consensus on Jason Varitek’s final seasons (via Eric Kilby).

We need to better understand catcher defense. It is not a matter of small weight. It is not a final flourish on player evaluation. It is a weighty, vital next and present step in baseball analytics.

Over the last decade, our metrics have blossomed, and we can propose with decent comfort: Miguel Cabrera has been worth around seven wins annually; Brandon Crawford has been worth around two wins annually; Mark Buehrle has lately managed an ERA and innings combo worth about 3.5 wins per season.

What we can not say with good comfort and what we should not be saying: Buster Posey was worth around about five wins in 2013, or Jonathan Lucroy was worth 3.6 wins each of his last two seasons. Why? Because a hearty chunk of the catcher’s role is not accounted for in any present form of WAR.

Of course, few good baseball writers make this error–the error of assuming the relative reliability of non-catcher WAR carries any similar weight to catcher WAR. A pitcher estimated at two WAR is nowhere as reliable as a catcher estimated at two WAR. The inscrutable wordsmith, Donald Rumsfeld, once summed the issue of catcher WAR in perfectly accurate and inaccessible language:

… [T]here are known knowns; there are things we know that we know. There are known unknowns; that is to say, there are things that we now know we don’t know. But there are also unknown unknowns – there are things we do not know we don’t know.

In world of catching, the unknown unknowns are few. Why? Because we know how catchers are taught and how current catchers teach other catchers. An unknown unknown would be something such as body type, ethnicity or fingernail length affecting a catcher’s ability. Nobody is making claims these elements affect a catchers ability, but that may be because they are unknown unknowns.


Right now, there are two enormous known unknowns: pitch framing and game-calling. Until the invention and implementation of PITCHf/x, these two elements had no hope of stepping into known-knowns. The baseball community has celebrated progress in these areas, mostly pitch framing. But further progress requires renewed urgency.

Matthew Carruth, a THT alumnus whose StatCorner site features the only publicly available pitch-framing database, explained the state of pitch-framing knowledge this way:

Observed Framing RAA = a * (framing skill) + b * (other skills) + c * randomness

“I think it’s important to remember that [the StatCorner] numbers aren’t a total reflection of a catcher’s skill,” Carruth says. “My hunch is that a is only at about 0.25 right now…”

And if we plumb the depth of PITCHf/x? If we beseech the heart of that dark and rich database and finally reach a point where we can alter the formula to a more confident:

Actual Framing RAA = a * (actual framing skill) + c * randomness

We still may have only threads in our hands. According to Carruth’s expectations, even if we managed to transition to the second formula, transition to a universe of known framing impact, then variable c would greatly outweigh variable a.

A Hardball Times Update
Goodbye for now.

“Baseball,” Carruth says, “is just incredibly random.”

How much can it matter?

I often discuss pitch framing with my colleagues. The most common source of doubt I hear: The numbers don’t pass the sniff test. The infamous Jose Molina has too many smart people crinkling their brows. This is a determination each of us has to make. Can there be a possible 5-win data inefficiency that existed for 100-plus years of baseball history? Can it be possible such a big deal was missed for so long?

We have to ask ourselves: How important is pitch framing and receiving? How important can it be? Let’s look at this both qualitatively and quantitatively.

The qualitative value

Let’s say it’s the fourth inning, runners on the corners. As the starting pitcher, your slider is not cooperating, and a walk and a duck-snort single have you in a jam. The manager brought the infield in, which increases your chances to prevent a groundball run, but also of a seeing-eye single, maybe a double.

It’s a 1-1 count. From a 2-1 count, hitters in 2013 have smashed a .351/.352/.580 slash. From 1-2, they hit .166/.173/.239. If you get a strike, you can even try throwing your slider–hopeless as it is today–but from 2-1, the slider is a non-option, possibly for the rest of the at-bat.

The next pitch matters. Even if the hitter leaves the bat on his shoulder, it could decide the fate of the inning, your outing, and the result of the game. You throw a two-seamer that tails toward the hitter’s knees. It misses the zone by at least two inches, but Lucroy–a master of receiving low strikes–snares it for a 1-2 strike.

The batter loses 185 points of batting average, 173 points of on-base percentage and 341 points of slugging average. He might as well be Neifi Perez with a tube of hard salami in his hands. The wild slider, which you’ve thrown only a few times, is now actually a weapon. He flails at it low in the zone, unsure where the zone ends, for a key strikeout. The infield moves back.

This hypothetical scenario may seem dramatic, but the most absurd element–the historical difference between a 2-1 hitter and a 1-2 hitter–is the most true part of it. Cabrera, the best, most fearsome man with a bat right now, has an 80 wRC+ after a 1-2 count. After 2-1, he smushes pitchers with a 167 wRC+. The power of a 1-1 pitch cannot be understated. A first strike is good, but even from 0-1, hitters had a .311/.319/.461 slash line in 2013.

Altogether, received pitches play a big role early in an at-bat and–as a 37 percent event–a significant role in 1-1 pitches:

Pitch Taking

With over a third of 1-1 pitches landing in a catcher’s glove as either a called strike or ball, being able to flip the borderline pitches can be nearly as damning as framing an 0-2 or 3-0 pitch, given how dramatically the hitter’s ability changes. Even the great Greg Maddux considered 1-1 pitches the key determinate of a plate appearance’s outcome (though shear quantity suggests 0-0 pitches matter more).

Let’s change perspectives and look at this from the batter’s box.

It’s the fifth inning. The pitcher, A.J. Burnett, is getting tired, and you’ve seen his every pitch. The game’s become a 5-4 slugfest, and this is your third at-bat. You fell behind early in your second at-bat and grounded out. During that at-bat, you got two good looks at his plus-plus curveball, with one whiff and one weak dribbler to short. The pitch is deadly.

Burnett misses the strike zone with a high fastball. The next pitch–the 1-0 pitch–matters. It matters a lot. From 2-0, Burnett will throw either a fastball or sinker, and you can handle either. The curveball, in a 2-0 count, is a three-percent event. From 1-1, there is almost a 40 percent chance he goes knuckle curve.

As he often does, Burnett goes fastball with his 1-0 pitch. It’s tight, and though you turn in, the pitch is not very tight. You’re hoping to influence the ump a bit because the fastball’s definitely brushed the zone; you could sense it a moment after you stopped your swing.

But Russell Martin isn’t catching today. Michael McKenry is behind the dish, and because he did not set up inside, and because his elbow has moved too much, the ump sees a ball. It’s 2-0, and Burnett has lost his best pitch, the curveball.

As the hitter, you don’t know it’s the catcher’s fault; you can’t credit him immediately. That’s the first inside pitch you’ve seen today; maybe the zone’s been tight all day? It makes you more patient. And when that surprise 2-0 curveball comes looping in over the outside corner, you take it for a happy strike.

And when the fourth pitch comes inside, you take it again for a ball. After that 1-0 pitch went for a ball, you get the feeling Burnett’s lost his control. He’s actually been popping the mitt, but the count is 3-1 when it should be 2-2. The Pirates have pitchers warming up fast in the bullpen. Whether the at-bat finishes with a single or strikeout, this could be Burnett’s last hitter, and the next batter will face a reliever with a rushed warm-up job.

Burnett throws a 3-1 sinker, but it’s headed for that narrow zone you’ve been focusing on since the 1-0 pitch. You blast the pitch right at Pedro Alvarez, who snares it for the out. Pedro is trying to shake feeling back into his fingers, and Clint Hurdle is marching to the mound before you even trot off the basepath.

The poorly framed 1-0 pitch has played a key role in changing the general course of the game. The bullpen enters earlier; the next pitcher has rushed his warm-up; the qualitative impact of that missed pitch has been potentially enormous.

Granted, these are high-leverage situations, illustrative scenarios of the importance of a called pitch. If the first pitch of a game is a borderline pitch and gets framed into a strike, it probably will not have an enormous effect on the game if the next pitch goes for a homer. But the point is this: Called pitches occur frequently, in both high- and low-leverage situations. It is a frequent event, a defensive event far more frequent than most other observed defensive events.

Jeff Sullivan of FanGraphs has explored the edges of PITCHf/x and framing data. In a recent conversation, Jeff explained his reasoning for why PITCHf/x data may provide even more reliable defensive numbers than UZR, but also how pitch framing could potentially be a catcher’s biggest defensive contribution:

A typical defender, like a middle infielder, sees a few hundred defensive opportunities each season, and the overwhelming bulk of those will either be fairly routine plays or unmakeable plays, so you have a pretty limited sample of plays where a really good or really bad defender can separate himself. But a catcher can catch up to 5,000 to 10,000 called pitches–and of course many of those are going to be automatic balls or automatic strikes. But a whole lot of those are going to be towards the fringes, and the fringes are actually pretty big.

I can buy that the very best and the very worst framers can make a pretty significant difference just by adding up the volume of pitches they actually catch around the corners.

In 2013, J.J. Hardy and Starlin Castro tied for 159 games started at shortstop. They played in 1,417 and 1,418 innings, respectively. Neither defender had more than 700 chances. Hardy’s teammate, backup catcher, Taylor Teagarden, appeared in 23 games and caught 1,296 called pitches.

Where does that lead us quantitatively?

The quantitative value

Tom Tango, in many ways an emissary of linear weights, offered this simple breakdown in 2011:

BB = +0.30 runs

SO = -0.27 runs


Called ball = +0.075 run state

Called strike = -0.09 run state

That’s a 0.16-run swing per framed pitch.

This could then extrapolate to about 20 runs per a full season (between 120 and 150 games) if the catcher can frame just one pitch per game.

This is the core of our analysis. But it does not consider how far the pitch was from the strike zone, nor does it consider an umpire’s tendencies or the leverage of the event. It does not consider the impact on later events, the potential for ripple effects (as in the second qualitative example).

At the simplest, we can believe an average pitch, converted from ball to strike by a superior reception, is worth 0.16 runs. This is a good starting point and a good sounding board–a structure for our sniff test of future numbers–but we should expect the truth to be more complex.

Three major methodologies have dominated the pitch-framing conversation. The first is the Mike Fast study. In 2010, then-Baseball Prospectus writer and Hardball Times alumnus, Fast published his seminal “Removing the Mask Encore Presentation” article in which he exposed a then little-known Molina brother as being perhaps the game’s greatest pitch-framer. He pegged Molina’s framing ability at about 3.5 wins per 120 games.

Fast admits he was not the first to explore the impact of pitch framing and receiving, but he appears to be the first researcher to put the pieces together so seamlessly. It certainly seems the baseball community took note, too. The winter following the publication of Fast’s data, the Rays signed a rare free agent deal with Molina, a deal made even more unusual in that it guaranteed Molina, then 37 years old, the first starting catcher job of his career.

One of the core difficulties of analyzing PITCHf/x framing data is that normal, publicly available PITCHf/x data does not include information about the defenders active in the field. It lists a pitcher and a hitter but no other players. Fast and Carruth both had to develop proprietary code magic in order to add catcher information to their PITCHf/x databases.

But another THT alumni and BP author, Max Marchi, employed Retrosheet data to slip around that problem (“Catcher Framing Before PITCHf/x”). Marchi had worked with no small amount of PITCHf/x pitch-framing data before looking at Retrosheet’s numbers, so he is among the best qualified to confirm or deny a correlation between the two. What he found, in short, was a more conservative estimation of expected impact, but a strongly similar one.

According to Marchi, the RetroFraming model and his PITCHf/x model had a covariance of 0.72, which is pretty good.

The third major study, one conducted relatively quietly (both Marchi and Fast got attention from the whole of the baseball community, including SABR), is Matthew Carruth’s methodology for his aforementioned publicly available framing data. While Carruth did not generate the waves Fast or Marchi did, his work has become the go-to resource for any baseball researcher without the coding know-how to build his own database. When I talked with Carruth, he was quick to admit his methodology wasn’t the trimmest or shiniest. But it does have a strong connection with Fast’s results:

Framing Comparisons and Distributions

The strong correlation is nice to see, but it can more illuminating to look at some specific entries in this data. And we can even fold in what few samples we have from Marchi’s RetroFraming study. Unfortunately, because he did not release a complete dataset–with individual season numbers and a full list of players–we are left with a rather select collection of catchers who played exceptionally and did so in the PITCHf/x era:


These comparisons don’t really maintain any easy pattern. Marchi says the RetroFraming numbers tended to be more conservative, but here they appear bullish on both Joe Mauer and Jason Varitek. Meanwhile, StatCorner–which, in my mind, was always the most radical–looks conservative with respect to both Mauer and Varitek. I imagine those two perceptions–StatCorner being aggressive and RetroFraming being conservative–play out over the full data, but in these small overlaps, we cannot see that.

If we break this comparison down more specifically, we can see the nature of how these metrics diverge. Again, RetroFraming comes without a complete dataset. We can, however, prorate the career numbers across innings played as a catcher and plot in the select seasons that we know. That gives us a plot somewhat like this:


The RetroFraming numbers, as in the non-prorated dots in 2008 and 2012, appear very similar to the numbers available via Mike Fast and StatCorner. But we also can see via the prorated numbers, which would be lower if they included the two RetroFraming dots, that RetroFraming is indeed the most conservative.


With Martin, we see StatCorner and RetroFraming matching in 2008, but in 2010, RetroFraming suggests an aggressive 18-run season from Martin. Adding those numbers to his prorated line would push his RetroFraming run estimates far lower than StatCorner and Fast.


Varitek has the most curious divergence in the group. In 2007, the first year with PITCHf/x data, RetroFraming believed he had a 26-run season. Both Fast and StatCorner had Varitek in negative run values.

It is quite possible, considering both Fast and StatCorner showed fairly precipitous declines late in Varitek’s career, that he was, in fact, a great receiver earlier in his career. And given the unreliability of PITCHf/x data in the early days, it would not be unreasonable to think the 2007 data is incorrect.

A Call for Progress

What I find most fascinating is the histogram from above (“Distribution of Framing Talent”). Granted, that’s a the minimum of 10,000 pitches received, so certain players may have had unusual seasons (10,000 pitches constitutes about a full season of catching). But I’m flummoxed that the three studies suggest there are about 15 catchers above 1.5 wins and about 15 catchers below 1.5 wins per season. This is mostly culled from data across the last seven seasons.

Can we trust the results from these recent studies? Consider this: The researchers have found steady year-to-year correlations. The different research methods have yielded strong inter-study correlations. Moreover, this is not a skill invented in the last 10 years, but one that has been taught since pitchers were no longer required to throw strikes.

Are the data perfect? No. The qualitative examples above demonstrate how there are impacts beyond the raw run value of a ball flipped to a strike. I think we may be many years away from an accurate distribution of credit and run values when it comes to framing, but that does not mean these early offerings are any worse than our present shift-weakened defensive run values.

It leads me to ask: Why can’t we fold pitch framing into catcher WAR?

A catcher’s contributions at the plate are obvious; we can grade them just as easily as any other hitter. A catcher’s job at controlling the running game appears increasingly less important in our understanding. The matter of blocking pitches and preventing passed balls also appears to offer only a minimal edge–a half-win advantage or penalty to the best or worst in 2013.

But the effect a catcher may have on a called pitch is potentially enormous. It’s time our data reflected that.

Newest Most Voted
Inline Feedbacks
View all comments
The Stranger
9 years ago

This is pretty fascinating stuff. I wonder, is this a zero-sum game in a lot of ways? If you increase catcher WAR to show the impact of pitch framing (and later, game calling), do you then have to decrease pitcher WAR by a comparable amount? You can’t prevent the same run twice, after all, and it seems like pitchers are currently getting credited with preventing the runs saved via pitch framing.

The Stranger
9 years ago

Allocating credit (or blame) for different things appropriately seems like the biggest challenge for defensive metrics in general but for catcher defense in particular. Even when we’re talking about TTOs, every pitch involves some interplay between the catcher calling/receiving the pitch and the pitcher executing the pitch that’s called for. If the catcher sets up just off the plate and the pitcher hits his spot perfectly for a called strike, the pitcher contributed as much to that “framed” pitch as the catcher did. And then when you start thinking about calling games, if the catcher calls for an inside fastball, it’s delivered perfectly, and the hitter homers because he was sitting on that pitch, the catcher maybe deserves some negative “runs saved” for calling that pitch. And to be fair, there should be an offset credited back to the pitcher – you can’t give up the same run twice, either.

On a related topic, it seems like there should be a similar relationship between defensive metrics and fielding-independent pitching metrics. Has anybody looked at how much of the difference between a pitching staff’s ERA and FIP (positive or negative) is captured by measures of the team’s defense?

Does this make any sense? It’s not something I’ve given a lot of thought to before, but intuitively, it seems that, if a team gives up 100 runs fewer than average over the course of a season, the players and the manager (manager WAR really needs to be a thing) did something to make that happen (assuming neutral luck/sequencing, which isn’t likely but should average out over larger samples). Which implies that, in a perfect world, some combination of pitching and defensive metrics should allocate credit for those 100 runs (and the associated WAR). Again, luck plays a role, but it seems like if the system is consistently allocating credit for more or fewer than 100 runs over a large enough sample, there’s room for improvement. The data to close those gaps may not be available, but the size of those gaps can tell us something (or nothing – if we’re double-counting 50 runs and ignoring 50, there won’t be a gap).

The rabbit hole here is absolutely endless. It makes me what to quit my job, learn how to do some of this high-end analysis, and dive in headfirst.

9 years ago
Reply to  The Stranger

You took the words right out of my fingers. The pitchers have been credited or discredited for the catchers’ framing skill or lack thereof for more than a century.

9 years ago

One thing about normalizing the strength of the strike/ball is that the data will minimize the expected micro and macro outcomes of the catching/pitching battery.

For example, Guys like Zaun were specifically catching certain pitchers toward the end of his career. Those comfort tandems (ie: Ace throws only to backup catcher) can influence a lot on how a game is pitched, and possibly the discomfort with pitcher throwing to another catcher, or the catcher catching someone he doesn’t usually play with, can skew the stats in favor of the comfortable pair. Even the pair baseline is out for the pitcher, I’d assume the catcher would be apt to get a good number of pitches at the border due to familiarity.

Another issue: Pitching style. Although framing is important, pitching style can also change with battery, leading to varying results that may over-amplify strengths and weaknesses. If Jon Lester or veteran throws to Varitek, they might be apt to throwing more offspeed pitches, which tend to be pretty tough to frame. The veterans might use these pitches with a catcher they’re comfortable with vs. a backup or newer catcher. So Varitek might see 6-7 more sliders in a game vs. another battery, and probably 2-3 more framing situations with pitches with crazier movements.

The stat is illuminating, but the fact that the deviations between some catchers seem large, and without bringing too much bias as a Red Sox fan, its hard to fathom that Varitek’s pitch-framing impact was that negative at any point in Red Sox history.

Which brings me to my real point: the quality of pitch-framing should be part of the larger discussion of catcher game-calling and management. And also the complexity of framing and “holding” pitches on the borderline.

Using Varitek as an example again (I could use Charlie O’Brien; similar styles), Varitek was constantly wary of either the hitter or men on base “communicating” how the pitcher may pitch. Varitek, with a runner on 2nd, would pass up a sign with his shoulder pads, move his body to the inner corner, and just before the pitcher releases his pitch, would move BACK to the outer corner.

His advantage that he kills any means of communication between the 2nd base and the hitter, and it creates a distraction where the hitter can constantly hear Varitek set-up but not gauge where he might be. As a batter you can sometimes sense where the catcher may be, so he creates a disturbance and keeps everyone (including opposing coaches that might try to notice trends) honest.

The disadvantage is that his moving around may affect some pitchers. I know that Dice-K had some issues throwing when Varitek wasn’t even set in his spot. And in all honesty, I can’t think of another catcher other than Charlie O’Brien who would do that. But that moving around costs him those corner calls, since he fakes his position until the ball is thrown.

Varitek has two pitch-framing techniques, and they both stem from his management with this staff. If you watch Varitek with Dice-K, his framing of Dice’s below-the-knee fastballs was amazing. I saw a pitch about 6 inches above the plate, and he caught it overhand without any movement. Although his overall pitch-framing isn’t great, when he employs it he’s about as good as anyone.

Another technique is that Varitek likes to do the quick nonchalant toss-back, where he ‘kinda’ frames the pitch, but his reaction is quick enough to assume he threw a strike. When the umpire calls ball, he’ll always suggest something and move on. But it’s crazier than framing, because he essentially gives the umpire less time to call a pitch, and he puts it in the umpires mind that he may have missed a call. I have seen him do this with pitches nowhere in the zone, and he’s gotten calls with it.

The last thing to defend Varitek is that he game-calling always played to the strength of getting the hitter jammed, not giving up on the fastball in any count (I have seen many 7,8 pitch all-fastball at-bats), and keeping the offspeed away from the zone and in on the hitter legs (Lester’s cut) if a throw-away pitch. He’s called some great games, and it was rare to see any pitcher uncomfortable with him ((sans Beckett for some reason). He was around a lot of pitchers who would either blow you away or get you chasing. Gameplan did backfire on him with some guys (Lackey, Beckett) since they were keeping their off-speed in the zone, but he was one of the best I’ve seen in utilizing the pitcher’s strength, and inducing weak-contact calls, and making his pitchers challenge and throw inside.

I think play-calling is complex because some managers do have a say in the battery. Some pitchers aren’t comfortable with catcher play-calling. Some catchers might be nurturing rookies. Others might be backups on championship teams and do more work with the relief staff. Some catchers call awful games (Vic Martinez, Posada) or pitches constantly. Some frame well.

My point is framing at some point will need to be a supplementary value to the entire contribution to the catching battery, which will also have to include how quantify pitch-call types, on-base situations, pitcher shake-offs etc. Guys like Doumit and Jose Molina are gifted catchers all around and this list rewards them. But there are so many other anomalies with catching that if any portion of Varitek’s contribution to wins is related to this stat, a lot more work needs to be done.

9 years ago

if you think about it, pitcher performance is also very difficult to quantify. Does this guy really have a good K rate, or is it because his catcher turns his balls into strikes?

I Believe that a pitcher’s numbers should be adjusted based on his catcher, maybe a pitcher is worth 2 WAR on paper, but there is a good chance that his catcher heavily contributed to his WAR values.

Michael Guetti
9 years ago

Asking a pitcher to hit a moving target — a catcher shifting around behind the plate — is as ridiculous as asking an umpire to make a decision on an on-the-corner pitch when said catcher is reaching across his body to receive it: With so much activity from the catcher, why would an ump call the pitch a strike?

I’m not sure what the definition of “framing” is. Is it holding the glove steady so the (sometimes myopic) ump gets a clear view where it was caught? Is it the movement to the edge of the strike zone when the pitch is two or three inches outside (some umps often see that two-or-three-inches-outside pitch as a strike: Didn’t Glavine build a career out there)?

Yes, it is certainly important how a catcher receives pitches but I’d suggest that the catcher who sits (in the true sense of the word) behind home plate, with his back straight and his feet firmly planted in the ground is not much help to his pitcher no matter how long he holds his glove steady or moves it to the edges of the strike zone.

In the 1950s and early ’60s — yep, I’m old — I did a lot of catching in the sandlots and in college. I also pitched, so I’ve seen this coming and going. What I wanted as a pitcher was a “quiet” catcher, one who was holding the glove in the required spot as I began my windup. There were times when I did not aim for the glove, of course, when I wanted to throw a pitch up and in on the hitter’s hands, for example, but my catcher didn’t need to be in on that. I always thought it was silly of Varitek when he would stand up behind the plate and put his glove at shoulder-level. Why announce your intention? That seemed like a grandstand play, you know, as Bird would describe guys exhibiting “fake hustle” on the basketball court.

And what’s the point of the catcher centering his body on the inside or outside edge of the plate? The plate is not that big, for goodness sake: The catcher should lean to the outside or inside, with the glove on the edge in question. If you shift all of the way outside, where does the ump go? Does he stay over the inside corner of the plate or does he move with the catcher? I’m not sure about this but it seems to me that the ump does not go with the catcher, putting the pitcher at a disadvantage in terms of strike-ball calls.

For that matter, most of the “inside-edge” umps do not have a clue whether the outside pitch is just on, or just off, the plate., no matter where the catcher sets up.

But, back to the catchers and helping their pitchers get the close calls: The best way to get the low strike is … to be low and to stay low, and to catch as many as possible with the fingers up. I used to catch (with no one on base) with my arms inside my knees and bent over towards the pitcher just about as far as I could go. I remember, as a young catcher, one umpire telling me, “Stay down, catch,” when I rose up for a high pitch. From then on, I stayed where I was and only put the glove up. I took him at his word: The lower I stayed, the more clearly he could see the low pitch, and the better that was for my pitcher.

So, really, we are talking about technique, both on the part of the catcher and of the umpire. I’m not sure if the umpire who calls the two-inches-outside-the-strike-zone pitch a strike is doing it because of the catcher’s good technique or because of the ump’s poor technique, but any catcher who wants the most help for his pitcher should stay low and stay quiet.

Eric Chalek
9 years ago

W/R/T game calling: Redsoxmaniac’s point about MGRs calling pitches is important. I remember TLR or his staff calling a lot of pitches. Lots of camera shots of catchers looking into the dugout. That one seems beyond parsing. At least framing has some discreetness to it as a skill, and I would love to see it included in WAR in some way.

And now here’s another wrinkle. Once we have a really firm grasp on what framing does to counting stats, can we find a way to apply it to pre-FX eras? Can we find some relationship among the counting stats of a catcher’s pitchers, or in PBP years among any available pitch-count data while he was in the game, to get some sense of historical framing skills? How would this affect our perceptions of Yogi, Bench, or Schalk, or even Torre or Simmons?

Hank G.
9 years ago

It would be ironic if sabermetricians figure out the true value of pitch framing right at the point that MLB institutes automatic ball/strike calling.

Avery B.
9 years ago

One thought about the chained effects of pitch framing. Your examples cover a few ways in which the impact of a single framed pitch can cascade through a game, but I wonder if it might have a similar impact on umpires. If a quality pitch framer (or just a really comfortable pitcher / catcher battery) successfully hit targets or frame pitches on the edges of the zone early in a game, could that have an impact on the likeliness of similar pitches being called for a strike later on in the game?

9 years ago

I’d love to see a follow-up that goes in-depth on the year-to-year correlation on pitch framing runs.