Catching Up and Catching Down

Pitch-framing! Am I right? It’s still very much a fascinating subject, which is one of the reasons I write about it so often. But by this point we have a pretty good idea who’s good at it and who’s bad at it. That ground’s been covered. We know that Jose Molina is great. We know that Ryan Doumit was a problem. Yet we can break things down further still. Often, people don’t go beyond describing a guy as good, bad, or okay. But there are actually specific types of framers.

Which makes plenty of sense, doesn’t it? There are great hitters and there are bad hitters. Among them, there are guys with tremendous plate coverage, but there are also high-ball hitters and low-ball hitters. Every part of the zone area is different, and every player is different, so we should expect that different players respond differently to pitches in different parts of the zone. How this relates to framing is that some guys might be better with receiving high pitches, while other guys might be better with receiving low pitches. Intuitively, why not? And thanks to some awesome updates at Baseball Savant, this couldn’t be much easier to examine.

Of course, there are lots of ways you could go with this. Probably, different catchers are differently able to receive different pitch types. Catchers are differently able to receive inside pitches and outside pitches, and there are differing abilities inside and outside of the zone. What follows is just going to look at high and low pitches on the border of or within the PITCHf/x strike zone. This is one of many ways to slice up the information.

So, who looks best on should-be high strikes, and who looks best on should-be low strikes? I collected data from the entire reliable PITCHf/x era, spanning 2008-2013. I set a minimum of 10,000 pitches, which yielded a sample of 102 different catchers. For low pitches within the zone, I selected the lowest three zone boxes. For high pitches within the zone, I selected the highest three zone boxes. This study ignores the middle three boxes, and also the areas outside of the PITCHf/x strike zone. All that information would be great, when tackling other questions.

The sample gave more than 200,000 called pitches in the lower three zones, of which more than 77% were called strikes. It gave more than 130,000 called pitches in the higher three zones, of which more than 85% were called strikes. In the sortable table now, I’m going to show you everything. These are all 102 catchers, their performances, and the differences between low-strike rate and high-strike rate.

Catcher Low# LowStr% High# HighStr% Diff
A.J. Ellis 2269 73.7% 1655 88.6% 15.0%
A.J. Pierzynski 4462 68.6% 3771 90.4% 21.8%
Adam Moore 564 70.4% 392 87.2% 16.9%
Alex Avila 3415 79.0% 2295 86.7% 7.7%
Bengie Molina 2336 69.6% 1844 85.1% 15.4%
Bobby Wilson 1063 82.7% 633 87.7% 5.0%
Brad Ausmus 749 76.8% 562 83.5% 6.7%
Brayan Pena 1792 78.7% 1175 89.5% 10.8%
Brett Hayes 658 78.3% 491 84.7% 6.5%
Brian McCann 4780 89.3% 2600 80.8% -8.4%
Brian Schneider 1767 72.5% 1149 85.5% 13.0%
Buster Posey 2285 89.4% 1721 88.1% -1.3%
Carlos Corporan 896 86.9% 500 83.8% -3.1%
Carlos Ruiz 4856 78.4% 3054 80.7% 2.4%
Carlos Santana 2161 71.6% 1643 89.5% 17.9%
Chris Coste 795 79.5% 570 77.9% -1.6%
Chris Iannetta 3577 68.7% 2456 88.5% 19.8%
Chris Snyder 2483 81.4% 1676 87.1% 5.7%
Chris Stewart 1520 87.1% 810 86.4% -0.7%
Corky Miller 556 80.2% 389 83.8% 3.6%
Craig Tatum 618 79.4% 432 85.9% 6.4%
David Ross 1986 87.1% 1205 82.3% -4.8%
Derek Norris 1133 86.8% 611 85.8% -1.0%
Devin Mesoraco 1090 80.3% 688 89.7% 9.4%
Dioner Navarro 2487 64.8% 2139 88.6% 23.8%
Drew Butera 1183 81.0% 778 86.4% 5.4%
Eli Whiteside 1243 86.1% 825 86.4% 0.3%
Erik Kratz 773 88.4% 494 88.1% -0.3%
Francisco Cervelli 1275 76.9% 785 84.5% 7.6%
George Kottaras 1536 77.0% 1030 85.6% 8.7%
Geovany Soto 3999 78.8% 2979 88.0% 9.2%
Gerald Laird 3055 68.5% 2028 85.1% 16.5%
Gregg Zaun 1245 81.8% 692 80.8% -1.0%
Guillermo Quiroz 568 70.8% 416 88.9% 18.2%
Hank Conger 996 88.9% 580 85.7% -3.2%
Hector Sanchez 633 80.3% 503 90.3% 10.0%
Henry Blanco 1650 80.4% 1037 81.5% 1.1%
Humberto Quintero 2403 79.4% 1538 82.5% 3.2%
Ivan Rodriguez 2485 76.1% 1634 80.2% 4.1%
J.P. Arencibia 2526 83.1% 1643 83.3% 0.2%
J.R. Towles 870 78.9% 478 75.9% -2.9%
Jarrod Saltalamacchia 3071 69.7% 2460 90.0% 20.2%
Jason Castro 1684 84.6% 1095 84.5% -0.1%
Jason Jaramillo 775 73.9% 475 81.1% 7.1%
Jason Kendall 3087 80.8% 1761 76.7% -4.1%
Jason LaRue 773 78.5% 493 75.1% -3.5%
Jason Varitek 2083 58.3% 1839 90.4% 32.0%
Jeff Mathis 3349 83.3% 1828 84.7% 1.4%
Jesus Flores 1396 78.2% 905 84.1% 5.9%
Jesus Montero 532 73.7% 438 85.2% 11.5%
Joe Mauer 3192 62.8% 2881 92.7% 29.9%
John Baker 1919 78.7% 1137 79.5% 0.8%
John Buck 4398 77.1% 2851 86.7% 9.6%
John Hester 562 82.0% 288 77.4% -4.6%
John Jaso 1614 78.4% 1075 83.5% 5.1%
Jonathan Lucroy 3342 91.4% 1638 83.9% -7.6%
Jorge Posada 1455 66.4% 976 84.7% 18.3%
Jose Lobaton 1207 86.5% 693 87.0% 0.5%
Jose Molina 2806 80.1% 2013 90.7% 10.6%
Josh Bard 1302 75.4% 772 82.8% 7.3%
Josh Thole 2036 84.2% 1402 87.0% 2.8%
Kelly Shoppach 2856 71.0% 1969 86.9% 15.9%
Kenji Johjima 1148 55.2% 848 88.6% 33.3%
Kevin Cash 642 67.9% 497 88.3% 20.4%
Koyie Hill 1602 75.3% 1108 82.7% 7.3%
Kurt Suzuki 5283 72.9% 3463 85.4% 12.5%
Landon Powell 757 71.7% 588 87.9% 16.2%
Lou Marson 1906 77.2% 1319 86.2% 9.0%
Martin Maldonado 960 89.9% 424 88.2% -1.7%
Matt Treanor 1806 68.2% 1315 85.6% 17.4%
Matt Wieters 4265 79.5% 3057 86.6% 7.2%
Michael McKenry 1137 79.1% 735 84.6% 5.6%
Miguel Montero 4518 88.7% 2543 85.3% -3.4%
Miguel Olivo 3487 74.9% 2177 86.1% 11.1%
Mike Napoli 2768 73.1% 1886 86.8% 13.7%
Mike Redmond 588 64.1% 440 89.1% 25.0%
Nick Hundley 3363 70.4% 2219 85.5% 15.2%
Omir Santos 660 68.0% 507 82.6% 14.6%
Paul Bako 941 79.0% 569 82.2% 3.3%
Ramon Castro 824 68.0% 689 87.8% 19.8%
Ramon Hernandez 2634 77.2% 1678 81.0% 3.8%
Raul Chavez 532 63.9% 424 85.1% 21.2%
Rob Brantly 743 78.1% 442 88.9% 10.9%
Rob Johnson 1618 66.4% 1138 88.3% 21.9%
Rod Barajas 3042 69.4% 2309 89.8% 20.4%
Ronny Paulino 1878 75.6% 1294 86.1% 10.5%
Russell Martin 5101 81.0% 3465 86.3% 5.2%
Ryan Doumit 3053 66.5% 1956 79.3% 12.9%
Ryan Hanigan 2854 82.8% 2115 89.1% 6.2%
Salvador Perez 1922 78.1% 1190 89.7% 11.6%
Taylor Teagarden 1134 73.3% 744 84.8% 11.5%
Tony Cruz 610 88.2% 382 84.8% -3.4%
Tyler Flowers 1170 83.3% 883 88.1% 4.8%
Victor Martinez 1645 71.2% 1184 84.6% 13.4%
Welington Castillo 1277 79.4% 715 84.6% 5.2%
Wil Nieves 1857 81.3% 1085 86.2% 4.9%
Wilin Rosario 1666 76.5% 995 88.0% 11.6%
Wilson Ramos 1438 80.8% 1023 91.2% 10.4%
Yadier Molina 5773 88.0% 3417 83.5% -4.5%
Yan Gomes 629 87.0% 454 89.2% 2.2%
Yasmani Grandal 565 92.4% 284 83.8% -8.6%
Yorvit Torrealba 3159 78.7% 1901 84.2% 5.6%

The king of low strikes has been Yasmani Grandal, although his sample is admittedly among the smallest. Following him are teammates Jonathan Lucroy and Martin Maldonado, and then Buster Posey’s a hair ahead of Brian McCann. At the other end, Kenji Johjima looks absolutely dreadful, although he hasn’t caught since 2009 and around then PITCHf/x had some more bugs. But Johjima was suspected to be a pretty lousy receiver. Jason Varitek and Joe Mauer are down there. Dioner Navarro’s still catching, and he’s had his issues with should-be low strikes.

And then you turn to high strikes, where suddenly Mauer reigns supreme. He’s got a big edge on Wilson Ramos, who has a smaller edge on Jose Molina, who has a smaller edge still on Varitek and A.J. Pierzynski. Turn this around, and Jason LaRue had some troubles. Carlos Ruiz looks the worst among prominent active types. Naturally, the bad end of the table features Ryan Doumit.

It’s interesting to see Mauer look so good up high and so bad down low. More generally, it’s interesting to observe that there doesn’t seem to be much of a relationship between low success and high success. The data isn’t entirely all over the map, but it’s pretty scattered about.

catchershighlow

The general trend is that the better a catcher is at receiving low strikes, the worse he is at receiving high strikes, and vice versa. It isn’t the strongest trend in the world, but it also makes sense that something like that would exist, and though I haven’t looked at it yet there’s probably a relationship here with catcher height. And given the sensitivity of good receiving, it’s probably quite difficult to prepare to receive and stick low pitches and high pitches. The required movements are going to be different. Catchers, individually, might be better at one than the other.

Included in the table is each catcher’s high-strike rate minus his low-strike rate. The greatest difference belongs to Johjima, then Varitek, then Mauer. So while Mauer isn’t a catcher anymore, as recently as last season he had the greatest difference between his ability to receive high and his ability to receive low. The lowest difference belongs to Grandal, who’s been better with low strikes than high strikes, by almost nine percentage points. Within the sample, 21 catchers have higher low-strike rates than high-strike rates. 35 catchers are within five percentage points of being even.

Given that Mauer and Grandal have been very different catchers, then, might we be able to see anything in the video? The answer is: this isn’t enough video. We can’t learn anything from one-pitch samples. But just for the hell of it, here’s Mauer catching a high strike and Grandal catching a high ball, and Mauer catching a low ball and Grandal catching a low strike.

MauerHigh.gif.opt

GrandalHigh.gif.opt

MauerLow.gif.opt

GrandalLow.gif.opt

Mauer, we know, is the taller catcher, by a few inches. It also seems like he has a bit of vertical glove drift as the pitcher is in his delivery, and it might be easier for him to continue that upward than to suddenly reverse direction. Grandal seems adept at catching the low ball in his palm, which helps to minimize the required glove movement with a low pitch. Grandal, in general, is pretty quiet — simply averaging low-strike rate and high-strike rate, Grandal would be tied for fourth in the table, behind Maldonado, Posey, and Erik Kratz. Based on Grandal’s playing time, receiving is a somewhat surprising strength of his.

There’s more to be done with this kind of data. There are a lot of different things that we can try to isolate. For now, this is a beginning attempt, with thanks again to Baseball Savant for being such an outstanding and user-friendly resource. There are most assuredly good framers and bad framers. It’s time to pay a little more attention to the subgroups.



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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.


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