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Catcher framing is the art of a catcher receiving a pitch in a way that makes it more likely for an umpire to call it a strike. This page breaks down the catcher’s view into eight zones around the strike zone and shows the called strike percentage of all non-swings in that zone. Strike Rate shows the cumulative total of all zones. Catcher Framing Runs converts strikes to runs saved on a .125 run/strike basis, and includes park and pitcher adjustments. To qualify, a catcher must receive 6 called pitches per team game.
How to say it: “In 2018, Jeff Mathis converted 55 percent of non-swing pitches into called strikes in the Shadow Zone, the best rate of any catcher in baseball.”
Qualifier: For catchers 6 called pitches (i.e., takes, or non-swings) in the ‘shadow zone’ per team game. For pitchers and batters 1.5 called pitches in the ‘shadow zone’ per team game. (The shadow zone is essentially the edges of the strike zone, roughly one ball width inside and one ball wide outside of the zone. See what that looks like here.)
For pitchers/batters: This shows the framing that occurred behind the plate while the player in question was pitching or hitting.


Rk. Catcher Team Pitches
Catcher
Framing
Runs
Strike
Rate
Zone 11
Zone 12
Zone 13
Zone 14
Zone 16
Zone 17
Zone 18
Zone 19
1 Narváez, Omar mil 2,980 10 49.2% 14.9% 47.6% 22.6% 65.4% 70.9% 35.1% 48.3% 27.5%
2 Heim, Jonah tex 1,993 9 51.9% 20% 58.8% 33.6% 65.4% 74% 32.8% 50.6% 26.1%
3 Murphy, Sean oak 2,874 9 49.8% 19.9% 48.8% 20.6% 63.6% 69.1% 32% 55.3% 27%
4 Trevino, Jose tex 2,379 8 51.8% 18.3% 57.8% 28% 65.4% 70.1% 37.8% 53.4% 31.1%
5 Zunino, Mike tb 2,705 7 51.7% 18.7% 56.4% 29% 56.7% 70.2% 26.6% 56.7% 34.3%
6 Stassi, Max ana 2,370 6 50% 22.2% 41.7% 19.7% 59.5% 75.8% 36% 55.1% 34.6%
7 Nido, Tomás nym 1,147 5 53.5% 20.3% 49.6% 26.2% 64.9% 79.9% 41.5% 51.4% 37.1%
8 Posey, Buster sf 2,883 5 49.2% 24.1% 51.9% 24.2% 68.1% 62.3% 33.9% 52.1% 19%
9 Barnhart, Tucker cin 2,991 5 49.6% 23.1% 45.7% 22.1% 65.1% 68.2% 34.7% 51.3% 28.6%
10 McGuire, Reese tor 1,730 4 48.9% 29.6% 48.1% 20.2% 66.8% 62.5% 32.8% 50.5% 25.2%
11 Realmuto, J.T. phi 3,335 4 48.7% 20.5% 45% 12% 69.6% 61.1% 38.9% 51.3% 27.3%
12 Garver, Mitch min 1,399 3 50.5% 14.9% 51% 33.8% 67.8% 69.5% 34.7% 52% 25.7%
13 Higashioka, Kyle nyy 1,631 3 50% 17.9% 46.4% 10.6% 67.1% 68.1% 43.8% 52% 33.5%
14 Piña, Manny mil 1,466 3 49% 15.2% 54.3% 24% 53.6% 71.2% 34.4% 56.3% 26.8%
15 Smith, Will la 3,445 2 49.2% 21.7% 45.5% 18.6% 65.3% 67.4% 28.9% 53.7% 31.4%
16 d'Arnaud, Travis atl 1,953 2 47.6% 18.9% 53.4% 19.6% 55.4% 61.9% 39.7% 55% 28.6%
17 Díaz, Elias col 2,628 2 47.1% 30.5% 42.8% 26.7% 73% 53.8% 43.6% 48.3% 14.4%
18 Vogt, Stephen atl 1,688 2 47.1% 14.7% 50.3% 29.6% 59.2% 72.2% 29.3% 40.7% 27.4%
19 Stallings, Jacob pit 2,982 2 48.1% 15% 45.3% 21.1% 61.6% 68.6% 28.1% 56.3% 30%
20 Jeffers, Ryan min 2,055 2 49.3% 22.2% 42.6% 22.5% 65.7% 67.9% 43.4% 55.4% 23.6%
21 Nola, Austin sd 1,388 2 49.3% 14.6% 45.9% 21.3% 59.6% 68.5% 38% 57.2% 28%
22 Raleigh, Cal sea 1,060 2 47.8% 29.5% 55.4% 28.1% 63.3% 61.3% 36.7% 45.2% 13.5%
23 Jansen, Danny tor 1,688 1 48.6% 29.3% 41.9% 11.3% 69.8% 60.8% 34.9% 52.3% 28%
24 Barnes, Austin la 1,361 1 50% 10.5% 33.7% 15.9% 72.2% 63.9% 35.4% 61% 36.2%
25 Vázquez, Christian bos 3,898 1 49.1% 23.8% 54.9% 31.3% 66.6% 66.1% 24.8% 48.7% 24.1%
26 Casali, Curt sf 1,574 1 49.4% 11.4% 33.8% 10% 66.1% 62.4% 41.2% 58.7% 28.6%
27 Plawecki, Kevin bos 1,168 1 47.3% 30.5% 49.6% 18.5% 71.1% 59.8% 22.9% 50.7% 17%
28 Grandal, Yasmani cws 2,105 1 48.3% 16.4% 54.1% 23.8% 64.2% 67.1% 36.1% 49.3% 25.3%
29 Maldonado, Martín hou 3,812 1 49% 17.5% 46.3% 21.2% 64.3% 66.5% 37% 53.6% 29.7%
30 Gallagher, Cam kc 1,032 1 50.2% 12.5% 52.8% 17.6% 68% 64.4% 37.9% 56.3% 32.6%
31 Kelly, Carson ari 2,443 1 48.3% 23.9% 49.4% 23.5% 62.4% 63.8% 35.2% 49.2% 25.7%
32 Nuñez, Dom col 2,145 1 47.1% 17.8% 35.3% 14.1% 67.1% 61.3% 44.7% 56.1% 21.7%
33 Hedges, Austin cle 2,356 1 47.3% 20% 48.8% 26% 61.1% 66.9% 38.8% 47.8% 23.6%
34 Knapp, Andrew phi 1,113 0 48.2% 11.1% 46.9% 17.4% 64.8% 66.1% 40.3% 47.5% 26.5%
35 León, Sandy mia 1,355 0 50.5% 33.3% 60.1% 33.3% 59.8% 68.6% 35% 49% 18.8%
36 Pérez, Roberto cle 1,116 0 48.5% 21% 55.2% 26.8% 65.6% 70.3% 26.5% 48.5% 25.8%
37 Alfaro, Jorge mia 1,577 0 48.5% 29.5% 58.8% 30.8% 64.1% 58.8% 28% 49.6% 20.1%
38 Gomes, Yan oak 2,618 0 46.9% 20.9% 47.9% 18.7% 70% 59.9% 29.3% 44% 26%
39 Varsho, Daulton ari 1,068 -1 47.6% 20.8% 47.8% 25% 67% 62.4% 38.6% 49% 16.5%
40 Castro, Jason hou 1,176 -1 48% 15.4% 45.4% 30.3% 64.5% 69.9% 29.7% 53.2% 22.9%
41 Kirk, Alejandro tor 1,057 -1 47.1% 21.8% 36.9% 17.6% 56.3% 56.5% 41% 61.4% 27.9%
42 Contreras, Willson chc 3,157 -1 49% 21.4% 56.1% 27.9% 65.9% 64.5% 27.8% 49.8% 19.8%
43 Murphy, Tom sea 2,279 -1 47.2% 24.2% 46.2% 15% 70.3% 62.2% 32.3% 52% 18.9%
44 Stephenson, Tyler cin 2,004 -1 48.6% 17.6% 45.3% 24.6% 67.2% 65.6% 29.4% 49.2% 29.7%
45 Contreras, William atl 1,317 -2 45.3% 19% 41.1% 21% 58.3% 56.5% 30.4% 53.1% 27%
46 Pérez, Michael pit 1,640 -2 46.1% 14.5% 58.1% 29.9% 63.7% 63% 27.4% 43.4% 14.9%
47 Caratini, Victor sd 2,811 -3 46.3% 16.1% 40.9% 15.5% 55.8% 67.5% 33.1% 48.9% 33.4%
48 Rogers, Jake det 1,004 -3 44.4% 14.1% 46.6% 17.2% 58.7% 62.8% 26.2% 52% 22.1%
49 McCann, James nym 2,601 -3 47.9% 12.4% 48% 17.5% 56.4% 73.8% 23.8% 51.7% 29.9%
50 Molina, Yadier stl 3,473 -3 48.4% 24.2% 58.6% 30.9% 64% 68.2% 32% 40.6% 25.1%
51 Knizner, Andrew stl 1,389 -4 43.8% 22.2% 45.1% 28.8% 57.8% 71.1% 27% 35.3% 22.1%
52 Wynns, Austin bal 1,304 -5 42.9% 19.3% 50.7% 19.5% 65.6% 56.9% 23.8% 36.8% 14.3%
53 Mejía, Francisco tb 1,704 -5 44.7% 14.6% 47.8% 20% 60% 64.7% 23.7% 46% 23.6%
54 Haase, Eric det 1,759 -5 44.8% 21.1% 42.8% 16% 63.2% 64.2% 28.9% 42.4% 17.9%
55 Suzuki, Kurt ana 1,963 -5 45.3% 19% 40.8% 16.5% 64.6% 67.2% 27.5% 45.8% 20.3%
56 Sánchez, Gary nyy 2,807 -6 45.9% 22% 44.4% 14.4% 64.3% 70.1% 23.2% 45.9% 29.1%
57 Severino, Pedro bal 3,132 -10 43.7% 17.3% 47.7% 18.4% 63.9% 59.7% 26.8% 45.7% 19%
58 Collins, Zack cws 1,708 -10 41.4% 21.9% 52.6% 19.4% 71% 48.8% 19.6% 36.1% 13.9%
59 Perez, Salvador kc 3,576 -18 44.8% 25.9% 53.9% 28% 65.1% 60.2% 28.5% 36.1% 19.4%