The system used to evaluate catchers is complex and I'm not going to rehash the whole thing here. If you want to see the details, you can read my earlier article. I do want to give credit to others who inspired me with similar work in the past: Sean Smith, Justin Inaz, Matt Klaasen and Mike Rogers.
First, remember that less than three months of defensive data is a relatively small sample size so you should use caution in interpreting the results. Also keep in mind that these numbers do not capture everything that a catcher does. For example, they say nothing about game calling or understanding of pitcher abilities and tendencies.
Another thing that is not included is the pitch framing data which has been one of the most interesting advances in the sabermetric world over the last couple of years. Mike Fast, formerly of Baseball Prospectus, and others have done some great work on that facet of catcher defense, but it is not publicly available at this time. So, I am only going to evaluate catchers based on what we can most easily measure - controlling the running game, pitch blocking and avoiding errors.
Table 1 contains data for all catchers with at least 280 innings through July 1 (I chose 280 so that Pena would be included). That covers most of the starting catchers in the majors and some frequently used backups. The CSRuns column gives us an estimation of how many runs each catcher saved/cost his team compared to the average catcher by controlling the running game. This statistic is based on stolen bases against and caught stealing.
Dodgers catcher A.J. Ellis is the MLB CSRuns leader with an estimated 6.5 runs saved over an average catcher. A negative sign before a number indicates that a catcher cost his team runs. The worst receiver in this category is Chris Iannetta who has cost the Angels an estimated -5.8 runs. Avila (-1.7) is in the bottom third and Pena (0.3) is near average.
The next column (WPPBRuns) tells us how many runs catchers saved/cost their teams with pitch blocking or preventing passed balls and wild pitches. Number one is Cardinals backstop Yadier Molina with 4.5 runs saved. Conversely, Carlos Santana has cost the Indians about five runs (-4.6). Avila is near average (-0.3) and Pena is in the top ten (1.2).
The TERuns column tells us about throwing errors. There is not a lot of variation between catchers here, but Russell Martin of the Pirates, A.J. Pierzynski of the Rangers and Iannetta lead with 0.7 runs saved. Wellington Castillo has cost the Cubs an estimated -0.9 runs on throwing errors. Avila checks in at 0.3 and Pena 0.1.
The FERuns column indicates how many runs catchers have saved/cost their teams with fielding errors. Again, there is not a lot of variation with numbers ranging from -0.4 to 0.6. There are too many ties to list all the leaders and trailers, but Pena (+0.2) has a slight edge over Avila (-0.2).
The final column (CatchRuns) is the sum of the previous four columns. It tells us how many runs catchers saved/cost their teams on the above items combined. The leader is Yadier Molina who has saved St.Louis more than seven runs (7.4). The worst is Santana costing the Pirates almost eight (-7.7) runs. Pena is 10th in MLB with 1.8 runs saved while Avila is 25th at -1.9.
In summary, Avila has had trouble throwing out runners (an area where he has done well in the past) and is in the middle of the pack on other numbers. Pena has been particularly good at pitch blocking and close to average in other areas. Based on these measures (which don't cover everything a catcher does), Pena has been better than Avila overall when accounting for controlling the running game, blocking pitching and avoiding errors.
Table 1: Catcher Runs Saved/Cost through July 1, 2012
Team | Inn | CSRuns | WPPBRuns | TERuns | FERuns | CatchRuns | |
Yadier Molina | STL | 650 | 2.8 | 4.5 | 0.6 | -0.5 | 7.4 |
A.J. Ellis | LAD | 461 | 6.5 | 0.3 | 0.4 | -0.2 | 6.9 |
Matt Wieters | BAL | 615 | 3.1 | 2.1 | 0.6 | -0.6 | 5.1 |
Russell Martin | PIT | 529 | 4.7 | -0.8 | 0.7 | 0.4 | 5.0 |
Joe Mauer | MIN | 449 | 1.9 | 2.6 | 0.3 | -0.2 | 4.7 |
John Buck | NYM | 595 | 1.9 | 2.6 | 0.3 | -0.1 | 4.7 |
Ryan Hanigan | CIN | 349 | 3.3 | 0.2 | 0.2 | 0.3 | 4.0 |
Chris Stewart | NYY | 401 | 2.4 | 0.0 | 0.6 | 0.3 | 3.3 |
Brian McCann | ATL | 315 | 0.4 | 2.0 | 0.4 | 0.2 | 3.1 |
Brayan Pena | DET | 282 | 0.3 | 1.2 | 0.1 | 0.2 | 1.8 |
Rob Brantly | MIA | 416 | 1.9 | -0.0 | -0.3 | -0.2 | 1.4 |
Nick Hundley | SDP | 433 | 1.1 | 0.5 | -0.5 | 0.3 | 1.3 |
Erik Kratz | PHI | 346 | -1.1 | 1.5 | 0.2 | 0.3 | 0.9 |
Buster Posey | SFG | 556 | -2.0 | 1.8 | 0.5 | 0.4 | 0.8 |
Derek Norris | OAK | 441 | -0.9 | 0.9 | 0.3 | 0.3 | 0.6 |
Kelly Shoppach | SEA | 291 | 1.7 | -1.4 | 0.1 | 0.2 | 0.6 |
Devin Mesoraco | CIN | 356 | -1.0 | 1.1 | -0.3 | 0.3 | 0.0 |
Salvador Perez | KCR | 547 | 1.6 | -1.4 | -0.6 | 0.4 | -0.0 |
Miguel Montero | ARI | 645 | -0.5 | -0.3 | 0.6 | -0.0 | -0.2 |
Kurt Suzuki | WSN | 527 | -4.1 | 3.7 | -0.1 | -0.1 | -0.6 |
A.J. Pierzynski | TEX | 488 | -2.3 | 0.6 | 0.7 | 0.4 | -0.6 |
Tyler Flowers | CHW | 525 | -0.6 | -1.1 | -0.1 | 0.4 | -1.4 |
Welington Castillo | CHC | 533 | 0.3 | -0.2 | -0.9 | -0.6 | -1.4 |
Jonathan Lucroy | MIL | 531 | -1.2 | -0.2 | 0.5 | -0.6 | -1.6 |
Alex Avila | DET | 418 | -1.7 | -0.3 | 0.3 | -0.2 | -1.9 |
Wilin Rosario | COL | 517 | 0.8 | -2.6 | -0.4 | -0.1 | -2.3 |
Jose Lobaton | TBR | 366 | -2.5 | -0.1 | -0.1 | 0.3 | -2.5 |
Jarrod Saltalamacchia | BOS | 519 | -2.7 | -0.1 | -0.4 | 0.4 | -2.8 |
Jason Castro | HOU | 513 | -1.7 | -1.3 | 0.2 | -0.1 | -3.0 |
J.P. Arencibia | TOR | 590 | -1.5 | -1.9 | 0.3 | -0.1 | -3.2 |
Jose Molina | TBR | 374 | -2.0 | -3.4 | -0.3 | -0.2 | -5.9 |
Chris Iannetta | LAA | 532 | -5.8 | -0.7 | 0.7 | -0.6 | -6.4 |
Carlos Santana | CLE | 429 | -3.2 | -4.6 | 0.3 | -0.2 | -7.7 |
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