2009 Catcher Defense: Filling in the Holes (yet again)
Even if you aren't a FanGraphs junkie like myself and so many others, if you spend any time there looking at the WAR rankings in order to, say, evaluate who should be the 2009 MVP candidates, you've undoubtedly noticed (due to Joe Mauer's incredible season) that currently, they do not have a system in place to evaluate catcher fielding. Hey, no one's perfect, and knowing Mr. Appleman and his crew, they're probably waiting until they get a system they're happy with before they implement something.
I don't make any great claim to originality here, as you will see if you read on, but for those of you who want a rough idea of how different catchers "measure up" behind the plate for your MVP arguments or to settle the eternal "I wonder just how bad a guy can be at blocking pitches," question, here is a rough attempt to evaluate every catcher's defensive 2009.
Choosing a Methodology (With Qualifications)
Before I go any further, I should make clear that for the purposes of this post that I assume that it is well-established that the differences between catchers with regard to gamecalling (as expressed in, e.g., "catcher's ERA") are negligible, and thus such issues will not be discussed in this post. When I discuss catcher defense, like most others, I will be discussing preventing stolen bases, blocking pitches, etc.
One of the difficulties with evaluating catcher defense with regard to even these issues is that, much more than with other fielding positions, the catcher's performance is dependent on another player -- namely, the pitcher. No matter now strong or weak the catcher's arm is, he can't escape the reality that he depends on the pitcher's skill with regard to holding runners, quickness to the plate, etc. While the catcher's skill with regard to blocking pitches that are off the mark is clearly important, catching Tim Wakefield poses a unique challenge (just ask Josh Bard). And so on.
For these reasons, probably the best way of measuring catcher defense is Tom Tango's WOWY (With or Without You) method of defensive evaluation as detailed the 2008 Hardball Times Annual. You can read about the details in the links provided. Versions of WOWY for catchers have also been done by Brian Cartwright and Dan Turkenkopf. I would do it that way if I could. The main issue is that 1) it's pretty complicated, and beyond my present capabilities, and 2) it requires something like Retrosheet, which isn't available until after the World Series is over, so even if I could do it, I couldn't get the numbers during the season of even now...
In lieu of that, I'm going to be doing something much simpler, which, while not quite as good, is, I think, pretty decent. Just keep in mind the qualifications about not adjusting for particular pitchers made above.
The Method Used Here
For non-WOWY catcher defense, the basic idea is to 1) choose what events you're going to deal with, 2) determine each catchers performance with respect to league average, and 3) decide the run value of each event. Like I said, this post isn't that original: very similar methods are used/suggested by Rally and chuckb. I have most closely modeled my "catcher defense metric" on the method outlined by the Amazing Justin Inaz (now a regular at Beyond the Box Score). His weights for each event seem about right to me, and the general principles are sound. One modification I've made (I'll note the other as I go along) is in the denominator of some stats. when Justin did his version, he was using THT's catcher defense stats, which only recorded catcher innings. Since then, the new Baseball Reference has come out with more detailed individual catcher defense stats, including plate appearances. While the difference isn't huge, I feel that it's more accurate to use plate appearances (batters faced) as the denominator for things like pitch blocking and errors, since while every inning (other than some ninth [or later] innings) has 3 outs, the catcher has to be out there whether there are 3 or 10 batters during those three outs. Otherwise, I'm pretty close to Justin's method, and you can read there for more details.
Stolen Bases/Caught Stealing: First, we figure out the league rate for caught stealing. One cool thing about the new Baseball Reference is that it separates out the catcher caught stealings from the pitcher pickoffs, so we can exclude the pickoffs (not under the catcher's control) from the equation. So we total the CSctch +SB to get total stolen base attempts (SBA) and then to total CSctch/total SBA for the lgCS rate. We use the weight of .63 runs for each caught stealing, which represents the average linear weight of the caught stealing (.44 runs) plus the weight of the stolen base not achieved (.19 runs). The formula for runs above/below average for each catcher is thus (CS - (lgCSrate) * SBA) * 0.63.
Wild pitches/passed balls: The league rate is (WPlg + PBlg)/lgPA. The linear weight for each passed ball/wild pitch is 0.28 runs, which we make negative since the more WP/PBs a catcher has, the worse his defense is. The formula for each player is ((WP + PB) - (lgWPPBrate * PA)) * -0.28.
Errors: Justin accounts for two kinds of errors -- throwing errors and fielding errors. Baseball Reference also includes catching errors (on throws). I've assimilated catching errors to fielding errors. There are separate linear weights for throwing errors (-0.48) and fielding errors (-0.75). The method is the same as above. Get the league rate, then see how far over/under the player is. For throwing errors: (TE - (lgTErate * PA)) * -0.48. Fielding errors: (FE - (lgFErate * PA)) * -0.75.
Then you just add them all up to get the total runs above/below average. It's not perfect, and hopefully, there will be some improved options soon, but the results do seem to reflect reality. I thought about coming up with a "rate" version like UZR/150, but that isn't as simple as prorating for innings caught/PA -- one needs to normalize each sort of event separately, the chart is confusing enough as it is. For now, this is just a value measurement of what each player did this season. But before the big chart, let's take a look at some standout performances. I've rounded to one decimal place to tone down the illusion of great precision.
Standouts and "Standouts"
Caught Stealing: Gerald Laird of the Tigers dominates here at + 11 runs. The next closest player was Johjima at +6.5 runs, then Koyie Hill at +5.4. Now, Laird had a lot more time behind the plate to accomplish that, but one wonders why teams kept trying to run on him. At the bottom of the rankings for CS runs are fan favorite A.J. Pierzynski at -4.5 runs, Yorvit Torrealbea at -5.1 runs, and blowing away the field is defensive legend and Boston Red Sox stalwart Jason Varitek, at -10.7 runs.
Pitch blocking: As for the actual "catching" part of catching, the best in baseball this season was the Phillies' Carlos Ruiz, at +5.6 runs. Jason Varitek gains some of his cred back here at +5.1 runs (I wonder what it would be if he had to catch Wakefield). The Man, the Myth, the Legend, Matt Wieters may not have quite cemented his Hall of Fame credentials, but he can block a pitch decently at +3.9 runs. The players are grouped by their performance for separate teams, so I just noticed that one of my favorites, Gregg Zaun, was +2.9 for the Orioles, and +1.4 for the Rays, which puts him at +4.3, or the real number 3. Maybe Baltimore let him go to soon -- he definite brings his Z-Game when he's blocking pitches. At the bottom of the rankings, Jorge Posada, Josh Bard, and and Rob Johnson (why did he get so much playing time?) are all tied at -3.8, Russell Martin (?!) is at -5.1 (although he saw more PA than just about any other catcher on the list). And bringing up the rear... this is going to be a shock, prepare yourself... Miguel Olivo, at -7.8. Think about that -- it's only -0.28 runs per WP/PB. Sure, he's "only" -2.7 runs worse thatn Martin, but Martin saw almost 1400 more PA than Olivo this season. This shows we're on the right track, as Brian Cartwright's WOWY study done previous to this season showed Olivo to be historically terrible at blocking the plate. Another great job of scouting by Dayton Moore and the Process Servers.
Throwing errors: Given that there's so little variance with this stat, there's probably less of a repeatable "skill" when it comes to this stuff. In other words, if we were doing a projection, there would be much more regression for TE and FE runs than others. Still, we're measuring value here, so it goes on the record. Gerald Laird leads the pack again at +1.5 runs, followed closely by Yorvit Torrealbea at +1.3 the Kurt Suzuki and Henry Blanco at +1.2 each. At the bottom, we have Rod Barajas (otherwise a good defensive catcher) at -1.6, Miguel Montero at -1.7, and sadly, my boy John Buck at -3.0. He had some really, really horrible games at the beginning of the season. At least he can move two inches to his right or left.
Fielding errors: Jason Kendall justifies his major league status with a +1.0 here, as does Russell Martin. Rod Barajas shows he's Joe Mauer's equal, as they both have +0.8. Mike Napoli is -1.6, the traitorous Paul Bako is at -2.0, and Brian McCann, who's decent at everything else, has an anomalous -3.6.
The Best and The Worst, and Others of Note: One Man, Five Tools, Indeed: Gerald Laird blows away the field at +13.3 runs. The Tigers made a conscious effort to improve their defense in the offseason, and whatever else happened, with Laird they certainly succeeded. At 0.9 WAR player without defense, with it he's about 2.2. Kenji Johjima might be overpaid, but at +8.8 runs defensively, he seems a bit less ridiculous. Dave Ross and Ryan Hanigan come in at +7.0 runs. Yadier Molina was very good, if not quite as godlike as some would think, but +6.6 runs is nothing to sneeze at, and makes him about a 4 WAR player this season. Joe Mauer's +4.3 is good, but he's not the best in baseball or the league, and that certainly doesn't make him a better MVP candidate than Zack Greinke. Matt Wieters is +2.5, so he'll probably stick at catcher, at least for a while.
Victor Martinez isn't as bad as some would say, being only -2.2 betweeen Boston and Cleveland. Jeff Mathis is a "great" defensive backup at -2.0. Or how about Jose Molina at -1.1 backing up Jorge Posada at -5.9? Giants cleanup hitter Bengie Molina is at -3.4
As for the bottom ranks... Josh Bard is at -7.3, the human swing machine, Miguel Olivo, is at -8.8, and the Living Stereotype, Mike Napoli, is at -9.7. No wonder the Angels think Mathis is a good defender.
The Big Chart
That's it. Keep in mind (along with the limitations mentioned above) that current season performance is not the same thing as true talent. I hope you will find this handy when trying to get various catchers' "real" WAR, and let others know about it. Let the arguments begin!
| Rank | Player | Tm | PA | CSRuns | WP/PBRns | TERns | FERns | TotalRuns |
| 1 | Gerald Laird | DET | 4842 | 11.0 | 0.6 | 1.5 | 0.2 | 13.3 |
| 2 | Kenji Johjima | SEA | 2597 | 6.5 | 0.9 | 0.9 | 0.5 | 8.8 |
| 3 | Dave Ross | ATL | 1517 | 4.8 | 1.6 | 0.3 | 0.3 | 7.0 |
| 4 | Ryan Hanigan | CIN | 2913 | 4.7 | 0.7 | 1.0 | 0.5 | 7.0 |
| 5 | Yadier Molina | STL | 5045 | 3.2 | 2.6 | 0.7 | 0.2 | 6.6 |
| 6 | Koyie Hill | CHC | 2755 | 5.4 | 0.2 | 0.0 | 0.5 | 6.1 |
| 7 | Henry Blanco | SDP | 2278 | 2.9 | 1.2 | 1.2 | 0.4 | 5.7 |
| 8 | Carlos Ruiz | PHI | 3887 | -1.5 | 5.6 | 0.6 | 0.7 | 5.4 |
| 9 | Raul Chavez | TOR | 1818 | 3.6 | 0.5 | 0.0 | 0.3 | 4.4 |
| 10 | Joe Mauer | MIN | 4153 | 0.5 | 2.4 | 0.7 | 0.8 | 4.3 |
| 11 | Rod Barajas | TOR | 4298 | 2.6 | 2.5 | -1.6 | 0.8 | 4.2 |
| 12 | Brian Schneider | NYM | 1976 | 1.6 | 1.2 | 1.0 | -0.4 | 3.5 |
| 13 | Ramon Hernandez | CIN | 2069 | 0.6 | 1.7 | 0.6 | 0.4 | 3.3 |
| 14 | Francisco Cervelli | NYY | 1024 | 2.0 | 0.8 | 0.0 | 0.2 | 3.1 |
| 15 | Lou Marson | CLE | 572 | 1.6 | 1.0 | -0.2 | 0.1 | 2.5 |
| 16 | Eliezer Alfonzo | SDP | 1128 | 2.2 | 0.3 | 0.6 | -0.5 | 2.5 |
| 17 | Matt Wieters | BAL | 3384 | -1.1 | 3.9 | -0.2 | -0.1 | 2.5 |
| 18 | Ronny Paulino | FLA | 2609 | 2.1 | -0.4 | 0.4 | 0.5 | 2.5 |
| 19 | Landon Powell | OAK | 1205 | 2.8 | 0.5 | -0.3 | -0.5 | 2.4 |
| 20 | Taylor Teagarden | TEX | 2180 | 3.1 | 0.9 | -1.3 | -0.3 | 2.4 |
| 21 | Omir Santos | NYM | 3092 | -0.7 | 2.8 | 1.1 | -0.9 | 2.4 |
| 22 | Ivan Rodriguez | HOU | 3327 | 1.4 | 0.4 | -0.2 | 0.6 | 2.2 |
| 23 | Chris Iannetta | COL | 3362 | 0.1 | 1.9 | -0.7 | 0.6 | 2.0 |
| 24 | Gregg Zaun | BAL | 1974 | 0.2 | 2.9 | -0.9 | -0.4 | 1.8 |
| 25 | Humberto Quintero | HOU | 1893 | 2.4 | 0.4 | -1.4 | 0.4 | 1.7 |
| 26 | Corky Miller | CIN | 702 | 0.4 | 0.8 | 0.4 | 0.1 | 1.7 |
| 27 | Ramon Castro | NYM | 822 | 1.8 | 0.6 | 0.4 | -1.3 | 1.4 |
| 28 | Mike Rivera | MIL | 1227 | -0.2 | 0.5 | 0.6 | 0.2 | 1.3 |
| 29 | Lou Marson | PHI | 245 | 0.7 | 0.4 | 0.1 | 0.0 | 1.2 |
| 30 | Jason LaRue | STL | 1139 | 0.0 | 0.9 | 0.1 | 0.2 | 1.2 |
| 31 | Craig Tatum | CIN | 749 | 0.5 | 0.6 | -0.1 | 0.1 | 1.1 |
| 32 | Chris Coste | PHI | 925 | -1.0 | 1.4 | 0.5 | 0.2 | 1.0 |
| 33 | Dusty Ryan | DET | 337 | 0.4 | 0.4 | 0.2 | 0.1 | 1.0 |
| 34 | Kurt Suzuki | OAK | 5222 | -3.4 | 3.6 | 1.2 | -0.5 | 0.9 |
| 35 | Michel Hernandez | TBR | 1140 | 0.1 | 1.1 | 0.1 | -0.5 | 0.8 |
| 36 | Geovany Soto | CHC | 3607 | 2.2 | -1.1 | 0.4 | -0.8 | 0.7 |
| 37 | Clint Sammons | ATL | 135 | 1.0 | -0.5 | 0.1 | 0.0 | 0.6 |
| 38 | Jamie Burke | WSN | 155 | 0.3 | 0.1 | 0.1 | 0.0 | 0.6 |
| 39 | Brad Ausmus | LAD | 1086 | -0.1 | -0.1 | 0.6 | 0.2 | 0.6 |
| 40 | Ivan Rodriguez | TEX | 961 | 1.4 | 0.1 | -0.5 | -0.6 | 0.5 |
| 41 | Matt Pagnozzi | STL | 40 | 0.3 | 0.1 | 0.0 | 0.0 | 0.5 |
| 42 | Chris Gimenez | CLE | 245 | -0.1 | 0.4 | 0.1 | 0.0 | 0.5 |
| 43 | Pablo Sandoval | SFG | 113 | 0.3 | 0.0 | 0.1 | 0.0 | 0.4 |
| 44 | Buster Posey | SFG | 179 | 0.3 | -0.1 | 0.1 | 0.0 | 0.4 |
| 45 | Dioner Navarro | TBR | 4097 | 0.5 | -0.3 | 0.2 | 0.0 | 0.4 |
| 46 | J.R. Towles | HOU | 538 | -1.0 | 0.9 | 0.3 | 0.1 | 0.3 |
| 47 | Wyatt Toregas | CLE | 710 | -0.5 | 0.3 | 0.4 | 0.1 | 0.3 |
| 48 | Alex Avila | DET | 709 | 0.4 | -0.6 | 0.4 | 0.1 | 0.3 |
| 49 | Steve Holm | SFG | 101 | 0.5 | -0.3 | 0.1 | 0.0 | 0.3 |
| 50 | Edwin Bellorin | COL | 69 | 0.0 | 0.2 | 0.0 | 0.0 | 0.2 |
| 51 | Dusty Brown | BOS | 49 | 0.0 | 0.1 | 0.0 | 0.0 | 0.2 |
| 52 | Jose Lobaton | SDP | 205 | 0.2 | 0.3 | -0.4 | 0.0 | 0.1 |
| 53 | Jason Jaramillo | PIT | 2347 | 0.2 | 0.2 | -0.7 | 0.4 | 0.1 |
| 54 | Jake Fox | CHC | 30 | 0.0 | 0.1 | 0.0 | 0.0 | 0.1 |
| 55 | Carlos Corporan | MIL | 6 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 56 | Ryan Budde | LAA | 38 | -0.1 | 0.1 | 0.0 | 0.0 | 0.0 |
| 57 | A.J. Ellis | LAD | 119 | -0.1 | 0.0 | 0.1 | 0.0 | 0.0 |
| 58 | Guillermo Rodriguez | BAL | 72 | 0.0 | -0.1 | 0.0 | 0.0 | 0.0 |
| 59 | Bobby Wilson | LAA | 98 | -0.1 | 0.0 | 0.1 | 0.0 | -0.1 |
| 60 | David Freese | STL | 10 | -0.1 | 0.0 | 0.0 | 0.0 | -0.1 |
| 61 | Kevin Cash | NYY | 297 | -0.3 | 0.0 | 0.2 | 0.1 | -0.1 |
| 62 | Chris Coste | HOU | 628 | -1.2 | 0.6 | 0.3 | 0.1 | -0.2 |
| 63 | Adam Moore | SEA | 241 | -0.1 | -0.2 | 0.1 | 0.0 | -0.2 |
| 64 | Corky Miller | CHW | 383 | -0.7 | 0.2 | 0.2 | 0.1 | -0.2 |
| 65 | Gregg Zaun | TBR | 928 | -1.5 | 1.4 | 0.5 | -0.6 | -0.2 |
| 66 | Jarrod Saltalamacchia | TEX | 3169 | -0.5 | 1.6 | -1.3 | -0.2 | -0.3 |
| 67 | Wil Nieves | WSN | 2538 | 1.4 | -0.4 | -1.1 | -0.3 | -0.3 |
| 68 | John Hester | ARI | 255 | -0.4 | -0.1 | 0.1 | 0.0 | -0.3 |
| 69 | Paul Hoover | PHI | 55 | -0.3 | -0.1 | 0.0 | 0.0 | -0.4 |
| 70 | Guillermo Quiroz | SEA | 161 | -0.1 | -0.4 | 0.1 | 0.0 | -0.4 |
| 71 | Dane Sardinha | DET | 404 | -0.5 | -0.3 | 0.2 | 0.1 | -0.5 |
| 72 | Shawn Riggans | TBR | 156 | -0.3 | 0.1 | -0.4 | 0.0 | -0.5 |
| 73 | Matt Treanor | DET | 157 | -0.6 | -0.1 | 0.1 | 0.0 | -0.6 |
| 74 | Kevin Richardson | TEX | 70 | -0.3 | -0.4 | 0.0 | 0.0 | -0.6 |
| 75 | Victor Martinez | CLE | 1991 | -2.7 | 0.7 | 1.0 | 0.4 | -0.6 |
| 76 | Josh Thole | NYM | 551 | -0.1 | -0.5 | -0.2 | 0.1 | -0.6 |
| 77 | Tyler Flowers | CHW | 123 | -0.3 | -0.5 | 0.1 | 0.0 | -0.7 |
| 78 | Michael Barrett | TOR | 174 | -0.3 | -0.6 | 0.1 | 0.0 | -0.8 |
| 79 | Luke Carlin | ARI | 176 | -0.9 | -0.1 | 0.1 | 0.0 | -0.8 |
| 80 | Kyle Phillips | TOR | 186 | -0.2 | -0.3 | -0.4 | 0.0 | -0.9 |
| 81 | Jesus Flores | WSN | 980 | 0.4 | -1.2 | 0.5 | -0.6 | -0.9 |
| 82 | Jose Molina | NYY | 1533 | -0.9 | -0.9 | 0.3 | 0.3 | -1.1 |
| 83 | Jamie Burke | SEA | 424 | 0.7 | -0.8 | 0.2 | -1.4 | -1.3 |
| 84 | Kelly Shoppach | CLE | 3042 | -0.7 | -0.9 | -0.4 | 0.6 | -1.5 |
| 85 | Victor Martinez | BOS | 1173 | -1.5 | 1.0 | -1.3 | 0.2 | -1.6 |
| 86 | Ramon Castro | CHW | 975 | -1.8 | 1.0 | -0.9 | 0.2 | -1.6 |
| 87 | Rob Johnson | SEA | 2927 | 2.4 | -3.8 | 0.5 | -1.0 | -1.8 |
| 88 | Ryan Doumit | PIT | 2754 | -1.0 | 0.5 | -0.5 | -1.0 | -2.0 |
| 89 | Chad Moeller | BAL | 1116 | -3.1 | 0.2 | 0.6 | 0.2 | -2.1 |
| 90 | Jeff Mathis | LAA | 2902 | 0.8 | -1.0 | -0.9 | -1.0 | -2.1 |
| 91 | Paul Phillips | COL | 502 | -1.8 | -0.3 | -0.2 | 0.1 | -2.3 |
| 92 | Mike Redmond | MIN | 1513 | -4.1 | 0.5 | 0.8 | 0.3 | -2.5 |
| 93 | Robinzon Diaz | PIT | 1268 | -1.0 | -1.6 | -0.3 | 0.2 | -2.6 |
| 94 | Yorvit Torrealba | COL | 2438 | -5.1 | 0.5 | 1.3 | 0.5 | -2.9 |
| 95 | Brayan Pena | KCR | 1012 | -0.5 | -3.1 | 0.5 | 0.2 | -2.9 |
| 96 | Brian McCann | ATL | 4763 | -0.7 | 1.8 | -0.4 | -3.6 | -3.0 |
| 97 | Chris Snyder | ARI | 1962 | -1.3 | -3.0 | 1.0 | 0.4 | -3.0 |
| 98 | Eli Whiteside | SFG | 1348 | 1.0 | -2.2 | -0.7 | -1.2 | -3.2 |
| 99 | John Baker | FLA | 3919 | -2.6 | -0.5 | -0.9 | 0.7 | -3.2 |
| 100 | Paul Bako | PHI | 1328 | -0.7 | -0.3 | -0.3 | -2.0 | -3.3 |
| 101 | Russell Martin | LAD | 5205 | 1.5 | -5.1 | -0.7 | 1.0 | -3.3 |
| 102 | Bengie Molina | SFG | 4582 | -1.0 | -2.6 | 0.9 | -0.6 | -3.4 |
| 103 | Jason Varitek | BOS | 4133 | -10.7 | 5.1 | 0.7 | 0.8 | -4.1 |
| 104 | George Kottaras | BOS | 1166 | -1.8 | -3.0 | 0.1 | 0.2 | -4.4 |
| 105 | Jason Kendall | MIL | 5296 | -2.9 | -1.5 | -1.1 | 1.0 | -4.5 |
| 106 | John Buck | KCR | 1693 | -2.0 | -0.1 | -3.0 | 0.3 | -4.8 |
| 107 | A.J. Pierzynski | CHW | 4927 | -4.5 | -0.8 | 1.1 | -0.6 | -4.8 |
| 108 | Jose Morales | MIN | 812 | -2.1 | -1.7 | -0.1 | -1.3 | -5.2 |
| 109 | Jorge Posada | NYY | 3653 | -0.8 | -3.8 | -0.5 | -0.8 | -5.9 |
| 110 | Miguel Montero | ARI | 4094 | -1.4 | -3.4 | -1.7 | 0.0 | -6.5 |
| 111 | Nick Hundley | SDP | 2877 | -3.7 | -2.0 | -0.9 | -0.2 | -6.8 |
| 112 | Josh Bard | WSN | 2902 | -2.8 | -3.8 | -0.4 | -0.2 | -7.3 |
| 113 | Miguel Olivo | KCR | 3821 | 0.7 | -7.8 | -0.9 | -0.8 | -8.8 |
| 114 | Mike Napoli | LAA | 3468 | -4.3 | -3.1 | -0.6 | -1.6 | -9.7 |
9 recs |
56 comments
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Comments
Yeah, cause Mauer needed another half win tacked onto his MVP case.
by cwyers on Oct 13, 2009 9:44 AM PDT reply actions 0 recs
he gives most of it back on the bases
about 3 runs
I'm not a sabermetrician, but I do play one at Driveline Mechanics.
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by devil_fingers on Oct 13, 2009 11:55 AM PDT up reply actions 0 recs
Nice work
I’m calculating catcher defense as I described in that link for the power rankings, though I haven’t been posting the data for individual players. Since I think the rest of our methods are the same, here are data from my stuff to compare to yours as a way of looking at the modification you’re using with respect to PA instead of Innings:
Mauer: +5
Laird: +14
McCann: -3
Pierzynski: -4
Martin: -4
Kendall: -6
Suzuki: +3
Y Molina: +7
B Molina: -3
Bard: -8
Olivo: -9
Napoli: -9
Overall, very good agreement, with a few small differences here and there. I think that PA is probably the way to go (pitches caught would be better for PB/WP), but I’m somewhat relieved to see it didn’t make a huge difference. :)
Cheers,
The Not So Amazing Justin
by JinAZ on Oct 13, 2009 10:20 AM PDT reply actions 0 recs
Also, I really, really wish that fangraphs would start using this
Something’s better than nothing. I can’t imagine why they haven’t adopted this yet. This summer, I saw this re-invented two or three other times because of the compelling need for it.
-j
by JinAZ on Oct 13, 2009 10:21 AM PDT up reply actions 0 recs
Agreed Justin
Hopefully in the offseason they implement something like this. I like the idea of granting “reputation runs” for being run upon less than usual (chuckb’s method did that), though I fear that may introduce further problems.
Also, I’m quite glad to see that the catching duo of John Baker and Ronny Paulino might not have cost the team as many runs as I thought. I have Baker as pretty bad and Paulino as at best average, but with these run totals I get a little more perspective. A catching tandem that’s worth 3.9 WAR is darn good.
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by SFiercex4 on Oct 13, 2009 11:10 AM PDT up reply actions 0 recs
I'm still not comfortable with reputation runs
If a team is running more, but they’re getting gunned down, then it’s actually valuable that teams are running on your catcher. I’m sure that issue can be addressed, but it just seems too fuzzy to me.
-j
by JinAZ on Oct 13, 2009 6:28 PM PDT up reply actions 0 recs
Isn’t it still valuable for your team that teams aren’t running on your catcher, though? It’s just not as valuable as it would be if your guy was gunning them down.
by Carpe Noctem on Oct 14, 2009 8:03 PM PDT up reply actions 0 recs
That's true, if they're stealing at a decent rate. What he's saying is...
Catcher A has no reputation. He has 100 guys run on him and throws out 50.
Catcher B has a good reputation. He has 50 guys run on him and throws out 25.
Catcher A and B both have the same CS rate, but Catcher A is more valuable because he made more outs.
Now, if it was 100 runners an 10 thrown out compared to 50 runners and 5 thrown out, that would be different. In that case Catcher B’s reputation did help.
by lookatthosetwins on Oct 14, 2009 8:19 PM PDT up reply actions 0 recs
True. But Catcher B’s value would still be above what you would except simply from looking at his number of SB and CS, which means this is undervaluing him.
by Carpe Noctem on Oct 14, 2009 8:21 PM PDT up reply actions 0 recs
I wonder if they have something else in the works
and are waiting for it to be implemented in a way that they feel good about, sort of like adjusting WAR for league difficulty — obviously, they could have implemented that right away, but it seems like they want to get it “just right.” (not sure about the whole story)
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by devil_fingers on Oct 13, 2009 11:52 AM PDT up reply actions 0 recs
I hope you're right...
Because at this point, those are the two things that actually have me considering generating my own WAR again. It’s been nice being able to appeal to authority this year and not having to generate my own linear weights and such. But it’s frustrating to have to manually adjust their replacement level or add in catcher fielding. My feeling is that they’re just getting it wrong at this point, and need to address the problem asap using the generally accepted solutions. Subsequent improvements can be made later.
-j
by JinAZ on Oct 13, 2009 6:33 PM PDT up reply actions 0 recs
This off-season
At this point doing catcher defense is more about getting the data in a good format. It’ll happen this off-season and we’ll probably use one of these simple methods to start and then explore other options.
We’ll try to make it so you don’t have to do your own calculations again, because if we’re doing things right, or at least some version of “right” (which we definitely want to do), you shouldn’t need to.
by dkappelman on Oct 13, 2009 10:02 PM PDT up reply actions 0 recs
yay
you guys are awesome, although you also make it harder for hacks like me to do “robo-posts” like this
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by devil_fingers on Oct 14, 2009 8:38 AM PDT up reply actions 0 recs
Thanks, Justin
I hope I didn’t horn in on your territory too much. If I’d known you were still going to publish your catcher defense stuff, I would have waited to bowed out.
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by devil_fingers on Oct 13, 2009 11:51 AM PDT up reply actions 0 recs
I hadn't decided to publish it
…so no biggie. The only reason I’m calculating it is because I have to do it in order to add those data at the team level in the power rankings. The thought had occurred to me to publish it now that the season was over, but it wasn’t a high priority item and in some ways I didn’t want to step on chuckb’s toes since he was the catcher dude at BtB. :)
-j
by JinAZ on Oct 13, 2009 6:27 PM PDT up reply actions 0 recs
With the way the new B-R works
if there isn’t something else, I might just do this and update it monthy next season
I’m thinking of doing my own WAR since I’m always behind anyway, and I’m always trying to catch up with people like you. If I wasn’t so lazy (and unsure of the hard drive space required), I’d get Retrosheet and use Colin’s SZR, the custom wOBA weights I can generate with BdB, and I also think I could figure out a good baserunning stat…
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by devil_fingers on Oct 13, 2009 6:46 PM PDT up reply actions 0 recs
and by":good" I mean "adequate"
What we really need next season is a day-by-day “true talent” marcels like THT used to have. ZiPS in=season was cool, but because of the playhing time adjustments, when there weren’t that many games left in the season,the numbers for RoS got a bit goofy.
It wouldn’t be that hard to do — especially if FanGraphs started putting the player age on the “basic” hitter/pitcher stats pages.
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by devil_fingers on Oct 13, 2009 6:48 PM PDT up reply actions 0 recs
Theoretically, I could have the “true” BA/OBP/SLG for the rest of the way up, but we don’t want the presentation to get too cluttered. Maybe David or I will think of a good way to present something like that without creating confusion. Believe you me, if the BA/OBP/SLG doesn’t match what you would calculate, you get a lot of annoyed e-mails about that! Seriously, the first couple years I did ZiPS, ZiPS calculated fractions of stats rounded to integers for reports and people would send constant e-mails, upset that they can’t reproduce the BA/OBP/SLG.
--
Dan Szymborski
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by D.Szymborski on Oct 13, 2009 7:26 PM PDT up reply actions 0 recs
Thanks for stopping by, Dan
I’m sure it’s easy enough for you to do. I understand why you did it the way you did it. Maybe the “true talent” thing is something only I would use for my dumb lineup posts. I wanted to do them for the playoffs, but I’m just swamped and putting together a Marcel spreadsheet is just too exhausting for me.
But, hey, if you have time and a way to make it easy for people to see…
All in all, I absolutely loved the “RoS” ZiPS at FanGraphs, and would love it if you and FGs did it again next season, in whatever form.
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by devil_fingers on Oct 13, 2009 7:37 PM PDT up reply actions 0 recs
agreed,
I used ZIPS up until the last few weeks when the numbers quit making sense, at least as “true talent” is concerned.
by lookatthosetwins on Oct 14, 2009 3:24 PM PDT up reply actions 0 recs
Frankly, given your recent stuff
I think you’ve long passed me by. :)
-j
by JinAZ on Oct 13, 2009 8:03 PM PDT up reply actions 0 recs
flattered
it’s not true, but I’m still flattered
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by devil_fingers on Oct 14, 2009 8:39 AM PDT up reply actions 0 recs
You want baserunning?
In order to generate it you need RE tables, which basically gives you the LTWS for “free.” Send me an e-mail. And get yourself a Retrosheet database.
by cwyers on Oct 14, 2009 11:40 AM PDT up reply actions 0 recs
framing pitches
I haven’t done much reading on catcher defense. Does anyone know if any work has been done on quantifying the catcher’s ability to frame pitches? It seems that with Pitch f/x data, we could measure called strikes outside the zone/balls inside the zone, and assign a run value to each catcher.
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by MBandi on Oct 13, 2009 10:51 AM PDT reply actions 0 recs
The problem with this is that umpires aren't consistent either
Each ump has a different strike zone, and we wouldn’t be able to tell without watching game vid whether the issue was framing or a bad call.
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by SFiercex4 on Oct 13, 2009 11:06 AM PDT up reply actions 0 recs
True
Would that even out over a large enough sample size, assuming each catcher plays in games called by a variety of different umpires? Or maybe some sort of adjustment can be made, depending on the umpire’s track record of calling games.
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by MBandi on Oct 13, 2009 11:11 AM PDT up reply actions 0 recs
That could be possible
You’d have to split per umpire and per handedness (since lefties get a significantly different strike zone). I’m thinking about it, but I’m no Pitch f/x whiz, so I can’t think of anything particular yet.
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by SFiercex4 on Oct 13, 2009 11:30 AM PDT up reply actions 0 recs
I have a friend working for a ML club in Pennsylvania who (while working for another club in California) wrote a study documenting umpire strike-calling tendencies. Apparently Greg Maddux, of all people, was very interested. So I’m positive that there are people looking into umpire performance as an exploitable factor.
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by gorilla_baller on Oct 13, 2009 12:37 PM PDT up reply actions 0 recs
Why do Mac's numbers look so bad?
Just as a fan from watching him, I’ve always thought that Brian McCann was maybe on the lower end of mediocre as a defensive catcher.
Should this make me think he’s outright defensive liability?
Obviously he’s the best hitting catcher in the league not named Mauer, but do you think he should be moved to 1st?
by TJ Eckleburg on Oct 13, 2009 11:36 AM PDT reply actions 0 recs
McCann
Cold medicine has me all messed up — it took me a bit to figureout who “Mac” was.
:-|
Keep in mind a few of things
1) This is just one season’s performance — I haven’t checked his prior seasons.
2) SCouting opinions (that includes those of fans such as yourself) also matter, I juste haven’t included them here for the sake of simplicity.
3) Specifically with McCann — yes, he’s -3.0 on the year, but keep in mind that -3.6 of that is Fielding Errors. So other than that, he’s about average (a bit above). Moreover, although I’m not sophisticated enough to figure it out already, I suspect that TE/FE has significantly less variance than CS/WP stuff. In other words, ut’s less reflective of repeatable skill, so McCann’s overall skills could be average or better, but this one area just represents an anomaly this season.
4) Even if he is a -3 catcher (and, remember, it’s just one season), while that’s below average for a catcher, that’s hardly a “liability” to his team, considering how hard it is to find catchers. Even if he were “only” an average hitter, his positional adjustment (prorated for games played) this year was 10.4, +18.4 replacment, thus even with -3.6 defense he’s about a 2.5 WAR player… and, of course, McCann is a very good hitter… In other words, I wouldn’t worry too much about him.
5) I’m cheer for the Royals, so I’m going to have a hard time feeling sorry for fans of teams with dudes l like Brian McCann, Russell Martin, Jorge Posada, etc. behind the plate.
(winky face)
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by devil_fingers on Oct 13, 2009 11:50 AM PDT up reply actions 0 recs
Interestingly,
The Braves also have Dave Ross, who, by this study is the best defensive catcher per PA by a good margin.
We always did feel the same, We just saw it from a different point of view, Tangled up in blue.
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by Royal Kingdom on Oct 14, 2009 7:45 AM PDT up reply actions 0 recs
and he's also a decent hitter, especially for a catcher
and isn’t getting paid jack. He could start for a lot of teams, and not just terrible ones
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by devil_fingers on Oct 14, 2009 8:40 AM PDT up reply actions 0 recs
Nice work
rec’d
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by Jeff Zimmerman (TucsonRoyal) on Oct 13, 2009 11:54 AM PDT reply actions 0 recs
Wowy!
Oh wait, that’s been taken. Too bad it is hard to come up with a catching defense acronym for OLIVO.
by Gopherballs on Oct 13, 2009 12:35 PM PDT reply actions 0 recs
Posted to Facebook.
At a quick glance, your scale from worst catcher to best catcher seems about right in line with what I read from John Dewan a while ago on his research for catching defense.
by philkid3 on Oct 13, 2009 4:49 PM PDT reply actions 0 recs
this is very good...
I enjoyed reading all this… really good how you evaluated every catchers defense and I like how you did evaluate the catchers fielding too.
damn nice! I just joined your blog. I think i might like what you got going on here :)
2010? 2011? 2012? 2013? 2014? 2015?
by hurlerhurley on Oct 13, 2009 7:53 PM PDT reply actions 0 recs
Interesting analysis but it is event driven.
A pitch in the dirt that is blocked becomes a non-event instead of a WP. An errant throw to 2B that the SS keeps from going into CF is just a SB and not a SB + E2. It also ignores high leverage situations. A blocked pitch with a runner on 3B is much more important than the same play with a runner on 1B.
|Space for Rent|
by RangerMad on Oct 14, 2009 6:11 AM PDT reply actions 0 recs
good points
as far as blocked pitches and stuff — this is part of why why WOWY is a better system. I hope I acknoweldged those limitations and stuff enough above.
As far as leverage, well, when we calculate offensive linear weights or other fielding numbers, we don’t count game/base/out state there, either. Although we could. B-R provides more data, I was just trying to keep it relatively basic.
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by devil_fingers on Oct 14, 2009 8:44 AM PDT up reply actions 0 recs
Good Stuff, me likey
There are still more layers to this onion, but these numbers make a little sense. There are so many moving parts to a SB that an accurate stat is going to be really hard to make. I have to think that Placido Polanco had something to do with OM5T’s dominance, and maybe ‘G-Money’ has great framing technology?
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by Jacobian on Oct 14, 2009 8:17 AM PDT reply actions 0 recs
good work
the numbers seem to line up with our perceptions (that can’t be right, can it?). but as others have said, there are so many things going on that we can’t really quantify properly. how well is the pitcher holding on the baserunner? with carlos ruiz and his negative SB score. he caught brad lidge all year. i don’t know if i could find it, but i’d imagine that lidge has had at least 20+ runners steal on him in the ninth inning alone. its not like ruiz can do anything about it when lidge doesn’t even look at the runner.
lots of little stuff. but this seems to be a GREAT start.
by jamiethekiller on Oct 14, 2009 8:23 AM PDT reply actions 0 recs
thanks
and WOWY WOWY WOWY
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by devil_fingers on Oct 14, 2009 8:45 AM PDT up reply actions 0 recs
I would prefer something that put more emphasis on WP/PB,
the ability to fake a throw to first and dive home to tag out a runner,
and on height.
Then we’d all see that Joe Mauer is the true MVP, and Greinke just had a good year.
by lookatthosetwins on Oct 14, 2009 6:41 PM PDT reply actions 0 recs
Mauer has had a great season -- ~8.5 wins once you include defense (good) and baserunning (not so good)
Greinke had the best season by any pitcher since 2004, at about 9.5 wins, one win better than Mauer.
And that doesn’t include pitcher fielding, at which Mr. Greinke also excels.
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by devil_fingers on Oct 14, 2009 7:35 PM PDT up reply actions 0 recs
But how are his sideburns?
Seriously though. Mauer is a bad baserunner? I didn’t look this year, but I thought he got great marks last year. I don’t know how well those things correlate from year to year.
by lookatthosetwins on Oct 14, 2009 7:42 PM PDT up reply actions 0 recs
I can't remember who's baserunning stats I was looking at,
so who knows.
by lookatthosetwins on Oct 14, 2009 7:43 PM PDT up reply actions 0 recs
Here we go
http://www.beyondtheboxscore.com/2009/2/18/762747/the-best-baserunners-of-20
It was Sky’s analysis of BPro’s baserunning. Not that any of this means much anyway. I guess a guy can be great at something one year and bad at it the next.
by lookatthosetwins on Oct 14, 2009 7:52 PM PDT up reply actions 0 recs
see the new post I just put up
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by devil_fingers on Oct 15, 2009 7:37 AM PDT up reply actions 0 recs
For one definition of replacement-level pitching, that is.
Rally doesn’t have ’09 numbers on his site yet, but I bet there Mauer would handily beat Grienke.
by cwyers on Oct 14, 2009 11:29 PM PDT up reply actions 0 recs
Great Stuff
I really appreciate being able to look at all of your work. I get exhausted at just the idea of doing it myself.
by bigjonempire on Oct 25, 2009 9:53 PM PDT reply actions 0 recs
thanks
I know what you mean… I’d meant to start doing it in July and updating every few weeks, but couldn’t bring myself to put in the effort.
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by devil_fingers on Oct 29, 2009 11:04 AM PDT up reply actions 0 recs
Thanks for your work DF
I had been looking for something about catcher’s fielding-expressed in runs. Thanks
Is it safe?
by KHAZAD on Oct 26, 2009 8:59 AM PDT reply actions 0 recs
no prob
it’s fun. rally also does something similar in historical WAR database, I just couldn’t wait for him to update! Hopefully, some other sites will start doing stuff like this, updated weekly or something… I have a feeling they will be. I was just using ideas from others and tweaking them.
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by devil_fingers on Oct 29, 2009 11:04 AM PDT up reply actions 0 recs
Other variables to consider
I wonder how much variance you’d see if you weighted WP/PB (and for that matter SB/CS) based on pitch type data for clubs. While I first thought of this in regards to your reference to Wakefield, seeing that Padres and Cubs pitchers threw sliders nearly 2.5 times more often than Red Sox and Mariners pitchers, I’m thinking the data here might overstate how bad Nick Hundley is and doesn’t tell the full story of just how brutal Varitek is.
Getting real readings on this would require crunching a LOT of granular-level data for WP/PB by pitch type on pitches which are not hit by the batter and SB/CS rates by pitch type (and, of course, is dependent on the assumption that pitch type is accurately recorded most of the time by Pitch f/x, an assumption I really haven’t been able to force myself to make just yet), but I think it would probably rather drastically change a number of the rankings.
by realitypolice on Nov 12, 2009 7:32 AM PST reply actions 0 recs














