Second basemen
Third basemen
Shortstops
Left fielders
Center fielders
Right Fielders
Adding Arms to the outfield
In this year's analysis, I am including the following measures:
These are not the only modern fielding measures but they are the ones for which I currently have data for 2008. I will try to add others later as they become available.
For each player in 2008, I converted each of the six measures to runs saved above average per 150 games. Last year, I covered in detail the algorithms for converting to runs saved. Rather than do that again this year, I will simply point you towards last year's articles which can be found in the Fielding Glossary. Many thanks go to Chris Dial, Tom Tango, Justin Inaz and others involved in developing these algorithms. I simply applied their work to this year's data.
There are a few purposes I can see for these data:
- I think it's useful for people to see all the data in one place making it easier to analyze the differences between the systems.
- It reinforces the idea that we should still not trust any one system and that there is is still a fair amount of disagreement between the systems for some players.
- I came up with an aggregate measure by averaging the results of all the systems together. This helps to eliminate the affect of an outlier where one system does not work for a particular player.
Others may not want to see the fan fielding data as part of the aggregate measure but I decided to include it because I think the information is valuable given the limitations of the quantitative measures. I tried it both ways (with and without fan data) and it does not change the final results dramatically. Anyway, the data from all systems will be listed side by side which gives people the option to combine the systems as they see fit.
Table 1 presents the results for first basemen with 700 or more innings played in 2008. The first thing to notice on the table is that much of the +/- data are unavailable. This is because only the top ten and bottom five fielders at each position are freely available. To obtain complete +/- data, you would need to get the Fielding Bible or purchase a subscription to BillJamesonline. Each average is based on 5 or 6 values depending on the availability of +/- for a given player.
It seems that every new offensive statistic invented ranks Pujols on top. The fielding statistics are no different. Depending on the system,Pujols ranks anywhere from 10 runs saved above the average first baseman (UZR) to 30 runs saved above average (PMR). His Average Runs Saved (ARS) is 21. Other first basemen who rank positively on every statistic are Lance Berkman (15), Mark Teixeira (15) and Todd Helton (13).
First sackers who rank poorly on all statistics are Mike Jacobs (-24), Jason Giambi (-16), Prince Fielder (-12) and Ryan Garko (-8). Just a little further up the list is the Tigers Miguel Cabrera at -6 runs saved below average, although the Zone Rating system (+2) rates him a little more favorably than the BIS systems.
Just as interesting as the aggregate scores are the disagreements among systems for some players. James Loney, for example, fell anywhere from -8 on UZR to 15 on RZR. Another player with a lot of variation was Adrian Gonzalez who ran from -12 on UZR to 12 for the fan scouting report.
Table 1: Range statistics for first basemen in 2008
player | team | inn | ZR | RZR | PMR | +/- | UZR | Fans | ARS |
Pujols | StL | 1,215 | 15 | 28 | 30 | 18 | 10 | 22 | 21 |
Berkman | Hou | 1,307 | 12 | 22 | 16 | 15 | 10 | 13 | 15 |
Teixeira | LAA/Atl | 1,335 | 12 | 16 | 15 | 19 | 10 | 15 | 15 |
Helton | Col | 715 | 7 | 26 | 9 | 9 | 10 | 15 | 13 |
Votto | Cin | 1,223 | 4 | 18 | 12 | 17 | 8 | -1 | 10 |
Pena | TB | 1,168 | 1 | 8 | 20 | 13 | 5 | 11 | 9 |
Kotchman | LAA/Atl | 1,210 | 4 | 13 | 8 | 11 | 6 | 12 | 9 |
Overbay | Tor | 1,354 | 7 | 7 | 0 | 9 | 1 | 13 | 6 |
Lee | ChC | 1,339 | 1 | 2 | 5 | N/A | 3 | 18 | 6 |
Youkilis | Bos | 984 | 3 | -4 | 6 | 6 | 5 | 15 | 5 |
Barton | Oak | 1,121 | 10 | 4 | 3 | 7 | 7 | -1 | 5 |
Loney | LA | 1,362 | -1 | 15 | -0 | N/A | -8 | 12 | 4 |
Gonzalez | SD | 1,417 | 4 | -12 | 5 | N/A | -7 | 18 | 2 |
Millar | Bal | 1,131 | -0 | 0 | 12 | N/A | -2 | -4 | 1 |
LaRoche | Pit | 1,135 | -5 | 1 | -2 | N/A | -7 | 5 | -2 |
Konerko | CWS | 995 | -3 | -1 | 6 | N/A | -2 | -14 | -3 |
Delgado | NYM | 1,376 | -2 | 1 | 0 | -12 | -4 | -15 | -5 |
Gload | KC | 878 | -2 | -18 | -11 | N/A | 2 | 0 | -6 |
Cabrera | Det | 1,204 | 2 | -6 | -13 | N/A | -5 | -8 | -6 |
Morneau | Min | 1,363 | -1 | -17 | -15 | N/A | -5 | 6 | -7 |
Howard | Phi | 1,402 | 4 | -9 | -11 | N/A | 1 | -22 | -8 |
Garko | Cle | 1,058 | -8 | -8 | -13 | N/A | -6 | -13 | -10 |
Fielder | Mil | 1,383 | -13 | -10 | -11 | -9 | -8 | -21 | -12 |
Giambi | NYY | 898 | -13 | -23 | -16 | -21 | -3 | -20 | -16 |
Jacobs | Fla | 927 | -19 | -34 | -23 | -31 | -17 | -23 | -24 |