Thursday, January 03, 2008

Probabilistic Model of Range - 2007

This is the fourth part of my series on fielding for 2007. The Table of Contents for the series is listed below:

Basic fielding stats
Converting Zone Rating to something useful
Revised Zone Rating
Probabilistic Model of Range
Fielding Bible
Ultimate Zone Rating
Fan Fielding Survey versus range measures
Outfield arms
Ranking the second basemen
Ranking the shortstops
Ranking the third basemen
Ranking the first baseman
Ranking the center fielders
Ranking the right fielders
Ranking the left fielders
What about catchers?

David Pinto at Baseball Musings finished his Probabilistic Model of Range (PMR) tables for 2007 in November. They can be found by scrolling through in his defense archives. PMR may be the most sophisticated freely available fielding statistic you can find on the internet. It is based on detailed play by play data collected by Baseball Info Solutions.

Here is how it works: The difficulty of turning a ball in play into an out is determine by several parameters: location of ball, how hard the ball is hit (soft, medium, hard), type of ball hit (e.g. ground ball, fly ball, line drive), handedness of batter and pitcher and ballpark. The expectation that a particular ball in play is turned into an out is determined by aggregation of this data for all games played in 2007.

Pinto then determined, for each fielder, how may balls were in play when he was on the field, how many he should have been expected to turn into outs and how many he actually turned into outs. The idea is that good fielders will record more outs than expected and poor fielders will record fewer outs than expected. David Pinto, himself, explains the whole PMR system in more detail on YouTube.

For example, 3,724 balls were in play when Placido Polanco was on the field. Based on all the parameters and data for all fielders, it was determined that Polanco should have turned approximatelly 409 balls into outs. In actuality, he turned 420 balls into outs. So he made 11 more plays than would be expected by the typical shortstop (PMAA). If you look at the PMR archives, you will see that the fielders are ranked according to "ratio". For example, Polanco had a 102.67 ratio (outs/predicted outs) which means that he made 2.67% more plays than average.

PMR is similar to zone rating (ZR) and revised zone rating (RZR) but there are some differences. One advantage the PMR system has over ZR and RZR is that it treats balls in different parts of the zone differently. Pinto considers some balls in a zone to be more difficult to reach than others and he takes this into consideration in his algorithm.

PMR has received some criticism for including pop ups for infielders whereas the zone rating systems do not. Some feel that catching pop ups doesn't really have a lot to do with range. I can see their point but I also think there are some fielders who get to a lot of pop ups that others might not have reached. I guess I'm on the fence on that one. One last thing to remember is that different collection systems are used. ZR uses data from STATS, Inc wheras RZR and PMR use data from BIS.

As we did for ZR and RZR, PMAA can be translated into runs saved above average (RSAA) using Chris Dial's method. As usual, PMAA and RSAA can easily be prorated to 150 games (PMAA/150 and RSAA/150). The results for Tigers in 2007 are shown in Table 1 below.

In Table 2, PMR is compared to ZR and RZR on RSAA/150. Using PMR, Curtis Granderson was 19 runs better than average, Brandon Inge (16), Jacque Jones (13) and Polanco (9). All four of them have been above average on all three measures so far. Craig Monroe (-12) is below average for the first time. The systems disagree on Sean Casey and Magglio Ordonez. Miguel Cabrera and Carlos Guillen rated poorly on all three systems.

Table 1: Plays Made and Runs Saved by Tigers fielders in 2007 according to PMR

Pos

player

Inn

outs

pred outs

PMAA

RSAA

PMAA/150

RSAA/150

1B

Casey

989

198

212

-14

-11

-18

-15

2B

Polanco

1,209

420

409

11

8

12

9

3B

Inge

1,310

400

380

20

16

20

16

3B

Cabrera

1,311

330

362

-32

-25

-32

-26

SS

Renteria

1,019

361

365

-4

-3

-5

-4

SS

Guillen

1,074

389

408

-19

-14

-24

-18

LF

Monroe

806

166

175

-9

-7

-14

-12

CF

Granderson

1,285

424

402

22

18

23

19

CF

Jones

645

195

187

8

7

16

13

RF

Ordonez

1,221

261

265

-4

-3

-4

-3



Table 2:
Runs Saved Per 150 Games - RZR vs ZR vs PMR

PLAYER

RZR

ZR

PMR

Granderson

34

10

19

Jones

24

9

13

Inge

13

12

16

Polanco

12

4

9

Monroe

9

7

-12

Renteria

5

-9

-4

Ordonez

-5

10

-3

Casey

-8

8

-15

Cabrera

-13

-16

-26

Guillen

-18

-7

-18

2 comments:

  1. Lee, FYI, there is actual chance data available at CNNSI.com for standard zone rating. It's what I use for my fielding calculations. I can send you my 2007 spreadsheet if you like.

    ReplyDelete
  2. Hi SG. Thanks for checking out my blog. I would be interested in seeing your spreadsheet. My e-mail is tiger337@comcast.net

    Lee

    ReplyDelete

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