A few weeks ago I posted a set of defensive projections for SS based on regressing a 3 year average UZR to a population based on the Fan’s Scouting Report created by tangotiger.  After some discussion over  at The Book Blog, I altered my methodology a little and have come up with a set of projections for all positions.

First a quick discussion about the methodology.  The projected values are a weighted average of the

  1. Players 3 year weighted UZR (5/4/3 style)
  2. The UZR mean of the “scouting population” to which the player belongs (more on this in a minute)
  3. The league average (i.e. 0).

The weights are

  1. Effective defensive games over the three year sample (also weighted, so not just the sum)
  2. 125 games
  3. 125 games

which basically means the larger the 3 year sample, the less impact the “regressions” have, which falls under the basic premise of the more data you have the less you need to regress.

The scouting population is determined by where the player ranks in Tango’s Fans Scouting Report (FSR).  I took the last three years of FSR data and found the average UZR/150s for various bins of players (currently done by ordinal ranking, but will likely transition to binning by overall score once 2009 numbers are computed by Tango ).  I then crossed that data with were the specific player ranked in the 2009 voting, with that number becoming the scouting regressing factor.

For those that read my previous post on it, Method 2 was the methodology adopted (as MGL pointed out that it was the correct method).  Anyway on to the results.  First the leaders (with a minimum of 60 effective DGs)

Name Pos UZR/150
Travis Ishikawa 1B 5.6
Chase Utley 2B 10.8
Omar Vizquel SS 9.3
Evan Longoria 3B 11.9
Carl Crawford LF 10.9
Franklin Gutierrez CF 12.2
Jayson Werth RF 11.2

You’ll note that the projections are for UZR/150 so you’d need to utilize an expected playing time to convert these to runs.  For example, I find it highly unlikely that Omar Vizquel will get enough playing time to save ~9 runs, but clearly if he played 75 DGs then he’d save ~4-5 runs.

Now for the laggards

Name Pos UZR/150
Jason Giambi 1B -5.6
Alberto Callaspo 2B -5.7
Yuniesky Betancourt SS -10.1
Edwin Encarnacion 3B -8.9
Adam Dunn LF -14.9
Vernon Wells CF -10.1
Brad Hawpe RF -19.1

For those that want to make the argument that Dunn won’t be playing left field again, second to last went to Delmon Young. For those making the same argument about Giambi, second to last there was Billy Butler. I’m posting the results spreadsheet on google docs with the link over on the sidebar, so feel free to download it and use it for whatever you want. The sheet contains the position the projection is for, the projection itself, 3 year UZR/150, and the effective DGs.

Finally, since this is a Cardinals blog, I wouldn’t leave you without giving you the key returning Cardinal players

Name Pos UZR/150
Brendan Ryan SS 7.2
Colby Rasmus CF 5.5
Albert Pujols 1B 5.0
Ryan Ludwick RF 1.0
Skip Schumaker 2B -5.1
Julio Lugo SS -5.9

A couple of final caveats about the projections. I know there are players missing, and there are definitely player/position combos missing. As a first pass I only projected the position that they had been identified with in the FSR. I plan to remedy that, but it’ll have to wait until the next iteration. Also, I didn’t apply an aging factor, which is clearly not a good way to go about projecting. In his BtB piece Jeff mentioned a -0.7 UZR, but I want to give some thought about how to apply that to UZR/150. Hopefully the next iteration will have some aging factor applied, up until then, apply whatever you see fit. Anyway, download away, and let me know if you have questions/problems.

Steve Sommer

Simulation analyst by day, father and baseball nerd by night

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9 Responses to “Defensive Projections Take 2”

  1. Steve,

    Great stuff, that’s really interesting. Are you 5/4/3-ing the FSR data as well to determine the bins?

    • As of right now I’m not. I put players in the bins just based on their 2009 FSR. However, I like the idea of some past info coming in there, but I think I’ll wait until I transition over to the actual scores vice ordinal rank. I also think I’d start with something that is slightly more skewed towards the present on the scouting side (7-3-1 maybe).

    • and thanks for the kind words.

  2. Good work. Let me know if you need help with the UZR/150 aging numbers. I can supply you with the data I used to determine it.

    • Hey Jeff,

      Thanks for the kind words, and I’d definitely love to take a look at your data. If you have it posted somewhere you can just link it, or you can email me at steve.sommer05 @ gmail . com. Going back and rereading the stuff you wrote on aging is high on my to do list… just have to find some time.

  3. [...] that have recently come out. Jeff Zimmerman of Beyond the Boxscore has cooked some up, and Steve Sommer has some projections that go the extra mile and regresses UZR to a population based on the Fan’s Scouting [...]

  4. [...] beauty of the two sets of projections are that the respective methodologies are discussed in the articles presenting them, and the projections are fairly simple to compare (i.e. only one number really).  [...]

  5. [...] January 10, 2010 — Matt Bandi Steve Sommer of Play a Hard Nine posted 2010 defensive projections in November, so let’s look at how the Pirates stack up. Steve combined UZR numbers and the [...]

  6. [...] defensive projections Steve Sommer of Play a Hard Nine posted 2010 defensive projections in November, so let’s look at how the Pirates stack up. Steve combined UZR numbers and the [...]

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