Friday, February 22, 2008

Dodgers WAR

WAR or Win Above Replacement, is the favorite method of the sabermetric community in determining the value, measured in the units of wins that a player has over the typical replacement level player. Tango Tiger and the USS Mariner blog both have great write-ups on how to calculate WAR. As an excercise in understanding how to calculate WAR I took to calculating WAR for all of the National League West teams and players. By summing the WAR of all the players on a team and accounting for playing time, one can get an idea of how many wins the team should get.

Please keep in mind that I am no Bill James, so this chart was done to the best of my ability. I do have wiggle room for some of the defense and base running adjustments, but they won't change the values significantly. All of these numbers are based off of 2008 ZIPS Projections and my estimates for playing time, therefore it is not a perfect science.
WAR - Los Angeles Dodgers
Hitters
Player Playing Time Park Adj wOBA Pre-WAR Pos/Def/BR WAR WAR$
R.Martin 0.80 .3537 .9127 3.0/0.0/0.1 3.19 $14.44M
G.Bennett 0.25 .2693 -.9962 3.0/0.0/-0.1 0.48 $2.49M
J.Loney 0.85 .3726 2.006 1.0/0.0/0.1 2.55 $11.64M
M.Sweeney 0.1 .3238 -.8222 1.0/-0.5/-0.1 -0.04 $0.21M
J.Kent 0.70 .3500 .6964 2.0/-0.5/-0.1 1.47 $6.86M
T.Abreu 0.35 .2988 -2.274 2.0/0.0/0.1 -0.06 $0.13M
A.LaRoche 0.60 .3416 .2082 2.0/0.0/0.0 1.32 $6.23M
N.Garciappara 0.50 .3190 -.1.099 2/-0.5/0.0 0.20 $1.28M
R.Furcal 0.85 .3311 -.3989 2.5/0.0/0.1 1.87 $8.63M
A.Ethier 0.65 .3568 1.087 1.5/0.5/0.1 2.07 $9.52M
J.Pierre 0.60 .3084 -1.719 1.5/0.0/1.0 0.47 $2.47M
D.Young 0.25 .3065 -1.829 1.5/-0.5/0.0 -0.21 $-0.51M
A.Jones 0.75 .3592 1.2306 2.5/1.0/0.0 3.55 $16.01M
M.Kemp 0.75 .3611 1.338 1.5/0.5/0.1 2.58 $11.75M
Total         19.46  
 
Pitchers
Player IP FIP ERA PA Lg Ave ERA RAR WAR WAR$
B.Penny 200 3.375 5.135 31.12 2.96 $13.44M
D.Lowe 210 4.105 5.135 24.05 2.29 $10.48M
C.Billingsley 180 4.161 5.135 19.48 1.86 $8.56
H.Kuroda 180 4.067 5.135 21.37 2.04 $9.36M
E.Loaiza 127 4.641 5.135 6.98 0.66 $3.32M
J.Schmidt 82 3.810 5.135 12.08 1.15 $5.46M
H.Guo 78 3.918 5.135 10.55 1.00 $4.82M
T.Saito 66 2.579 5.135 18.75 1.79 $8.26M
J.Broxton 96 2.794 5.135 24.98 2.38 $10.87M
J.Biemel 73 3.967 5.135 9.48 0.90 $4.37M
S.Proctor 93 4.888 5.135 2.55 0.24 $1.47M
R.Seanez 65 4.031 5.135 7.98 0.76 $3.74M
Bullpen 471       7.07451  
Rotation 979       10.95968  
Total 1450       18.03419  


Now let's take a look at how that stacks up with the rest of the NL West teams. Keep in mind that a team comprised only of replacement level players would win about 50 games, therefore to get the total number of wins we need to use the following simple formula (Team WAR = 50 + Offense WAR + Pitching WAR).
NL West - WAR
Team Hitting WAR Rotation WAR Bullpen WAR Total WAR Simulator
DBacks 18.44 5.86 13.72 88.03 82.36
Dodgers 19.46 7.07 10.96 87.50 85.88
Rockies 18.67 4.46 6.81 79.95 81.68
Padres 18.03 3.76 8.06 79.84 82.76
Giants 8.26 3.82 9.41 71.49 75.16

7 comments:

  1. Surely it should be "WOR", not "WAR"? And what do all the other acronyms stand for? There seem to be about a dozen of them.

    Did you put up the table (or text)somewhat prematurely? Your text refers to having got "WAR" numbers for all NL West players, but the table lists Dodgers and has figures only for Russell Martin. Presumably others will be forthcoming.

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  2. Ooh, all the TBDs have suddenly disappeared, superseding my last comment. And Bennett is now suddenly up, so the others must be on their way too.

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  3. haha, I am in the middle of entering the data. The rest of the data is coming. Sorry. :)
    vr, Xei

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  4. It's Wins Above Replacement, berkowit.

    As for the other numbers... wOBA is a rate stat version of linear weights. Pre-WAR looks like Wins Above Average on offense. The next column is adjustments to average: a bonus to players based on their position, a bonus based on their defensive value... I presume BR is baserunning. And WAR$ is WAR converted to salary.

    What I don't get is the Age adjustment - shouldn't that already be accounted for in the forecast wOBA?

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  5. Colin is correct. As far as the aging column goes you make a good point. Perhaps that should only be used for evaluating a long term contract. Thoughts?
    vr, Xei

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  6. Ok, I took out the aging adjustments. They should only be applied when looking at a long term deal. The WAR values match up with the simulator results pretty well, except for the Diamondbacks. Those pesky Diamondbacks are always over-performing. :)

    vr, Xei

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  7. Very nice work. I have a couple of questions:

    How did you park adjust wOBA?

    And how do you calculate FIP-ERA?

    Thanks

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