Wages of Wins Journal article

[ziggy]

Wins produced by team
http://www.wagesofwins.com/AllTeamMid0809.html

Wins produced ranked league overall
http://www.wagesofwins.com/AllPlayerMid0809.html



Top 100
Just a note the highest rated rookie is Kevin Love

All Players at the Midpoint of the 2008-09 Season                   After 41 Games                   Ranked in terms of Wins Produced                   WP48 = Wins Produced per 48 minutes                   Data taken from Basketball-Reference.com                   Return to The Wages of Wins Journal                   Rank   Player   Team   Games   Minutes   WP48   Wins Produced 1   Chris Paul   New Orleans   41   1,550   0.493   15.9 2   Dwight Howard   Orlando   39   1,413   0.435   12.8 3   LeBron James   Cleveland   41   1,533   0.398   12.7 4   Marcus Camby   LA Clippers   35   1,225   0.437   11.1 5   Jason Kidd   Dallas   41   1,454   0.36   10.9 6   Rajon Rondo   Boston   41   1,324   0.332   9.2 7   Dwyane Wade   Miami   41   1,572   0.278   9.1 8   Andris Biedrins   Golden State   41   1,315   0.331   9.1 9   Tim Duncan   San Antonio   41   1,440   0.283   8.5 10   David Lee   New York   41   1,430   0.28   8.4 11   Emeka Okafor   Charlotte   41   1,427   0.264   7.9 12   Kevin Garnett   Boston   40   1,316   0.28   7.7 13   Pau Gasol   LA Lakers   40   1,417   0.254   7.5 14   Kobe Bryant   LA Lakers   41   1,498   0.237   7.4 15   Andre Iguodala   Philadelphia   41   1,578   0.222   7.3 16   Troy Murphy   Indiana   36   1,199   0.287   7.2 17   Yao Ming   Houston   40   1,334   0.254   7.1 18   Chris Bosh   Toronto   41   1,586   0.202   6.7 19   Gerald Wallace   Charlotte   37   1,395   0.228   6.6 20   Mike Bibby   Atlanta   41   1,441   0.219   6.6 21   Joel Przybilla   Portland   41   914   0.338   6.4 22   Brandon Roy   Portland   37   1,374   0.223   6.4 23   Jose Calderon   Toronto   32   1,122   0.267   6.2 24   Shawn Marion   Miami   36   1,297   0.227   6.1 25   Jameer Nelson   Orlando   36   1,134   0.255   6 26   Chauncey Billups   Denver-Detroit   39   1,391   0.207   6 27   Al Jefferson   Minnesota   41   1,490   0.193   6 28   Andrew Bogut   Milwaukee   34   1,091   0.257   5.8 29   Andre Miller   Philadelphia   41   1,475   0.184   5.7 30   Chris Duhon   New York   41   1,614   0.168   5.7 31   Steve Nash   Phoenix   37   1,256   0.215   5.6 32   Paul Pierce   Boston   41   1,511   0.174   5.5 33   Nene Hilario   Denver   40   1,332   0.196   5.4 34   Vince Carter   New Jersey   41   1,503   0.173   5.4 35   Paul Millsap   Utah   35   1,101   0.234   5.4 36   Shaquille O'Neal   Phoenix   34   1,037   0.246   5.3 37   Trevor Ariza   LA Lakers   41   1,011   0.251   5.3 38   Erick Dampier   Dallas   41   934   0.268   5.2 39   Devin Harris   New Jersey   35   1,246   0.197   5.1 40   Ray Allen   Boston   41   1,496   0.163   5.1 41   Manu Ginobili   San Antonio   29   772   0.297   4.8 42   Ben Wallace   Cleveland   39   956   0.238   4.7 43   Delonte West   Cleveland   37   1,231   0.185   4.7 44   Dirk Nowitzki   Dallas   40   1,509   0.15   4.7 45   Antawn Jamison   Washington   41   1,578   0.141   4.6 46   Andrei Kirilenko   Utah   37   1,131   0.194   4.6 47   Tayshaun Prince   Detroit   41   1,550   0.14   4.5 48   James Posey   New Orleans   41   1160   0.182   4.4 49   Kevin Love   Minnesota   41   932   0.225   4.4 50   Mehmet Okur   Utah   33   1,145   0.18   4.3 51   Al Horford   Atlanta   33   1,085   0.189   4.3 52   Joe Johnson   Atlanta   41   1,638   0.122   4.2 53   Mike Miller   Minnesota   32   974   0.205   4.2 54   Brad Miller   Sacramento   36   1,167   0.171   4.1 55   Andrew Bynum   LA Lakers   41   1,210   0.163   4.1 56   Anderson Varejao   Cleveland   41   1,141   0.173   4.1 57   Kevin Durant   Oklahoma   40   1,556   0.125   4.1 58   Luke Ridnour   Milwaukee   38   1,172   0.165   4 59   Jamario Moon   Toronto   40   989   0.195   4 60   Amare Stoudemire   Phoenix   41   1,514   0.125   3.9 61   Caron Butler   Washington   38   1,463   0.128   3.9 62   Luis Scola   Houston   41   1,152   0.157   3.8 63   Tony Parker   San Antonio   32   1,070   0.167   3.7 64   Rodney Stuckey   Detroit   39   1,194   0.147   3.6 65   Samuel Dalembert   Philadelphia   41   995   0.173   3.6 66   Steve Blake   Portland   38   1,175   0.144   3.5 67   Rudy Fernandez   Portland   40   1,060   0.159   3.5 68   Kendrick Perkins   Boston   37   1,069   0.157   3.5 69   Matt Bonner   San Antonio   40   883   0.18   3.3 70   Ramon Sessions   Milwaukee   38   908   0.174   3.3 71   Jeff Foster   Indiana   40   1,006   0.156   3.3 72   Danny Granger   Indiana   38   1,410   0.111   3.3 73   Tracy McGrady   Houston   28   948   0.163   3.2 74   Carl Landry   Houston   41   875   0.175   3.2 75   Udonis Haslem   Miami   40   1,403   0.108   3.2 76   Hedo Turkoglu   Orlando   40   1,485   0.102   3.1 77   Zydrunas Ilgauskas   Cleveland   28   735   0.205   3.1 78   Kyle Lowry   Memphis   41   968   0.155   3.1 79   Maurice Williams   Cleveland   41   1,364   0.109   3.1 80   Antonio McDyess   Detroit   22   524   0.281   3.1 81   Joakim Noah   Chicago   39   712   0.206   3.1 82   Grant Hill   Phoenix   41   1,172   0.124   3 83   Carlos Boozer   Utah   12   405   0.357   3 84   Deron Williams   Utah   28   987   0.145   3 85   Jason Terry   Dallas   41   1,429   0.098   2.9 86   Chris Andersen   Denver   31   566   0.248   2.9 87   Marvin Williams   Atlanta   37   1,285   0.108   2.9 88   Rashard Lewis   Orlando   41   1,511   0.091   2.9 89   Brook Lopez   New Jersey   41   1,211   0.113   2.8 90   Marc Gasol   Memphis   41   1,247   0.11   2.8 91   Raymond Felton   Charlotte   41   1,533   0.089   2.8 92   Dominic McGuire   Washington   38   719   0.188   2.8 93   Zach Randolph   LA Clippers-New York   25   936   0.142   2.8 94   Tyson Chandler   New Orleans   32   995   0.132   2.7 95   Anthony Carter   Denver   41   967   0.135   2.7 96   Nate Robinson   New York   34   982   0.131   2.7 97   Carmelo Anthony   Denver   31   1,053   0.121   2.7 98   Allen Iverson   Denver-Detroit   40   1,537   0.083   2.6 99   Mario Chalmers   Miami   41   1,278   0.097   2.6 100   Derrick Rose   Chicago   41   1,538   0.08   2.6

[westkoast]

Is there a link to explain how they got this?  When I followed the ones you posted it just shows the line up.

I am pretty interested on how they came up with this.  Look at the Clippers for example.  Marcus Camby is the only guy who does anything but I can't say I've seen more than one or two games this year where he really effected the outcome of a game like that...

[ziggy]

Is there a link to explain how they got this?  When I followed the ones you posted it just shows the line up.

I am pretty interested on how they came up with this.  Look at the Clippers for example.  Marcus Camby is the only guy who does anything but I can't say I've seen more than one or two games this year where he really effected the outcome of a game like that...

http://www.basketball-reference.com/about/ws.html

Calculating Win Shares

Note: This article was edited on August 4, 2008. I made some major modifications to the Win Shares system to address two primary concerns with the old system: (1) that the results were expressed in "shares" rather than "wins" (i.e., that there was a 3:1 ratio of Win Shares to wins rather than a 1:1 ratio) and (2) that players who played on poor teams were being unfairly penalized. Please read the explanation below for complete details.
Introduction

Stealing a page from baseball's Bill James, I decided to attempt to calculate basketball Win Shares. Due to data limitations the current system only works for the 1973-74 season forward, but at some point I hope to modify the system for seasons prior to 1973-74. This article will describe how I came up with the Win Shares system for basketball.
What is a Win Share?

Bill James developed his system such that one win is equivalent to three Win Shares. My system deviates from James's system in three key ways:

   1. In my system, one win is equivalent to one Win Share.
   2. James made team Win Shares directly proportional to team wins. In his system, a baseball team that wins 80 games will have exactly 240 Win Shares, a baseball team that wins 90 games will have exactly 270 Win Shares, etc. In my system, a basketball team that wins 50 games will have about 50 Win Shares, give or take.
   3. James did not allow for the possibility of negative Win Shares. In his system, the fewest number of Win Shares a player can have is zero. In my system, a player can have negative Win Shares. I justify this by thinking about it in the following way: a player with negative Win Shares was so poor that he essentially took away wins that his teammates had generated.

Crediting Offensive Win Shares to Players

Offensive Win Shares are credited to players based on Dean Oliver's Offensive Rating. Offensive Rating is an estimate of the player's points produced per 100 offensive possessions. The formula is quite detailed, so I would point you to Oliver's book Basketball on Paper for complete details. The process for crediting offensive Win Shares is outlined below (using Tim Duncan of the 2003-04 Spurs as an example):

   1. Calculate the Offensive Rating for each player. In 2003-04, Tim Duncan's Offensive Rating was 107.385.
   2. Calculate offensive possessions for each player. Once again, I would point you to Oliver's book for complete details on calculating player offensive possessions. Tim Duncan had an estimated 1373.19 offensive possessions in 2003-04.
   3. Calculate marginal offense for each player. Marginal offense is equal to (player possessions) * ((player Offensive Rating) / 100) - 0.92 * (league points per possession)). For Tim Duncan this is 1373.19 * ((107.385 / 100) - 0.92 * (1.02929)) = 174.26. Note that this formula may produce a negative result for some players.
   4. Calculate league marginal points per win. League marginal points per win reduces to 0.32 * (league points per game) . For the 2003-04 NBA season this is 0.32 * 93.3966 = 29.8869.
   5. Credit offensive Win Shares to the players. Offensive Win Shares are credited using the following formula: (player marginal offense) / (league marginal points per win). Tim Duncan gets credit for 174.26 / 29.8869 = 5.83 offensive Win Shares.

Crediting Defensive Win Shares to Players

Crediting defensive Win Shares to players is based on Dean Oliver's Defensive Rating. Defensive Rating is an estimate of the player's points allowed per 100 defensive possessions. I know I'm sounding like a broken record, but please see Oliver's book for further details. Here is the process, once again using Tim Duncan as an example:

   1. Calculate the Defensive Rating for each player. Tim Duncan's Defensive Rating in 2003-04 was 88.501.
   2. Calculate marginal defense for each player. Marginal defense is equal to (player minutes played / team minutes played) * (team defensive possessions) * (1.08 * (league points per possession) - ((player Defensive Rating) / 100)). For Tim Duncan this is (2527 / 19755) * 7353.42 * ((1.08 * 1.02929) - (88.5001 / 100)) = 213.18. Note that this formula may produce a negative result for some players.
   3. Calculate league marginal points per win. League marginal points per win reduces to 0.32 * (league points per game) . For the 2003-04 NBA season this is 0.32 * 93.3966 = 29.8869.
   4. Credit defensive Win Shares to the players. Defensive Win Shares are credited using the following formula: (player marginal defense) / (league marginal points per win). Tim Duncan gets credit for 213.18 / 29.8869 = 7.13 defensive Win Shares.

Putting It All Together

The final step of the process is to add offensive Win Shares to defensive Win Shares. In our example, Tim Duncan's total is 5.83 + 7.13 = 12.96 Win Shares.
Does This Work?

Because this metric is designed to estimate a player's win contribution, it makes sense to see if the sum of player Win Shares for a particular team closely matches the team win total. For the 2003-04 Spurs the sum of player Win Shares is 61.76, while the team win total is 57, an error of 57 - 61.76 = -4.76 wins. This error is actually larger than the "typical" error; looking at all NBA teams since the 1973-74 season, the root mean squared error (rmse) is 3.466 wins.

[westkoast]

Is there a link to explain how they got this?  When I followed the ones you posted it just shows the line up.

I am pretty interested on how they came up with this.  Look at the Clippers for example.  Marcus Camby is the only guy who does anything but I can't say I've seen more than one or two games this year where he really effected the outcome of a game like that...

http://www.basketball-reference.com/about/ws.html

Calculating Win Shares

Note: This article was edited on August 4, 2008. I made some major modifications to the Win Shares system to address two primary concerns with the old system: (1) that the results were expressed in "shares" rather than "wins" (i.e., that there was a 3:1 ratio of Win Shares to wins rather than a 1:1 ratio) and (2) that players who played on poor teams were being unfairly penalized. Please read the explanation below for complete details.
Introduction

Stealing a page from baseball's Bill James, I decided to attempt to calculate basketball Win Shares. Due to data limitations the current system only works for the 1973-74 season forward, but at some point I hope to modify the system for seasons prior to 1973-74. This article will describe how I came up with the Win Shares system for basketball.
What is a Win Share?

Bill James developed his system such that one win is equivalent to three Win Shares. My system deviates from James's system in three key ways:

   1. In my system, one win is equivalent to one Win Share.
   2. James made team Win Shares directly proportional to team wins. In his system, a baseball team that wins 80 games will have exactly 240 Win Shares, a baseball team that wins 90 games will have exactly 270 Win Shares, etc. In my system, a basketball team that wins 50 games will have about 50 Win Shares, give or take.
   3. James did not allow for the possibility of negative Win Shares. In his system, the fewest number of Win Shares a player can have is zero. In my system, a player can have negative Win Shares. I justify this by thinking about it in the following way: a player with negative Win Shares was so poor that he essentially took away wins that his teammates had generated.

Crediting Offensive Win Shares to Players

Offensive Win Shares are credited to players based on Dean Oliver's Offensive Rating. Offensive Rating is an estimate of the player's points produced per 100 offensive possessions. The formula is quite detailed, so I would point you to Oliver's book Basketball on Paper for complete details. The process for crediting offensive Win Shares is outlined below (using Tim Duncan of the 2003-04 Spurs as an example):

   1. Calculate the Offensive Rating for each player. In 2003-04, Tim Duncan's Offensive Rating was 107.385.
   2. Calculate offensive possessions for each player. Once again, I would point you to Oliver's book for complete details on calculating player offensive possessions. Tim Duncan had an estimated 1373.19 offensive possessions in 2003-04.
   3. Calculate marginal offense for each player. Marginal offense is equal to (player possessions) * ((player Offensive Rating) / 100) - 0.92 * (league points per possession)). For Tim Duncan this is 1373.19 * ((107.385 / 100) - 0.92 * (1.02929)) = 174.26. Note that this formula may produce a negative result for some players.
   4. Calculate league marginal points per win. League marginal points per win reduces to 0.32 * (league points per game) . For the 2003-04 NBA season this is 0.32 * 93.3966 = 29.8869.
   5. Credit offensive Win Shares to the players. Offensive Win Shares are credited using the following formula: (player marginal offense) / (league marginal points per win). Tim Duncan gets credit for 174.26 / 29.8869 = 5.83 offensive Win Shares.

Crediting Defensive Win Shares to Players

Crediting defensive Win Shares to players is based on Dean Oliver's Defensive Rating. Defensive Rating is an estimate of the player's points allowed per 100 defensive possessions. I know I'm sounding like a broken record, but please see Oliver's book for further details. Here is the process, once again using Tim Duncan as an example:

   1. Calculate the Defensive Rating for each player. Tim Duncan's Defensive Rating in 2003-04 was 88.501.
   2. Calculate marginal defense for each player. Marginal defense is equal to (player minutes played / team minutes played) * (team defensive possessions) * (1.08 * (league points per possession) - ((player Defensive Rating) / 100)). For Tim Duncan this is (2527 / 19755) * 7353.42 * ((1.08 * 1.02929) - (88.5001 / 100)) = 213.18. Note that this formula may produce a negative result for some players.
   3. Calculate league marginal points per win. League marginal points per win reduces to 0.32 * (league points per game) . For the 2003-04 NBA season this is 0.32 * 93.3966 = 29.8869.
   4. Credit defensive Win Shares to the players. Defensive Win Shares are credited using the following formula: (player marginal defense) / (league marginal points per win). Tim Duncan gets credit for 213.18 / 29.8869 = 7.13 defensive Win Shares.

Putting It All Together

The final step of the process is to add offensive Win Shares to defensive Win Shares. In our example, Tim Duncan's total is 5.83 + 7.13 = 12.96 Win Shares.
Does This Work?

Because this metric is designed to estimate a player's win contribution, it makes sense to see if the sum of player Win Shares for a particular team closely matches the team win total. For the 2003-04 Spurs the sum of player Win Shares is 61.76, while the team win total is 57, an error of 57 - 61.76 = -4.76 wins. This error is actually larger than the "typical" error; looking at all NBA teams since the 1973-74 season, the root mean squared error (rmse) is 3.466 wins.

Pretty interesting.  You stat geeks are nutso though!!  It's crazy with some of the ways that they come up with ways to break stats down like this.

[ziggy]

Pretty interesting.  You stat geeks are nutso though!!  It's crazy with some of the ways that they come up with ways to break stats down like this.

Just to set the record straight, I don't own the book, and I take what he does at face value.  It is not as if I fully understand exactly how he calculates offensive rating.  Some people may tell you they know exactly what is happening when they actually are clueless, don't for a second misinterpret that I am doing so with this, or a bunch of other things for that matter.

[WayOutWest]

Pretty interesting.  You stat geeks are nutso though!!  It's crazy with some of the ways that they come up with ways to break stats down like this.

Just to set the record straight, I don't own the book, and I take what he does at face value.  It is not as if I fully understand exactly how he calculates offensive rating.  Some people may tell you they know exactly what is happening when they actually are clueless, don't for a second misinterpret that I am doing so with this, or a bunch of other things for that matter.

You had me at "record".........................