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Net Pts values, both methods

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  • Dean Oliver
    Having referred to both methods for calculating Net Pts per 48 minutes, here are the # s along with the average used before. I will discuss at the bottom my
    Message 1 of 1 , Jun 13, 2001
      Having referred to both methods for calculating Net Pts per 48 minutes,
      here are the #'s along with the average used before. I will discuss at
      the bottom my efforts to make a better combination

      FullName Team NetPts/48 NetPts2/48 AvgNetPts
      Shaquill O'Neal lal 4.31 14.34 9.32
      Allen Iverson phi 2.62 15.35 8.99
      Chris Webber sac 2.75 12.34 7.54
      Jerr Stackhouse det 0.39 14.61 7.50
      Kobe Bryant lal 2.33 12.55 7.44
      Karl Malone uta 3.21 11.56 7.39
      Vince Carter tor 2.91 11.83 7.37
      Tracy McGrady orl 2.29 12.08 7.19
      Tim Duncan san 3.33 9.97 6.65
      Paul Pierce bos 1.72 10.60 6.16
      Stephon Marbury njn 0.51 10.89 5.70
      David Robinson san 4.57 6.39 5.48
      Dirk Nowitzki dal 4.09 6.84 5.47
      Ray Allen mil 3.47 7.36 5.41
      Kevin Garnett min 2.17 8.30 5.23
      Gary Payton sea 1.30 8.73 5.01
      Steve Francis hou 2.19 7.19 4.69
      John Stockton uta 3.53 4.96 4.25
      Sam Cassell mil 1.03 6.72 3.88
      Glenn Robinson mil -0.01 7.60 3.79
      Antoine Walker bos -0.44 7.95 3.75
      Antonio McDyess den 1.07 6.28 3.68
      Jason Kidd pho 1.55 5.66 3.61
      Shawn Marion pho 2.99 4.17 3.58
      Rasheed Wallace por 2.53 4.62 3.58
      Eddie Jones mia 2.19 4.90 3.54
      Steve Nash dal 2.05 4.69 3.37
      Jamal Mashburn cha 0.41 6.29 3.35
      Andre Miller cle 0.83 5.57 3.20
      Pred Stojakovic sac 2.45 3.67 3.06
      Derek Anderson san 2.22 3.65 2.93
      Allan Houston nyk 0.94 4.89 2.91
      Jalen Rose ind 0.45 5.36 2.91
      Tim Hardaway mia 0.68 5.08 2.88
      Corey Maggette lac 0.78 4.76 2.77
      Donyel Marshall uta 2.28 3.09 2.68
      Antawn Jamison gsw -0.84 6.03 2.59
      Terrell Brandon min 1.21 3.96 2.59
      Michael Finley dal 0.36 4.74 2.55
      Bonzi Wells por 1.11 3.98 2.55
      Brian Grant mia 1.39 3.69 2.54
      Lamar Odom lac 0.33 4.69 2.51
      Sha Abdur-Rahim van 0.57 4.41 2.49
      Cuttino Mobley hou 0.80 4.15 2.47
      Darre Armstrong orl 1.56 3.32 2.44
      Jason Terry atl -0.22 5.10 2.44
      Marcus Camby nyk 3.64 1.20 2.42
      Elton Brand chi -0.53 5.30 2.39
      Reggie Miller ind 2.03 2.57 2.30
      Hakeem Olajuwon hou 1.64 2.94 2.29
      Ruben Patterson sea 0.58 3.77 2.18
      Nick Van Exel den 0.22 4.09 2.16
      Anthony Mason mia 2.06 2.07 2.07
      Elden Campbell cha 1.02 2.70 1.86
      Latrel Sprewell nyk -0.45 4.11 1.83
      Cliff Robinson pho -0.10 3.74 1.82
      Vlade Divac sac 1.45 2.13 1.79
      David Wesley cha 0.56 2.85 1.70
      Kurt Thomas nyk 2.38 0.97 1.67
      Steve Smith por 1.95 1.36 1.65
      Damo Stoudamire por 0.62 2.52 1.57
      Rodney Rogers pho 0.17 2.75 1.46
      Tim Thomas mil 1.08 1.67 1.37
      Travis Best ind 1.28 1.44 1.36
      Baron Davis cha 1.11 1.49 1.30
      Richar Hamilton was -2.45 4.78 1.17
      Antonio Daniels san 2.04 0.10 1.07
      Jermaine O'Neal ind 0.58 1.39 0.98
      Chris Gatling cle -1.16 3.06 0.95
      Glen Rice nyk 0.97 0.66 0.82
      Austin Croshere ind -0.51 2.09 0.79
      Joe Smith det 0.20 1.35 0.78
      Rashard Lewis sea 1.77 -0.36 0.70
      Aaron McKie phi 0.81 0.54 0.67
      Mike Bibby van -0.60 1.85 0.62
      Antonio Davis tor 0.87 0.30 0.58
      Keith Van Horn njn -0.68 1.72 0.52
      Lindsey Hunter mil 0.69 0.31 0.50
      Tony Delk pho -0.07 0.95 0.44
      Raef Lafrentz den 1.36 -0.50 0.43
      LaPhonso Ellis min 0.69 0.16 0.42
      Lorenzen Wright atl -0.92 1.71 0.40
      Juwan Howard was -1.89 2.61 0.36
      Maurice Taylor hou -0.93 1.38 0.23
      Jeff McInnis lac 0.78 -0.41 0.19
      Chaunc Billups min 0.19 0.00 0.09
      Scottie Pippen por 0.70 -0.54 0.08
      Bryon Russell uta 1.43 -1.30 0.07
      Doug Christie sac 1.63 -1.64 0.00
      Wal Szczerbiak min 1.00 -1.03 -0.02
      Eric Piatkowski lac 1.36 -1.54 -0.09
      Morris Peterson tor 0.02 -0.48 -0.23
      Lamond Murray cle -1.58 0.90 -0.34
      Johnny Newman njn -0.31 -0.37 -0.34
      Cl Weatherspoon cle 1.81 -2.63 -0.41
      Alvin Williams tor 0.47 -1.37 -0.45
      Mike Miller orl 0.66 -1.60 -0.47
      Ron Mercer chi -2.31 1.29 -0.51
      Vin Baker sea -2.14 1.03 -0.55
      Aaron Williams njn 0.35 -1.50 -0.58
      Chucky Atkins det -1.19 -0.04 -0.61
      Alan Henderson atl -1.79 0.51 -0.64
      Rick Fox lal 0.88 -2.35 -0.73
      Voshon Lenard den -0.28 -1.33 -0.80
      Larry Hughes gsw -3.00 1.33 -0.83
      Micha Dickerson van -2.04 0.05 -1.00
      Larry Johnson nyk -0.02 -2.25 -1.13
      Ron Artest chi -1.84 -0.49 -1.16
      Darius Miles lac -0.75 -1.66 -1.20
      Dale Davis por 1.56 -4.00 -1.22
      Jason Williams sac -0.26 -2.18 -1.22
      George McCloud den -0.88 -1.64 -1.26
      Tyrone Hill phi 0.43 -3.09 -1.33
      Anthony Peeler min -0.45 -2.34 -1.39
      Mookie Blaylock gsw -0.63 -2.39 -1.51
      Patrick Ewing sea -1.53 -1.65 -1.59
      Kenyon Martin njn -1.63 -1.81 -1.72
      Howard Eisley dal 0.16 -3.78 -1.81
      Horace Grant lal 1.48 -5.11 -1.81
      P.J. Brown cha 1.20 -4.99 -1.90
      Vital Potapenko bos -0.37 -3.47 -1.92
      George Lynch phi 0.73 -4.71 -1.99
      Charles Outlaw orl 1.65 -5.76 -2.06
      Lucious Harris njn -0.30 -4.08 -2.19
      Shando Anderson hou -0.19 -4.26 -2.22
      Marcus Fizer chi -4.08 -0.40 -2.24
      Bryant Stith bos 0.56 -5.08 -2.26
      John Starks uta -1.15 -3.66 -2.40
      James Posey den -0.02 -4.90 -2.46
      Charles Oakley tor -0.97 -4.31 -2.64
      John Amaechi orl -3.12 -2.27 -2.69
      Mich Olowokandi lac -3.23 -3.01 -3.12
      Ben Wallace det 0.53 -7.06 -3.26


      FullName Team NetPts/48 NetPts2/48 AvgNetPts
      Shawn Bradley dal 1.64 -3.64 -1.00
      Marc Jackson gsw -0.26 -0.06 -0.16
      Toni Kukoc atl 2.01 6.85 4.43
      Toni Kukoc phi 0.87 0.63 0.75
      Chris Laettner dal 0.79 1.82 1.30
      Chris Laettner was 0.40 1.71 1.05
      Brad Miller chi 0.37 -0.81 -0.22
      Nazr Mohammed phi 0.42 3.43 1.93
      Nazr Mohammed atl 0.78 4.00 2.39
      Dikembe Mutombo phi 3.07 0.43 1.75
      Dikembe Mutombo atl 0.94 -4.28 -1.67
      Theo Ratliff phi 1.50 -1.06 0.22
      Arvydas Sabonis por 1.23 3.68 2.46
      Corl Williamson tor -1.84 -0.12 -0.98
      Corl Williamson det 1.36 2.54 1.95

      NetPts version 1 estimates a player's productivity by the difference
      between his offensive and defensive ratings. A player with a 106
      offensive rating and a 102 defensive rating gets a + result, no matter how
      often they score. It is a measure of efficiency.

      Net Pts version 2 estimates a player's productivity bythe difference
      between the number of points produced by the player and the estimated
      number of points allowed while on the court. A player with a 106
      offensive rating and a 102 defensive rating may get a - rating if he
      doesn't score very often because he allows his man to score a fair amount,
      albeit at a reduced efficiency.

      In combining the two numbers, the thought is that players have to trade
      points for efficiency. A player who scores a lot can't score as
      efficienty because they are getting more pressure defensively. Shaq is
      near the top of both lists, which is why he really looks valuable. David
      Robinson looks as efficient as Shaq, but just doesn't score as often. Tim
      Duncan is not as efficient as Robinson, but scores a lot to take the
      pressure off of Robinson, allowing him to be efficient. Stackhouse is so
      high with method 2 that his mediocre method 1 value gets washed out,
      basically saying that he is benefitting his teammates' efficiencies by
      scoring so much. Mutombo is efficient, but scores so rarely that it must
      hurt his teammates.

      Right now, the combination is just an average. I am working on a more
      true combination, one that does better to approximate the balance between
      lots of points and efficiency. Basically, I want to look at players who
      change roles from team to team and look for patterns to help stabilize the
      estimate of NetPts. I've thought of this for a long time, but I don't
      have time to do the whole job. A more formal way to do this is outlined
      in

      http://www.tsoft.com/~deano/articles/aa021998.htm

      (Of Grant Hill and Basketball Relationships)

      Gotta get a student to work on that one day...

      Dean Oliver
      Journal of Basketball Studies
      www.tsoft.com/~deano/index.html
      deano@...
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