Update: New ratings are here. <hr> Recently there's been some debate over who's the best "playmaker" on the team. Most of us, and I'm guessing the team's coaching staff as well, probably thinks this is James Harden. After all, we've been entrusting him with the ball in key possessions all season. Some have argued that Jeremy Lin is actually our best playmaker, and that this is evident from the stats if you know how to look at it, but he hasn't been allowed to showcase those abilities enough. Some stats that have been referenced for guaging playmaking ability include points scored, assists, assists/turnover ratio, % of assits that were bad passes, etc. But how do we put all this information together and come up with a useful metric for playmaking ability? What does it even mean to be a good playmaker? First, I'll start with a definition: a playmaker is a player you entrust with the ball in order to generate a quality shot for the team. While its true one can help "make a play" by making a great basket cut, grabbing an offensive rebound, or setting a solid screen, I'll limit my view of playmaking ability to when the team gives a player the ball and the play is initiated from there. Here's a proposal for a formula that is (relatively) simple to calculate from the basic box score stats to assess a player's "playmaking" ability. PLA = FGA + 0.5*FTA + 1.5*AST + TOV ("plays attempted") PLM = FGM + 0.5*FTM + AST ("plays made") PLX = PLA - PLM ("plays failed") PLM_RTG = (LgPace/TmPace) * (36/MP) * (2*PLM- PLX) ("playmaking rating") Also, to assess general scoring efficiency for playmaking purposes (again, not distinguishing 3-pointers from 2-pointers), I include a metric below I'm calling Score%. Score% = (FGM + 0.5FTM) / (FGA + 0.5*FTA) One note is that I'm not giving extra credit here for made 3-pointers over 2-pointers. For playmaking ability, I'm more interested in the ability to make a positive play relative to a miscue of some sort (not hitting the shot, a turnover, or not creating a good shot with the pass). Like any composite rating, this isn't perfect and for some players the results may look a bit weird. In particular, there's no good way to simply get at whether the player is "making" the play or merely finishing the play in the boxscore. I could incorporate percentage of made field goals that were assisted as a refinement (HoopData.com provides this, I believe). I thought I'd keep it a little simpler for now so that it can be computed easily from the stats available from the more visible website (e.g. basketball-reference.com). Even with its limitations, I think for the most part it passes the "smell test". It tends to favor point guards and efficient high scorers. Here are the results for all players this year that have played at least 200 minutes: Code: [SIZE="1"] [B]Player Age Tm G MPG PTS/36 AST/36 TOV/36 Score% PLM_RTG[/B] 1 Chris Paul 27 LAC 18 33.9 17.1 10.1 2.5 54.7% 22.0 2 Rajon Rondo 26 BOS 15 37.1 12.8 12.4 3.2 52.3% 22.0 3 LeBron James 28 MIA 16 37.6 23.7 6.5 2.4 54.6% 20.2 4 Tony Parker 30 SAS 17 32.7 20.1 8.0 2.5 52.2% 20.0 5 Kobe Bryant 34 LAL 19 36.8 27.4 4.8 3.7 55.8% 18.5 6 Kevin Durant 24 OKC 19 39.2 24.3 4.0 3.0 59.5% 18.1 7 Russell Westbrook 24 OKC 19 35.7 21.1 8.8 3.6 46.9% 18.0 8 Jrue Holiday 22 PHI 18 38.1 17.2 8.8 3.8 48.9% 17.3 9 Deron Williams 28 BRK 17 36.2 16.3 8.7 2.9 46.0% 17.0 10 Dwyane Wade 31 MIA 13 33.8 21.2 5.1 2.3 52.9% 16.8 11 Kyle Lowry 26 TOR 13 32.1 20.5 6.7 2.8 50.4% 16.7 12 Goran Dragic 26 PHO 19 32.2 17.3 7.4 2.6 51.4% 16.4 13 Greivis Vasquez 26 NOH 17 33.0 14.4 9.5 3.8 45.1% 16.3 14 Tim Duncan 36 SAS 18 31.0 21.9 3.0 1.8 56.8% 15.9 15 Kyrie Irving 20 CLE 10 35.2 23.4 5.7 4.2 51.3% 15.8 16 Jose Calderon 31 TOR 19 27.7 12.8 9.2 2.6 46.4% 15.6 17 Jeff Teague 24 ATL 15 30.9 15.6 8.0 3.4 47.9% 15.0 18 Marc Gasol 28 MEM 16 36.6 15.5 4.3 1.5 57.5% 14.9 19 Brian Roberts 27 NOH 17 15.4 17.5 5.7 2.2 49.4% 14.8 20 Mike Conley 25 MEM 15 34.5 15.6 6.6 3.1 53.1% 14.7 21 Nate Robinson 28 CHI 17 20.6 19.8 5.9 3.3 49.4% 14.6 22 Mo Williams 30 UTA 16 33.0 15.2 7.5 2.9 47.3% 14.5 23 Andre Miller 36 DEN 19 24.6 12.3 7.6 3.5 52.9% 14.4 24 Chris Bosh 28 MIA 16 33.9 20.5 1.6 2.0 61.8% 14.3 25 Eric Bledsoe 23 LAC 18 18.6 19.1 5.3 3.6 52.0% 14.2 26 Jose Barea 28 MIN 12 21.8 14.7 7.8 3.3 46.2% 14.2 27 Raymond Felton 28 NYK 17 33.4 16.4 7.4 2.4 43.8% 14.2 28 Louis Williams 26 ATL 15 24.6 20.6 5.1 2.1 48.8% 14.1 29 Beno Udrih 30 MIL 13 18.8 15.9 6.3 2.8 50.0% 14.0 30 Darren Collison 25 DAL 17 31.5 13.9 7.0 2.9 50.1% 14.0 31 Ramon Sessions 26 CHA 17 28.1 19.4 5.7 2.7 46.8% 14.0 32 Jarrett Jack 29 GSW 18 25.1 14.2 6.4 2.6 51.2% 13.7 33 Kemba Walker 22 CHA 17 36.3 17.0 6.2 2.3 46.4% 13.7 34 Damian Lillard 22 POR 19 37.9 18.3 6.0 3.0 48.6% 13.7 35 Stephen Curry 24 GSW 18 37.1 18.6 6.4 3.0 47.4% 13.7 36 Kevin Garnett 36 BOS 18 28.7 19.7 2.5 2.2 56.4% 13.6 37 J.J. Redick 28 ORL 17 30.6 16.4 6.0 2.6 50.0% 13.5 38 James Harden 23 HOU 17 38.8 21.9 5.0 3.8 49.9% 13.3 39 Blake Griffin 23 LAC 18 32.9 19.2 3.5 2.8 53.5% 13.3 40 Brandan Wright 25 DAL 13 16.9 17.0 1.6 1.5 65.0% 13.1 41 Brook Lopez 24 BRK 14 29.7 22.4 1.0 2.1 54.6% 13.0 42 Carmelo Anthony 28 NYK 17 35.6 26.6 2.1 3.0 51.1% 13.0 43 David West 32 IND 19 34.2 18.2 2.8 1.9 52.4% 12.4 44 Tyson Chandler 30 NYK 17 29.9 15.1 0.7 1.2 73.2% 12.4 45 Al Horford 26 ATL 14 37.0 16.1 3.4 1.9 54.1% 12.4 46 Tiago Splitter 28 SAS 19 19.0 16.9 2.1 2.3 62.1% 12.4 47 Monta Ellis 27 MIL 17 35.2 19.2 5.5 2.7 44.7% 12.4 48 Jordan Crawford 24 WAS 15 24.9 19.8 5.2 3.2 46.0% 12.3 49 Ty Lawson 25 DEN 19 36.2 14.3 7.1 3.3 44.5% 12.2 50 Brandon Jennings 23 MIL 17 36.2 16.7 6.1 2.2 44.0% 12.1 51 Jerryd Bayless 24 MEM 16 17.1 14.2 6.3 2.9 46.4% 12.1 52 Jameer Nelson 30 ORL 11 33.9 14.2 6.9 2.7 43.5% 12.1 53 David Lee 29 GSW 18 37.5 16.9 3.6 2.6 52.8% 12.0 54 Manu Ginobili 35 SAS 16 24.6 17.0 6.4 3.2 45.0% 12.0 55 Tyreke Evans 23 SAC 15 32.5 17.1 4.0 2.4 50.1% 12.0 56 Carl Landry 29 GSW 18 26.6 18.5 1.4 2.5 60.5% 11.8 57 Luke Ridnour 31 MIN 17 30.8 13.4 5.2 2.1 49.2% 11.7 58 JaVale McGee 25 DEN 19 19.3 20.2 1.0 2.2 56.9% 11.7 59 O.J. Mayo 25 DAL 18 34.6 20.5 3.5 2.5 51.3% 11.7 60 George Hill 26 IND 19 35.3 14.9 5.3 1.9 45.8% 11.7 61 Jamal Crawford 32 LAC 18 29.1 22.0 2.3 2.3 52.2% 11.6 62 Andray Blatche 26 BRK 17 19.3 19.8 2.1 2.3 51.0% 11.6 63 Jamaal Tinsley 34 UTA 16 20.4 4.7 9.8 3.4 34.3% 11.6 64 Al Jefferson 28 UTA 20 33.4 18.8 2.1 1.6 51.3% 11.5 65 Paul Pierce 35 BOS 18 33.2 20.7 3.4 2.8 49.4% 11.5 66 Jason Kidd 39 NYK 13 26.0 11.0 4.5 0.9 58.1% 11.4 67 Ben Gordon 29 CHA 15 25.3 21.5 4.1 3.1 48.7% 11.4 68 Anderson Varejao 30 CLE 18 36.6 14.7 3.2 1.9 53.9% 11.4 69 LaMarcus Aldridge 27 POR 18 38.5 19.3 2.4 2.0 49.4% 11.2 70 Andrew Nicholson 23 ORL 17 12.8 18.8 1.0 2.1 57.6% 11.2 71 Richard Hamilton 34 CHI 15 27.1 18.4 3.1 2.9 50.6% 11.0 72 Evan Turner 24 PHI 18 34.7 14.9 4.1 1.9 48.2% 11.0 73 Ray Allen 37 MIA 16 27.3 17.4 2.6 1.7 55.1% 10.9 74 Will Bynum 30 DET 16 14.6 13.7 6.2 2.9 42.9% 10.8 75 Leandro Barbosa 30 BOS 18 13.4 15.9 3.9 1.5 47.8% 10.8 76 Robin Lopez 24 NOH 17 27.5 15.7 1.4 1.8 57.5% 10.7 77 Kevin Martin 29 OKC 19 29.6 19.0 2.0 2.0 54.8% 10.6 78 Alexey Shved 24 MIN 17 24.9 15.7 5.3 2.8 45.5% 10.5 79 Greg Monroe 22 DET 20 32.8 16.9 3.8 3.7 49.8% 10.5 80 Pablo Prigioni 35 NYK 16 14.4 8.0 7.0 3.4 48.4% 10.5 81 Sebastian Telfair 27 PHO 18 17.6 12.5 5.5 1.8 44.4% 10.5 82 Brandon Knight 21 DET 20 30.9 15.1 6.0 4.0 46.0% 10.5 83 Kirk Hinrich 32 CHI 16 27.4 8.5 7.6 2.5 38.0% 10.3 84 Jeremy Lin 24 HOU 17 33.5 11.2 6.8 3.0 42.8% 10.3 85 Dwight Howard 27 LAL 19 35.9 18.6 1.7 3.1 55.3% 10.3 86 Serge Ibaka 23 OKC 19 31.4 16.6 0.4 1.8 62.4% 10.2 87 Paul Millsap 27 UTA 20 31.2 16.6 2.9 2.4 50.6% 10.1 88 A.J. Price 26 WAS 15 29.2 11.4 6.3 1.8 39.8% 10.1 89 Jason Terry 35 BOS 18 28.8 15.0 2.8 1.6 54.0% 10.0 90 Joakim Noah 27 CHI 17 39.4 11.9 3.9 2.4 51.4% 9.9 91 Tayshaun Prince 32 DET 20 32.7 14.2 2.8 1.2 49.8% 9.8 92 Rodney Stuckey 26 DET 19 28.3 12.7 5.0 1.7 42.4% 9.7 93 Ryan Anderson 24 NOH 17 32.9 20.0 1.5 1.1 49.7% 9.7 94 Jeremy Pargo 26 CLE 12 26.4 15.7 5.2 3.2 43.6% 9.6 95 Andrei Kirilenko 31 MIN 13 36.4 12.9 3.3 2.6 54.8% 9.5 96 Mario Chalmers 26 MIA 16 24.9 9.2 6.2 2.4 42.3% 9.5 97 Zach Randolph 31 MEM 16 36.8 17.3 1.4 2.4 53.1% 9.5 98 Ed Davis 23 TOR 19 15.8 14.1 1.4 1.8 58.4% 9.4 99 DeMar DeRozan 23 TOR 19 37.2 17.6 1.8 1.7 49.4% 9.4 100 Gary Neal 28 SAS 17 24.5 17.2 2.9 2.2 48.4% 9.3 101 Luis Scola 32 PHO 19 27.5 16.6 2.1 1.9 49.4% 9.3 102 Nick Collison 32 OKC 19 18.5 11.4 2.3 2.1 63.8% 9.3 103 Chris Kaman 30 DAL 16 27.2 18.0 1.3 2.9 54.4% 9.3 104 Thaddeus Young 24 PHI 18 35.1 14.8 1.4 1.3 53.6% 9.3 105 Luol Deng 27 CHI 17 40.8 16.1 2.4 2.4 50.9% 9.2 106 Glen Davis 27 ORL 18 32.4 17.7 2.3 1.9 46.7% 9.2 107 Chris Duhon 30 LAL 15 21.2 5.4 6.0 1.2 43.7% 9.1 108 J.R. Smith 27 NYK 17 33.2 14.7 3.1 1.3 45.9% 9.0 109 Patrick Patterson 23 HOU 16 29.9 16.9 1.4 1.4 52.5% 9.0 110 Boris Diaw 30 SAS 19 24.0 8.5 3.6 1.6 60.4% 9.0 111 DeMarcus Cousins 22 SAC 15 30.1 19.9 2.4 3.2 46.7% 8.9 112 Shannon Brown 27 PHO 19 23.8 18.0 3.0 2.2 45.4% 8.9 113 Chandler Parsons 24 HOU 16 37.9 14.9 3.3 2.0 49.7% 8.9 114 Carlos Boozer 31 CHI 17 29.6 16.4 2.5 2.4 47.9% 8.9 115 Jimmy Butler 23 CHI 17 16.7 11.5 1.4 0.8 58.8% 8.9 116 Arron Afflalo 27 ORL 18 34.8 16.7 2.6 2.2 48.6% 8.8 117 Gordon Hayward 22 UTA 20 28.0 17.2 2.6 2.5 48.4% 8.8 118 Nikola Pekovic 27 MIN 15 31.2 16.4 1.5 2.4 52.5% 8.8 119 Pau Gasol 32 LAL 17 34.8 13.0 3.6 1.9 46.3% 8.8 120 M. Kidd-Gilchrist 19 CH 17 27.2 14.3 2.2 2.1 51.8% 8.7 121 Mike Dunleavy 32 MIL 15 26.7 14.5 3.2 1.5 47.7% 8.7 122 Chris Wilcox 30 BOS 17 12.8 12.1 0.7 1.8 70.9% 8.7 123 Vince Carter 36 DAL 18 23.4 20.4 2.6 1.9 46.0% 8.7 124 Jermaine O'Neal 34 PHO 12 18.5 15.9 0.5 2.1 58.0% 8.7 125 Amir Johnson 25 TOR 19 20.7 12.1 2.4 1.6 53.3% 8.7 126 Joe Johnson 31 BRK 17 37.9 14.9 3.6 1.7 43.5% 8.7 127 Samuel Dalembert 31 MIL 14 17.1 13.4 1.4 2.6 62.9% 8.6 128 Andre Iguodala 29 DEN 19 35.4 14.7 3.9 3.0 47.1% 8.6 129 Jonas Valanciunas 20 TOR 19 23.6 13.3 1.9 2.0 54.1% 8.6 130 Josh Smith 27 ATL 14 34.6 16.7 3.7 3.2 44.7% 8.6 131 Devin Harris 29 ATL 13 22.5 11.6 4.3 2.1 46.3% 8.5 132 Shawn Marion 34 DAL 13 28.9 11.9 3.4 2.6 52.0% 8.4 133 Jason Thompson 26 SAC 17 30.8 12.9 1.3 1.2 54.8% 8.3 134 Tobias Harris 20 MIL 16 16.3 15.0 1.4 1.8 54.2% 8.3 135 Kenneth Faried 23 DEN 19 30.4 15.2 0.7 1.7 55.4% 8.3 136 Marcin Gortat 28 PHO 19 31.4 13.4 1.3 1.8 56.1% 8.3 137 Wesley Matthews 26 POR 19 37.7 15.4 2.6 1.4 46.6% 8.2 138 Nicolas Batum 24 POR 19 38.8 15.7 3.0 2.3 47.4% 8.2 139 Isaiah Thomas 23 SAC 14 18.7 16.4 3.4 3.7 48.1% 8.1 140 Rudy Gay 26 MEM 16 37.1 18.0 2.2 2.4 46.1% 8.0 141 Danilo Gallinari 24 DEN 18 33.6 16.7 2.7 1.7 44.6% 8.0 142 Marcus Thornton 25 SAC 17 28.1 18.5 1.9 1.1 44.7% 7.9 143 Martell Webster 26 WAS 14 22.3 14.4 1.8 2.1 53.8% 7.9 144 Dante Cunningham 25 MIN 17 22.3 13.0 1.0 0.8 51.5% 7.7 145 Jason Smith 26 NOH 17 17.3 16.4 1.1 2.6 50.4% 7.7 146 J.J. Hickson 24 POR 18 28.4 13.9 1.2 2.2 54.1% 7.7 147 Kevin Love 24 MIN 8 34.4 20.3 2.5 2.4 42.6% 7.6 148 DeMarre Carroll 26 UTA 15 17.1 12.2 1.4 0.6 50.6% 7.6 149 Paul George 22 IND 19 35.2 15.3 3.5 2.6 43.8% 7.5 150 E'Twaun Moore 23 ORL 18 25.5 13.5 4.3 3.1 43.6% 7.5 151 Marquis Daniels 32 MIL 13 17.1 12.8 2.9 1.6 44.8% 7.4 152 Aaron Brooks 28 SAC 17 22.9 12.3 3.4 1.7 44.4% 7.4 153 Lance Stephenson 22 IND 19 25.5 9.6 3.5 1.9 48.1% 7.4 154 Dion Waiters 21 CLE 17 32.0 17.1 3.8 2.1 40.0% 7.3 155 DeAndre Jordan 24 LAC 18 25.9 14.1 0.5 2.2 57.4% 7.3 156 Larry Sanders 24 MIL 17 22.7 12.4 1.4 2.1 55.6% 7.3 157 DeJuan Blair 23 SAS 16 17.3 13.1 2.2 2.3 49.3% 7.2 158 John Salmons 33 SAC 12 26.7 9.9 3.3 1.2 45.3% 7.2 159 Zaza Pachulia 28 ATL 15 24.3 10.6 2.4 2.5 54.3% 7.2 160 Randy Foye 29 UTA 20 26.2 15.7 2.5 1.6 45.3% 7.1 161 D.J. Augustin 25 IND 19 13.3 9.0 6.5 2.1 31.2% 7.0 162 Marvin Williams 26 UTA 17 27.5 13.4 1.4 1.3 50.5% 7.0 163 Kevin Seraphin 23 WAS 14 25.0 17.0 1.7 3.5 48.0% 7.0 164 C.J. Watson 28 BRK 17 18.9 13.0 3.4 1.7 42.0% 7.0 165 Andre Drummond 19 DET 20 17.6 13.0 0.9 1.7 53.6% 7.0 166 Kris Humphries 27 BRK 17 25.2 11.9 0.8 1.0 52.0% 7.0 167 Jared Sullinger 20 BOS 18 18.2 11.0 1.2 1.1 54.1% 6.9 168 Kawhi Leonard 21 SAS 9 28.9 13.2 1.7 2.4 54.1% 6.9 169 Eric Maynor 25 OKC 19 13.6 10.7 5.6 2.4 35.7% 6.9 170 P.J. Tucker 27 PHO 19 19.1 8.7 2.2 1.0 52.8% 6.9 171 Kendrick Perkins 28 OKC 19 25.4 7.4 2.4 1.6 58.6% 6.8 172 Kyle Singler 24 DET 20 27.6 12.9 1.2 1.4 52.4% 6.8 173 Brandon Bass 27 BOS 18 27.9 12.5 1.1 1.1 49.7% 6.8 174 Josh McRoberts 25 ORL 17 15.2 8.8 2.8 1.4 49.2% 6.7 175 Jared Dudley 27 PHO 19 26.1 12.2 2.4 1.4 46.9% 6.7 176 Jason Richardson 32 PHI 14 29.1 15.8 1.7 0.9 44.8% 6.7 177 Chuck Hayes 29 SAC 17 20.5 5.7 3.8 1.2 44.4% 6.7 178 Daniel Gibson 26 CLE 16 24.6 12.5 3.0 1.0 42.4% 6.7 179 Thabo Sefolosha 28 OKC 19 28.2 9.6 2.4 1.3 52.9% 6.6 180 Mike Miller 32 MIA 14 15.1 9.4 3.4 1.0 44.1% 6.6 181 Harrison Barnes 20 GSW 18 27.9 12.7 1.9 1.7 48.7% 6.6 182 Markieff Morris 23 PHO 19 21.3 15.0 2.0 1.6 44.3% 6.6 183 Spencer Hawes 24 PHI 18 20.2 12.8 2.5 2.0 44.9% 6.6 184 Antawn Jamison 36 LAL 19 20.3 14.6 1.2 1.5 50.4% 6.6 185 Al-Farouq Aminu 22 NOH 17 31.2 11.3 2.3 2.9 50.3% 6.6 186 Willie Green 31 LAC 15 18.2 12.3 2.0 1.3 48.8% 6.5 187 Nick Young 27 PHI 16 23.3 14.9 2.0 1.4 43.6% 6.4 188 Nikola Vucevic 22 ORL 18 29.9 12.0 1.9 2.0 48.2% 6.4 189 Ronnie Brewer 27 NYK 17 22.6 11.4 2.1 0.6 44.7% 6.4 190 Toney Douglas 26 HOU 16 16.3 14.8 4.0 3.2 41.6% 6.4 191 Jordan Hill 25 LAL 18 14.6 14.5 1.1 2.6 50.2% 6.2 192 Derrick Favors 21 UTA 17 22.8 14.7 0.8 2.4 49.8% 6.2 193 Jason Maxiell 29 DET 20 26.8 11.6 0.9 1.8 53.2% 6.2 194 Andrea Bargnani 27 TOR 18 34.1 17.8 1.5 1.9 43.7% 6.1 195 Kyle Korver 31 ATL 13 29.3 13.2 2.0 0.9 45.3% 6.0 196 Lavoy Allen 23 PHI 18 23.1 9.7 1.7 1.3 48.5% 5.9 197 Norris Cole 24 MIA 14 19.6 9.3 4.2 2.6 40.4% 5.9 198 Gerald Wallace 30 BRK 10 31.5 11.3 2.9 1.9 43.3% 5.9 199 Elton Brand 33 DAL 17 22.3 10.8 2.5 1.8 44.7% 5.9 200 Rashard Lewis 33 MIA 14 15.9 13.6 1.5 1.9 50.7% 5.9 201 Enes Kanter 20 UTA 20 14.4 13.8 1.0 3.5 53.7% 5.9 202 Kosta Koufos 23 DEN 18 21.6 10.6 0.8 1.2 52.3% 5.7 203 Marco Belinelli 26 CHI 16 16.9 13.2 1.5 1.5 46.5% 5.7 204 Malcolm Lee 22 MIN 14 18.4 10.0 2.7 1.1 42.1% 5.7 205 Jeff Green 26 BOS 18 21.7 14.7 1.3 2.5 47.6% 5.7 206 Meyers Leonard 20 POR 19 18.6 9.7 0.4 1.1 57.6% 5.6 207 Tyler Hansbrough 27 IND 19 17.0 13.6 0.4 1.8 49.4% 5.6 208 Ekpe Udoh 25 MIL 17 22.4 9.1 1.5 1.3 51.3% 5.6 209 Alonzo Gee 25 CLE 19 32.9 13.0 2.2 2.6 45.4% 5.6 210 Matt Barnes 32 LAC 17 25.3 12.1 1.6 1.7 47.6% 5.6 211 Corey Brewer 26 DEN 19 22.9 17.2 1.2 1.7 44.3% 5.5 212 Carlos Delfino 30 HOU 10 23.7 14.1 3.2 1.5 39.1% 5.5 213 Emeka Okafor 30 WAS 15 21.3 11.8 1.5 1.5 45.3% 5.5 214 Trevor Booker 25 WAS 9 24.1 10.1 2.2 2.0 45.9% 5.5 215 Marreese Speights 25 MEM 16 15.6 14.5 1.4 2.2 44.4% 5.5 216 Klay Thompson 22 GSW 18 35.2 16.4 2.2 2.1 41.9% 5.4 217 Metta World Peace 33 LAL 19 35.5 13.1 2.1 1.9 44.9% 5.3 218 Darius Morris 22 LAL 17 21.1 9.4 4.3 2.7 38.8% 5.3 219 Marcus Morris 23 HOU 17 20.3 14.6 1.3 1.1 44.5% 5.3 220 Thomas Robinson 21 SAC 15 16.3 11.4 1.6 3.2 51.7% 5.3 221 Hasheem Thabeet 25 OKC 17 12.6 9.4 0.2 2.7 73.7% 5.3 222 Jeff Taylor 23 CHA 16 25.9 11.3 1.4 1.2 47.1% 5.2 223 Quincy Pondexter 24 MEM 16 24.0 9.8 2.2 0.9 43.7% 5.2 224 Caron Butler 32 LAC 17 24.6 14.7 1.4 1.3 44.2% 5.2 225 Omer Asik 26 HOU 17 32.3 12.2 1.3 3.1 51.7% 5.1 226 Michael Beasley 24 PHO 19 27.8 14.8 3.1 3.4 40.8% 5.1 227 Taj Gibson 27 CHI 17 20.8 10.9 1.5 2.0 46.9% 5.1 228 Trevor Ariza 27 WAS 15 25.1 11.6 3.0 1.9 39.2% 5.0 229 Chris Singleton 23 WAS 15 17.6 10.8 1.5 1.9 46.7% 5.0 230 Tristan Thompson 21 CLE 19 30.5 10.6 1.4 1.7 47.1% 5.0 231 Roger Mason 32 NOH 17 21.0 9.5 2.2 1.0 42.1% 4.9 232 Ersan Ilyasova 25 MIL 16 23.3 11.7 2.2 1.0 39.6% 4.9 233 Bradley Beal 19 WAS 15 27.0 14.6 2.4 2.2 40.4% 4.8 234 Wayne Ellington 25 MEM 16 16.9 10.8 2.7 0.9 38.1% 4.8 235 Jae Crowder 22 DAL 17 20.0 11.6 2.3 1.4 40.9% 4.7 236 Darius Miller 22 NOH 16 13.3 5.6 2.7 0.8 41.0% 4.6 237 Derrick Williams 21 MIN 14 19.9 16.3 1.0 2.3 43.7% 4.5 238 Omri Casspi 24 CLE 15 14.3 14.9 1.0 1.7 45.2% 4.5 239 Danny Green 25 SAS 17 30.2 11.6 1.7 1.3 43.4% 4.5 240 Courtney Lee 27 BOS 18 24.6 8.3 2.1 2.1 47.1% 4.4 241 Stephen Jackson 34 SAS 10 23.2 11.9 2.3 2.0 41.4% 4.4 242 Tony Allen 31 MEM 13 24.4 11.8 0.9 1.5 44.6% 4.4 243 Tyler Zeller 23 CLE 15 22.3 11.1 1.3 1.9 45.4% 4.4 244 Brendan Haywood 33 CHA 16 27.3 8.4 0.8 1.7 54.3% 4.3 245 Austin Rivers 20 NOH 16 27.0 8.1 4.0 2.0 33.6% 4.3 246 Rasheed Wallace 38 NYK 16 14.8 16.8 0.8 1.2 41.2% 4.1 247 Maurice Harkless 19 ORL 15 18.1 8.1 1.2 1.1 46.5% 4.1 248 Byron Mullens 23 CHA 17 32.7 13.7 1.4 1.4 40.4% 3.9 249 Ian Mahinmi 26 IND 19 14.9 12.5 0.4 3.2 50.5% 3.8 250 Ryan Hollins 28 LAC 17 12.8 7.6 0.3 2.3 64.8% 3.7 251 Reggie Evans 32 BRK 16 19.6 5.6 1.3 2.1 58.3% 3.6 252 Dahntay Jones 32 DAL 18 11.1 9.2 1.3 1.1 42.9% 3.6 253 Jodie Meeks 25 LAL 17 13.4 15.4 2.5 2.5 38.7% 3.6 254 Steve Novak 29 NYK 17 23.9 12.3 0.6 0.3 42.1% 3.5 255 Roy Hibbert 26 IND 19 29.4 11.9 1.7 2.4 40.6% 3.4 256 Terrence Ross 21 TOR 17 15.4 13.4 1.2 1.8 41.0% 3.3 257 Dominic McGuire 27 TOR 15 15.3 5.0 1.6 1.1 45.7% 3.3 258 Dorell Wright 27 PHI 18 21.4 13.2 1.6 1.8 39.8% 3.2 259 Shane Battier 34 MIA 13 26.5 9.5 1.0 1.0 45.7% 3.2 260 Jonas Jerebko 25 DET 13 17.0 12.2 1.1 1.5 40.0% 3.1 261 Linas Kleiza 28 TOR 11 19.7 12.8 1.3 1.8 39.9% 3.1 262 DeShawn Stevenson 31 ATL 12 26.2 9.1 1.4 0.8 40.9% 3.0 263 Sam Young 27 IND 17 16.5 9.6 1.9 2.2 40.0% 2.9 264 Bismack Biyombo 20 CHA 15 21.1 7.3 0.3 1.6 52.5% 2.9 265 Keith Bogans 32 BRK 15 14.3 7.4 2.9 1.9 34.0% 2.7 266 Gerald Green 27 IND 19 21.9 12.3 0.9 1.7 40.5% 2.5 267 Troy Murphy 32 DAL 14 18.3 9.1 1.0 1.0 40.6% 2.5 268 James Johnson 25 SAC 17 19.5 8.8 2.1 2.8 39.9% 2.5 269 Festus Ezeli 23 GSW 18 16.8 7.7 0.5 1.8 47.4% 2.3 270 Udonis Haslem 32 MIA 16 17.9 7.0 0.8 2.1 48.3% 2.2 271 Draymond Green 22 GSW 18 11.6 6.9 1.2 1.4 36.7% 1.3 272 Lamar Odom 33 LAC 18 14.3 5.7 2.7 2.0 29.8% 1.0 273 C.J. Miles 25 CLE 13 15.5 14.1 1.6 2.7 33.7% -0.1[/SIZE] Here it is for just Rockets players: Code: [SIZE="1"] [B]Player Age Tm G MPG PTS/36 AST/36 TOV/36 Score% PLM_RTG[/B] 38 James Harden 23 HOU 17 38.8 21.9 5.0 3.8 49.9% 13.3 84 Jeremy Lin 24 HOU 17 33.5 11.2 6.8 3.0 42.8% 10.3 109 Patrick Patterson 23 HOU 16 29.9 16.9 1.4 1.4 52.5% 9.0 113 Chandler Parsons 24 HOU 16 37.9 14.9 3.3 2.0 49.7% 8.9 190 Toney Douglas 26 HOU 16 16.3 14.8 4.0 3.2 41.6% 6.4 212 Carlos Delfino 30 HOU 10 23.7 14.1 3.2 1.5 39.1% 5.5 219 Marcus Morris 23 HOU 17 20.3 14.6 1.3 1.1 44.5% 5.3 225 Omer Asik 26 HOU 17 32.3 12.2 1.3 3.1 51.7% 5.1[/SIZE] Last year, Lin's PLM_RTG was exceptional for a young player -- 17.3. Harden, in a smaller role with OKC, had a PLM_RTG of 14.3. Harden's 13.3 PLM_RTG this year is above average for his position, but not close to an "elite" level for playmaking perimeter players. He'll need to improve. As for Lin, there's no question that Lin had a fantastic run last year over a 2-3 week period when the Knicks essentially turned the keys to the offense over to him. Typically, when you increase the "usage" for a player their efficiency will drop. So the question I have is should we expect Lin to revert to last year's form (and something close to that) if we give him more playmaking responsibility? Or will his efficiency remain well below average? I don't think the Rockets want to take that risk, so in my opinion Lin needs to prove that he can make plays in an efficient manner (that means, up the FG% and do a better job at getting to the line) with the touches he currently has. He can get comfortable to doing that in a somewhat reduced role, he'll gradually be given more opportunities to do that in a larger role.
I find that ratio, somewhat high. You pass to a jumpshooter, he has less than 66% probability of making it. BTW, thanks for doing this. I was going to attempt to do it but the some of the '12ers aren't worth my time or effort.
Yeah, the rationale is that when you make a "potential" assist, it will result in an actual assist about 2/3 of the time. It is of course a simplification. I suppose that multiplier could realistically be anywhere from 1 to 3. 1.5 seemed about right to me.
I don't understand why assist gets 1.5 multiplier for attempts, while 1 for managed. Doesn't that completely downplays the assist of playmaking?
great post, I was wondering if you could measure this out for Lin and harden with out each other on the floor.....it would be interesting to see, I would assume the play maker ability goes up for both. My theory is that because both require the ball they actually have a reduced play making ability being on the floor together. THoughts?
I understand your reasoning for not giving extra credit for 3 pointers but to me this would still be much more interesting if it did.
In other words, James Harden and Jeremy Lin needs to pass more. Both need to average 8+ assists a game.
There are 6 guys in the league who average 8+ assists a game. JUST 6. And all of them are the primary playmakers for their teams with a minimum of 20% USG. But you're asking two guys who share playmaking responsibilities to AVERAGE 8+ assists a game?
Let me clarify a bit. Tell me if I misunderstood, but in your calculations PLA = FGA + 0.5*FTA + 1.5*AST + TOV ("plays attempted") PLM = FGM + 0.5*FTM + AST ("plays made") PLX = PLA - PLM ("plays failed") Is the AST for PLM a stat calculated for when the assisted player scores? For example, every time the assisted player scores, the assist player gets one AST to his stat. And so I assumed it'd made sense that the attempts for assist be the same ratio as the made assist because if not, the PLX rating will be heavily counted towards scoring players, where as AST contributes the same amount of points as a FGM. So if you could clarify that for me that'd be great. However, good job on collecting the data, there's one more question I have and that is if this also includes AST that leads to FTA.
Interesting analysis. Only a couple things. While I understand your argument for excluding 3 point shots, given that the 3 point shots are weighted in score value, it seems unusual to NOT include them. The corner 3 pointer is the 2nd most efficient shot in basketball (just behind shots at the rim). A player that generates more 3 point shots and shots at the rim is by definition creating better "plays" than one that generates shots in the mid range. Similarly, a player who shoots 33% from 3point land is MORE efficient than a player who shoots 40% from 2 point land. This should be accurately represented. The FT metric seems a bit high. Most analyses only attribute 0.44 to FT's, as some portion of them is And1's vs pure foul shots. Finally, I do have concerns that this calculation doesn't include the percentage of "empty" assists. IE, passes that lead to FT's (which would ideally be attributed to some degree). In terms of tracking assists, those who are on teams where they have high percentage shooters have their numbers invariably skewed towards those that have team mates with lower percentage shooters. I know there's no ready source of this data (outside of picking apart Synergy replays), however without this data, it's seems that you're going to end up with some rather bizarre results. Perhaps there is a way to normalize the results around average shooting levels in terms of assists generated? As for "making" the play vs "finishing" the play, perhaps you *could* look at %age points assisted and work off some derivative of that? According to your numbers, Tyson Chandler is number 44... which is absolutely bizarre. Do you really see Tyson Chandler as the "go to" ball handler on ANY team?
AST is just what's recorded in the boxscore. So for every assist that leads to a made basket, I'm giving 1 credit to the assistant. The formula is assuming, essentially, that the success rate for a potential assist is 67%. It could be argued that this is a touch too high, meaning players with high assist totals are getting a little too much credit. On the other hand, I'm not giving credit for potential assists leading to trip to the foul line. So (I hope) it comes close to "evening out".
Thanks for the good feedback. I have some thoughts on addressing the "play maker" versus "play finisher" issue (I agree with above poster who thought Patterson's rating was to high relative to Parsons's). As I alluded to in the first post, I'll need to make use of %Ast or estimate it. By the way, another one of my reasons for not giving extra credit to 3-point shots is I didn't want to bias the rating towards spot-up shooters who rely on plays created by others. Maybe I can avoid this by incorporating %Ast. And I went with 0.5 instead of 0.44 mostly because it makes the formula look cleaner )), but seriously I think the ability to get to the line is a special skill for "playmakers" that deserves a little extra weightage.
pure mathematically: PLM_RTG = (LgPace/TmPace) * (36/MP) * (2*PLM- PLX) ("playmaking rating") this term is more related to how many plays you made in a game than how good the play you made though. It pretty much telling that in your team pace, normalized to 36min, how may play you made and off set with bad plays. It has nothing to do with what percentage of the play you made is good. Any chance to list the actual numbers of PLA, PLM and PLX numbers for the player? I'd like to see PLX/PLA number, that might be a better number to say who is better in play making. I think PLM_RTG is more of an indication on who is the main play maker in the league or who is most efficient in making play given playing time. And in our team, that has a lot to do with who is given the right to make play. Thus use this data to prove who should be given more right to make play is really misleading. However, really appreciate OP digging out the data and introduce the analysis though...
82 games has a nice breakdown of %assisted. For example, it currently has Tyson Chandler being assisted on 64% of his plays. It also has them broken down by range/type, but unfortunately does not distinguish between 3 point assists and jump shot assists. http://www.82games.com/1213/12NYK15.HTM The only down side is you would have to extract it as 82games doesn't really have a search tool for that (as far as I know). Still, it would help to normalize some of your results to something a little more representative of what you're trying to find.
I think this is all moot... Lin wont be here in 3 years times... I do not think he will be able to improve his outside shooting before his contract expires... there is better PGs suited for the direction this team is taking... and that will factor in if Lin stays
Yeah, like I said in the first post its available at HoopData.com: http://hoopdata.com/shotstats.aspx I think what I'll do is make use of that for this season, and create an estimator for %Ast using the conventional box score stats so that PLM_RTG can be calculated for historical player-seasons as well.
