├── README.md ├── all-graphs ├── ast-usg-clustered.png ├── pca-deriv.png ├── pca-variance.png ├── pts-usg-clustered.png ├── silhouette-diff-score.png ├── silhouette-score.png ├── stl-blk-clustered.png ├── stl-blk-separated.png └── stl-blk.png ├── excel-master-positional-clustering.xlsx ├── final-csv-data ├── advanced-stats.csv ├── clustered-nba.csv ├── clustering-example.csv ├── counting-stats.csv └── full-nba-data.csv ├── python-master-positional-clustering-NO-OUTPUTS.ipynb └── python-master-positional-clustering.ipynb /README.md: -------------------------------------------------------------------------------- 1 | # METHODOLOGY: Defining NBA players by role with k-means clustering 2 | 3 | [Link to blog post.](https://dribbleanalytics.blog/2019/04/positional-clustering) 4 | 5 | ## Data collection 6 | 7 | First, I created a database of all players who played at least 50 games and 1,000 minutes as of the end of the 2018-19 regular season. This resulted a data set of 256 players. 8 | 9 | The following stats were recorded for all these players: 10 | 11 | |Shooting (raw)|Shooting (percentages)|Rebounding|Passing|Defense|Advanced efficiency stats|Other| 12 | :--|:--|:--|:--|:--|:--|:--| 13 | |FG|FG%|ORB|AST|STL|PER|POS*| 14 | |FGA|3P%|DRB|TOV|BLK|OWS|USG%| 15 | |3P|2P%|TRB|AST%|PF|DWS|| 16 | |3PA|eFG%|ORB%|TOV%|STL%|WS|| 17 | |2P|FT%|DRB%||BLK%|WS/48|| 18 | |2PA|TS%|TRB%||TOV%|OBPM|| 19 | |FT|3PAr||||DBPM|| 20 | |FTA|FTr||||BPM|| 21 | |PPG|||||VORP|| 22 | 23 | 24 | *POS = position as a number; 1 = guard, 2 = wing, 3 = big 25 | 26 | All data was taken from [Basketball Reference](http://basketball-reference.com/). 27 | 28 | ## Dimensionality reduction 29 | 30 | A principal components analysis with n_components = 6 was performed on the features. These 6 components explained 85.85% of the data set's variance. 31 | 32 | n_components = 6 was used by examining the dy/dx between different n_components values and choosing the one with the biggest change. 33 | 34 | ## Clustering 35 | 36 | By examining silhouette scores, we chose to use n_clusters = 12 for our k-means algorithm. The algorithm separated the data set into 12 groups (clsuters), each with a clear theme. We then labeled these groups with a role, thereby defining every NBA player into a set of roles. 37 | 38 | The roles, example players, and average stats are below. 39 | 40 | |Role|Notable players|PTS/REB/AST|STL/BLK|FG/3P/FT/USG| 41 | :--|:--|:--|:--|:--| 42 | |3&D forward|P.J. Tucker, OG Anunoby|7.5/4.4/1.3|0.7/0.5|46%/33%/74%/15%| 43 | |3&D guard|Danny Green, Wesley Matthews|8.9/2.4/1.6|0.6/0.2|44%/39%/83%/16%| 44 | |???|Collin Sexton, Josh Jackson|9.2/3.1/2.5|0.8/0.3|42%/32%/75%/19%| 45 | |Do it all big|Al Horford, Paul Millsap|12.9/6.9/2.2|1/1.2|51%/37%/74%/19%| 46 | |Floor general|Ricky Rubio, Kyle Lowry|11.2/4.2/5.3|1.3/0.4|44%/35%/78%/18%| 47 | |Inside big|Julius Randle, LaMarcus Aldridge|17.3/9.3/2.4|0.7/0.9|56%/25%/75%/24%| 48 | |Perimiter scorer|Tobias Harris, Jayson Tatum|14.7/5.9/2.1|0.8/0.5|46%/35%/77%/22%| 49 | |Rim runner|Clint Capela, Jarrett Allen|9.6/7.5/1.3|0.7/1.2|61%/9%/65%/17%| 50 | |Shooter|Klay Thompson, Buddy Hield|16.7/3.7/3.2|0.8/0.3|45%/38%/85%/23%| 51 | |Star ball handler|James Harden, Damian Lillard|27.3/6.6/5.9|1.4/0.5|47%/38%/84%/31%| 52 | |Star big|Giannis Antetokounmpo, Joel Embiid|21.9/12.2/5|1.3/1.5|53%/24%/73%/27%| 53 | |Team-leading guard|Trae Young, Jrue Holiday|21.9/4.6/6.1|1.3/0.4|45%/34%/81%/29%| 54 | 55 | Each player's roles can be viewed in an interactive table in the bottom of the blog post [here](https://dribbleanalytics.blog/2019/04/positional-clustering). 56 | -------------------------------------------------------------------------------- /all-graphs/ast-usg-clustered.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/dribbleanalytics/positional-clustering/511f0f3cc8053292f6ce785657f433b6b96b5bc8/all-graphs/ast-usg-clustered.png -------------------------------------------------------------------------------- /all-graphs/pca-deriv.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/dribbleanalytics/positional-clustering/511f0f3cc8053292f6ce785657f433b6b96b5bc8/all-graphs/pca-deriv.png -------------------------------------------------------------------------------- /all-graphs/pca-variance.png: 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Rk,Player,Pos,Age,Tm,G,MP,PER,TS%,3PAr,FTr,ORB%,DRB%,TRB%,AST%,STL%,BLK%,TOV%,USG%,OWS,DWS,WS,WS/48,OBPM,DBPM,BPM,VORP 2 | 1,James Harden,PG,29,HOU,78,2867,30.6,0.616,0.539,0.449,2.5,17.8,10,39.5,2.7,1.7,14.5,40.5,11.4,3.8,15.2,0.254,10.5,1.1,11.7,9.9 3 | 2,Paul George,SF,28,OKC,77,2841,23.3,0.583,0.469,0.335,3.7,19.6,11.4,17.7,2.8,1,10,29.5,7,4.9,11.9,0.201,4.7,0.7,5.5,5.3 4 | 3,Giannis Antetokounmpo,PF,24,MIL,72,2358,30.9,0.644,0.163,0.55,7.3,30,19.3,30.3,1.8,3.9,14.8,32.3,8.9,5.5,14.4,0.292,5.7,5,10.8,7.6 5 | 4,Joel Embiid,C,24,PHI,64,2154,26.1,0.593,0.219,0.541,8.1,34,21.4,18.4,1,4.4,13.2,33.3,4.9,3.8,8.7,0.194,2,2.1,4.1,3.3 6 | 5,Stephen Curry,PG,30,GSW,69,2331,24.4,0.641,0.604,0.214,2.2,14.2,8.4,24.2,1.9,0.9,11.6,30.4,7.2,2.5,9.7,0.199,7.7,-1.4,6.3,4.9 7 | 6,Kawhi Leonard,SF,27,TOR,60,2040,25.8,0.606,0.267,0.377,4.2,18.6,11.6,16.4,2.5,1,8.4,30.3,6.1,3.4,9.5,0.224,4.3,0.7,5,3.6 8 | 7,Devin Booker,SG,22,PHO,64,2242,20.2,0.584,0.33,0.362,1.9,11.3,6.5,34.1,1.2,0.5,15.4,32.9,3.3,0.3,3.5,0.076,3.8,-3,0.8,1.6 9 | 8,Kevin Durant,PF,30,GSW,78,2702,24.2,0.631,0.281,0.366,1.4,17.5,9.8,26.2,1,2.6,12.3,29,8.6,2.9,11.5,0.204,4.2,0.1,4.3,4.3 10 | 9,Damian Lillard,PG,28,POR,80,2838,23.7,0.588,0.419,0.335,2.6,11.1,7,30.6,1.5,1,10.8,29.3,9.7,2.4,12.1,0.205,6.6,-1.1,5.5,5.4 11 | 10,Bradley Beal,SG,25,WAS,82,3028,20.8,0.581,0.37,0.278,3.1,11.7,7.4,24.1,1.9,1.6,11,28.4,5.9,1.7,7.6,0.12,3.9,-1.1,2.8,3.7 12 | 11,Kemba Walker,PG,28,CHO,82,2863,21.7,0.558,0.434,0.267,1.9,11.9,6.8,29.4,1.7,1,10.1,31.5,5.5,1.9,7.4,0.123,5.1,-1.7,3.3,3.9 13 | 12,Blake Griffin,PF,29,DET,75,2622,21,0.581,0.389,0.41,4,20.1,11.8,27.1,1,0.9,13.8,30.2,5.1,2.9,8,0.147,4.2,0.4,4.6,4.4 14 | 13,Karl-Anthony Towns,C,23,MIN,77,2545,26.3,0.622,0.27,0.342,10.9,29.3,20,17.2,1.3,4.2,13.7,28.9,7.2,3.2,10.4,0.197,4.8,2,6.8,5.7 15 | 14,Kyrie Irving,PG,26,BOS,67,2214,24.3,0.592,0.35,0.197,3.4,12.7,8.1,35,2.2,1.4,11.3,29.6,6.2,2.9,9.1,0.197,6,0.4,6.4,4.7 16 | 15,Donovan Mitchell,SG,22,UTA,77,2598,17.2,0.537,0.339,0.259,2.5,10.5,6.6,21.2,2,0.9,11.3,31.6,1.3,3.7,5,0.092,0.8,-0.2,0.6,1.7 17 | 16,Zach LaVine,SG,23,CHI,63,2171,18.7,0.574,0.283,0.33,2,12.9,7.4,22.6,1.3,1,14.2,30.5,1.7,1.1,2.8,0.062,1.8,-1.7,0,1.1 18 | 17,Russell Westbrook,PG,30,OKC,73,2630,21.1,0.501,0.279,0.306,4.1,28.3,15.8,46.5,2.5,1.1,16.3,30.9,1.8,5,6.8,0.124,2.5,3.9,6.5,5.6 19 | 18,Klay Thompson,SG,28,GSW,78,2652,16.6,0.571,0.427,0.113,1.6,10.1,6,10.5,1.5,1.5,7.2,25.6,2.9,2.3,5.3,0.095,1.2,-2,-0.8,0.8 20 | 19,Julius Randle,PF,24,NOP,73,2232,21,0.6,0.179,0.447,7.6,21.6,14.7,15.8,1.1,1.6,13.8,27.8,4.2,1.9,6.1,0.131,1.8,-0.4,1.4,1.9 21 | 20,LaMarcus Aldridge,C,33,SAS,81,2687,22.9,0.576,0.032,0.312,10.3,19.8,15.1,11.6,0.8,3.4,8.8,26.9,6.4,2.9,9.3,0.167,1.2,0.5,1.6,2.5 22 | 21,Jrue Holiday,SG,28,NOP,67,2402,19.4,0.555,0.313,0.234,3.3,11,7.2,31.8,2.1,1.8,14.1,25.4,3.5,1.9,5.4,0.108,2.9,-0.1,2.8,2.9 23 | 22,DeMar DeRozan,SG,29,SAS,77,2688,19.6,0.542,0.034,0.336,2.2,16.4,9.4,27.6,1.6,1.1,11.7,27.9,3.6,2.6,6.3,0.112,0.4,0.5,0.9,2 24 | 23,Luka Doncic,SG,19,DAL,72,2318,19.6,0.545,0.433,0.409,4,21.9,13,31.6,1.6,0.9,15,30.5,2.1,2.8,4.9,0.101,2.9,1.2,4.1,3.6 25 | 24,Mike Conley,PG,31,MEM,70,2342,21.4,0.569,0.38,0.363,1.9,9.7,5.7,33.4,2,0.9,9.1,27.3,5.7,2.3,8,0.164,4.8,-1.3,3.4,3.2 26 | 25,D'Angelo Russell,PG,22,BRK,81,2448,19.4,0.533,0.419,0.135,2.3,11.2,6.8,41.3,1.9,0.6,13.6,31.9,2.4,2.6,5,0.097,3.9,-0.5,3.4,3.3 27 | 26,CJ McCollum,SG,27,POR,70,2375,17,0.553,0.358,0.154,2.9,9.7,6.3,13.8,1.1,0.9,7.4,25.5,4,1.7,5.6,0.114,2.2,-1.9,0.3,1.3 28 | 27,Nikola Vucevic,C,28,ORL,80,2510,25.5,0.573,0.171,0.168,9.4,31.9,20.5,21.9,1.6,3,9.9,28,5.4,4.7,10.1,0.193,3,3.4,6.4,5.3 29 | 28,Buddy Hield,SG,26,SAC,82,2615,17.5,0.587,0.479,0.142,4.1,12.4,8.1,11.9,1,1.1,9.2,25.1,4.3,1.6,5.9,0.108,3.1,-2,1.1,2.1 30 | 29,Nikola Jokic,C,23,DEN,80,2504,26.3,0.589,0.224,0.292,9.8,27.6,18.7,37,2.1,1.9,15.4,27.4,7.5,4.3,11.8,0.226,5.7,3.8,9.5,7.3 31 | 30,Tobias Harris,PF,26,TOT,82,2847,17.2,0.592,0.313,0.245,2.6,20.8,12,12.5,0.8,1,9.8,22.8,4.5,2.6,7.1,0.12,1.1,-0.6,0.5,1.8 32 | 31,Lou Williams,SG,32,LAC,75,1993,21.2,0.554,0.256,0.426,2.2,9.4,5.9,33,1.3,0.4,11.8,32.4,3.9,1.2,5.1,0.123,3.1,-2.6,0.4,1.2 33 | 32,Danilo Gallinari,SF,30,LAC,68,2059,21,0.633,0.421,0.459,2.9,18.1,10.7,13.2,1.1,0.9,8.5,23.8,6.4,1.8,8.2,0.191,4.2,-1.2,2.9,2.6 34 | 33,John Collins,PF,21,ATL,61,1829,21.8,0.627,0.19,0.32,12.3,22.1,17.1,11,0.6,1.8,11.2,23.7,5,1,6,0.158,2.6,-1.2,1.4,1.6 35 | 34,Trae Young,PG,20,ATL,81,2503,17,0.539,0.384,0.33,2.6,10.2,6.3,40.5,1.3,0.5,17.6,28.4,2.5,0.7,3.3,0.062,1.8,-2.8,-1.1,0.6 36 | 35,Jimmy Butler,SF-SG,29,TOT,65,2185,20.2,0.571,0.213,0.404,6,10.5,8.3,18,2.7,1.4,8.2,22.3,5.4,2.5,7.9,0.173,2.6,0.6,3.2,2.9 37 | 36,Kyle Kuzma,PF,23,LAL,70,2314,14,0.546,0.388,0.23,2.7,14.1,8.5,11.5,0.8,0.9,10,23.8,1.2,1.9,3.1,0.065,-0.3,-1.3,-1.7,0.2 38 | 37,Khris Middleton,SF,27,MIL,77,2393,16.5,0.558,0.413,0.225,2.3,16.5,9.8,20.1,1.6,0.2,12.1,25.1,2.5,3.6,6.1,0.123,0.7,0.1,0.8,1.7 39 | 38,Jamal Murray,PG,21,DEN,75,2447,16,0.538,0.353,0.19,2.9,11.2,7,22.4,1.3,1,11.1,24.9,2.8,2.3,5.1,0.1,1.1,-1,0.1,1.3 40 | 39,Andrew Wiggins,SF,23,MIN,73,2543,12.4,0.493,0.288,0.245,3.5,11.4,7.4,10.9,1.3,1.6,9.3,24.4,-0.6,1.3,0.6,0.012,-1.7,-1.3,-2.9,-0.6 41 | 40,J.J. Redick,SG,34,PHI,76,2379,15.1,0.602,0.589,0.248,0.9,7.2,4.1,12.9,0.6,0.6,8.1,21.9,4.6,1.2,5.9,0.118,2.7,-3.3,-0.7,0.8 42 | 41,Tim Hardaway,SG,26,TOT,65,2057,13.6,0.527,0.48,0.278,1.7,9.8,5.7,12.8,1.3,0.3,8.6,25.4,1,0.9,1.8,0.043,0.5,-2.9,-2.4,-0.2 43 | 42,Bojan Bogdanovic,SF,29,IND,81,2573,16.1,0.613,0.367,0.29,1.5,12.7,7.2,9.5,1.3,0,10.2,22.4,3.9,2.8,6.8,0.126,1.4,-1.4,0,1.3 44 | 43,Andre Drummond,C,25,DET,79,2647,23.4,0.555,0.036,0.392,16.8,34.7,25.4,7.2,2.5,4.4,12.4,22.9,4.1,5.9,10,0.181,-0.7,3.6,2.9,3.3 45 | 44,De'Aaron Fox,PG,21,SAC,81,2546,18.1,0.544,0.211,0.378,1.7,10.8,6.2,33.2,2.4,1.5,15,24.5,3.2,2.5,5.6,0.106,1.1,0,1.1,2 46 | 45,Ben Simmons,PG,22,PHI,79,2700,20,0.582,0.006,0.446,6.9,20,13.7,34.2,2,1.8,19.3,22.1,4.6,3.6,8.2,0.146,1.4,2.6,4.1,4.1 47 | 46,Pascal Siakam,PF,24,TOR,80,2548,18.7,0.628,0.226,0.32,5.4,17.5,11.6,14.6,1.4,1.7,12.5,20.8,5.7,3.6,9.3,0.175,2,1.4,3.4,3.5 48 | 47,Spencer Dinwiddie,PG,25,BRK,68,1914,16.3,0.58,0.447,0.43,1.4,7.6,4.6,25.6,1,0.7,13.4,24.9,3.5,1.4,4.8,0.121,1.9,-2.1,-0.2,0.8 49 | 48,Jordan Clarkson,SG,26,CLE,81,2214,16.8,0.539,0.377,0.163,3.9,9.9,6.8,15.6,1.3,0.5,9.6,27.6,1.9,-0.1,1.8,0.039,1.5,-3.5,-2,0 50 | 49,Collin Sexton,PG,20,CLE,82,2605,12,0.52,0.245,0.211,2.3,8,5,15.3,0.8,0.2,12.3,25.2,-0.1,-0.5,-0.6,-0.011,-1.5,-3.7,-5.2,-2.1 51 | 50,Clint Capela,C,24,HOU,67,2249,23.8,0.658,0,0.357,14.4,27.6,20.8,7.1,1,3.9,10,18.2,7.8,3,10.8,0.23,1.3,1.6,2.9,2.8 52 | -------------------------------------------------------------------------------- /final-csv-data/clustered-nba.csv: -------------------------------------------------------------------------------- 1 | ,Player,Cluster,Role,PTS,TRB,AST,STL,BLK,FG%,3P%,FT%,USG% 2 | 0,James Harden,7,Star ball handler,36.1,6.6,7.5,2.0,0.7,0.442,0.368,0.879,40.5 3 | 1,Paul George,7,Star ball handler,28.0,8.2,4.1,2.2,0.4,0.43799999999999994,0.386,0.8390000000000001,29.5 4 | 2,Giannis Antetokounmpo,5,Star big,27.7,12.5,5.9,1.3,1.5,0.578,0.256,0.7290000000000001,32.3 5 | 3,Joel Embiid,5,Star big,27.5,13.6,3.7,0.7,1.9,0.484,0.3,0.804,33.3 6 | 4,LeBron James,7,Star ball handler,27.4,8.5,8.3,1.3,0.6,0.51,0.33899999999999997,0.665,31.6 7 | 5,Stephen Curry,7,Star ball handler,27.3,5.3,5.2,1.3,0.4,0.47200000000000003,0.43700000000000006,0.9159999999999999,30.4 8 | 6,Devin Booker,8,Team-leading guard,26.6,4.1,6.8,0.9,0.2,0.467,0.326,0.866,32.9 9 | 7,Kawhi Leonard,7,Star ball handler,26.6,7.3,3.3,1.8,0.4,0.496,0.371,0.8540000000000001,30.3 10 | 8,Kevin Durant,7,Star ball handler,26.0,6.4,5.9,0.7,1.1,0.521,0.353,0.885,29.0 11 | 9,Anthony Davis,5,Star big,25.9,12.0,3.9,1.6,2.4,0.517,0.331,0.794,29.5 12 | 10,Damian Lillard,7,Star ball handler,25.8,4.6,6.9,1.1,0.4,0.444,0.369,0.912,29.3 13 | 11,Bradley Beal,8,Team-leading guard,25.6,5.0,5.5,1.5,0.7,0.475,0.35100000000000003,0.8079999999999999,28.4 14 | 12,Kemba Walker,8,Team-leading guard,25.6,4.4,5.9,1.2,0.4,0.434,0.35600000000000004,0.8440000000000001,31.5 15 | 13,Blake Griffin,7,Star ball handler,24.5,7.5,5.4,0.7,0.4,0.462,0.36200000000000004,0.753,30.2 16 | 14,Karl-Anthony Towns,5,Star big,24.4,12.4,3.4,0.9,1.6,0.518,0.4,0.836,28.9 17 | 15,Kyrie Irving,7,Star ball handler,23.8,5.0,6.9,1.5,0.5,0.48700000000000004,0.401,0.873,29.6 18 | 16,Donovan Mitchell,8,Team-leading guard,23.8,4.1,4.2,1.4,0.4,0.43200000000000005,0.36200000000000004,0.8059999999999999,31.6 19 | 17,Zach LaVine,8,Team-leading guard,23.7,4.7,4.5,1.0,0.4,0.467,0.374,0.8320000000000001,30.5 20 | 18,Russell Westbrook,5,Star big,22.9,11.1,10.7,1.9,0.5,0.428,0.29,0.6559999999999999,30.9 21 | 19,Klay Thompson,6,Shooter,21.5,3.8,2.4,1.1,0.6,0.467,0.402,0.816,25.6 22 | 20,Julius Randle,11,Inside big,21.4,8.7,3.1,0.7,0.6,0.524,0.344,0.731,27.8 23 | 21,LaMarcus Aldridge,11,Inside big,21.3,9.2,2.4,0.5,1.3,0.519,0.23800000000000002,0.847,26.9 24 | 22,DeMar DeRozan,8,Team-leading guard,21.2,6.0,6.2,1.1,0.5,0.48100000000000004,0.156,0.83,27.9 25 | 23,Luka Doncic,8,Team-leading guard,21.2,7.8,6.0,1.1,0.3,0.42700000000000005,0.327,0.713,30.5 26 | 24,Jrue Holiday,8,Team-leading guard,21.2,5.0,7.7,1.6,0.8,0.47200000000000003,0.325,0.768,25.4 27 | 25,Mike Conley,8,Team-leading guard,21.1,3.4,6.4,1.3,0.3,0.43799999999999994,0.364,0.845,27.3 28 | 26,D'Angelo Russell,8,Team-leading guard,21.1,3.9,7.0,1.2,0.2,0.434,0.369,0.78,31.9 29 | 27,CJ McCollum,6,Shooter,21.0,4.0,3.0,0.8,0.4,0.45899999999999996,0.375,0.828,25.5 30 | 28,Nikola Vucevic,5,Star big,20.8,12.0,3.8,1.0,1.1,0.518,0.364,0.789,28.0 31 | 29,Buddy Hield,6,Shooter,20.7,5.0,2.5,0.7,0.4,0.45799999999999996,0.42700000000000005,0.8859999999999999,25.1 32 | 30,Nikola Jokic,5,Star big,20.1,10.8,7.3,1.4,0.7,0.511,0.307,0.821,27.4 33 | 31,Tobias Harris,2,Perimiter scorer,20.0,7.9,2.8,0.6,0.5,0.48700000000000004,0.397,0.866,22.8 34 | 32,Lou Williams,8,Team-leading guard,20.0,3.0,5.4,0.8,0.1,0.425,0.361,0.8759999999999999,32.4 35 | 33,Danilo Gallinari,6,Shooter,19.8,6.1,2.6,0.7,0.3,0.46299999999999997,0.433,0.904,23.8 36 | 34,John Collins,11,Inside big,19.5,9.8,2.0,0.4,0.6,0.56,0.348,0.763,23.7 37 | 35,Trae Young,8,Team-leading guard,19.1,3.7,8.1,0.9,0.2,0.418,0.324,0.8290000000000001,28.4 38 | 36,Jimmy Butler,8,Team-leading guard,18.7,5.3,4.0,1.9,0.6,0.462,0.34700000000000003,0.855,22.3 39 | 37,Kyle Kuzma,2,Perimiter scorer,18.7,5.5,2.5,0.6,0.4,0.456,0.303,0.752,23.8 40 | 38,Lauri Markkanen,2,Perimiter scorer,18.7,9.0,1.4,0.7,0.6,0.43,0.361,0.872,25.1 41 | 39,Brandon Ingram,2,Perimiter scorer,18.3,5.1,3.0,0.5,0.6,0.49700000000000005,0.33,0.675,23.2 42 | 40,Khris Middleton,6,Shooter,18.3,6.0,4.3,1.0,0.1,0.441,0.37799999999999995,0.8370000000000001,25.1 43 | 41,Jamal Murray,6,Shooter,18.2,4.2,4.8,0.9,0.4,0.43700000000000006,0.36700000000000005,0.848,24.9 44 | 42,Tim Hardaway,6,Shooter,18.1,3.4,2.4,0.8,0.1,0.39299999999999996,0.34,0.841,25.4 45 | 43,J.J. Redick,6,Shooter,18.1,2.4,2.7,0.4,0.2,0.44,0.397,0.894,21.9 46 | 44,Andrew Wiggins,2,Perimiter scorer,18.1,4.8,2.5,1.0,0.7,0.41200000000000003,0.33899999999999997,0.6990000000000001,24.4 47 | 45,Bojan Bogdanovic,6,Shooter,18.0,4.1,2.0,0.9,0.0,0.49700000000000005,0.425,0.807,22.4 48 | 46,Derrick Rose,6,Shooter,18.0,2.7,4.3,0.6,0.2,0.48200000000000004,0.37,0.856,27.3 49 | 47,Andre Drummond,5,Star big,17.3,15.6,1.4,1.7,1.7,0.5329999999999999,0.132,0.59,22.9 50 | 48,De'Aaron Fox,8,Team-leading guard,17.3,3.8,7.3,1.6,0.6,0.45799999999999996,0.371,0.727,24.5 51 | 49,Pascal Siakam,9,Do it all big,16.9,6.9,3.1,0.9,0.7,0.5489999999999999,0.369,0.785,20.8 52 | 50,Ben Simmons,5,Star big,16.9,8.8,7.7,1.4,0.8,0.563,0.0,0.6,22.1 53 | 51,Jordan Clarkson,6,Shooter,16.8,3.3,2.4,0.7,0.2,0.44799999999999995,0.324,0.8440000000000001,27.6 54 | 52,Spencer Dinwiddie,6,Shooter,16.8,2.4,4.6,0.6,0.3,0.442,0.335,0.8059999999999999,24.9 55 | 53,Collin Sexton,4,???,16.7,2.9,3.0,0.5,0.1,0.43,0.402,0.8390000000000001,25.2 56 | 54,Clint Capela,3,Rim runner,16.6,12.7,1.4,0.7,1.5,0.648,0.0,0.636,18.2 57 | 55,Montrezl Harrell,11,Inside big,16.6,6.5,2.0,0.9,1.3,0.615,0.17600000000000002,0.643,23.5 58 | 56,Josh Richardson,6,Shooter,16.6,3.6,4.1,1.1,0.5,0.41200000000000003,0.35700000000000004,0.861,20.9 59 | 57,Harrison Barnes,6,Shooter,16.4,4.7,1.5,0.6,0.2,0.42,0.395,0.8240000000000001,20.9 60 | 58,Deandre Ayton,11,Inside big,16.3,10.3,1.8,0.9,0.9,0.585,0.0,0.746,21.2 61 | 59,Eric Gordon,6,Shooter,16.2,2.2,1.9,0.6,0.4,0.409,0.36,0.7829999999999999,22.0 62 | 60,Aaron Gordon,2,Perimiter scorer,16.0,7.4,3.7,0.7,0.7,0.449,0.349,0.731,21.8 63 | 61,Eric Bledsoe,10,Floor general,15.9,4.6,5.5,1.5,0.4,0.484,0.32899999999999996,0.75,22.9 64 | 62,Rudy Gobert,5,Star big,15.9,12.9,2.0,0.8,2.3,0.669,0.0,0.636,17.8 65 | 63,Jayson Tatum,2,Perimiter scorer,15.7,6.0,2.1,1.1,0.7,0.45,0.373,0.855,22.1 66 | 64,Malcolm Brogdon,6,Shooter,15.6,4.5,3.2,0.7,0.2,0.505,0.426,0.9279999999999999,20.7 67 | 65,Jusuf Nurkic,11,Inside big,15.6,10.4,3.2,1.0,1.4,0.508,0.10300000000000001,0.773,24.7 68 | 66,Chris Paul,10,Floor general,15.6,4.6,8.2,2.0,0.3,0.419,0.358,0.862,22.5 69 | 67,Dennis Schroder,4,???,15.5,3.6,4.1,0.8,0.2,0.414,0.341,0.8190000000000001,24.2 70 | 68,Reggie Jackson,6,Shooter,15.4,2.6,4.2,0.7,0.1,0.42100000000000004,0.369,0.8640000000000001,24.5 71 | 69,Jeremy Lamb,6,Shooter,15.3,5.5,2.2,1.1,0.4,0.44,0.348,0.888,22.5 72 | 70,Kelly Oubre,2,Perimiter scorer,15.2,4.7,1.2,1.2,0.9,0.445,0.32,0.775,23.2 73 | 71,Evan Fournier,6,Shooter,15.1,3.2,3.6,0.9,0.1,0.43799999999999994,0.34,0.8059999999999999,22.1 74 | 72,Terrence Ross,6,Shooter,15.1,3.5,1.7,0.9,0.4,0.428,0.38299999999999995,0.875,23.9 75 | 73,Serge Ibaka,9,Do it all big,15.0,8.1,1.3,0.4,1.4,0.529,0.29,0.763,22.9 76 | 74,Dwyane Wade,2,Perimiter scorer,15.0,4.0,4.2,0.8,0.5,0.433,0.33,0.708,27.9 77 | 75,Marvin Bagley,2,Perimiter scorer,14.9,7.6,1.0,0.5,1.0,0.504,0.313,0.691,24.2 78 | 76,Emmanuel Mudiay,4,???,14.8,3.3,3.9,0.7,0.3,0.446,0.32899999999999996,0.774,25.6 79 | 77,Jabari Parker,2,Perimiter scorer,14.5,6.6,2.4,0.7,0.5,0.493,0.313,0.7120000000000001,24.6 80 | 78,Kyle Lowry,10,Floor general,14.2,4.8,8.7,1.4,0.5,0.41100000000000003,0.34700000000000003,0.83,19.6 81 | 79,Bobby Portis,2,Perimiter scorer,14.2,8.1,1.4,0.7,0.4,0.444,0.39299999999999996,0.794,24.6 82 | 80,Bogdan Bogdanovic,6,Shooter,14.1,3.5,3.8,1.0,0.2,0.418,0.36,0.8270000000000001,22.3 83 | 81,Domantas Sabonis,11,Inside big,14.1,9.3,2.9,0.6,0.4,0.59,0.529,0.715,23.5 84 | 82,Steven Adams,3,Rim runner,13.9,9.5,1.6,1.5,1.0,0.595,0.0,0.5,16.4 85 | 83,Marcus Morris,2,Perimiter scorer,13.9,6.1,1.5,0.6,0.3,0.447,0.375,0.8440000000000001,20.9 86 | 84,Otto Porter,2,Perimiter scorer,13.9,5.6,2.1,1.5,0.6,0.465,0.406,0.813,19.1 87 | 85,Jaren Jackson,9,Do it all big,13.8,4.7,1.1,0.9,1.4,0.506,0.359,0.7659999999999999,22.8 88 | 86,Rudy Gay,2,Perimiter scorer,13.7,6.8,2.6,0.8,0.5,0.504,0.402,0.816,22.1 89 | 87,Joe Harris,6,Shooter,13.7,3.8,2.4,0.5,0.2,0.5,0.474,0.8270000000000001,17.0 90 | 88,Enes Kanter,11,Inside big,13.7,9.8,1.7,0.5,0.4,0.5489999999999999,0.294,0.787,23.1 91 | 89,Marc Gasol,9,Do it all big,13.6,7.9,4.4,1.1,1.1,0.44799999999999995,0.363,0.759,20.7 92 | 90,Jerami Grant,9,Do it all big,13.6,5.2,1.0,0.8,1.3,0.49700000000000005,0.392,0.71,15.4 93 | 91,Al Horford,9,Do it all big,13.6,6.7,4.2,0.9,1.3,0.535,0.36,0.821,18.9 94 | 92,Dennis Smith,4,???,13.6,2.9,4.8,1.3,0.4,0.428,0.322,0.635,24.8 95 | 93,Taurean Waller-Prince,1,3&D guard,13.5,3.6,2.1,1.0,0.3,0.441,0.39,0.8190000000000001,19.5 96 | 94,Myles Turner,9,Do it all big,13.3,7.2,1.6,0.8,2.7,0.48700000000000004,0.38799999999999996,0.736,20.0 97 | 95,Jaylen Brown,2,Perimiter scorer,13.0,4.2,1.4,0.9,0.4,0.465,0.344,0.6579999999999999,22.1 98 | 96,Cedi Osman,4,???,13.0,4.7,2.6,0.8,0.1,0.42700000000000005,0.348,0.779,18.6 99 | 97,Gary Harris,4,???,12.9,2.8,2.2,1.0,0.3,0.424,0.33899999999999997,0.799,20.0 100 | 98,Kevin Knox,4,???,12.8,4.5,1.1,0.6,0.3,0.37,0.34299999999999997,0.7170000000000001,22.3 101 | 99,Ricky Rubio,10,Floor general,12.7,3.6,6.1,1.3,0.1,0.40399999999999997,0.311,0.855,22.7 102 | 100,Paul Millsap,9,Do it all big,12.6,7.2,2.0,1.2,0.8,0.484,0.365,0.727,19.6 103 | 101,Justise Winslow,10,Floor general,12.6,5.4,4.3,1.1,0.3,0.433,0.375,0.628,20.8 104 | 102,Thaddeus Young,9,Do it all big,12.6,6.5,2.5,1.5,0.4,0.527,0.349,0.644,18.0 105 | 103,Trevor Ariza,4,???,12.5,5.4,3.7,1.3,0.3,0.39899999999999997,0.33399999999999996,0.7929999999999999,16.6 106 | 104,Brook Lopez,9,Do it all big,12.5,4.9,1.2,0.6,2.2,0.452,0.365,0.8420000000000001,16.7 107 | 105,Jeff Green,2,Perimiter scorer,12.3,4.0,1.8,0.6,0.5,0.475,0.34700000000000003,0.888,17.8 108 | 106,Hassan Whiteside,3,Rim runner,12.3,11.3,0.8,0.6,1.9,0.5710000000000001,0.125,0.449,22.6 109 | 107,Wesley Matthews,1,3&D guard,12.2,2.5,2.3,0.8,0.2,0.4,0.37200000000000005,0.81,17.8 110 | 108,Joe Ingles,10,Floor general,12.1,4.0,5.7,1.2,0.2,0.44799999999999995,0.391,0.7070000000000001,17.5 111 | 109,JaVale McGee,3,Rim runner,12.0,7.5,0.7,0.6,2.0,0.624,0.083,0.632,20.2 112 | 110,Willie Cauley-Stein,9,Do it all big,11.9,8.4,2.4,1.2,0.6,0.556,0.5,0.551,17.5 113 | 111,Jae Crowder,2,Perimiter scorer,11.9,4.8,1.7,0.8,0.4,0.39899999999999997,0.331,0.721,19.1 114 | 112,E'Twaun Moore,1,3&D guard,11.9,2.4,1.9,0.8,0.2,0.48100000000000004,0.43200000000000005,0.763,17.3 115 | 113,Derrick Favors,3,Rim runner,11.8,7.4,1.2,0.7,1.4,0.586,0.218,0.675,19.4 116 | 114,Bryn Forbes,1,3&D guard,11.8,2.9,2.1,0.5,0.0,0.456,0.426,0.885,17.4 117 | 115,D.J. Augustin,6,Shooter,11.7,2.5,5.3,0.6,0.0,0.47,0.42100000000000004,0.866,17.2 118 | 116,Kent Bazemore,4,???,11.6,3.9,2.3,1.3,0.6,0.402,0.32,0.726,22.0 119 | 117,Gordon Hayward,2,Perimiter scorer,11.5,4.5,3.4,0.9,0.3,0.466,0.33299999999999996,0.8340000000000001,19.0 120 | 118,Josh Jackson,4,???,11.5,4.4,2.3,0.9,0.7,0.413,0.324,0.6709999999999999,23.9 121 | 119,Kentavious Caldwell-Pope,1,3&D guard,11.4,2.9,1.3,0.9,0.2,0.43,0.34700000000000003,0.867,18.1 122 | 120,Malik Beasley,1,3&D guard,11.3,2.5,1.2,0.7,0.1,0.474,0.402,0.848,18.7 123 | 121,Reggie Bullock,1,3&D guard,11.3,2.7,2.0,0.6,0.2,0.41200000000000003,0.377,0.8590000000000001,15.8 124 | 122,Darren Collison,10,Floor general,11.2,3.1,6.0,1.4,0.1,0.467,0.40700000000000003,0.8320000000000001,17.7 125 | 123,Rodney Hood,1,3&D guard,11.2,2.2,1.8,0.8,0.2,0.435,0.35600000000000004,0.884,18.1 126 | 124,DeMarre Carroll,2,Perimiter scorer,11.1,5.2,1.3,0.5,0.1,0.395,0.342,0.76,18.6 127 | 125,Alex Len,2,Perimiter scorer,11.1,5.5,1.1,0.4,0.9,0.494,0.363,0.648,22.1 128 | 126,DeAndre Jordan,3,Rim runner,11.0,13.1,2.3,0.6,1.1,0.6409999999999999,0.0,0.705,15.0 129 | 127,Fred VanVleet,6,Shooter,11.0,2.6,4.8,0.9,0.3,0.41,0.37799999999999995,0.843,17.9 130 | 128,Jarrett Allen,3,Rim runner,10.9,8.4,1.4,0.5,1.5,0.59,0.133,0.7090000000000001,15.9 131 | 129,Trey Burke,4,???,10.9,1.7,2.7,0.6,0.1,0.431,0.35200000000000004,0.831,24.8 132 | 130,Tyler Johnson,4,???,10.9,3.0,2.9,0.9,0.5,0.413,0.34600000000000003,0.748,18.5 133 | 131,Allonzo Trier,4,???,10.9,3.1,1.9,0.4,0.2,0.44799999999999995,0.39399999999999996,0.8029999999999999,21.5 134 | 132,Dewayne Dedmon,9,Do it all big,10.8,7.5,1.4,1.1,1.1,0.49200000000000005,0.382,0.8140000000000001,16.7 135 | 133,Taj Gibson,9,Do it all big,10.8,6.5,1.2,0.8,0.6,0.5660000000000001,0.324,0.757,17.2 136 | 134,Shai Gilgeous-Alexander,10,Floor general,10.8,2.8,3.3,1.2,0.5,0.47600000000000003,0.36700000000000005,0.8,18.3 137 | 135,Damyean Dotson,4,???,10.7,3.6,1.8,0.8,0.1,0.415,0.368,0.745,17.3 138 | 136,Dwight Powell,3,Rim runner,10.6,5.3,1.5,0.6,0.6,0.597,0.307,0.772,17.2 139 | 137,Dario Saric,2,Perimiter scorer,10.6,5.6,1.6,0.6,0.1,0.43700000000000006,0.365,0.88,17.8 140 | 138,Marco Belinelli,1,3&D guard,10.5,2.5,1.7,0.4,0.1,0.413,0.37200000000000005,0.903,19.8 141 | 139,Thomas Bryant,3,Rim runner,10.5,6.3,1.3,0.3,0.9,0.616,0.33299999999999996,0.7809999999999999,17.6 142 | 140,Justin Holiday,4,???,10.5,3.9,1.8,1.5,0.4,0.386,0.348,0.8959999999999999,15.7 143 | 141,Monte Morris,1,3&D guard,10.4,2.4,3.6,0.9,0.0,0.493,0.414,0.802,17.1 144 | 142,Wayne Ellington,1,3&D guard,10.3,2.0,1.4,1.0,0.1,0.40299999999999997,0.371,0.7959999999999999,17.2 145 | 143,Danny Green,1,3&D guard,10.3,4.0,1.6,0.9,0.7,0.465,0.455,0.841,14.1 146 | 144,Tyreke Evans,4,???,10.2,2.9,2.4,0.8,0.3,0.389,0.35600000000000004,0.7190000000000001,26.4 147 | 145,Marvin Williams,12,3&D forward,10.1,5.4,1.2,0.9,0.8,0.42200000000000004,0.366,0.767,14.9 148 | 146,Kelly Olynyk,12,3&D forward,10.0,4.7,1.8,0.7,0.5,0.46299999999999997,0.354,0.8220000000000001,18.0 149 | 147,Avery Bradley,4,???,9.9,2.8,2.4,0.7,0.3,0.408,0.35100000000000003,0.86,16.2 150 | 148,Patty Mills,1,3&D guard,9.9,2.2,3.0,0.6,0.1,0.425,0.39399999999999996,0.8540000000000001,18.5 151 | 149,Derrick White,10,Floor general,9.9,3.7,3.9,1.0,0.7,0.479,0.33799999999999997,0.772,17.7 152 | 150,Kevin Huerter,4,???,9.7,3.3,2.9,0.9,0.3,0.419,0.385,0.732,15.7 153 | 151,Luke Kennard,1,3&D guard,9.7,2.9,1.8,0.4,0.2,0.43799999999999994,0.39399999999999996,0.836,18.1 154 | 152,Nemanja Bjelica,12,3&D forward,9.6,5.8,1.9,0.7,0.7,0.479,0.401,0.7609999999999999,16.5 155 | 153,Jonathan Isaac,12,3&D forward,9.6,5.5,1.1,0.8,1.3,0.429,0.32299999999999995,0.815,16.3 156 | 154,Jeremy Lin,4,???,9.6,2.4,3.1,0.6,0.2,0.44,0.294,0.838,21.8 157 | 155,Robin Lopez,12,3&D forward,9.5,3.9,1.2,0.1,1.1,0.568,0.226,0.7240000000000001,18.6 158 | 156,Tony Parker,4,???,9.5,1.5,3.7,0.4,0.1,0.46,0.255,0.7340000000000001,25.5 159 | 157,Al-Farouq Aminu,12,3&D forward,9.4,7.5,1.3,0.8,0.4,0.433,0.34299999999999997,0.867,13.7 160 | 158,JaMychal Green,12,3&D forward,9.4,6.3,0.8,0.7,0.5,0.483,0.40299999999999997,0.792,19.4 161 | 159,Markieff Morris,12,3&D forward,9.4,4.6,1.4,0.6,0.4,0.42100000000000004,0.335,0.772,19.1 162 | 160,Larry Nance,9,Do it all big,9.4,8.2,3.2,1.5,0.6,0.52,0.337,0.716,15.5 163 | 161,Nicolas Batum,12,3&D forward,9.3,5.2,3.3,0.9,0.6,0.45,0.389,0.865,13.2 164 | 162,Jalen Brunson,4,???,9.3,2.3,3.2,0.5,0.1,0.467,0.348,0.725,19.1 165 | 163,Gerald Green,1,3&D guard,9.2,2.5,0.5,0.5,0.4,0.4,0.354,0.838,19.5 166 | 164,Landry Shamet,1,3&D guard,9.1,1.7,1.5,0.5,0.1,0.431,0.42200000000000004,0.8059999999999999,15.0 167 | 165,Terry Rozier,4,???,9.0,3.9,2.9,0.9,0.3,0.387,0.353,0.785,18.6 168 | 166,Bam Adebayo,3,Rim runner,8.9,7.3,2.2,0.9,0.8,0.5760000000000001,0.2,0.735,15.8 169 | 167,Rondae Hollis-Jefferson,4,???,8.9,5.3,1.6,0.7,0.5,0.41100000000000003,0.184,0.645,21.6 170 | 168,Malik Monk,4,???,8.9,1.9,1.6,0.5,0.3,0.387,0.33,0.882,24.6 171 | 169,Tomas Satoransky,10,Floor general,8.9,3.5,5.0,1.0,0.2,0.485,0.395,0.8190000000000001,14.1 172 | 170,Marcus Smart,10,Floor general,8.9,2.9,4.0,1.8,0.4,0.42200000000000004,0.364,0.8059999999999999,14.6 173 | 171,Ish Smith,4,???,8.9,2.6,3.6,0.5,0.2,0.419,0.326,0.758,19.9 174 | 172,Ivica Zubac,3,Rim runner,8.9,6.1,1.1,0.2,0.9,0.5589999999999999,0.0,0.802,20.3 175 | 173,Alec Burks,4,???,8.8,3.7,2.0,0.6,0.3,0.405,0.363,0.823,19.0 176 | 174,Mario Hezonja,4,???,8.8,4.1,1.5,1.0,0.1,0.41200000000000003,0.276,0.763,21.3 177 | 175,Delon Wright,10,Floor general,8.7,3.5,3.3,1.2,0.4,0.434,0.298,0.7929999999999999,18.1 178 | 176,Kyle Korver,1,3&D guard,8.6,2.3,1.2,0.4,0.2,0.41600000000000004,0.397,0.8220000000000001,18.5 179 | 177,Norman Powell,1,3&D guard,8.6,2.3,1.5,0.7,0.2,0.483,0.4,0.8270000000000001,19.0 180 | 178,Rodions Kurucs,12,3&D forward,8.5,3.9,0.8,0.7,0.4,0.45,0.315,0.7829999999999999,18.4 181 | 179,Trey Lyles,4,???,8.5,3.8,1.4,0.5,0.4,0.418,0.255,0.698,23.4 182 | 180,DeAndre' Bembry,4,???,8.4,4.4,2.5,1.3,0.5,0.446,0.289,0.64,17.2 183 | 181,Langston Galloway,1,3&D guard,8.4,2.1,1.1,0.5,0.1,0.38799999999999996,0.355,0.8440000000000001,16.1 184 | 182,Noah Vonleh,12,3&D forward,8.4,7.8,1.9,0.7,0.8,0.47,0.336,0.7120000000000001,14.8 185 | 183,Mikal Bridges,12,3&D forward,8.3,3.2,2.1,1.6,0.5,0.43,0.335,0.805,12.2 186 | 184,Richaun Holmes,3,Rim runner,8.2,4.7,0.9,0.6,1.1,0.608,0.0,0.731,17.9 187 | 185,Darius Miller,1,3&D guard,8.2,1.9,2.1,0.6,0.3,0.39,0.365,0.789,13.4 188 | 186,Frank Jackson,4,???,8.1,2.2,1.1,0.4,0.0,0.434,0.314,0.74,18.5 189 | 187,Austin Rivers,4,???,8.1,2.1,2.2,0.6,0.3,0.406,0.318,0.526,14.5 190 | 188,Davis Bertans,1,3&D guard,8.0,3.5,1.3,0.5,0.4,0.45,0.429,0.883,14.1 191 | 189,Jamal Crawford,4,???,7.9,1.3,3.6,0.5,0.2,0.397,0.332,0.845,20.8 192 | 190,Seth Curry,1,3&D guard,7.9,1.6,0.9,0.5,0.2,0.456,0.45,0.846,16.6 193 | 191,Josh Hart,12,3&D forward,7.8,3.7,1.4,1.0,0.6,0.40700000000000003,0.336,0.688,13.5 194 | 192,James Johnson,4,???,7.8,3.2,2.5,0.6,0.5,0.433,0.336,0.7140000000000001,17.8 195 | 193,Mason Plumlee,3,Rim runner,7.8,6.4,3.0,0.8,0.9,0.593,0.2,0.561,16.2 196 | 194,Garrett Temple,4,???,7.8,2.9,1.4,1.0,0.4,0.42200000000000004,0.341,0.748,13.2 197 | 195,Ante Zizic,12,3&D forward,7.8,5.4,0.9,0.2,0.4,0.5529999999999999,0.0,0.705,18.2 198 | 196,Maurice Harkless,12,3&D forward,7.7,4.5,1.2,1.1,0.9,0.48700000000000004,0.275,0.6709999999999999,13.9 199 | 197,Josh Okogie,4,???,7.7,2.9,1.2,1.2,0.4,0.386,0.27899999999999997,0.728,15.4 200 | 198,Patrick Beverley,10,Floor general,7.6,5.0,3.8,0.9,0.6,0.40700000000000003,0.397,0.78,12.2 201 | 199,George Hill,1,3&D guard,7.6,2.5,2.3,0.9,0.1,0.452,0.314,0.8240000000000001,15.1 202 | 200,Jake Layman,12,3&D forward,7.6,3.1,0.7,0.4,0.4,0.509,0.326,0.7040000000000001,15.9 203 | 201,Rodney McGruder,4,???,7.6,3.6,1.7,0.5,0.2,0.40299999999999997,0.35100000000000003,0.722,15.4 204 | 202,Miles Bridges,12,3&D forward,7.5,4.0,1.2,0.7,0.6,0.46399999999999997,0.325,0.753,15.1 205 | 203,Dorian Finney-Smith,12,3&D forward,7.5,4.8,1.2,0.9,0.4,0.43200000000000005,0.311,0.7090000000000001,14.0 206 | 204,Shelvin Mack,4,???,7.5,1.8,3.2,0.8,0.1,0.40399999999999997,0.354,0.69,18.1 207 | 205,Iman Shumpert,4,???,7.5,3.0,1.8,1.0,0.4,0.374,0.348,0.8,14.5 208 | 206,Vince Carter,1,3&D guard,7.4,2.6,1.1,0.6,0.4,0.419,0.389,0.7120000000000001,16.7 209 | 207,Draymond Green,10,Floor general,7.4,7.3,6.9,1.4,1.1,0.445,0.285,0.6920000000000001,13.1 210 | 208,Doug McDermott,1,3&D guard,7.3,1.4,0.9,0.2,0.1,0.491,0.408,0.835,16.3 211 | 209,Mitchell Robinson,3,Rim runner,7.3,6.4,0.6,0.8,2.4,0.6940000000000001,0.0,0.6,12.1 212 | 210,P.J. Tucker,12,3&D forward,7.3,5.8,1.2,1.6,0.5,0.396,0.377,0.695,9.5 213 | 211,Justin Jackson,1,3&D guard,7.2,2.6,1.2,0.4,0.2,0.447,0.355,0.785,14.3 214 | 212,Lance Stephenson,4,???,7.2,3.2,2.1,0.6,0.1,0.426,0.371,0.685,20.3 215 | 213,OG Anunoby,12,3&D forward,7.0,2.9,0.7,0.7,0.3,0.45299999999999996,0.332,0.581,15.5 216 | 214,Derrick Jones,12,3&D forward,7.0,4.0,0.6,0.8,0.7,0.494,0.308,0.607,15.6 217 | 215,Mike Muscala,12,3&D forward,7.0,3.8,1.2,0.3,0.6,0.402,0.348,0.8240000000000001,14.3 218 | 216,Pat Connaughton,12,3&D forward,6.9,4.2,2.0,0.5,0.4,0.466,0.33,0.725,13.3 219 | 217,Quinn Cook,1,3&D guard,6.9,2.1,1.6,0.3,0.0,0.465,0.405,0.769,20.2 220 | 218,Terrance Ferguson,1,3&D guard,6.9,1.9,1.0,0.5,0.2,0.429,0.366,0.725,10.6 221 | 219,Stanley Johnson,4,???,6.9,3.3,1.3,0.9,0.2,0.389,0.28800000000000003,0.7809999999999999,19.4 222 | 220,Tyus Jones,4,???,6.9,2.0,4.8,1.2,0.1,0.415,0.317,0.841,14.1 223 | 221,Wayne Selden,4,???,6.9,2.4,1.5,0.4,0.2,0.406,0.316,0.728,18.4 224 | 222,Ersan Ilyasova,12,3&D forward,6.8,4.5,0.8,0.5,0.3,0.43799999999999994,0.363,0.8240000000000001,15.7 225 | 223,Maxi Kleber,12,3&D forward,6.8,4.6,1.0,0.5,1.1,0.45299999999999996,0.353,0.784,13.5 226 | 224,Evan Turner,4,???,6.8,4.5,3.9,0.5,0.2,0.46,0.212,0.708,15.9 227 | 225,Ryan Arcidiacono,1,3&D guard,6.7,2.7,3.3,0.8,0.0,0.447,0.373,0.873,11.7 228 | 226,James Ennis,12,3&D forward,6.7,3.1,0.7,0.7,0.4,0.469,0.353,0.716,12.7 229 | 227,Michael Kidd-Gilchrist,12,3&D forward,6.7,3.8,1.0,0.5,0.6,0.47600000000000003,0.34,0.772,15.7 230 | 228,Zach Collins,12,3&D forward,6.6,4.2,0.9,0.3,0.9,0.473,0.331,0.746,16.6 231 | 229,Shaquille Harrison,4,???,6.5,3.0,1.9,1.2,0.4,0.43200000000000005,0.27,0.667,16.5 232 | 230,Cory Joseph,4,???,6.5,3.4,3.9,1.1,0.3,0.41200000000000003,0.322,0.698,13.7 233 | 231,Jonathon Simmons,4,???,6.5,2.3,2.3,0.5,0.3,0.38,0.26899999999999996,0.742,18.7 234 | 232,Sterling Brown,12,3&D forward,6.4,3.2,1.4,0.4,0.1,0.465,0.361,0.69,15.2 235 | 233,Gorgui Dieng,12,3&D forward,6.4,4.1,0.9,0.6,0.5,0.501,0.33899999999999997,0.83,19.6 236 | 234,T.J. McConnell,4,???,6.4,2.3,3.4,1.0,0.2,0.525,0.33299999999999996,0.784,15.0 237 | 235,Devin Harris,4,???,6.3,1.6,1.8,0.5,0.2,0.38,0.31,0.7609999999999999,18.5 238 | 236,Jonas Jerebko,12,3&D forward,6.3,3.9,1.3,0.4,0.2,0.45899999999999996,0.36700000000000005,0.8,15.2 239 | 237,Kevon Looney,3,Rim runner,6.3,5.2,1.5,0.6,0.7,0.625,0.1,0.619,12.8 240 | 238,Wilson Chandler,12,3&D forward,6.0,4.2,1.6,0.5,0.4,0.418,0.373,0.72,11.8 241 | 239,Tony Snell,1,3&D guard,6.0,2.1,0.9,0.4,0.2,0.452,0.397,0.8809999999999999,12.9 242 | 240,Yogi Ferrell,1,3&D guard,5.9,1.5,1.9,0.5,0.1,0.435,0.36200000000000004,0.8959999999999999,16.3 243 | 241,Nik Stauskas,1,3&D guard,5.9,1.9,1.2,0.3,0.1,0.402,0.37200000000000005,0.8909999999999999,17.6 244 | 242,Ed Davis,3,Rim runner,5.8,8.6,0.8,0.4,0.4,0.616,0.0,0.617,12.7 245 | 243,Juan Hernangomez,12,3&D forward,5.8,3.8,0.8,0.4,0.3,0.439,0.365,0.767,12.2 246 | 244,Mike Scott,1,3&D guard,5.8,3.5,0.8,0.3,0.2,0.4,0.401,0.667,14.4 247 | 245,Torrey Craig,12,3&D forward,5.7,3.5,1.0,0.5,0.6,0.442,0.324,0.7,12.4 248 | 246,Andre Iguodala,12,3&D forward,5.7,3.7,3.2,0.9,0.8,0.5,0.33299999999999996,0.5820000000000001,10.4 249 | 247,Jakob Poeltl,3,Rim runner,5.5,5.3,1.2,0.4,0.9,0.645,0.0,0.5329999999999999,13.1 250 | 248,Tim Frazier,4,???,5.3,2.8,4.2,0.5,0.1,0.444,0.366,0.759,13.3 251 | 249,Royce O'Neale,12,3&D forward,5.2,3.5,1.5,0.7,0.3,0.475,0.386,0.762,11.0 252 | 250,Wesley Iwundu,4,???,5.0,2.7,1.1,0.4,0.3,0.41200000000000003,0.36700000000000005,0.816,12.8 253 | 251,Anthony Tolliver,1,3&D guard,5.0,2.7,0.7,0.3,0.3,0.382,0.377,0.7829999999999999,12.5 254 | 252,Jared Dudley,12,3&D forward,4.9,2.6,1.4,0.6,0.3,0.423,0.35100000000000003,0.696,10.4 255 | 253,Nerlens Noel,3,Rim runner,4.9,4.2,0.6,0.9,1.2,0.5870000000000001,0.0,0.684,13.8 256 | 254,Alfonzo McKinnie,12,3&D forward,4.7,3.4,0.4,0.3,0.2,0.48700000000000004,0.35600000000000004,0.563,13.9 257 | 255,Bruce Brown,4,???,4.3,2.5,1.2,0.5,0.5,0.39799999999999996,0.258,0.75,11.5 258 | -------------------------------------------------------------------------------- /final-csv-data/clustering-example.csv: -------------------------------------------------------------------------------- 1 | Rk,Player,Pos,Age,Tm,G,GS,MP,FG,FGA,FG%,3P,3PA,3P%,2P,2PA,2P%,eFG%,FT,FTA,FT%,ORB,DRB,TRB,AST,STL,BLK,TOV,PF,PTS 2 | 1,Paul George,SF,28,OKC,77,77,36.9,9.2,21,0.438,3.8,9.8,0.386,5.4,11.1,0.484,0.529,5.9,7,0.839,1.4,6.8,8.2,4.1,2.2,0.4,2.7,2.8,28 3 | 2,James Harden,PG,29,HOU,78,78,36.8,10.8,24.5,0.442,4.8,13.2,0.368,6,11.3,0.528,0.541,9.7,11,0.879,0.8,5.8,6.6,7.5,2,0.7,5,3.1,36.1 4 | 3,Chris Paul,PG,33,HOU,58,58,32,5.2,12.4,0.419,2.2,6.1,0.358,3,6.3,0.479,0.508,3,3.5,0.862,0.6,3.9,4.6,8.2,2,0.3,2.6,2.5,15.6 5 | 4,Jimmy Butler,SF-SG,29,TOT,65,65,33.6,6.4,13.9,0.462,1,3,0.347,5.4,10.9,0.494,0.499,4.8,5.6,0.855,1.9,3.4,5.3,4,1.9,0.6,1.5,1.7,18.7 6 | 5,Russell Westbrook,PG,30,OKC,73,73,36,8.6,20.2,0.428,1.6,5.6,0.29,7,14.5,0.481,0.468,4.1,6.2,0.656,1.5,9.6,11.1,10.7,1.9,0.5,4.5,3.4,22.9 7 | 1,Myles Turner,C,22,IND,74,74,28.6,5.1,10.5,0.487,1,2.6,0.388,4.1,7.9,0.521,0.536,2,2.7,0.736,1.4,5.8,7.2,1.6,0.8,2.7,1.4,2.6,13.3 8 | 2,Mitchell Robinson,C,20,NYK,66,19,20.6,3.1,4.4,0.694,0,0,,3.1,4.4,0.694,0.694,1.2,2,0.6,2.7,3.7,6.4,0.6,0.8,2.4,0.5,3.3,7.3 9 | 3,Rudy Gobert,C,26,UTA,81,80,31.8,5.9,8.8,0.669,0,0,,5.9,8.8,0.669,0.669,4.1,6.4,0.636,3.8,9,12.9,2,0.8,2.3,1.6,2.9,15.9 10 | 4,Brook Lopez,C,30,MIL,81,81,28.7,4.4,9.7,0.452,2.3,6.3,0.365,2.1,3.4,0.613,0.571,1.4,1.6,0.842,0.4,4.5,4.9,1.2,0.6,2.2,1,2.3,12.5 11 | 5,JaVale McGee,C,31,LAL,75,62,22.3,5.3,8.5,0.624,0,0.2,0.083,5.3,8.4,0.634,0.625,1.3,2,0.632,2.6,4.9,7.5,0.7,0.6,2,1.4,2.8,12 12 | -------------------------------------------------------------------------------- /final-csv-data/counting-stats.csv: -------------------------------------------------------------------------------- 1 | Rk,Player,Pos,Age,Tm,G,GS,MP,FG,FGA,FG%,3P,3PA,3P%,2P,2PA,2P%,eFG%,FT,FTA,FT%,ORB,DRB,TRB,AST,STL,BLK,TOV,PF,PTS 2 | 1,James Harden,PG,29,HOU,78,78,36.8,10.8,24.5,0.442,4.8,13.2,0.368,6,11.3,0.528,0.541,9.7,11,0.879,0.8,5.8,6.6,7.5,2,0.7,5,3.1,36.1 3 | 2,Paul George,SF,28,OKC,77,77,36.9,9.2,21,0.438,3.8,9.8,0.386,5.4,11.1,0.484,0.529,5.9,7,0.839,1.4,6.8,8.2,4.1,2.2,0.4,2.7,2.8,28 4 | 3,Giannis Antetokounmpo,PF,24,MIL,72,72,32.8,10,17.3,0.578,0.7,2.8,0.256,9.3,14.5,0.641,0.599,6.9,9.5,0.729,2.2,10.3,12.5,5.9,1.3,1.5,3.7,3.2,27.7 5 | 4,Joel Embiid,C,24,PHI,64,64,33.7,9.1,18.7,0.484,1.2,4.1,0.3,7.8,14.6,0.535,0.517,8.2,10.1,0.804,2.5,11.1,13.6,3.7,0.7,1.9,3.5,3.3,27.5 6 | 5,Stephen Curry,PG,30,GSW,69,69,33.8,9.2,19.4,0.472,5.1,11.7,0.437,4,7.7,0.525,0.604,3.8,4.2,0.916,0.7,4.7,5.3,5.2,1.3,0.4,2.8,2.4,27.3 7 | 6,Kawhi Leonard,SF,27,TOR,60,60,34,9.3,18.8,0.496,1.9,5,0.371,7.5,13.8,0.542,0.546,6.1,7.1,0.854,1.3,6,7.3,3.3,1.8,0.4,2,1.5,26.6 8 | 7,Devin Booker,SG,22,PHO,64,64,35,9.2,19.6,0.467,2.1,6.5,0.326,7,13.1,0.536,0.521,6.1,7.1,0.866,0.6,3.5,4.1,6.8,0.9,0.2,4.1,3.1,26.6 9 | 8,Kevin Durant,PF,30,GSW,78,78,34.6,9.2,17.7,0.521,1.8,5,0.353,7.5,12.8,0.587,0.571,5.7,6.5,0.885,0.4,5.9,6.4,5.9,0.7,1.1,2.9,2,26 10 | 9,Damian Lillard,PG,28,POR,80,80,35.5,8.5,19.2,0.444,3,8,0.369,5.6,11.1,0.499,0.522,5.9,6.4,0.912,0.9,3.8,4.6,6.9,1.1,0.4,2.7,1.9,25.8 11 | 10,Bradley Beal,SG,25,WAS,82,82,36.9,9.3,19.6,0.475,2.5,7.3,0.351,6.8,12.4,0.548,0.54,4.4,5.5,0.808,1.1,3.9,5,5.5,1.5,0.7,2.7,2.8,25.6 12 | 11,Kemba Walker,PG,28,CHO,82,82,34.9,8.9,20.5,0.434,3.2,8.9,0.356,5.7,11.6,0.494,0.511,4.6,5.5,0.844,0.6,3.8,4.4,5.9,1.2,0.4,2.6,1.6,25.6 13 | 12,Blake Griffin,PF,29,DET,75,75,35,8.3,17.9,0.462,2.5,7,0.362,5.7,10.9,0.525,0.532,5.5,7.3,0.753,1.3,6.2,7.5,5.4,0.7,0.4,3.4,2.7,24.5 14 | 13,Karl-Anthony Towns,C,23,MIN,77,77,33.1,8.8,17.1,0.518,1.8,4.6,0.4,7,12.5,0.562,0.572,4.9,5.8,0.836,3.4,9,12.4,3.4,0.9,1.6,3.1,3.8,24.4 15 | 14,Kyrie Irving,PG,26,BOS,67,67,33,9,18.5,0.487,2.6,6.5,0.401,6.4,12,0.533,0.557,3.2,3.7,0.873,1.1,3.9,5,6.9,1.5,0.5,2.6,2.5,23.8 16 | 15,Donovan Mitchell,SG,22,UTA,77,77,33.7,8.6,19.9,0.432,2.4,6.7,0.362,6.1,13.1,0.468,0.493,4.1,5.1,0.806,0.8,3.3,4.1,4.2,1.4,0.4,2.8,2.7,23.8 17 | 16,Zach LaVine,SG,23,CHI,63,62,34.5,8.4,18,0.467,1.9,5.1,0.374,6.5,12.9,0.504,0.52,5,6,0.832,0.6,4,4.7,4.5,1,0.4,3.4,2.2,23.7 18 | 17,Russell Westbrook,PG,30,OKC,73,73,36,8.6,20.2,0.428,1.6,5.6,0.29,7,14.5,0.481,0.468,4.1,6.2,0.656,1.5,9.6,11.1,10.7,1.9,0.5,4.5,3.4,22.9 19 | 18,Klay Thompson,SG,28,GSW,78,78,34,8.4,18,0.467,3.1,7.7,0.402,5.3,10.3,0.516,0.553,1.7,2,0.816,0.5,3.4,3.8,2.4,1.1,0.6,1.5,2,21.5 20 | 19,Julius Randle,PF,24,NOP,73,49,30.6,7.8,14.9,0.524,0.9,2.7,0.344,6.9,12.2,0.564,0.555,4.9,6.7,0.731,2.2,6.5,8.7,3.1,0.7,0.6,2.8,3.4,21.4 21 | 20,LaMarcus Aldridge,C,33,SAS,81,81,33.2,8.4,16.3,0.519,0.1,0.5,0.238,8.3,15.8,0.528,0.522,4.3,5.1,0.847,3.1,6.1,9.2,2.4,0.5,1.3,1.8,2.2,21.3 22 | 21,Jrue Holiday,SG,28,NOP,67,67,35.9,8.2,17.3,0.472,1.8,5.4,0.325,6.4,11.9,0.539,0.523,3.1,4,0.768,1.1,3.9,5,7.7,1.6,0.8,3.1,2.2,21.2 23 | 22,DeMar DeRozan,SG,29,SAS,77,77,34.9,8.2,17.1,0.481,0.1,0.6,0.156,8.1,16.5,0.492,0.483,4.8,5.7,0.83,0.7,5.3,6,6.2,1.1,0.5,2.6,2.3,21.2 24 | 23,Luka Doncic,SG,19,DAL,72,72,32.2,7,16.5,0.427,2.3,7.1,0.327,4.7,9.3,0.503,0.497,4.8,6.7,0.713,1.2,6.6,7.8,6,1.1,0.3,3.4,1.9,21.2 25 | 24,Mike Conley,PG,31,MEM,70,70,33.5,7,16,0.438,2.2,6.1,0.364,4.8,9.9,0.483,0.507,4.9,5.8,0.845,0.6,2.8,3.4,6.4,1.3,0.3,1.9,1.8,21.1 26 | 25,D'Angelo Russell,PG,22,BRK,81,81,30.2,8.1,18.7,0.434,2.9,7.8,0.369,5.2,10.9,0.482,0.512,2,2.5,0.78,0.7,3.2,3.9,7,1.2,0.2,3.1,1.7,21.1 27 | 26,CJ McCollum,SG,27,POR,70,70,33.9,8.2,17.8,0.459,2.4,6.4,0.375,5.8,11.4,0.506,0.527,2.3,2.7,0.828,0.9,3.1,4,3,0.8,0.4,1.5,2.5,21 28 | 27,Nikola Vucevic,C,28,ORL,80,80,31.4,8.8,16.9,0.518,1.1,2.9,0.364,7.7,14,0.549,0.549,2.2,2.8,0.789,2.8,9.2,12,3.8,1,1.1,2,2,20.8 29 | 28,Buddy Hield,SG,26,SAC,82,82,31.9,7.6,16.6,0.458,3.4,7.9,0.427,4.2,8.6,0.487,0.56,2.1,2.4,0.886,1.3,3.7,5,2.5,0.7,0.4,1.8,2.5,20.7 30 | 29,Nikola Jokic,C,23,DEN,80,80,31.3,7.7,15.1,0.511,1,3.4,0.307,6.7,11.7,0.569,0.545,3.6,4.4,0.821,2.9,8,10.8,7.3,1.4,0.7,3.1,2.9,20.1 31 | 30,Tobias Harris,PF,26,TOT,82,82,34.7,7.5,15.3,0.487,1.9,4.8,0.397,5.5,10.5,0.528,0.549,3.2,3.7,0.866,0.8,7,7.9,2.8,0.6,0.5,1.8,2.2,20 32 | 31,Lou Williams,SG,32,LAC,75,1,26.6,6.5,15.2,0.425,1.4,3.9,0.361,5.1,11.3,0.447,0.471,5.7,6.5,0.876,0.5,2.4,3,5.4,0.8,0.1,2.4,1.1,20 33 | 32,Danilo Gallinari,SF,30,LAC,68,68,30.3,6,13,0.463,2.4,5.5,0.433,3.6,7.5,0.484,0.554,5.4,6,0.904,0.8,5.3,6.1,2.6,0.7,0.3,1.5,1.9,19.8 34 | 33,John Collins,PF,21,ATL,61,59,30,7.6,13.6,0.56,0.9,2.6,0.348,6.7,11,0.609,0.593,3.3,4.4,0.763,3.6,6.2,9.8,2,0.4,0.6,2,3.3,19.5 35 | 34,Trae Young,PG,20,ATL,81,81,30.9,6.5,15.5,0.418,1.9,6,0.324,4.6,9.6,0.477,0.48,4.2,5.1,0.829,0.8,2.9,3.7,8.1,0.9,0.2,3.8,1.7,19.1 36 | 35,Jimmy Butler,SF-SG,29,TOT,65,65,33.6,6.4,13.9,0.462,1,3,0.347,5.4,10.9,0.494,0.499,4.8,5.6,0.855,1.9,3.4,5.3,4,1.9,0.6,1.5,1.7,18.7 37 | 36,Kyle Kuzma,PF,23,LAL,70,68,33.1,7.1,15.5,0.456,1.8,6,0.303,5.3,9.5,0.553,0.515,2.7,3.6,0.752,0.9,4.6,5.5,2.5,0.6,0.4,1.9,2.4,18.7 38 | 37,Khris Middleton,SF,27,MIL,77,77,31.1,6.6,14.9,0.441,2.3,6.2,0.378,4.2,8.8,0.485,0.519,2.8,3.4,0.837,0.6,5.3,6,4.3,1,0.1,2.3,2.2,18.3 39 | 38,Jamal Murray,PG,21,DEN,75,74,32.6,6.8,15.6,0.437,2,5.5,0.367,4.8,10.1,0.476,0.502,2.5,3,0.848,0.9,3.4,4.2,4.8,0.9,0.4,2.1,2,18.2 40 | 39,Andrew Wiggins,SF,23,MIN,73,73,34.8,6.8,16.6,0.412,1.6,4.8,0.339,5.2,11.8,0.441,0.461,2.8,4.1,0.699,1.1,3.7,4.8,2.5,1,0.7,1.9,2.1,18.1 41 | 40,J.J. Redick,SG,34,PHI,76,63,31.3,5.9,13.5,0.44,3.2,8,0.397,2.8,5.6,0.502,0.557,3,3.4,0.894,0.3,2.2,2.4,2.7,0.4,0.2,1.3,1.7,18.1 42 | 41,Tim Hardaway,SG,26,TOT,65,63,31.6,6,15.3,0.393,2.5,7.3,0.34,3.5,7.9,0.442,0.474,3.6,4.2,0.841,0.5,2.9,3.4,2.4,0.8,0.1,1.6,2.2,18.1 43 | 42,Bojan Bogdanovic,SF,29,IND,81,81,31.8,6.4,13,0.497,2,4.8,0.425,4.4,8.2,0.538,0.575,3,3.8,0.807,0.4,3.7,4.1,2,0.9,0,1.7,1.7,18 44 | 43,Andre Drummond,C,25,DET,79,79,33.5,7.1,13.3,0.533,0.1,0.5,0.132,7,12.8,0.548,0.536,3.1,5.2,0.59,5.4,10.2,15.6,1.4,1.7,1.7,2.2,3.4,17.3 45 | 44,De'Aaron Fox,PG,21,SAC,81,81,31.4,6.2,13.6,0.458,1.1,2.9,0.371,5.2,10.7,0.482,0.497,3.7,5.1,0.727,0.5,3.2,3.8,7.3,1.6,0.6,2.8,2.5,17.3 46 | 45,Ben Simmons,PG,22,PHI,79,79,34.2,6.8,12.2,0.563,0,0.1,0,6.8,12.1,0.566,0.563,3.3,5.4,0.6,2.2,6.6,8.8,7.7,1.4,0.8,3.5,2.6,16.9 47 | 46,Pascal Siakam,PF,24,TOR,80,79,31.9,6.5,11.8,0.549,1,2.7,0.369,5.5,9.1,0.602,0.591,3,3.8,0.785,1.6,5.3,6.9,3.1,0.9,0.7,1.9,3,16.9 48 | 47,Spencer Dinwiddie,PG,25,BRK,68,4,28.1,5.4,12.2,0.442,1.8,5.4,0.335,3.6,6.7,0.528,0.517,4.2,5.2,0.806,0.4,2.1,2.4,4.6,0.6,0.3,2.2,2.8,16.8 49 | 48,Jordan Clarkson,SG,26,CLE,81,0,27.3,6.5,14.6,0.448,1.8,5.5,0.324,4.8,9.1,0.524,0.509,2,2.4,0.844,1,2.3,3.3,2.4,0.7,0.2,1.7,1.4,16.8 50 | 49,Collin Sexton,PG,20,CLE,82,72,31.8,6.3,14.7,0.43,1.5,3.6,0.402,4.9,11.1,0.44,0.48,2.6,3.1,0.839,0.7,2.2,2.9,3,0.5,0.1,2.3,2.3,16.7 51 | 50,Clint Capela,C,24,HOU,67,67,33.6,7.1,10.9,0.648,0,0,0,7.1,10.9,0.648,0.648,2.5,3.9,0.636,4.4,8.2,12.7,1.4,0.7,1.5,1.4,2.5,16.6 52 | -------------------------------------------------------------------------------- /final-csv-data/full-nba-data.csv: -------------------------------------------------------------------------------- 1 | Player,Pos,Age,Tm,G,MP,MPG,FG,FGA,FG%,3P,3PA,3P%,2P,2PA,2P%,eFG%,FT,FTA,FT%,ORB,DRB,TRB,AST,STL,BLK,TOV,PF,PTS,PER,TS%,3PAr,FTr,ORB%,DRB%,TRB%,AST%,STL%,BLK%,TOV%,USG%,OWS,DWS,WS,WS/48,OBPM,DBPM,BPM,VORP 2 | James Harden,1,29,HOU,78,2867,36.8,10.8,24.5,0.442,4.8,13.2,0.368,6,11.3,0.528,0.541,9.7,11,0.879,0.8,5.8,6.6,7.5,2,0.7,5,3.1,36.1,30.6,0.616,0.539,0.449,2.5,17.8,10,39.5,2.7,1.7,14.5,40.5,11.4,3.8,15.2,0.254,10.5,1.1,11.7,9.9 3 | Paul George,2,28,OKC,77,2841,36.9,9.2,21,0.438,3.8,9.8,0.386,5.4,11.1,0.484,0.529,5.9,7,0.839,1.4,6.8,8.2,4.1,2.2,0.4,2.7,2.8,28,23.3,0.583,0.469,0.335,3.7,19.6,11.4,17.7,2.8,1,10,29.5,7,4.9,11.9,0.201,4.7,0.7,5.5,5.3 4 | Giannis Antetokounmpo,3,24,MIL,72,2358,32.8,10,17.3,0.578,0.7,2.8,0.256,9.3,14.5,0.641,0.599,6.9,9.5,0.729,2.2,10.3,12.5,5.9,1.3,1.5,3.7,3.2,27.7,30.9,0.644,0.163,0.55,7.3,30,19.3,30.3,1.8,3.9,14.8,32.3,8.9,5.5,14.4,0.292,5.7,5,10.8,7.6 5 | Joel Embiid,3,24,PHI,64,2154,33.7,9.1,18.7,0.484,1.2,4.1,0.3,7.8,14.6,0.535,0.517,8.2,10.1,0.804,2.5,11.1,13.6,3.7,0.7,1.9,3.5,3.3,27.5,26.1,0.593,0.219,0.541,8.1,34,21.4,18.4,1,4.4,13.2,33.3,4.9,3.8,8.7,0.194,2,2.1,4.1,3.3 6 | LeBron James,2,34,LAL,55,1937,35.2,10.1,19.9,0.51,2,5.9,0.339,8.1,14,0.582,0.56,5.1,7.6,0.665,1,7.4,8.5,8.3,1.3,0.6,3.6,1.7,27.4,25.6,0.588,0.299,0.382,3.1,21.3,12.4,39.4,1.7,1.4,13.3,31.6,4.7,2.6,7.2,0.179,6.2,1.9,8.1,4.9 7 | Stephen Curry,1,30,GSW,69,2331,33.8,9.2,19.4,0.472,5.1,11.7,0.437,4,7.7,0.525,0.604,3.8,4.2,0.916,0.7,4.7,5.3,5.2,1.3,0.4,2.8,2.4,27.3,24.4,0.641,0.604,0.214,2.2,14.2,8.4,24.2,1.9,0.9,11.6,30.4,7.2,2.5,9.7,0.199,7.7,-1.4,6.3,4.9 8 | Devin Booker,1,22,PHO,64,2242,35,9.2,19.6,0.467,2.1,6.5,0.326,7,13.1,0.536,0.521,6.1,7.1,0.866,0.6,3.5,4.1,6.8,0.9,0.2,4.1,3.1,26.6,20.2,0.584,0.33,0.362,1.9,11.3,6.5,34.1,1.2,0.5,15.4,32.9,3.3,0.3,3.5,0.076,3.8,-3,0.8,1.6 9 | Kawhi Leonard,2,27,TOR,60,2040,34,9.3,18.8,0.496,1.9,5,0.371,7.5,13.8,0.542,0.546,6.1,7.1,0.854,1.3,6,7.3,3.3,1.8,0.4,2,1.5,26.6,25.8,0.606,0.267,0.377,4.2,18.6,11.6,16.4,2.5,1,8.4,30.3,6.1,3.4,9.5,0.224,4.3,0.7,5,3.6 10 | Kevin Durant,3,30,GSW,78,2702,34.6,9.2,17.7,0.521,1.8,5,0.353,7.5,12.8,0.587,0.571,5.7,6.5,0.885,0.4,5.9,6.4,5.9,0.7,1.1,2.9,2,26,24.2,0.631,0.281,0.366,1.4,17.5,9.8,26.2,1,2.6,12.3,29,8.6,2.9,11.5,0.204,4.2,0.1,4.3,4.3 11 | Anthony Davis,3,25,NOP,56,1850,33,9.5,18.3,0.517,0.9,2.6,0.331,8.6,15.7,0.547,0.54,6.1,7.7,0.794,3.1,8.9,12,3.9,1.6,2.4,2,2.4,25.9,30.3,0.597,0.141,0.422,9.9,27.5,18.8,19,2.2,6,8.4,29.5,6.4,3.1,9.5,0.247,4.7,3.9,8.5,4.9 12 | Damian Lillard,1,28,POR,80,2838,35.5,8.5,19.2,0.444,3,8,0.369,5.6,11.1,0.499,0.522,5.9,6.4,0.912,0.9,3.8,4.6,6.9,1.1,0.4,2.7,1.9,25.8,23.7,0.588,0.419,0.335,2.6,11.1,7,30.6,1.5,1,10.8,29.3,9.7,2.4,12.1,0.205,6.6,-1.1,5.5,5.4 13 | Bradley Beal,1,25,WAS,82,3028,36.9,9.3,19.6,0.475,2.5,7.3,0.351,6.8,12.4,0.548,0.54,4.4,5.5,0.808,1.1,3.9,5,5.5,1.5,0.7,2.7,2.8,25.6,20.8,0.581,0.37,0.278,3.1,11.7,7.4,24.1,1.9,1.6,11,28.4,5.9,1.7,7.6,0.12,3.9,-1.1,2.8,3.7 14 | Kemba Walker,1,28,CHO,82,2863,34.9,8.9,20.5,0.434,3.2,8.9,0.356,5.7,11.6,0.494,0.511,4.6,5.5,0.844,0.6,3.8,4.4,5.9,1.2,0.4,2.6,1.6,25.6,21.7,0.558,0.434,0.267,1.9,11.9,6.8,29.4,1.7,1,10.1,31.5,5.5,1.9,7.4,0.123,5.1,-1.7,3.3,3.9 15 | Blake Griffin,3,29,DET,75,2622,35,8.3,17.9,0.462,2.5,7,0.362,5.7,10.9,0.525,0.532,5.5,7.3,0.753,1.3,6.2,7.5,5.4,0.7,0.4,3.4,2.7,24.5,21,0.581,0.389,0.41,4,20.1,11.8,27.1,1,0.9,13.8,30.2,5.1,2.9,8,0.147,4.2,0.4,4.6,4.4 16 | Karl-Anthony Towns,3,23,MIN,77,2545,33.1,8.8,17.1,0.518,1.8,4.6,0.4,7,12.5,0.562,0.572,4.9,5.8,0.836,3.4,9,12.4,3.4,0.9,1.6,3.1,3.8,24.4,26.3,0.622,0.27,0.342,10.9,29.3,20,17.2,1.3,4.2,13.7,28.9,7.2,3.2,10.4,0.197,4.8,2,6.8,5.7 17 | Kyrie Irving,1,26,BOS,67,2214,33,9,18.5,0.487,2.6,6.5,0.401,6.4,12,0.533,0.557,3.2,3.7,0.873,1.1,3.9,5,6.9,1.5,0.5,2.6,2.5,23.8,24.3,0.592,0.35,0.197,3.4,12.7,8.1,35,2.2,1.4,11.3,29.6,6.2,2.9,9.1,0.197,6,0.4,6.4,4.7 18 | Donovan Mitchell,1,22,UTA,77,2598,33.7,8.6,19.9,0.432,2.4,6.7,0.362,6.1,13.1,0.468,0.493,4.1,5.1,0.806,0.8,3.3,4.1,4.2,1.4,0.4,2.8,2.7,23.8,17.2,0.537,0.339,0.259,2.5,10.5,6.6,21.2,2,0.9,11.3,31.6,1.3,3.7,5,0.092,0.8,-0.2,0.6,1.7 19 | Zach LaVine,1,23,CHI,63,2171,34.5,8.4,18,0.467,1.9,5.1,0.374,6.5,12.9,0.504,0.52,5,6,0.832,0.6,4,4.7,4.5,1,0.4,3.4,2.2,23.7,18.7,0.574,0.283,0.33,2,12.9,7.4,22.6,1.3,1,14.2,30.5,1.7,1.1,2.8,0.062,1.8,-1.7,0,1.1 20 | Russell Westbrook,1,30,OKC,73,2630,36,8.6,20.2,0.428,1.6,5.6,0.29,7,14.5,0.481,0.468,4.1,6.2,0.656,1.5,9.6,11.1,10.7,1.9,0.5,4.5,3.4,22.9,21.1,0.501,0.279,0.306,4.1,28.3,15.8,46.5,2.5,1.1,16.3,30.9,1.8,5,6.8,0.124,2.5,3.9,6.5,5.6 21 | Klay Thompson,1,28,GSW,78,2652,34,8.4,18,0.467,3.1,7.7,0.402,5.3,10.3,0.516,0.553,1.7,2,0.816,0.5,3.4,3.8,2.4,1.1,0.6,1.5,2,21.5,16.6,0.571,0.427,0.113,1.6,10.1,6,10.5,1.5,1.5,7.2,25.6,2.9,2.3,5.3,0.095,1.2,-2,-0.8,0.8 22 | Julius Randle,3,24,NOP,73,2232,30.6,7.8,14.9,0.524,0.9,2.7,0.344,6.9,12.2,0.564,0.555,4.9,6.7,0.731,2.2,6.5,8.7,3.1,0.7,0.6,2.8,3.4,21.4,21,0.6,0.179,0.447,7.6,21.6,14.7,15.8,1.1,1.6,13.8,27.8,4.2,1.9,6.1,0.131,1.8,-0.4,1.4,1.9 23 | LaMarcus Aldridge,3,33,SAS,81,2687,33.2,8.4,16.3,0.519,0.1,0.5,0.238,8.3,15.8,0.528,0.522,4.3,5.1,0.847,3.1,6.1,9.2,2.4,0.5,1.3,1.8,2.2,21.3,22.9,0.576,0.032,0.312,10.3,19.8,15.1,11.6,0.8,3.4,8.8,26.9,6.4,2.9,9.3,0.167,1.2,0.5,1.6,2.5 24 | DeMar DeRozan,1,29,SAS,77,2688,34.9,8.2,17.1,0.481,0.1,0.6,0.156,8.1,16.5,0.492,0.483,4.8,5.7,0.83,0.7,5.3,6,6.2,1.1,0.5,2.6,2.3,21.2,19.6,0.542,0.034,0.336,2.2,16.4,9.4,27.6,1.6,1.1,11.7,27.9,3.6,2.6,6.3,0.112,0.4,0.5,0.9,2 25 | Luka Doncic,1,19,DAL,72,2318,32.2,7,16.5,0.427,2.3,7.1,0.327,4.7,9.3,0.503,0.497,4.8,6.7,0.713,1.2,6.6,7.8,6,1.1,0.3,3.4,1.9,21.2,19.6,0.545,0.433,0.409,4,21.9,13,31.6,1.6,0.9,15,30.5,2.1,2.8,4.9,0.101,2.9,1.2,4.1,3.6 26 | Jrue Holiday,1,28,NOP,67,2402,35.9,8.2,17.3,0.472,1.8,5.4,0.325,6.4,11.9,0.539,0.523,3.1,4,0.768,1.1,3.9,5,7.7,1.6,0.8,3.1,2.2,21.2,19.4,0.555,0.313,0.234,3.3,11,7.2,31.8,2.1,1.8,14.1,25.4,3.5,1.9,5.4,0.108,2.9,-0.1,2.8,2.9 27 | Mike Conley,1,31,MEM,70,2342,33.5,7,16,0.438,2.2,6.1,0.364,4.8,9.9,0.483,0.507,4.9,5.8,0.845,0.6,2.8,3.4,6.4,1.3,0.3,1.9,1.8,21.1,21.4,0.569,0.38,0.363,1.9,9.7,5.7,33.4,2,0.9,9.1,27.3,5.7,2.3,8,0.164,4.8,-1.3,3.4,3.2 28 | D'Angelo Russell,1,22,BRK,81,2448,30.2,8.1,18.7,0.434,2.9,7.8,0.369,5.2,10.9,0.482,0.512,2,2.5,0.78,0.7,3.2,3.9,7,1.2,0.2,3.1,1.7,21.1,19.4,0.533,0.419,0.135,2.3,11.2,6.8,41.3,1.9,0.6,13.6,31.9,2.4,2.6,5,0.097,3.9,-0.5,3.4,3.3 29 | CJ McCollum,1,27,POR,70,2375,33.9,8.2,17.8,0.459,2.4,6.4,0.375,5.8,11.4,0.506,0.527,2.3,2.7,0.828,0.9,3.1,4,3,0.8,0.4,1.5,2.5,21,17,0.553,0.358,0.154,2.9,9.7,6.3,13.8,1.1,0.9,7.4,25.5,4,1.7,5.6,0.114,2.2,-1.9,0.3,1.3 30 | Nikola Vucevic,3,28,ORL,80,2510,31.4,8.8,16.9,0.518,1.1,2.9,0.364,7.7,14,0.549,0.549,2.2,2.8,0.789,2.8,9.2,12,3.8,1,1.1,2,2,20.8,25.5,0.573,0.171,0.168,9.4,31.9,20.5,21.9,1.6,3,9.9,28,5.4,4.7,10.1,0.193,3,3.4,6.4,5.3 31 | Buddy Hield,1,26,SAC,82,2615,31.9,7.6,16.6,0.458,3.4,7.9,0.427,4.2,8.6,0.487,0.56,2.1,2.4,0.886,1.3,3.7,5,2.5,0.7,0.4,1.8,2.5,20.7,17.5,0.587,0.479,0.142,4.1,12.4,8.1,11.9,1,1.1,9.2,25.1,4.3,1.6,5.9,0.108,3.1,-2,1.1,2.1 32 | Nikola Jokic,3,23,DEN,80,2504,31.3,7.7,15.1,0.511,1,3.4,0.307,6.7,11.7,0.569,0.545,3.6,4.4,0.821,2.9,8,10.8,7.3,1.4,0.7,3.1,2.9,20.1,26.3,0.589,0.224,0.292,9.8,27.6,18.7,37,2.1,1.9,15.4,27.4,7.5,4.3,11.8,0.226,5.7,3.8,9.5,7.3 33 | Tobias Harris,3,26,TOT,82,2847,34.7,7.5,15.3,0.487,1.9,4.8,0.397,5.5,10.5,0.528,0.549,3.2,3.7,0.866,0.8,7,7.9,2.8,0.6,0.5,1.8,2.2,20,17.2,0.592,0.313,0.245,2.6,20.8,12,12.5,0.8,1,9.8,22.8,4.5,2.6,7.1,0.12,1.1,-0.6,0.5,1.8 34 | Lou Williams,1,32,LAC,75,1993,26.6,6.5,15.2,0.425,1.4,3.9,0.361,5.1,11.3,0.447,0.471,5.7,6.5,0.876,0.5,2.4,3,5.4,0.8,0.1,2.4,1.1,20,21.2,0.554,0.256,0.426,2.2,9.4,5.9,33,1.3,0.4,11.8,32.4,3.9,1.2,5.1,0.123,3.1,-2.6,0.4,1.2 35 | Danilo Gallinari,2,30,LAC,68,2059,30.3,6,13,0.463,2.4,5.5,0.433,3.6,7.5,0.484,0.554,5.4,6,0.904,0.8,5.3,6.1,2.6,0.7,0.3,1.5,1.9,19.8,21,0.633,0.421,0.459,2.9,18.1,10.7,13.2,1.1,0.9,8.5,23.8,6.4,1.8,8.2,0.191,4.2,-1.2,2.9,2.6 36 | John Collins,3,21,ATL,61,1829,30,7.6,13.6,0.56,0.9,2.6,0.348,6.7,11,0.609,0.593,3.3,4.4,0.763,3.6,6.2,9.8,2,0.4,0.6,2,3.3,19.5,21.8,0.627,0.19,0.32,12.3,22.1,17.1,11,0.6,1.8,11.2,23.7,5,1,6,0.158,2.6,-1.2,1.4,1.6 37 | Trae Young,1,20,ATL,81,2503,30.9,6.5,15.5,0.418,1.9,6,0.324,4.6,9.6,0.477,0.48,4.2,5.1,0.829,0.8,2.9,3.7,8.1,0.9,0.2,3.8,1.7,19.1,17,0.539,0.384,0.33,2.6,10.2,6.3,40.5,1.3,0.5,17.6,28.4,2.5,0.7,3.3,0.062,1.8,-2.8,-1.1,0.6 38 | Jimmy Butler,2,29,TOT,65,2185,33.6,6.4,13.9,0.462,1,3,0.347,5.4,10.9,0.494,0.499,4.8,5.6,0.855,1.9,3.4,5.3,4,1.9,0.6,1.5,1.7,18.7,20.2,0.571,0.213,0.404,6,10.5,8.3,18,2.7,1.4,8.2,22.3,5.4,2.5,7.9,0.173,2.6,0.6,3.2,2.9 39 | Kyle Kuzma,3,23,LAL,70,2314,33.1,7.1,15.5,0.456,1.8,6,0.303,5.3,9.5,0.553,0.515,2.7,3.6,0.752,0.9,4.6,5.5,2.5,0.6,0.4,1.9,2.4,18.7,14,0.546,0.388,0.23,2.7,14.1,8.5,11.5,0.8,0.9,10,23.8,1.2,1.9,3.1,0.065,-0.3,-1.3,-1.7,0.2 40 | Lauri Markkanen,3,21,CHI,52,1682,32.3,6.6,15.3,0.43,2.3,6.4,0.361,4.3,8.9,0.479,0.506,3.3,3.8,0.872,1.4,7.6,9,1.4,0.7,0.6,1.6,2.3,18.7,17.1,0.553,0.418,0.245,4.7,25.9,15.2,7.2,1.1,1.7,8.8,25.1,1.3,1.5,2.7,0.078,-0.3,-1.6,-1.9,0 41 | Brandon Ingram,2,21,LAL,52,1760,33.8,7,14,0.497,0.6,1.8,0.33,6.4,12.2,0.521,0.518,3.8,5.6,0.675,0.8,4.3,5.1,3,0.5,0.6,2.5,2.9,18.3,13.4,0.555,0.129,0.396,2.5,13,7.8,12.9,0.7,1.4,13.1,23.2,0.6,1.4,2,0.055,-2.2,-0.6,-2.8,-0.3 42 | Khris Middleton,2,27,MIL,77,2393,31.1,6.6,14.9,0.441,2.3,6.2,0.378,4.2,8.8,0.485,0.519,2.8,3.4,0.837,0.6,5.3,6,4.3,1,0.1,2.3,2.2,18.3,16.5,0.558,0.413,0.225,2.3,16.5,9.8,20.1,1.6,0.2,12.1,25.1,2.5,3.6,6.1,0.123,0.7,0.1,0.8,1.7 43 | Jamal Murray,1,21,DEN,75,2447,32.6,6.8,15.6,0.437,2,5.5,0.367,4.8,10.1,0.476,0.502,2.5,3,0.848,0.9,3.4,4.2,4.8,0.9,0.4,2.1,2,18.2,16,0.538,0.353,0.19,2.9,11.2,7,22.4,1.3,1,11.1,24.9,2.8,2.3,5.1,0.1,1.1,-1,0.1,1.3 44 | Tim Hardaway,1,26,TOT,65,2057,31.6,6,15.3,0.393,2.5,7.3,0.34,3.5,7.9,0.442,0.474,3.6,4.2,0.841,0.5,2.9,3.4,2.4,0.8,0.1,1.6,2.2,18.1,13.6,0.527,0.48,0.278,1.7,9.8,5.7,12.8,1.3,0.3,8.6,25.4,1,0.9,1.8,0.043,0.5,-2.9,-2.4,-0.2 45 | J.J. Redick,1,34,PHI,76,2379,31.3,5.9,13.5,0.44,3.2,8,0.397,2.8,5.6,0.502,0.557,3,3.4,0.894,0.3,2.2,2.4,2.7,0.4,0.2,1.3,1.7,18.1,15.1,0.602,0.589,0.248,0.9,7.2,4.1,12.9,0.6,0.6,8.1,21.9,4.6,1.2,5.9,0.118,2.7,-3.3,-0.7,0.8 46 | Andrew Wiggins,2,23,MIN,73,2543,34.8,6.8,16.6,0.412,1.6,4.8,0.339,5.2,11.8,0.441,0.461,2.8,4.1,0.699,1.1,3.7,4.8,2.5,1,0.7,1.9,2.1,18.1,12.4,0.493,0.288,0.245,3.5,11.4,7.4,10.9,1.3,1.6,9.3,24.4,-0.6,1.3,0.6,0.012,-1.7,-1.3,-2.9,-0.6 47 | Bojan Bogdanovic,2,29,IND,81,2573,31.8,6.4,13,0.497,2,4.8,0.425,4.4,8.2,0.538,0.575,3,3.8,0.807,0.4,3.7,4.1,2,0.9,0,1.7,1.7,18,16.1,0.613,0.367,0.29,1.5,12.7,7.2,9.5,1.3,0,10.2,22.4,3.9,2.8,6.8,0.126,1.4,-1.4,0,1.3 48 | Derrick Rose,1,30,MIN,51,1392,27.3,7.1,14.8,0.482,1.1,2.9,0.37,6.1,11.9,0.509,0.518,2.7,3.1,0.856,0.6,2.1,2.7,4.3,0.6,0.2,1.6,1.1,18,19.5,0.557,0.194,0.212,2.5,8.3,5.4,26.4,1.1,0.7,9.1,27.3,2.6,0.3,3,0.102,2.3,-2.9,-0.6,0.5 49 | Andre Drummond,3,25,DET,79,2647,33.5,7.1,13.3,0.533,0.1,0.5,0.132,7,12.8,0.548,0.536,3.1,5.2,0.59,5.4,10.2,15.6,1.4,1.7,1.7,2.2,3.4,17.3,23.4,0.555,0.036,0.392,16.8,34.7,25.4,7.2,2.5,4.4,12.4,22.9,4.1,5.9,10,0.181,-0.7,3.6,2.9,3.3 50 | De'Aaron Fox,1,21,SAC,81,2546,31.4,6.2,13.6,0.458,1.1,2.9,0.371,5.2,10.7,0.482,0.497,3.7,5.1,0.727,0.5,3.2,3.8,7.3,1.6,0.6,2.8,2.5,17.3,18.1,0.544,0.211,0.378,1.7,10.8,6.2,33.2,2.4,1.5,15,24.5,3.2,2.5,5.6,0.106,1.1,0,1.1,2 51 | Pascal Siakam,3,24,TOR,80,2548,31.9,6.5,11.8,0.549,1,2.7,0.369,5.5,9.1,0.602,0.591,3,3.8,0.785,1.6,5.3,6.9,3.1,0.9,0.7,1.9,3,16.9,18.7,0.628,0.226,0.32,5.4,17.5,11.6,14.6,1.4,1.7,12.5,20.8,5.7,3.6,9.3,0.175,2,1.4,3.4,3.5 52 | Ben Simmons,1,22,PHI,79,2700,34.2,6.8,12.2,0.563,0,0.1,0,6.8,12.1,0.566,0.563,3.3,5.4,0.6,2.2,6.6,8.8,7.7,1.4,0.8,3.5,2.6,16.9,20,0.582,0.006,0.446,6.9,20,13.7,34.2,2,1.8,19.3,22.1,4.6,3.6,8.2,0.146,1.4,2.6,4.1,4.1 53 | Jordan Clarkson,1,26,CLE,81,2214,27.3,6.5,14.6,0.448,1.8,5.5,0.324,4.8,9.1,0.524,0.509,2,2.4,0.844,1,2.3,3.3,2.4,0.7,0.2,1.7,1.4,16.8,16.8,0.539,0.377,0.163,3.9,9.9,6.8,15.6,1.3,0.5,9.6,27.6,1.9,-0.1,1.8,0.039,1.5,-3.5,-2,0 54 | Spencer Dinwiddie,1,25,BRK,68,1914,28.1,5.4,12.2,0.442,1.8,5.4,0.335,3.6,6.7,0.528,0.517,4.2,5.2,0.806,0.4,2.1,2.4,4.6,0.6,0.3,2.2,2.8,16.8,16.3,0.58,0.447,0.43,1.4,7.6,4.6,25.6,1,0.7,13.4,24.9,3.5,1.4,4.8,0.121,1.9,-2.1,-0.2,0.8 55 | Collin Sexton,1,20,CLE,82,2605,31.8,6.3,14.7,0.43,1.5,3.6,0.402,4.9,11.1,0.44,0.48,2.6,3.1,0.839,0.7,2.2,2.9,3,0.5,0.1,2.3,2.3,16.7,12,0.52,0.245,0.211,2.3,8,5,15.3,0.8,0.2,12.3,25.2,-0.1,-0.5,-0.6,-0.011,-1.5,-3.7,-5.2,-2.1 56 | Clint Capela,3,24,HOU,67,2249,33.6,7.1,10.9,0.648,0,0,0,7.1,10.9,0.648,0.648,2.5,3.9,0.636,4.4,8.2,12.7,1.4,0.7,1.5,1.4,2.5,16.6,23.8,0.658,0,0.357,14.4,27.6,20.8,7.1,1,3.9,10,18.2,7.8,3,10.8,0.23,1.3,1.6,2.9,2.8 57 | Montrezl Harrell,3,25,LAC,82,2158,26.3,6.7,10.8,0.615,0,0.2,0.176,6.6,10.6,0.623,0.617,3.2,5,0.643,2.2,4.3,6.5,2,0.9,1.3,1.6,3.1,16.6,23.4,0.636,0.019,0.466,9.3,16.7,13.1,12.5,1.6,4,11,23.5,6.1,2.6,8.7,0.193,2.6,1.6,4.2,3.4 58 | Josh Richardson,1,25,MIA,73,2539,34.8,5.8,14.1,0.412,2.2,6.3,0.357,3.5,7.8,0.458,0.492,2.7,3.2,0.861,0.7,2.9,3.6,4.1,1.1,0.5,1.5,2.7,16.6,14,0.536,0.448,0.225,2.3,8.8,5.5,17.9,1.5,1.2,9.1,20.9,3,2.6,5.6,0.106,1,-0.4,0.6,1.7 59 | Harrison Barnes,2,26,TOT,77,2533,32.9,5.6,13.3,0.42,2.3,5.7,0.395,3.3,7.6,0.439,0.504,3,3.6,0.824,0.7,3.9,4.7,1.5,0.6,0.2,1.3,1.6,16.4,12.8,0.55,0.429,0.271,2.4,12.7,7.5,6.7,0.9,0.4,7.9,20.9,2,1.6,3.6,0.068,-0.6,-1.8,-2.3,-0.2 60 | Deandre Ayton,3,20,PHO,71,2183,30.7,7.2,12.3,0.585,0,0.1,0,7.2,12.2,0.588,0.585,2,2.7,0.746,3.1,7.1,10.3,1.8,0.9,0.9,1.8,2.9,16.3,20.5,0.608,0.005,0.217,11.1,26.1,18.5,9.6,1.3,2.6,11.7,21.2,4.1,1.7,5.8,0.128,-0.1,0.2,0.2,1.2 61 | Eric Gordon,1,30,HOU,68,2158,31.7,5.6,13.8,0.409,3.2,8.8,0.36,2.5,5,0.497,0.525,1.8,2.2,0.783,0.3,1.9,2.2,1.9,0.6,0.4,1.3,2.1,16.2,12.2,0.549,0.64,0.162,0.9,6.9,3.8,9.4,0.9,1.1,8.2,22,1.7,1,2.6,0.059,0,-2.9,-2.9,-0.5 62 | Aaron Gordon,3,23,ORL,78,2633,33.8,6,13.4,0.449,1.6,4.4,0.349,4.5,9,0.499,0.507,2.4,3.2,0.731,1.7,5.7,7.4,3.7,0.7,0.7,2.1,2.2,16,15.1,0.538,0.332,0.242,5.2,18.4,11.7,16.6,1.1,1.8,12.3,21.8,1.8,3.3,5.1,0.093,-0.2,1.2,1,2 63 | Eric Bledsoe,1,29,MIL,78,2272,29.1,6,12.4,0.484,1.6,4.8,0.329,4.4,7.6,0.582,0.548,2.3,3,0.75,1.1,3.6,4.6,5.5,1.5,0.4,2.1,2,15.9,19.3,0.577,0.388,0.243,3.9,11.8,8.1,27.4,2.4,1.1,13.3,22.9,4.4,3.7,8.2,0.173,2.5,1,3.5,3.2 64 | Rudy Gobert,3,26,UTA,81,2577,31.8,5.9,8.8,0.669,0,0,0,5.9,8.8,0.669,0.669,4.1,6.4,0.636,3.8,9,12.9,2,0.8,2.3,1.6,2.9,15.9,24.6,0.682,0,0.733,13.2,30.2,21.9,9.6,1.2,5.8,12.1,17.8,8.7,5.7,14.4,0.268,2,5.1,7,5.9 65 | Jayson Tatum,2,20,BOS,79,2455,31.1,5.9,13.1,0.45,1.5,3.9,0.373,4.4,9.2,0.483,0.506,2.5,2.9,0.855,0.9,5.2,6,2.1,1.1,0.7,1.5,2.1,15.7,15.1,0.547,0.3,0.22,3,17.7,10.4,10,1.6,2.1,9.7,22.1,1.6,3.4,5,0.097,-1.4,0.6,-0.8,0.8 66 | Malcolm Brogdon,1,26,MIL,64,1832,28.6,5.9,11.7,0.505,1.6,3.8,0.426,4.3,7.9,0.544,0.575,2.2,2.4,0.928,1,3.5,4.5,3.2,0.7,0.2,1.4,1.6,15.6,17.8,0.614,0.326,0.203,3.8,11.7,8,16.2,1.2,0.6,10,20.7,4.2,2.3,6.5,0.171,1.9,-0.3,1.5,1.6 67 | Jusuf Nurkic,3,24,POR,72,1974,27.4,5.8,11.5,0.508,0,0.4,0.103,5.8,11.1,0.523,0.51,3.9,5.1,0.773,3.4,7,10.4,3.2,1,1.4,2.3,3.5,15.6,23.4,0.57,0.035,0.442,13.4,26.7,20.2,17.9,1.7,4.2,14.6,24.7,4.4,3.3,7.8,0.189,1.6,3.6,5.1,3.5 68 | Chris Paul,1,33,HOU,58,1857,32,5.2,12.4,0.419,2.2,6.1,0.358,3,6.3,0.479,0.508,3,3.5,0.862,0.6,3.9,4.6,8.2,2,0.3,2.6,2.5,15.6,19.7,0.56,0.493,0.282,2.1,13.9,7.9,39.3,3,0.8,15.8,22.5,4.4,2.2,6.6,0.172,2.9,0.2,3,2.4 69 | Dennis Schroder,1,25,OKC,79,2314,29.3,5.8,14,0.414,1.6,4.6,0.341,4.2,9.4,0.45,0.47,2.4,2.9,0.819,0.5,3.1,3.6,4.1,0.8,0.2,2.2,2.4,15.5,12.7,0.508,0.33,0.206,1.6,11.3,6.3,20.4,1.3,0.4,12.5,24.2,0.4,2.4,2.9,0.06,-1.6,-1.5,-3.1,-0.6 70 | Reggie Jackson,1,28,DET,82,2289,27.9,5.4,12.8,0.421,2.1,5.7,0.369,3.3,7,0.464,0.504,2.5,2.9,0.864,0.5,2.1,2.6,4.2,0.7,0.1,1.8,2.5,15.4,15.2,0.547,0.45,0.225,2.1,8.5,5.2,24.7,1.2,0.3,11.4,24.5,3.1,1.9,5,0.105,1.8,-2,-0.3,1 71 | Jeremy Lamb,1,26,CHO,79,2250,28.5,5.5,12.4,0.44,1.5,4.2,0.348,4,8.2,0.487,0.499,2.9,3.3,0.888,0.8,4.7,5.5,2.2,1.1,0.4,1,1.8,15.3,17.3,0.552,0.337,0.266,3.1,18.1,10.4,11.9,1.9,1.2,6.8,22.5,3.3,2,5.3,0.113,0.6,-0.6,0.1,1.2 72 | Kelly Oubre,2,23,TOT,69,1935,28,5.4,12.2,0.445,1.6,4.9,0.32,3.9,7.3,0.53,0.51,2.7,3.5,0.775,1,3.7,4.7,1.2,1.2,0.9,1.5,2.6,15.2,15.2,0.551,0.401,0.29,4,14.6,9.2,6.8,2.1,2.5,9.8,23.2,0.9,1.3,2.2,0.054,-0.9,-1.2,-2.2,-0.1 73 | Evan Fournier,1,26,ORL,81,2553,31.5,5.8,13.2,0.438,1.9,5.6,0.34,3.9,7.6,0.509,0.509,1.7,2.1,0.806,0.5,2.7,3.2,3.6,0.9,0.1,1.9,2.8,15.1,12.3,0.536,0.421,0.159,1.6,9.4,5.4,17.6,1.4,0.4,11.9,22.1,0.8,2.5,3.2,0.061,-0.4,-1.1,-1.5,0.3 74 | Terrence Ross,1,27,ORL,81,2150,26.5,5.4,12.7,0.428,2.7,7,0.383,2.8,5.7,0.484,0.534,1.6,1.8,0.875,0.3,3.1,3.5,1.7,0.9,0.4,1.1,1.5,15.1,15.4,0.561,0.551,0.14,1.3,12.8,7,9.9,1.6,1.1,7.6,23.9,1.7,2.6,4.3,0.095,1,-1.3,-0.3,0.9 75 | Serge Ibaka,3,29,TOR,74,2010,27.2,6.3,11.9,0.529,0.7,2.3,0.29,5.6,9.6,0.586,0.557,1.8,2.4,0.763,2.1,6,8.1,1.3,0.4,1.4,1.5,2.9,15,18.7,0.582,0.193,0.202,8.6,23.2,16.1,7.7,0.7,4.3,10.7,22.9,2.8,3.3,6.1,0.146,-0.7,1.2,0.5,1.3 76 | Dwyane Wade,1,37,MIA,72,1885,26.2,5.8,13.3,0.433,1.2,3.6,0.33,4.6,9.7,0.472,0.478,2.3,3.2,0.708,1,3,4,4.2,0.8,0.5,2.3,1.6,15,15.8,0.51,0.272,0.243,3.9,12.2,8,26.5,1.5,1.8,13.5,27.9,0.1,2.3,2.4,0.061,-0.4,0,-0.5,0.7 77 | Marvin Bagley,3,19,SAC,62,1567,25.3,5.7,11.4,0.504,0.5,1.5,0.313,5.3,9.8,0.534,0.525,2.9,4.2,0.691,2.6,5,7.6,1,0.5,1,1.6,1.9,14.9,18.9,0.562,0.136,0.371,10.4,20.8,15.5,5.9,1,3.2,10.7,24.2,2,1.6,3.6,0.11,-1.2,-0.7,-1.8,0.1 78 | Emmanuel Mudiay,1,22,NYK,59,1607,27.2,5.6,12.5,0.446,1.2,3.6,0.329,4.4,9,0.492,0.493,2.4,3.2,0.774,0.6,2.8,3.3,3.9,0.7,0.3,2.4,1.7,14.8,14.6,0.531,0.284,0.251,2.1,10.9,6.4,24.2,1.3,1,14.6,25.6,0.1,0.7,0.8,0.023,-0.5,-1.9,-2.4,-0.2 79 | Jabari Parker,3,23,TOT,64,1724,26.9,5.8,11.7,0.493,1,3,0.313,4.8,8.7,0.556,0.533,2,2.9,0.712,1.2,5.3,6.6,2.4,0.7,0.5,2.4,2.3,14.5,15.5,0.56,0.26,0.246,4.9,21.8,13.3,14.1,1.3,1.5,15.4,24.6,0.1,1.3,1.4,0.039,-1.5,-0.5,-2.1,0 80 | Kyle Lowry,1,32,TOR,65,2213,34,4.7,11.4,0.411,2.4,7,0.347,2.3,4.4,0.514,0.518,2.5,3,0.83,0.6,4.2,4.8,8.7,1.4,0.5,2.8,2.6,14.2,16.5,0.562,0.613,0.263,2.1,12.9,7.6,34.8,2,1.2,18.1,19.6,3.6,3,6.6,0.144,2.5,0.6,3.1,2.8 81 | Bobby Portis,3,23,TOT,50,1299,26,5.6,12.6,0.444,1.5,3.8,0.393,4.1,8.7,0.467,0.504,1.5,1.9,0.794,2.2,5.9,8.1,1.4,0.7,0.4,1.5,2.9,14.2,16.1,0.529,0.304,0.154,9,24.9,16.8,8.8,1.3,1.3,9.9,24.6,0.5,1.1,1.6,0.06,-1.2,-1.7,-2.9,-0.3 82 | Bogdan Bogdanovic,1,26,SAC,70,1947,27.8,5.2,12.3,0.418,1.9,5.3,0.36,3.2,7,0.462,0.496,1.9,2.3,0.827,0.6,2.9,3.5,3.8,1,0.2,1.7,2,14.1,14.1,0.53,0.431,0.188,2.1,11,6.4,19.3,1.7,0.7,11.1,22.3,1.3,1.4,2.7,0.067,0.5,-1.2,-0.7,0.6 83 | Domantas Sabonis,3,22,IND,74,1838,24.8,5.6,9.5,0.59,0.1,0.2,0.529,5.5,9.2,0.592,0.596,2.8,3.9,0.715,2.5,6.8,9.3,2.9,0.6,0.4,2.2,3.2,14.1,21.9,0.63,0.024,0.416,11.5,29.8,20.8,18.2,1.3,1.5,16.2,23.5,4.3,3.3,7.6,0.197,1.5,2.2,3.7,2.6 84 | Steven Adams,3,25,OKC,80,2669,33.4,6,10.1,0.595,0,0,0,6,10.1,0.596,0.595,1.8,3.7,0.5,4.9,4.6,9.5,1.6,1.5,1,1.7,2.6,13.9,18.5,0.591,0.002,0.361,14.7,14.8,14.7,6.6,2,2.4,12.6,16.4,5.1,4,9.1,0.163,0.6,2.1,2.7,3.2 85 | Marcus Morris,3,29,BOS,75,2091,27.9,5,11.3,0.447,1.9,5.2,0.375,3.1,6.1,0.508,0.533,1.9,2.3,0.844,1,5.1,6.1,1.5,0.6,0.3,1.2,2.4,13.9,14.2,0.568,0.461,0.205,3.9,19.5,11.7,7.5,1,1.1,9.1,20.9,2.1,2.5,4.5,0.104,-0.4,-1,-1.4,0.3 86 | Otto Porter,2,25,TOT,56,1683,30.1,5.3,11.5,0.465,1.9,4.6,0.406,3.5,6.9,0.504,0.546,1.4,1.7,0.813,1,4.6,5.6,2.1,1.5,0.6,1.2,1.9,13.9,15.9,0.569,0.398,0.149,3.4,17,10.1,10.6,2.3,1.6,8.7,19.1,1.8,1.5,3.2,0.093,0.4,0.1,0.5,1 87 | Jaren Jackson,3,19,MEM,58,1515,26.1,5.1,10.2,0.506,0.9,2.4,0.359,4.3,7.7,0.553,0.549,2.6,3.4,0.766,1.3,3.4,4.7,1.1,0.9,1.4,1.7,3.8,13.8,16.4,0.591,0.241,0.334,5.3,15,10.1,7.2,1.7,5.1,12.7,22.8,1.2,2.2,3.3,0.105,-1.4,1.4,0.1,0.8 88 | Rudy Gay,3,32,SAS,69,1842,26.7,5.4,10.8,0.504,1.1,2.7,0.402,4.4,8.1,0.537,0.554,1.7,2.1,0.816,0.9,5.9,6.8,2.6,0.8,0.5,1.7,2.3,13.7,17.5,0.583,0.247,0.197,3.8,23.9,13.9,14.7,1.4,1.6,12.3,22.1,2.2,2.2,4.4,0.115,0.2,0.8,1,1.4 89 | Joe Harris,1,27,BRK,76,2293,30.2,4.9,9.8,0.5,2.4,5.1,0.474,2.5,4.8,0.528,0.622,1.4,1.8,0.827,0.7,3.1,3.8,2.4,0.5,0.2,1.6,2.4,13.7,13.5,0.645,0.516,0.178,2.4,10.9,6.7,11.9,0.8,0.6,13,17,3.8,1.7,5.5,0.116,1.4,-0.5,1,1.7 90 | Enes Kanter,3,26,TOT,67,1640,24.5,5.6,10.2,0.549,0.1,0.5,0.294,5.4,9.7,0.562,0.556,2.3,2.9,0.787,3.8,6,9.8,1.7,0.5,0.4,1.8,2.5,13.7,22.3,0.594,0.05,0.288,16.4,26.1,21.1,12.1,0.9,1.3,13.3,23.1,3.9,1.6,5.4,0.159,1.5,-0.2,1.3,1.4 91 | Marc Gasol,3,34,TOT,79,2436,30.8,4.9,11,0.448,1.3,3.5,0.363,3.7,7.6,0.487,0.505,2.4,3.2,0.759,1,6.9,7.9,4.4,1.1,1.1,2,2.7,13.6,16.7,0.546,0.314,0.291,3.6,25.1,14.3,22.2,1.7,3.2,13.6,20.7,2,4,6,0.118,-0.3,3.1,2.8,3 92 | Jerami Grant,3,24,OKC,80,2612,32.7,5.1,10.3,0.497,1.4,3.7,0.392,3.7,6.6,0.555,0.567,2,2.8,0.71,1.2,4,5.2,1,0.8,1.3,0.8,2.7,13.6,13.8,0.592,0.356,0.269,3.7,13.1,8.2,4.2,1.1,3.2,6.8,15.4,4,3.3,7.3,0.134,-0.6,0.9,0.3,1.5 93 | Al Horford,3,32,BOS,68,1973,29,5.7,10.6,0.535,1.1,3,0.36,4.6,7.6,0.604,0.586,1.1,1.4,0.821,1.8,5,6.7,4.2,0.9,1.3,1.5,1.9,13.6,20.2,0.605,0.281,0.131,6.5,18.3,12.4,21.2,1.4,3.9,11.8,18.9,4.5,2.9,7.5,0.181,2.1,2.7,4.8,3.4 94 | Dennis Smith,1,21,TOT,53,1508,28.5,5.2,12.3,0.428,1.3,3.9,0.322,4,8.3,0.477,0.479,1.9,2.9,0.635,0.6,2.3,2.9,4.8,1.3,0.4,2.9,2.4,13.6,12.3,0.502,0.32,0.24,2.2,8.7,5.5,27.3,2.1,1.1,17.6,24.8,-1.2,1.2,0,0.001,-1.7,-0.9,-2.5,-0.2 95 | Taurean Waller-Prince,2,24,ATL,55,1552,28.2,4.8,10.8,0.441,2.2,5.7,0.39,2.5,5.1,0.498,0.545,1.7,2.1,0.819,0.4,3.2,3.6,2.1,1,0.3,1.8,2.6,13.5,11.9,0.575,0.53,0.195,1.5,12.3,6.7,11.1,1.6,1.1,13.4,19.5,0.8,0.7,1.5,0.047,-0.4,-1.5,-1.9,0 96 | Myles Turner,3,22,IND,74,2119,28.6,5.1,10.5,0.487,1,2.6,0.388,4.1,7.9,0.521,0.536,2,2.7,0.736,1.4,5.8,7.2,1.6,0.8,2.7,1.4,2.6,13.3,18,0.567,0.251,0.258,5.4,22,13.9,8,1.4,8.4,10.3,20,1.9,4.4,6.3,0.144,-1.4,4.7,3.3,2.8 97 | Jaylen Brown,1,22,BOS,74,1913,25.9,5,10.7,0.465,1.3,3.7,0.344,3.7,7,0.529,0.525,1.8,2.7,0.658,0.9,3.4,4.2,1.4,0.9,0.4,1.3,2.5,13,13.5,0.547,0.348,0.255,3.6,13.9,8.7,7.7,1.7,1.5,10.1,22.1,0.7,2.4,3,0.076,-1.5,-0.6,-2.1,0 98 | Cedi Osman,2,23,CLE,76,2444,32.2,4.7,11.1,0.427,1.7,4.9,0.348,3,6.2,0.489,0.504,1.9,2.4,0.779,0.6,4.1,4.7,2.6,0.8,0.1,1.5,2.6,13,11.5,0.536,0.443,0.214,2,14.8,8.1,12.1,1.2,0.4,11,18.6,1.2,0.2,1.5,0.029,-0.4,-1.7,-2.1,-0.1 99 | Gary Harris,1,24,DEN,57,1639,28.8,4.7,11.2,0.424,1.4,4.2,0.339,3.3,6.9,0.476,0.488,2,2.5,0.799,0.7,2.1,2.8,2.2,1,0.3,1.2,2,12.9,12.2,0.526,0.38,0.226,2.7,7.9,5.3,11,1.6,1,8.9,20,1.1,1.5,2.6,0.076,-0.7,-1,-1.8,0.1 100 | Kevin Knox,3,19,NYK,75,2158,28.8,4.5,12.2,0.37,1.7,4.9,0.343,2.8,7.3,0.387,0.438,2.2,3,0.717,0.8,3.7,4.5,1.1,0.6,0.3,1.5,2.3,12.8,8.7,0.475,0.398,0.247,2.9,13.6,8.1,6,1,0.9,10.1,22.3,-2.2,0.9,-1.3,-0.03,-3.6,-2.4,-6,-2.2 101 | Ricky Rubio,1,28,UTA,68,1899,27.9,4.3,10.7,0.404,1.2,3.7,0.311,3.2,7,0.454,0.458,2.9,3.4,0.855,0.5,3.1,3.6,6.1,1.3,0.1,2.6,2.6,12.7,14,0.52,0.348,0.312,1.9,11.8,6.9,32.1,2.3,0.4,17.8,22.7,0.9,2.8,3.7,0.095,-0.6,0.6,0,0.9 102 | Paul Millsap,3,33,DEN,70,1895,27.1,4.6,9.5,0.484,0.8,2.3,0.365,3.8,7.2,0.522,0.528,2.6,3.6,0.727,2.2,5,7.2,2,1.2,0.8,1.4,2.6,12.6,17.9,0.57,0.239,0.374,8.7,20.2,14.4,10.6,2.2,2.5,10.9,19.6,3.2,2.9,6.1,0.155,0.5,1.9,2.4,2.1 103 | Justise Winslow,2,22,MIA,66,1959,29.7,4.9,11.3,0.433,1.5,3.9,0.375,3.5,7.5,0.462,0.497,1.3,2.1,0.628,1,4.4,5.4,4.3,1.1,0.3,2.2,2.7,12.6,12.8,0.513,0.342,0.183,3.4,15.9,9.6,21.9,1.8,0.9,14.9,20.8,0.2,2.6,2.7,0.067,-1.1,1,-0.1,1 104 | Thaddeus Young,3,30,IND,81,2489,30.7,5.5,10.4,0.527,0.6,1.8,0.349,4.8,8.6,0.564,0.557,1.1,1.7,0.644,2.4,4.1,6.5,2.5,1.5,0.4,1.5,2.4,12.6,16.2,0.569,0.174,0.161,8.7,14.4,11.7,12,2.4,1.3,12,18,3,3.9,6.9,0.133,0.8,2.1,2.9,3.1 105 | Trevor Ariza,2,33,TOT,69,2349,34,4.3,10.7,0.399,2.1,6.3,0.334,2.2,4.4,0.493,0.498,1.9,2.4,0.793,0.7,4.7,5.4,3.7,1.3,0.3,1.5,1.9,12.5,12.1,0.534,0.59,0.223,2.3,15.2,8.6,14.8,1.8,0.7,11.6,16.6,1.3,1.2,2.5,0.052,-0.1,-0.4,-0.5,0.9 106 | Brook Lopez,3,30,MIL,81,2322,28.7,4.4,9.7,0.452,2.3,6.3,0.365,2.1,3.4,0.613,0.571,1.4,1.6,0.842,0.4,4.5,4.9,1.2,0.6,2.2,1,2.3,12.5,14.6,0.597,0.651,0.169,1.5,15,8.7,5.7,1,6.5,8.9,16.7,2.3,4.3,6.7,0.138,-0.2,2.9,2.7,2.8 107 | Jeff Green,3,32,WAS,77,2097,27.2,4.2,8.9,0.475,1.4,4.2,0.347,2.8,4.8,0.586,0.555,2.4,2.7,0.888,0.7,3.3,4,1.8,0.6,0.5,1.3,2.1,12.3,13.6,0.608,0.466,0.3,2.9,13.3,8,9.2,1,1.6,11.5,17.8,2.8,0.8,3.6,0.083,0.2,-1.4,-1.2,0.4 108 | Hassan Whiteside,3,29,MIA,72,1674,23.3,5.4,9.4,0.571,0,0.2,0.125,5.4,9.2,0.581,0.572,1.5,3.4,0.449,3.6,7.8,11.3,0.8,0.6,1.9,1.3,2.7,12.3,23.5,0.564,0.024,0.357,16.3,35.6,25.9,5.6,1.3,7.3,11,22.6,2.3,4,6.3,0.18,-2.2,3,0.8,1.2 109 | Wesley Matthews,2,32,TOT,69,2091,30.3,4,10.1,0.4,2.2,5.8,0.372,1.9,4.3,0.437,0.507,1.9,2.4,0.81,0.5,2,2.5,2.3,0.8,0.2,1.3,2.3,12.2,10.3,0.546,0.577,0.234,1.7,7.1,4.4,11.1,1.3,0.7,10.6,17.8,1.1,1.5,2.7,0.062,-0.3,-1.2,-1.5,0.3 110 | Joe Ingles,3,31,UTA,82,2568,31.3,4.4,9.8,0.448,2.3,5.9,0.391,2.1,3.9,0.533,0.565,1.1,1.5,0.707,0.4,3.6,4,5.7,1.2,0.2,2.4,2.2,12.1,13.4,0.581,0.602,0.153,1.5,12.2,7,26.1,1.8,0.6,18.4,17.5,2.5,3.6,6,0.113,1,0.8,1.8,2.5 111 | JaVale McGee,3,31,LAL,75,1671,22.3,5.3,8.5,0.624,0,0.2,0.083,5.3,8.4,0.634,0.625,1.3,2,0.632,2.6,4.9,7.5,0.7,0.6,2,1.4,2.8,12,21.8,0.634,0.019,0.237,12.3,22.5,17.5,4.8,1.3,7.3,13.2,20.2,3,2.9,5.9,0.171,-0.9,2.8,1.9,1.7 112 | Willie Cauley-Stein,3,25,SAC,81,2213,27.3,5.1,9.1,0.556,0,0,0.5,5.1,9.1,0.556,0.557,1.7,3.1,0.551,2.2,6.1,8.4,2.4,1.2,0.6,1,2.8,11.9,18,0.566,0.003,0.343,8.2,23.7,15.8,12.3,2,2,9,17.5,3.8,2.9,6.7,0.146,-0.2,2.2,2,2.3 113 | Jae Crowder,2,28,UTA,80,2166,27.1,4,10,0.399,2.2,6.5,0.331,1.8,3.4,0.527,0.508,1.8,2.5,0.721,0.8,4.1,4.8,1.7,0.8,0.4,1.1,2.1,11.9,12.1,0.538,0.655,0.247,3.1,15.9,9.6,8.9,1.4,1.1,8.8,19.1,1.3,3.1,4.4,0.097,0,0.4,0.4,1.3 114 | E'Twaun Moore,1,29,NOP,53,1463,27.6,4.8,10,0.481,1.4,3.3,0.432,3.4,6.7,0.506,0.553,0.8,1.1,0.763,0.7,1.7,2.4,1.9,0.8,0.2,1.1,2.1,11.9,11.5,0.567,0.331,0.111,2.5,6.4,4.5,9.5,1.3,0.4,9.6,17.3,1.2,0.5,1.7,0.055,-0.2,-1.9,-2.2,-0.1 115 | Derrick Favors,3,27,UTA,76,1766,23.2,4.8,8.1,0.586,0.2,1,0.218,4.6,7.1,0.64,0.6,2,3,0.675,2.7,4.6,7.4,1.2,0.7,1.4,1.1,2.1,11.8,21.8,0.624,0.126,0.368,12.9,21.3,17.2,8,1.5,4.8,10.5,19.4,4.4,3.5,7.9,0.215,1.1,3.2,4.3,2.8 116 | Bryn Forbes,1,25,SAS,82,2293,28,4.4,9.6,0.456,2.1,5,0.426,2.3,4.6,0.489,0.568,0.8,1,0.885,0.2,2.7,2.9,2.1,0.5,0,1,1.9,11.8,12,0.586,0.522,0.099,0.9,10.4,5.7,10.6,1,0.1,8.8,17.4,2.5,1.3,3.8,0.079,1,-1.7,-0.7,0.7 117 | D.J. Augustin,1,31,ORL,81,2269,28,3.9,8.4,0.47,1.6,3.8,0.421,2.3,4.5,0.511,0.566,2.2,2.6,0.866,0.5,2,2.5,5.3,0.6,0,1.6,1.4,11.7,15.7,0.616,0.459,0.309,1.9,7.8,4.8,26.9,1.1,0.1,14.3,17.2,5,1.9,6.9,0.146,1.7,-2,-0.3,1 118 | Kent Bazemore,1,29,ATL,67,1643,24.5,4.1,10.3,0.402,1.4,4.5,0.32,2.7,5.8,0.465,0.472,1.9,2.6,0.726,0.6,3.3,3.9,2.3,1.3,0.6,1.8,2.5,11.6,11.9,0.507,0.434,0.253,2.3,14.6,8.3,13.5,2.5,2.2,13.6,22,-0.7,1.4,0.7,0.021,-2.2,0,-2.2,-0.1 119 | Gordon Hayward,3,28,BOS,72,1863,25.9,4.1,8.8,0.466,1.1,3.2,0.333,3,5.6,0.542,0.527,2.2,2.6,0.834,0.7,3.8,4.5,3.4,0.9,0.3,1.5,1.4,11.5,15.6,0.575,0.364,0.294,2.9,15.5,9.2,18.4,1.6,1.1,12.8,19,2.6,2.3,4.9,0.126,0.1,0.4,0.5,1.2 120 | Josh Jackson,1,21,PHO,79,1988,25.2,4.4,10.6,0.413,0.9,2.8,0.324,3.5,7.8,0.445,0.456,1.8,2.7,0.671,0.8,3.6,4.4,2.3,0.9,0.7,2.2,2.6,11.5,10.6,0.487,0.268,0.253,3.6,15.9,9.7,14.1,1.8,2.3,15.6,23.9,-2.8,1.1,-1.7,-0.04,-4.3,-0.5,-4.8,-1.4 121 | Kentavious Caldwell-Pope,1,25,LAL,82,2035,24.8,4,9.2,0.43,1.8,5.3,0.347,2.1,3.9,0.542,0.53,1.7,1.9,0.867,0.6,2.3,2.9,1.3,0.9,0.2,0.8,1.7,11.4,12.9,0.568,0.575,0.209,2.5,9.4,6,7.5,1.7,0.5,7.3,18.1,2.3,1.8,4,0.095,0.6,-1.2,-0.6,0.7 122 | Malik Beasley,1,22,DEN,81,1879,23.2,4.3,9.1,0.474,2,5,0.402,2.3,4.1,0.56,0.584,0.7,0.8,0.848,0.4,2,2.5,1.2,0.7,0.1,0.7,1.4,11.3,14.2,0.599,0.55,0.09,2,9.5,5.8,7.5,1.4,0.5,6.7,18.7,2.9,1.6,4.5,0.115,1.4,-1.9,-0.5,0.7 123 | Reggie Bullock,1,27,TOT,63,1879,29.8,3.9,9.4,0.412,2.3,6.2,0.377,1.5,3.2,0.483,0.537,1.2,1.3,0.859,0.3,2.4,2.7,2,0.6,0.2,1,1.7,11.3,10.5,0.563,0.662,0.143,1.2,8.8,4.9,10.1,1,0.5,9.3,15.8,1.6,1.4,3.1,0.078,0.1,-1,-0.9,0.5 124 | Darren Collison,1,31,IND,76,2143,28.2,4.1,8.7,0.467,1,2.6,0.407,3,6.1,0.492,0.527,2.1,2.5,0.832,0.5,2.6,3.1,6,1.4,0.1,1.6,1.8,11.2,16.7,0.574,0.294,0.288,1.9,9.9,6,29.9,2.5,0.4,14.4,17.7,3.9,2.9,6.8,0.153,1.2,0,1.2,1.8 125 | Rodney Hood,1,26,TOT,72,1893,26.3,4.1,9.3,0.435,1.2,3.3,0.356,2.9,6,0.478,0.498,1.9,2.2,0.884,0.3,1.8,2.2,1.8,0.8,0.2,0.8,2,11.2,12.3,0.545,0.352,0.231,1.4,7.9,4.6,10,1.5,0.5,6.9,18.1,2.1,0.5,2.6,0.065,-0.2,-2.1,-2.4,-0.2 126 | DeMarre Carroll,3,32,BRK,67,1703,25.4,3.4,8.6,0.395,1.6,4.6,0.342,1.8,4,0.457,0.487,2.7,3.6,0.76,1,4.2,5.2,1.3,0.5,0.1,1.1,1.7,11.1,12.1,0.546,0.539,0.421,4.2,17.3,10.8,7.2,0.9,0.5,9.7,18.6,1.5,1.6,3.1,0.088,-1,-0.7,-1.7,0.1 127 | Alex Len,3,25,ATL,77,1544,20.1,4.2,8.4,0.494,1,2.6,0.363,3.2,5.8,0.554,0.551,1.8,2.8,0.648,2.1,3.5,5.5,1.1,0.4,0.9,1.3,2.6,11.1,17.2,0.575,0.315,0.333,10.5,18.5,14.4,8.6,0.8,3.9,11.5,22.1,2.2,1,3.2,0.1,-0.1,-0.8,-0.9,0.4 128 | DeAndre Jordan,3,30,TOT,69,2047,29.7,4.1,6.5,0.641,0,0,0,4.1,6.5,0.641,0.641,2.7,3.8,0.705,3.3,9.8,13.1,2.3,0.6,1.1,2.2,2.4,11,19,0.674,0,0.592,11.7,35.2,23.5,11.6,1,3,21.4,15,4,3.1,7.1,0.167,-0.9,3.3,2.4,2.3 129 | Fred VanVleet,1,24,TOR,64,1760,27.5,3.8,9.4,0.41,1.8,4.6,0.378,2.1,4.8,0.441,0.503,1.5,1.8,0.843,0.3,2.3,2.6,4.8,0.9,0.3,1.3,1.7,11,13.7,0.539,0.493,0.192,1.3,8.7,5.1,23.9,1.6,0.9,11.2,17.9,2.4,1.9,4.3,0.117,0.7,-0.7,0,0.9 130 | Jarrett Allen,3,20,BRK,80,2096,26.2,4.2,7.1,0.59,0.1,0.6,0.133,4.1,6.5,0.629,0.595,2.5,3.5,0.709,2.4,6,8.4,1.4,0.5,1.5,1.3,2.3,10.9,18.5,0.632,0.079,0.489,9.6,24,16.8,7.9,1,4.5,13,15.9,4.4,3.3,7.7,0.175,-0.7,3.2,2.5,2.4 131 | Trey Burke,1,26,TOT,58,1125,19.4,4.1,9.4,0.431,1,2.7,0.352,3.1,6.7,0.463,0.482,1.8,2.1,0.831,0.5,1.2,1.7,2.7,0.6,0.1,0.8,1,10.9,16.5,0.524,0.29,0.226,2.6,6.7,4.6,24.1,1.4,0.5,7.5,24.8,1.4,0.5,1.9,0.081,0.7,-3.2,-2.5,-0.1 132 | Tyler Johnson,1,26,TOT,57,1529,26.8,3.8,9.2,0.413,1.6,4.6,0.346,2.2,4.7,0.477,0.498,1.7,2.2,0.748,0.6,2.4,3,2.9,0.9,0.5,1.4,1.7,10.9,12.4,0.532,0.494,0.241,2.4,9.8,6.1,15.9,1.7,1.6,11.7,18.5,0.9,1.4,2.3,0.071,-0.6,-0.4,-1,0.4 133 | Allonzo Trier,1,23,NYK,64,1459,22.8,3.6,8.1,0.448,0.8,2.1,0.394,2.8,6,0.466,0.498,2.8,3.5,0.803,0.5,2.6,3.1,1.9,0.4,0.2,1.8,1.8,10.9,12.2,0.564,0.255,0.431,2.2,12.2,7.1,12.9,0.9,0.8,15.8,21.5,0.4,0.5,0.9,0.03,-2.2,-2,-4.2,-0.8 134 | Dewayne Dedmon,3,29,ATL,64,1609,25.1,4,8.2,0.492,1.3,3.4,0.382,2.8,4.8,0.57,0.571,1.4,1.8,0.814,1.6,5.9,7.5,1.4,1.1,1.1,1.3,3.3,10.8,16,0.602,0.413,0.215,6.7,25,15.7,8.1,2,3.8,12.7,16.7,2.1,1.9,4,0.119,-0.4,1.7,1.3,1.3 135 | Taj Gibson,3,33,MIN,70,1686,24.1,4.3,7.7,0.566,0.2,0.5,0.324,4.2,7.2,0.583,0.576,1.9,2.5,0.757,2.5,4.1,6.5,1.2,0.8,0.6,1,2.7,10.8,17.8,0.612,0.063,0.33,10.8,18.3,14.5,7.3,1.5,2,10.6,17.2,3.7,1.4,5.1,0.144,0.8,0.2,1,1.3 136 | Shai Gilgeous-Alexander,1,20,LAC,82,2174,26.5,4.2,8.7,0.476,0.6,1.7,0.367,3.5,7,0.503,0.512,1.9,2.4,0.8,0.7,2.1,2.8,3.3,1.2,0.5,1.7,2.1,10.8,13.4,0.554,0.194,0.272,2.9,8.3,5.7,17.8,2.1,1.6,15,18.3,1.5,1.9,3.3,0.074,-0.6,0.2,-0.3,0.9 137 | Damyean Dotson,1,24,NYK,73,2004,27.5,4,9.6,0.415,1.7,4.7,0.368,2.2,4.9,0.461,0.506,1,1.3,0.745,0.5,3.1,3.6,1.8,0.8,0.1,1,1.8,10.7,10.8,0.526,0.49,0.14,1.7,12.2,6.8,10.4,1.4,0.4,8.7,17.3,0.7,0.9,1.5,0.037,-0.9,-1.4,-2.3,-0.2 138 | Dwight Powell,3,27,DAL,77,1662,21.6,3.8,6.3,0.597,0.5,1.6,0.307,3.3,4.7,0.699,0.637,2.5,3.3,0.772,1.8,3.5,5.3,1.5,0.6,0.6,0.9,2.6,10.6,20.4,0.682,0.261,0.523,9.1,17.3,13.2,10.7,1.3,2.6,10.1,17.2,5.6,1.9,7.5,0.215,2.8,1.2,4,2.5 139 | Dario Saric,3,24,TOT,81,2023,25,3.8,8.6,0.437,1.5,4,0.365,2.3,4.6,0.499,0.522,1.6,1.9,0.88,1.6,4.1,5.6,1.6,0.6,0.1,1.2,2.2,10.6,13.1,0.563,0.464,0.216,6.6,17.5,12.1,8.8,1.1,0.4,11.3,17.8,2.3,1.2,3.5,0.084,0.3,-1.4,-1.1,0.5 140 | Marco Belinelli,1,32,SAS,79,1815,23,3.6,8.7,0.413,1.9,5,0.372,1.7,3.7,0.468,0.52,1.4,1.6,0.903,0.2,2.3,2.5,1.7,0.4,0.1,0.9,1.5,10.5,11.9,0.557,0.572,0.18,1,10.8,5.9,10.1,0.9,0.4,8.8,19.8,1.4,1.1,2.5,0.065,0.3,-2.4,-2.1,0 141 | Thomas Bryant,3,21,WAS,72,1496,20.8,4.3,7,0.616,0.5,1.4,0.333,3.8,5.6,0.685,0.648,1.5,1.9,0.781,1.6,4.7,6.3,1.3,0.3,0.9,0.8,1.8,10.5,21,0.674,0.197,0.273,8.1,25.1,16.5,9.3,0.8,3.8,9.6,17.6,4.3,1.3,5.6,0.178,1.2,0.4,1.6,1.3 142 | Justin Holiday,1,29,TOT,82,2607,31.8,3.7,9.5,0.386,2,5.7,0.348,1.7,3.8,0.442,0.49,1.2,1.3,0.896,0.6,3.4,3.9,1.8,1.5,0.4,1.3,2,10.5,10,0.52,0.598,0.136,1.9,11.9,6.8,8.1,2.3,1.2,11.2,15.7,-0.4,2.5,2.1,0.038,-1.3,0.6,-0.8,0.8 143 | Monte Morris,1,23,DEN,82,1970,24,4.2,8.6,0.493,1.1,2.8,0.414,3.1,5.8,0.531,0.56,0.8,1,0.802,0.4,1.9,2.4,3.6,0.9,0,0.6,1.2,10.4,16.2,0.577,0.323,0.115,1.9,8.8,5.3,21.7,1.8,0.2,6.6,17.1,4.4,1.8,6.2,0.151,1.5,-1.3,0.2,1.1 144 | Wayne Ellington,1,31,TOT,53,1297,24.5,3.5,8.6,0.403,2.6,7,0.371,0.9,1.6,0.541,0.554,0.7,0.9,0.796,0.3,1.8,2,1.4,1,0.1,0.8,1.7,10.3,11.8,0.569,0.814,0.107,1.1,7.9,4.5,8.3,2,0.4,7.7,17.2,1.3,1.4,2.6,0.097,1.2,-1,0.2,0.7 145 | Danny Green,1,31,TOR,80,2216,27.7,3.7,7.9,0.465,2.5,5.4,0.455,1.2,2.4,0.487,0.622,0.5,0.6,0.841,0.8,3.2,4,1.6,0.9,0.7,0.9,2.1,10.3,13,0.632,0.69,0.07,3,12.2,7.7,7.7,1.6,2,10.4,14.1,3,2.9,5.9,0.128,1.7,1.2,2.9,2.7 146 | Tyreke Evans,1,29,IND,69,1402,20.3,3.7,9.6,0.389,1.1,3.1,0.356,2.6,6.4,0.405,0.448,1.7,2.3,0.719,0.5,2.4,2.9,2.4,0.8,0.3,1.7,1.7,10.2,11.5,0.483,0.327,0.242,2.7,13,7.9,17.5,2,1.1,13.9,26.4,-1.7,2,0.3,0.01,-3.1,-0.5,-3.6,-0.6 147 | Marvin Williams,3,32,CHO,75,2133,28.4,3.7,8.7,0.422,1.9,5.1,0.366,1.8,3.6,0.5,0.529,0.9,1.1,0.767,1,4.4,5.4,1.2,0.9,0.8,0.6,2.1,10.1,12.6,0.548,0.586,0.132,3.8,17.1,10.3,6.1,1.6,2.5,6.4,14.9,1.9,1.9,3.8,0.086,-0.2,0.5,0.3,1.3 148 | Kelly Olynyk,3,27,MIA,79,1812,22.9,3.3,7.1,0.463,1.4,4,0.354,1.9,3.1,0.604,0.563,1.9,2.3,0.822,0.9,3.8,4.7,1.8,0.7,0.5,1.4,2.3,10,14.4,0.61,0.566,0.328,4.2,17.8,11,11.4,1.4,1.8,15,18,2.3,2.5,4.7,0.125,0.3,0.8,1.1,1.4 149 | Avery Bradley,1,28,TOT,63,1905,30.2,3.9,9.7,0.408,1.4,3.9,0.351,2.6,5.8,0.446,0.479,0.7,0.8,0.86,0.7,2.1,2.8,2.4,0.7,0.3,1.4,2.7,9.9,7.6,0.496,0.403,0.082,2.5,7.3,4.9,11.8,1,0.7,12.4,16.2,-0.6,1,0.3,0.009,-1.7,-1,-2.8,-0.4 150 | Patty Mills,1,30,SAS,82,1908,23.3,3.4,8.1,0.425,1.9,4.9,0.394,1.5,3.2,0.475,0.545,1.1,1.3,0.854,0.3,1.9,2.2,3,0.6,0.1,1.1,1.6,9.9,13.2,0.572,0.609,0.155,1.4,8.9,5.2,17.6,1.3,0.4,11.6,18.5,2.2,1.2,3.5,0.087,1.5,-2,-0.5,0.7 151 | Derrick White,1,24,SAS,67,1728,25.8,3.9,8.1,0.479,0.7,2.1,0.338,3.2,6,0.529,0.523,1.4,1.8,0.772,0.5,3.2,3.7,3.9,1,0.7,1.4,2.2,9.9,14.8,0.555,0.262,0.227,2.2,13.3,7.8,21,1.9,2.3,14,17.7,1.7,1.9,3.6,0.101,-0.2,1.1,0.9,1.3 152 | Kevin Huerter,1,20,ATL,75,2048,27.3,3.7,8.8,0.419,1.8,4.7,0.385,1.9,4.1,0.457,0.522,0.5,0.7,0.732,0.8,2.5,3.3,2.9,0.9,0.3,1.5,2.1,9.7,10.1,0.533,0.537,0.085,3,9.7,6.3,14.5,1.5,1.1,13.8,15.7,0.7,0.7,1.5,0.034,-0.9,-1,-1.9,0.1 153 | Luke Kennard,1,22,DET,63,1437,22.8,3.6,8.3,0.438,1.7,4.3,0.394,1.9,4,0.486,0.54,0.8,1,0.836,0.2,2.7,2.9,1.8,0.4,0.2,0.9,1.5,9.7,11.9,0.56,0.517,0.117,0.9,13.5,7,12.3,0.9,0.6,9.4,18.1,1.3,1.3,2.5,0.085,-0.5,-1,-1.5,0.2 154 | Nemanja Bjelica,3,30,SAC,77,1788,23.2,3.7,7.7,0.479,1.3,3.3,0.401,2.4,4.4,0.539,0.566,0.9,1.2,0.761,1.6,4.1,5.8,1.9,0.7,0.7,1.1,2.6,9.6,15.4,0.585,0.433,0.155,7,18.8,12.8,11.1,1.4,2.7,11.5,16.5,2.7,1.9,4.5,0.122,0.8,1.2,2,1.8 155 | Jonathan Isaac,3,21,ORL,75,1996,26.6,3.5,8.1,0.429,1.1,3.5,0.323,2.3,4.6,0.51,0.499,1.5,1.8,0.815,1.3,4.2,5.5,1.1,0.8,1.3,1,1.9,9.6,13,0.537,0.435,0.221,5.2,17,11,5.7,1.4,4.1,10.1,16.3,0.9,3.1,4,0.096,-1.9,2,0.1,1.1 156 | Jeremy Lin,1,30,TOT,74,1436,19.4,3.2,7.3,0.44,0.7,2.5,0.294,2.5,4.8,0.517,0.491,2.4,2.8,0.838,0.3,2.1,2.4,3.1,0.6,0.2,1.7,1.9,9.6,13.5,0.558,0.346,0.388,1.6,11.7,6.6,23.4,1.5,0.8,16.4,21.8,1.2,0.9,2.1,0.07,-1.1,-1.8,-2.9,-0.3 157 | Robin Lopez,3,30,CHI,74,1606,21.7,4.1,7.2,0.568,0.1,0.4,0.226,4,6.8,0.589,0.575,1.2,1.7,0.724,1.9,2,3.9,1.2,0.1,1.1,1.3,1.7,9.5,15.9,0.598,0.058,0.23,9.4,10,9.7,8.8,0.3,4.2,14,18.6,2,0.7,2.7,0.081,-1,-0.1,-1.1,0.4 158 | Tony Parker,1,36,CHO,56,1003,17.9,3.8,8.3,0.46,0.2,0.9,0.255,3.6,7.4,0.485,0.474,1.6,2.2,0.734,0.3,1.2,1.5,3.7,0.4,0.1,1.3,0.9,9.5,15.3,0.512,0.11,0.268,1.5,7.6,4.5,33.3,1,0.6,12.7,25.5,0.6,0.3,0.9,0.044,-1.5,-3.7,-5.3,-0.8 159 | Al-Farouq Aminu,3,28,POR,81,2292,28.3,3.2,7.3,0.433,1.2,3.5,0.343,2,3.9,0.514,0.514,1.9,2.1,0.867,1.4,6.1,7.5,1.3,0.8,0.4,0.9,1.8,9.4,13.2,0.568,0.472,0.292,5.3,22.6,14.2,6,1.4,1.2,9.7,13.7,3,2.8,5.8,0.121,0.1,0.8,0.9,1.7 160 | JaMychal Green,3,28,TOT,65,1371,21.1,3.5,7.3,0.483,1.1,2.7,0.403,2.4,4.6,0.53,0.558,1.2,1.6,0.792,1.6,4.7,6.3,0.8,0.7,0.5,1.3,3,9.4,14.7,0.587,0.37,0.212,8.3,24.3,16.4,5.8,1.6,2.3,14.3,19.4,0.9,1.9,2.9,0.101,-1.5,0,-1.5,0.2 161 | Markieff Morris,3,29,TOT,58,1270,21.9,3.5,8.3,0.421,1.2,3.5,0.335,2.3,4.8,0.484,0.492,1.2,1.6,0.772,1.1,3.5,4.6,1.4,0.6,0.4,0.9,3,9.4,11.7,0.521,0.419,0.19,5,17.5,11.1,8.8,1.3,1.5,9.3,19.1,0.6,1.1,1.6,0.061,-1.7,-1.1,-2.8,-0.3 162 | Larry Nance,3,26,CLE,67,1795,26.8,3.7,7.1,0.52,0.5,1.5,0.337,3.2,5.7,0.567,0.554,1.4,2,0.716,2.5,5.7,8.2,3.2,1.5,0.6,1.4,2.9,9.4,18.6,0.583,0.205,0.28,10,24.9,17.1,17.8,2.8,1.9,15.3,15.5,3.3,1.6,4.9,0.131,1.4,2.6,4,2.7 163 | Nicolas Batum,2,30,CHO,75,2354,31.4,3.4,7.5,0.45,1.5,4,0.389,1.8,3.5,0.519,0.553,1,1.2,0.865,0.9,4.3,5.2,3.3,0.9,0.6,1.6,1.9,9.3,11.9,0.581,0.53,0.158,3.2,14.9,8.9,14.5,1.5,1.6,16.3,13.2,2,1.7,3.7,0.076,-0.1,0.9,0.8,1.7 164 | Jalen Brunson,1,22,DAL,73,1591,21.8,3.6,7.7,0.467,0.9,2.5,0.348,2.8,5.3,0.523,0.523,1.2,1.6,0.725,0.3,2,2.3,3.2,0.5,0.1,1.2,1.7,9.3,12.8,0.549,0.32,0.212,1.7,9.6,5.7,22.6,1.1,0.2,12.5,19.1,1.5,1,2.6,0.077,-0.8,-1.6,-2.5,-0.2 165 | Gerald Green,1,33,HOU,73,1473,20.2,3.2,7.9,0.4,2.1,6,0.354,1,1.9,0.547,0.535,0.8,0.9,0.838,0.4,2.1,2.5,0.5,0.5,0.4,0.8,1.7,9.2,11.4,0.555,0.763,0.118,2.2,11.7,6.8,4.1,1.1,1.6,8.3,19.5,0.9,1,1.9,0.061,-0.8,-2.6,-3.4,-0.5 166 | Landry Shamet,1,21,TOT,79,1802,22.8,3,7.1,0.431,2.1,5,0.422,0.9,2,0.453,0.581,0.9,1.2,0.806,0.3,1.4,1.7,1.5,0.5,0.1,0.6,2,9.1,11,0.604,0.711,0.167,1.3,6.4,3.9,9,1,0.4,7,15,2.7,0.9,3.6,0.095,1.4,-2.4,-1,0.5 167 | Terry Rozier,1,24,BOS,79,1791,22.7,3.3,8.4,0.387,1.5,4.3,0.353,1.8,4.2,0.422,0.477,0.9,1.2,0.785,0.4,3.5,3.9,2.9,0.9,0.3,0.9,1.3,9,12.9,0.501,0.506,0.14,1.9,16.4,9.1,17.7,1.8,1,8.8,18.6,0.9,2.3,3.2,0.086,-1,0.2,-0.7,0.6 168 | Bam Adebayo,3,21,MIA,82,1913,23.3,3.4,5.9,0.576,0,0.2,0.2,3.4,5.7,0.588,0.579,2,2.8,0.735,2,5.3,7.3,2.2,0.9,0.8,1.5,2.5,8.9,17.9,0.623,0.031,0.465,9.2,24,16.6,14.2,1.8,3,17.1,15.8,3.4,3.4,6.8,0.171,-0.6,3.6,3,2.4 169 | Rondae Hollis-Jefferson,2,24,BRK,59,1234,20.9,3.4,8.3,0.411,0.2,0.8,0.184,3.2,7.4,0.436,0.42,2,3.1,0.645,1.4,3.8,5.3,1.6,0.7,0.5,1.2,1.8,8.9,12.5,0.464,0.101,0.376,7.1,19.2,13.2,11.7,1.7,1.7,10.7,21.6,-0.5,1.7,1.2,0.047,-4.3,1.2,-3,-0.3 170 | Malik Monk,1,20,CHO,73,1258,17.2,3.1,8,0.387,1.5,4.5,0.33,1.6,3.5,0.461,0.48,1.2,1.4,0.882,0.2,1.7,1.9,1.6,0.5,0.3,1.2,1.5,8.9,11.8,0.518,0.563,0.174,1.3,10.6,5.9,14.3,1.4,1.3,12,24.6,-0.4,0.7,0.3,0.012,-1.1,-2.7,-3.9,-0.6 171 | Tomas Satoransky,1,27,WAS,80,2164,27.1,3.2,6.6,0.485,0.8,2,0.395,2.4,4.6,0.524,0.545,1.6,2,0.819,1,2.5,3.5,5,1,0.2,1.5,2.2,8.9,14.1,0.59,0.306,0.302,4,10,7,24.6,1.8,0.5,16.7,14.1,3.8,0.9,4.7,0.104,0.4,-1,-0.6,0.8 172 | Marcus Smart,1,24,BOS,80,2200,27.5,3,7.1,0.422,1.6,4.3,0.364,1.4,2.8,0.511,0.533,1.3,1.6,0.806,0.7,2.2,2.9,4,1.8,0.4,1.5,2.5,8.9,13.1,0.568,0.61,0.228,2.8,8.6,5.7,19.1,3.1,1.1,16.5,14.6,2.2,3.1,5.3,0.116,0.6,1.3,1.8,2.1 173 | Ish Smith,1,30,DET,56,1251,22.3,3.7,8.7,0.419,0.8,2.4,0.326,2.9,6.3,0.455,0.464,0.8,1.1,0.758,0.4,2.2,2.6,3.6,0.5,0.2,1.1,1.9,8.9,11.8,0.485,0.276,0.127,1.9,11.1,6.3,25.4,1.1,0.7,10.6,19.9,0.5,1.1,1.7,0.064,-1.7,-1.1,-2.8,-0.3 174 | Ivica Zubac,3,21,TOT,59,1040,17.6,3.6,6.4,0.559,0,0,0,3.6,6.4,0.559,0.559,1.7,2.1,0.802,1.9,4.2,6.1,1.1,0.2,0.9,1.2,2.3,8.9,18.9,0.604,0,0.332,11.9,24.2,18.2,9.1,0.6,4,13.9,20.3,1.9,1.3,3.2,0.148,-1.2,1,-0.3,0.5 175 | Alec Burks,1,27,TOT,64,1375,21.5,3,7.4,0.405,1,2.6,0.363,2,4.8,0.428,0.469,1.8,2.2,0.823,0.5,3.2,3.7,2,0.6,0.3,1,1.4,8.8,12.7,0.523,0.354,0.297,2.3,17,9.4,13.7,1.4,1.3,10.8,19,0.7,0.8,1.5,0.052,-1.5,-0.6,-2.2,-0.1 176 | Mario Hezonja,2,23,NYK,58,1206,20.8,3.3,8,0.412,0.7,2.6,0.276,2.6,5.4,0.478,0.457,1.5,2,0.763,0.5,3.6,4.1,1.5,1,0.1,1.5,1.9,8.8,10.8,0.497,0.328,0.246,2.4,18.7,10.4,11.5,2.3,0.6,14.6,21.3,-1.1,1.1,-0.1,-0.003,-3.6,-0.4,-4,-0.6 177 | Delon Wright,1,26,TOT,75,1699,22.7,3.2,7.4,0.434,0.7,2.2,0.298,2.6,5.2,0.492,0.478,1.6,2,0.793,0.9,2.6,3.5,3.3,1.2,0.4,1,1.4,8.7,15.5,0.523,0.301,0.269,4.4,12.8,8.6,21.6,2.5,1.6,11,18.1,1.9,2.4,4.3,0.121,0,1.5,1.5,1.5 178 | Kyle Korver,1,37,TOT,70,1334,19.1,2.9,6.9,0.416,2,5,0.397,0.9,1.9,0.467,0.559,0.9,1,0.822,0.1,2.2,2.3,1.2,0.4,0.2,0.8,1.5,8.6,11.2,0.582,0.72,0.151,0.7,12.4,6.6,8.9,0.9,0.7,10.3,18.5,1,1.3,2.3,0.082,0,-1.5,-1.5,0.2 179 | Norman Powell,1,25,TOR,60,1126,18.8,3.2,6.7,0.483,1.1,2.8,0.4,2.1,3.8,0.543,0.568,1,1.3,0.827,0.3,2.1,2.3,1.5,0.7,0.2,1.1,1.6,8.6,13.3,0.596,0.425,0.188,1.6,11.5,6.7,11.6,1.7,1,13.1,19,1,1.4,2.4,0.102,-0.4,-0.3,-0.7,0.4 180 | Rodions Kurucs,2,20,BRK,63,1294,20.5,3.2,7.1,0.45,0.9,2.9,0.315,2.3,4.2,0.543,0.514,1.1,1.5,0.783,0.9,3,3.9,0.8,0.7,0.4,1.2,2.3,8.5,11,0.545,0.41,0.205,4.6,15.4,10,6,1.5,1.5,13.6,18.4,0.1,1.5,1.6,0.059,-2.6,0.2,-2.4,-0.1 181 | Trey Lyles,3,23,DEN,64,1120,17.5,3.2,7.7,0.418,0.8,3.1,0.255,2.4,4.6,0.529,0.47,1.3,1.8,0.698,0.7,3.2,3.8,1.4,0.5,0.4,1.1,1.5,8.5,12.7,0.5,0.404,0.234,4.2,19.6,11.9,11.3,1.3,1.8,11.1,23.4,-0.2,1.4,1.2,0.05,-2.6,-0.7,-3.3,-0.4 182 | DeAndre' Bembry,1,24,ATL,82,1931,23.5,3.4,7.5,0.446,0.6,2.1,0.289,2.7,5.4,0.508,0.487,1.1,1.7,0.64,0.7,3.7,4.4,2.5,1.3,0.5,1.7,2.3,8.4,10.8,0.508,0.281,0.221,2.9,16.9,9.7,14.7,2.5,1.8,17.4,17.2,-0.9,1.7,0.9,0.022,-3.3,1.1,-2.2,-0.1 183 | Langston Galloway,1,27,DET,80,1745,21.8,2.9,7.3,0.388,1.7,4.8,0.355,1.2,2.6,0.449,0.503,1,1.2,0.844,0.6,1.5,2.1,1.1,0.5,0.1,0.3,1.7,8.4,10.7,0.534,0.647,0.164,3,7.9,5.4,7.3,1,0.4,3.7,16.1,2.1,1.3,3.4,0.094,0.2,-1.6,-1.3,0.3 184 | Noah Vonleh,3,23,NYK,68,1722,25.3,3,6.5,0.47,0.7,2,0.336,2.4,4.5,0.531,0.523,1.6,2.3,0.712,1.7,6.1,7.8,1.9,0.7,0.8,1.3,2.6,8.4,13.9,0.561,0.311,0.355,6.7,25.8,16,11.1,1.3,2.5,14.7,14.8,1.5,1.7,3.2,0.09,-1.6,1.6,0,0.9 185 | Mikal Bridges,2,22,PHO,82,2417,29.5,3,6.9,0.43,1.3,3.8,0.335,1.7,3,0.548,0.523,1.2,1.4,0.805,0.7,2.5,3.2,2.1,1.6,0.5,0.9,2.5,8.3,10.8,0.556,0.556,0.21,2.5,9.7,6,9.8,2.5,1.3,10.2,12.2,1.7,1.2,2.9,0.058,-0.5,0.3,-0.2,1.1 186 | Richaun Holmes,3,25,PHO,70,1184,16.9,3.2,5.2,0.608,0,0,0,3.2,5.2,0.608,0.608,1.8,2.5,0.731,1.6,3.1,4.7,0.9,0.6,1.1,0.7,2.8,8.2,20.7,0.647,0,0.479,10.6,20.5,15.5,7.9,1.7,5.6,10.5,17.9,3.1,1.1,4.3,0.173,-0.1,1.5,1.4,1 187 | Darius Miller,2,28,NOP,69,1757,25.5,2.7,7,0.39,1.9,5.3,0.365,0.8,1.7,0.467,0.528,0.8,1,0.789,0.2,1.7,1.9,2.1,0.6,0.3,0.9,2.4,8.2,8.4,0.55,0.752,0.147,0.8,6.6,3.8,10.4,1.1,1.1,10.3,13.4,1.1,0.6,1.6,0.045,-0.1,-1.5,-1.7,0.1 188 | Frank Jackson,1,20,NOP,61,1169,19.2,3.2,7.3,0.434,0.9,2.8,0.314,2.3,4.6,0.507,0.493,0.9,1.2,0.74,0.4,1.8,2.2,1.1,0.4,0,0.8,1.5,8.1,9.4,0.517,0.378,0.163,2.2,9.5,5.9,8,1,0.1,9.1,18.5,0.1,0.4,0.4,0.018,-2.2,-2.8,-5,-0.9 189 | Austin Rivers,1,26,TOT,76,2028,26.7,3.1,7.5,0.406,1.4,4.3,0.318,1.7,3.2,0.522,0.497,0.7,1.3,0.526,0.3,1.8,2.1,2.2,0.6,0.3,0.9,2.7,8.1,7.7,0.503,0.572,0.166,1.3,7.5,4.4,11.5,1.1,1,10,14.5,0.4,0.8,1.2,0.028,-2,-1.5,-3.5,-0.7 190 | Davis Bertans,3,26,SAS,76,1632,21.5,2.7,6,0.45,1.9,4.4,0.429,0.8,1.5,0.513,0.61,0.7,0.8,0.883,0.3,3.2,3.5,1.3,0.5,0.4,0.6,1.8,8,13,0.632,0.746,0.132,1.6,16,8.8,8.2,1,1.7,8.2,14.1,2.6,1.5,4,0.118,1.6,-0.4,1.2,1.3 191 | Jamal Crawford,1,38,PHO,64,1211,18.9,2.7,6.8,0.397,1,3.2,0.332,1.7,3.7,0.453,0.474,1.5,1.7,0.845,0.1,1.2,1.3,3.6,0.5,0.2,1.5,1.2,7.9,11.7,0.522,0.461,0.251,0.7,7.2,3.9,27.7,1.3,0.8,16.9,20.8,0.1,0,0.2,0.006,-2,-4.1,-6,-1.2 192 | Seth Curry,1,28,POR,74,1399,18.9,2.9,6.3,0.456,1.5,3.4,0.45,1.3,2.9,0.463,0.577,0.6,0.7,0.846,0.4,1.3,1.6,0.9,0.5,0.2,0.8,1.3,7.9,11.4,0.595,0.54,0.112,2.1,6.9,4.6,6.5,1.2,0.7,11.1,16.6,1.5,0.9,2.4,0.082,0.5,-1.8,-1.3,0.2 193 | Josh Hart,1,23,LAL,67,1715,25.6,2.8,6.9,0.407,1.4,4.1,0.336,1.4,2.8,0.511,0.506,0.8,1.2,0.688,0.5,3.2,3.7,1.4,1,0.6,0.9,2.2,7.8,9.3,0.526,0.591,0.172,2.2,12.6,7.5,7,1.7,1.9,10.4,13.5,0.2,1.9,2.1,0.059,-1.8,1.1,-0.7,0.6 194 | James Johnson,3,31,MIA,55,1164,21.2,3,6.9,0.433,0.9,2.7,0.336,2.1,4.2,0.496,0.499,0.9,1.3,0.714,0.4,2.8,3.2,2.5,0.6,0.5,1.3,2.1,7.8,10.9,0.522,0.393,0.185,2,14.1,8,17,1.5,2.1,15.3,17.8,0,1.5,1.5,0.062,-2.5,0.9,-1.6,0.1 195 | Mason Plumlee,3,28,DEN,82,1731,21.1,3.2,5.4,0.593,0,0.1,0.2,3.2,5.3,0.602,0.595,1.4,2.4,0.561,2,4.4,6.4,3,0.8,0.9,1.5,3.1,7.8,17.8,0.602,0.023,0.448,10.3,22.5,16.4,19.5,1.9,3.9,19.2,16.2,2.9,2.9,5.8,0.16,-0.1,3.9,3.8,2.6 196 | Garrett Temple,1,32,TOT,75,2040,27.2,2.8,6.6,0.422,1.2,3.5,0.341,1.6,3.1,0.515,0.513,1.1,1.4,0.748,0.4,2.5,2.9,1.4,1,0.4,0.9,2.7,7.8,8.5,0.543,0.535,0.217,1.5,10.2,5.8,7.4,1.8,1.4,11.5,13.2,0.3,2,2.2,0.052,-1.7,0.6,-1.2,0.4 197 | Ante Zizic,3,22,CLE,59,1082,18.3,3.1,5.6,0.553,0,0,0,3.1,5.6,0.553,0.553,1.6,2.2,0.705,1.8,3.6,5.4,0.9,0.2,0.4,1,1.9,7.8,16.2,0.59,0,0.399,10.6,22.8,16.4,7.7,0.6,1.8,13.6,18.2,1.7,0.3,2,0.087,-1.7,-1.4,-3.1,-0.3 198 | Maurice Harkless,2,25,POR,60,1415,23.6,3.2,6.5,0.487,0.6,2,0.275,2.6,4.5,0.582,0.53,0.8,1.2,0.671,1.3,3.2,4.5,1.2,1.1,0.9,0.8,2.7,7.7,13.2,0.547,0.309,0.188,5.9,14.1,10.1,7.1,2.3,3,9.7,13.9,1.5,1.9,3.4,0.114,-0.1,2.3,2.2,1.5 199 | Josh Okogie,1,20,MIN,74,1757,23.7,2.6,6.9,0.386,0.8,2.9,0.279,1.8,4,0.464,0.445,1.6,2.2,0.728,0.6,2.4,2.9,1.2,1.2,0.4,0.9,2.2,7.7,9.4,0.492,0.423,0.319,2.5,10.9,6.6,6.9,2.4,1.6,9.8,15.4,-0.1,1.4,1.2,0.034,-2,0.4,-1.7,0.1 200 | Patrick Beverley,1,30,LAC,78,2137,27.4,2.5,6.1,0.407,1.4,3.6,0.397,1.1,2.5,0.421,0.524,1.2,1.6,0.78,1,4,5,3.8,0.9,0.6,1.1,3.4,7.6,11.8,0.561,0.591,0.258,3.9,15,9.6,18.4,1.5,1.6,13.8,12.2,2.8,2,4.8,0.108,1.2,1.2,2.4,2.3 201 | George Hill,1,32,TOT,60,1302,21.7,2.8,6.3,0.452,0.8,2.6,0.314,2,3.7,0.547,0.516,1.2,1.4,0.824,0.7,1.8,2.5,2.3,0.9,0.1,0.9,1.7,7.6,12.1,0.554,0.407,0.226,3.2,8.3,5.9,14,1.9,0.5,11,15.1,1.5,1.3,2.8,0.103,-0.6,-0.4,-1,0.3 202 | Jake Layman,2,24,POR,71,1327,18.7,3,6,0.509,0.8,2.5,0.326,2.2,3.4,0.646,0.579,0.7,1,0.704,0.8,2.3,3.1,0.7,0.4,0.4,0.6,1.6,7.6,13.5,0.594,0.427,0.167,4.6,12.6,8.7,5.6,1.1,1.8,9.2,15.9,1.9,1.2,3.1,0.111,0.4,-0.6,-0.3,0.6 203 | Rodney McGruder,1,27,MIA,66,1550,23.5,2.8,7,0.403,1.2,3.4,0.351,1.6,3.6,0.453,0.489,0.8,1.1,0.722,0.9,2.7,3.6,1.7,0.5,0.2,1,1.7,7.6,9.4,0.51,0.488,0.156,4.1,12.2,8.2,10.3,1.1,0.7,11.5,15.4,0.4,1.6,1.9,0.059,-1.9,-0.1,-2,0 204 | Miles Bridges,2,20,CHO,80,1696,21.2,3,6.4,0.464,0.8,2.5,0.325,2.2,3.9,0.553,0.527,0.7,1,0.753,0.8,3.2,4,1.2,0.7,0.6,0.6,1.4,7.5,13.1,0.548,0.391,0.151,4.2,16.6,10.3,8.1,1.6,2.5,8.4,15.1,1.4,1.5,2.9,0.083,-1.2,0.5,-0.6,0.6 205 | Dorian Finney-Smith,2,25,DAL,81,1985,24.5,2.8,6.5,0.432,1,3.1,0.311,1.8,3.4,0.544,0.507,0.9,1.3,0.709,1.7,3.1,4.8,1.2,0.9,0.4,0.9,2.3,7.5,11,0.53,0.481,0.195,7.5,13.4,10.5,6.9,1.7,1.5,11.4,14,1.2,2,3.3,0.079,-1,1.1,0.2,1.1 206 | Shelvin Mack,1,28,TOT,57,1246,21.9,2.9,7.1,0.404,0.8,2.3,0.354,2.1,4.8,0.429,0.462,1,1.5,0.69,0.3,1.5,1.8,3.2,0.8,0.1,1.2,1.5,7.5,10.4,0.489,0.323,0.208,1.6,7.9,4.7,22.6,1.9,0.3,13,18.1,-0.2,1.1,0.9,0.034,-2.6,-1.5,-4.1,-0.7 207 | Iman Shumpert,1,28,TOT,62,1481,23.9,2.7,7.2,0.374,1.5,4.4,0.348,1.2,2.8,0.416,0.481,0.6,0.7,0.8,0.4,2.5,3,1.8,1,0.4,0.8,2,7.5,9.1,0.499,0.612,0.101,1.9,11.4,6.5,9.9,1.9,1.4,9.7,14.5,0.1,1.2,1.4,0.045,-1.5,0.1,-1.4,0.2 208 | Vince Carter,2,42,ATL,76,1330,17.5,2.6,6.2,0.419,1.6,4.2,0.389,1,2,0.48,0.55,0.6,0.9,0.712,0.4,2.1,2.6,1.1,0.6,0.4,0.6,1.9,7.4,11.8,0.565,0.675,0.141,2.4,13.2,7.7,9.3,1.5,1.8,8.8,16.7,1.2,0.7,1.9,0.07,-0.2,-1.4,-1.6,0.1 209 | Draymond Green,3,28,GSW,66,2065,31.3,2.8,6.4,0.445,0.7,2.5,0.285,2.1,3.9,0.549,0.501,1,1.4,0.692,0.9,6.4,7.3,6.9,1.4,1.1,2.6,3,7.4,12.9,0.526,0.391,0.216,3.2,20.8,12.4,26.8,2.2,2.8,26.8,13.1,1.1,3.2,4.3,0.1,-1.4,3.4,2,2.1 210 | Doug McDermott,2,27,IND,77,1340,17.4,2.7,5.5,0.491,1.1,2.7,0.408,1.6,2.8,0.569,0.59,0.9,1,0.835,0.2,1.2,1.4,0.9,0.2,0.1,0.5,1.4,7.3,11.6,0.617,0.488,0.187,1.4,7.5,4.5,7.1,0.7,0.5,8.4,16.3,1.8,1.1,2.9,0.103,0,-2.1,-2.1,0 211 | Mitchell Robinson,3,20,NYK,66,1360,20.6,3.1,4.4,0.694,0,0,0,3.1,4.4,0.694,0.694,1.2,2,0.6,2.7,3.7,6.4,0.6,0.8,2.4,0.5,3.3,7.3,22,0.692,0,0.464,13.3,19.4,16.3,4.2,1.8,10,9.1,12.1,4,2.2,6.1,0.217,0.5,5.2,5.7,2.7 212 | P.J. Tucker,3,33,HOU,82,2802,34.2,2.5,6.4,0.396,1.8,4.7,0.377,0.7,1.7,0.449,0.535,0.5,0.7,0.695,1.5,4.4,5.8,1.2,1.6,0.5,0.8,3.1,7.3,9.2,0.547,0.74,0.113,4.7,14.4,9.5,4.6,2.3,1.2,10.3,9.5,2,3,5,0.086,-0.5,1.8,1.3,2.3 213 | Justin Jackson,2,23,TOT,81,1614,19.9,2.7,6,0.447,1.1,3,0.355,1.6,3,0.542,0.537,0.8,1,0.785,0.5,2.1,2.6,1.2,0.4,0.2,0.4,1.2,7.2,11.3,0.561,0.505,0.163,2.8,11,6.9,8.1,0.9,0.7,5.3,14.3,2,0.9,2.9,0.086,-0.4,-1.2,-1.6,0.2 214 | Lance Stephenson,1,28,LAL,68,1123,16.5,2.7,6.4,0.426,1.1,2.9,0.371,1.6,3.5,0.472,0.51,0.7,1.1,0.685,0.5,2.7,3.2,2.1,0.6,0.1,1.3,1.6,7.2,11.8,0.529,0.456,0.169,3,16.5,9.9,17.3,1.7,0.5,15.6,20.3,-0.1,1.2,1.1,0.049,-1.7,-0.4,-2.1,0 215 | OG Anunoby,2,21,TOR,67,1352,20.2,2.7,6,0.453,1,3,0.332,1.7,3,0.574,0.536,0.5,0.9,0.581,0.9,2.1,2.9,0.7,0.7,0.3,0.8,2.1,7,9.8,0.544,0.5,0.153,4.8,10.8,7.9,4.7,1.6,1.3,11.3,15.5,0.3,1.7,2,0.07,-1.3,0.1,-1.2,0.3 216 | Derrick Jones,2,21,MIA,60,1153,19.2,2.7,5.4,0.494,0.5,1.5,0.308,2.2,3.9,0.567,0.537,1.2,2,0.607,1.6,2.4,4,0.6,0.8,0.7,0.7,2.1,7,14,0.559,0.281,0.377,8.8,13.3,11.1,4.7,1.9,3.3,10.2,15.6,1.2,1.7,2.9,0.121,-1.3,1.5,0.2,0.6 217 | Mike Muscala,3,27,TOT,64,1306,20.4,2.3,5.6,0.402,1.4,4,0.348,0.9,1.6,0.533,0.525,1.1,1.3,0.824,0.9,2.9,3.8,1.2,0.3,0.6,0.8,2,7,10.8,0.564,0.709,0.235,4.7,14.7,9.8,7.7,0.8,2.3,10.8,14.3,1.2,1.2,2.5,0.091,-0.3,-0.3,-0.7,0.4 218 | Pat Connaughton,1,26,MIL,61,1261,20.7,2.7,5.7,0.466,1.1,3.3,0.33,1.6,2.5,0.647,0.56,0.5,0.7,0.725,1,3.2,4.2,2,0.5,0.4,0.5,1.3,6.9,13.6,0.573,0.571,0.114,5.2,15,10.4,12.6,1.2,1.7,8.2,13.3,2,1.9,3.9,0.149,0.4,1.2,1.6,1.2 219 | Quinn Cook,1,25,GSW,74,1059,14.3,2.8,5.9,0.465,1.1,2.7,0.405,1.7,3.2,0.515,0.557,0.3,0.4,0.769,0.3,1.8,2.1,1.6,0.3,0,0.7,1.2,6.9,13.1,0.565,0.456,0.059,2.3,13,7.9,15.2,0.9,0.2,10,20.2,1,0.8,1.8,0.082,-0.2,-2.7,-2.9,-0.2 220 | Terrance Ferguson,1,20,OKC,74,1931,26.1,2.5,5.8,0.429,1.4,3.9,0.366,1.1,1.9,0.56,0.552,0.5,0.7,0.725,0.4,1.5,1.9,1,0.5,0.2,0.6,3.1,6.9,6.4,0.566,0.673,0.118,1.7,6,3.8,4.8,1,0.7,9.4,10.6,1.2,1.6,2.8,0.07,-1.5,-0.5,-1.9,0 221 | Stanley Johnson,2,22,TOT,66,1208,18.3,2.6,6.7,0.389,0.9,3.3,0.288,1.7,3.4,0.484,0.459,0.8,1,0.781,0.5,2.8,3.3,1.3,0.9,0.2,1.2,1.7,6.9,9.6,0.485,0.489,0.145,3,16.9,9.7,10.6,2.4,1,14.7,19.4,-1.1,1.6,0.5,0.021,-3.2,0.6,-2.6,-0.2 222 | Tyus Jones,1,22,MIN,68,1560,22.9,2.7,6.6,0.415,0.6,1.9,0.317,2.1,4.7,0.453,0.46,0.9,1,0.841,0.3,1.6,2,4.8,1.2,0.1,0.7,1.1,6.9,13.7,0.491,0.283,0.155,1.6,7.7,4.6,28.3,2.5,0.3,9,14.1,2.1,0.9,3,0.091,-0.3,-1.5,-1.8,0.1 223 | Wayne Selden,1,24,TOT,75,1439,19.2,2.6,6.4,0.406,0.7,2.3,0.316,1.9,4.1,0.456,0.463,0.9,1.2,0.728,0.5,1.9,2.4,1.5,0.4,0.2,1.1,1.7,6.9,8.3,0.491,0.36,0.19,2.8,11,6.9,11.3,1.1,0.8,13.1,18.4,-1,0.8,-0.3,-0.009,-3.5,-1.6,-5.1,-1.1 224 | Ersan Ilyasova,3,31,MIL,67,1231,18.4,2.5,5.7,0.438,0.9,2.4,0.363,1.6,3.3,0.493,0.514,0.9,1.1,0.824,1.4,3.1,4.5,0.8,0.5,0.3,0.7,2.6,6.8,11.6,0.548,0.42,0.194,8.2,16.2,12.5,5.5,1.2,1.4,10.4,15.7,1.2,1.9,3,0.119,-1.5,0.1,-1.3,0.2 225 | Maxi Kleber,3,27,DAL,71,1502,21.2,2.5,5.4,0.453,1.1,3.1,0.353,1.4,2.4,0.583,0.553,0.8,1,0.784,1.3,3.4,4.6,1,0.5,1.1,0.8,2,6.8,13.1,0.579,0.565,0.192,6.5,16.9,11.7,6.8,1.2,4.4,11.4,13.5,1.6,1.8,3.5,0.111,-0.8,2.3,1.5,1.3 226 | Evan Turner,1,30,POR,73,1605,22,2.8,6.1,0.46,0.2,0.7,0.212,2.6,5.4,0.494,0.473,1,1.5,0.708,0.5,4,4.5,3.9,0.5,0.2,1.6,1.5,6.8,11.6,0.504,0.117,0.239,2.5,18.9,10.9,23.6,1,0.9,18.9,15.9,0.5,1.5,2,0.06,-2.5,0.7,-1.8,0.1 227 | Ryan Arcidiacono,1,24,CHI,81,1961,24.2,2.3,5.2,0.447,1,2.7,0.373,1.3,2.5,0.527,0.544,1.1,1.3,0.873,0.3,2.4,2.7,3.3,0.8,0,0.8,2.1,6.7,11.6,0.588,0.519,0.244,1.5,10.8,6.1,18.9,1.6,0.2,12,11.7,2.8,0.9,3.7,0.09,-0.1,-1,-1,0.5 228 | James Ennis,2,28,TOT,58,1230,21.2,2.4,5.1,0.469,0.9,2.7,0.353,1.4,2.4,0.601,0.563,1,1.4,0.716,1,2.1,3.1,0.7,0.7,0.4,0.6,2.6,6.7,11,0.59,0.531,0.276,5.3,10.9,8.1,4.7,1.6,1.6,9.3,12.7,1.6,1,2.6,0.103,-0.5,-0.2,-0.7,0.4 229 | Michael Kidd-Gilchrist,3,25,CHO,64,1179,18.4,2.5,5.2,0.476,0.3,0.7,0.34,2.2,4.5,0.498,0.5,1.5,1.9,0.772,1.4,2.5,3.8,1,0.5,0.6,0.7,2.4,6.7,13.3,0.553,0.142,0.37,7.9,14.8,11.3,7.4,1.3,2.9,10,15.7,1.5,1,2.5,0.1,-1.7,0.4,-1.3,0.2 230 | Zach Collins,3,21,POR,77,1356,17.6,2.5,5.2,0.473,0.5,1.6,0.331,1.9,3.6,0.534,0.523,1.2,1.6,0.746,1.4,2.8,4.2,0.9,0.3,0.9,1,2.3,6.6,13.5,0.562,0.303,0.315,8.8,16.5,12.7,7.1,0.9,3.9,14.5,16.6,1.4,1.5,2.9,0.104,-0.9,1,0.1,0.7 231 | Shaquille Harrison,1,25,CHI,73,1430,19.6,2.5,5.8,0.432,0.3,1.2,0.27,2.2,4.6,0.475,0.46,1.1,1.7,0.667,0.5,2.6,3,1.9,1.2,0.4,0.8,1.7,6.5,12.4,0.494,0.209,0.289,2.5,14.5,8.4,14.1,3,1.8,11.1,16.5,-0.1,1.6,1.4,0.048,-2.7,1.4,-1.3,0.2 232 | Cory Joseph,1,27,IND,82,2063,25.2,2.8,6.7,0.412,0.7,2.1,0.322,2.1,4.6,0.454,0.463,0.4,0.5,0.698,0.5,2.9,3.4,3.9,1.1,0.3,1,1.6,6.5,11,0.474,0.312,0.078,2.1,12.6,7.5,20.7,2.2,0.9,12.4,13.7,0.5,2.9,3.5,0.081,-2,1.4,-0.5,0.8 233 | Jonathon Simmons,2,29,TOT,56,1064,19,2.4,6.3,0.38,0.5,1.9,0.269,1.9,4.4,0.427,0.42,1.3,1.7,0.742,0.5,1.8,2.3,2.3,0.5,0.3,1.2,1.6,6.5,8.5,0.466,0.297,0.277,2.7,10,6.3,16.7,1.3,1.2,14.8,18.7,-0.8,1.1,0.3,0.013,-4.1,-0.6,-4.8,-0.7 234 | Sterling Brown,1,23,MIL,58,1034,17.8,2.5,5.4,0.465,0.9,2.5,0.361,1.6,2.8,0.558,0.55,0.5,0.7,0.69,0.5,2.7,3.2,1.4,0.4,0.1,0.8,1.5,6.4,10.9,0.563,0.471,0.135,3,14.4,9,10.7,1.1,0.7,12.2,15.2,0.7,1.4,2.1,0.098,-1.6,0,-1.6,0.1 235 | Gorgui Dieng,3,29,MIN,76,1031,13.6,2.5,5,0.501,0.3,0.7,0.339,2.2,4.2,0.53,0.527,1.2,1.4,0.83,1.1,3,4.1,0.9,0.6,0.5,0.8,1.8,6.4,18.1,0.572,0.149,0.281,8.3,24.1,16.1,10.3,2.2,3.4,11.9,19.6,1.5,1.3,2.8,0.132,-0.9,1.4,0.5,0.7 236 | T.J. McConnell,1,26,PHI,76,1470,19.3,2.9,5.5,0.525,0.2,0.6,0.333,2.7,5,0.546,0.542,0.4,0.5,0.784,0.4,1.9,2.3,3.4,1,0.2,1.2,1.4,6.4,13.4,0.555,0.1,0.088,2.1,10.2,6.3,24.7,2.5,0.9,17.3,15,1.2,1.7,2.9,0.094,-1.7,0,-1.6,0.1 237 | Devin Harris,1,35,DAL,68,1071,15.8,1.9,5.1,0.38,0.9,2.9,0.31,1,2.2,0.476,0.47,1.5,2,0.761,0.2,1.5,1.6,1.8,0.5,0.2,0.8,2,6.3,10.7,0.527,0.576,0.386,1.2,9.9,5.6,16.7,1.6,1.3,12.1,18.5,0.6,0.9,1.5,0.068,-1.3,-0.9,-2.2,-0.1 238 | Jonas Jerebko,3,31,GSW,73,1218,16.7,2.2,4.9,0.459,0.9,2.6,0.367,1.3,2.3,0.563,0.556,0.9,1.1,0.8,1,3,3.9,1.3,0.4,0.2,0.6,1.9,6.3,13.5,0.588,0.53,0.225,6.6,18.1,12.6,10.1,1.1,1.2,9.9,15.2,2.1,1.2,3.3,0.131,0.6,-0.6,0,0.6 239 | Kevon Looney,3,22,GSW,80,1481,18.5,2.7,4.3,0.625,0,0.1,0.1,2.7,4.2,0.641,0.627,0.8,1.3,0.619,2.4,2.8,5.2,1.5,0.6,0.7,0.6,2.6,6.3,17.3,0.636,0.029,0.303,14.6,15.4,15,10.9,1.5,3,11.5,12.8,4.2,1.8,6,0.194,1.9,1.8,3.7,2.1 240 | Wilson Chandler,2,31,TOT,51,1177,23.1,2.2,5.4,0.418,1.2,3.1,0.373,1.1,2.3,0.478,0.526,0.4,0.5,0.72,0.9,3.3,4.2,1.6,0.5,0.4,0.9,2.4,6,8.5,0.537,0.579,0.092,4.4,14.6,9.7,9.1,1,1.4,13.9,11.8,0.5,1,1.5,0.062,-1.3,0.3,-1,0.3 241 | Tony Snell,2,27,MIL,74,1304,17.6,2.2,4.9,0.452,1.1,2.8,0.397,1.1,2.1,0.522,0.564,0.5,0.6,0.881,0.4,1.7,2.1,0.9,0.4,0.2,0.3,1.2,6,10.7,0.585,0.565,0.116,2.4,9.4,6.1,6.7,0.9,1.2,5.7,12.9,1.6,1.6,3.2,0.117,-0.7,-0.4,-1,0.3 242 | Yogi Ferrell,1,25,SAC,71,1067,15,2.2,5,0.435,0.8,2.1,0.362,1.4,2.9,0.488,0.511,0.8,0.9,0.896,0.2,1.4,1.5,1.9,0.5,0.1,0.6,0.9,5.9,12.7,0.55,0.423,0.19,1.2,9.5,5.3,17,1.6,0.3,9.5,16.3,1.3,0.6,1.9,0.087,-0.5,-1.8,-2.3,-0.1 243 | Nik Stauskas,1,25,TOT,68,1015,14.9,2,5,0.402,1,2.8,0.372,1,2.2,0.44,0.506,0.8,0.9,0.891,0.3,1.6,1.9,1.2,0.3,0.1,0.8,0.7,5.9,10.9,0.545,0.556,0.189,1.9,11.7,6.8,11.1,1,0.6,12.2,17.6,0.6,0.5,1.1,0.052,-0.9,-2.2,-3.2,-0.3 244 | Ed Davis,3,29,BRK,81,1446,17.9,2.3,3.7,0.616,0,0,0,2.3,3.7,0.62,0.616,1.2,2,0.617,2.7,5.9,8.6,0.8,0.4,0.4,0.8,2.8,5.8,17.3,0.632,0.007,0.536,15.8,34.6,25.2,6,1.2,1.8,14.6,12.7,3.3,2.5,5.7,0.191,-1.4,1.7,0.4,0.9 245 | Juan Hernangomez,3,23,DEN,70,1358,19.4,2,4.5,0.439,0.9,2.6,0.365,1,1.9,0.541,0.545,0.9,1.2,0.767,0.9,2.9,3.8,0.8,0.4,0.3,0.5,1.3,5.8,11,0.58,0.576,0.274,5.1,16.1,10.6,5.3,1,1.6,9.5,12.2,1.6,1.4,3,0.105,-0.9,0,-0.9,0.4 246 | Mike Scott,3,30,TOT,79,1395,17.7,2.1,5.3,0.4,1.3,3.2,0.401,0.8,2.1,0.399,0.52,0.3,0.4,0.667,0.5,2.9,3.5,0.8,0.3,0.2,0.6,2,5.8,8.6,0.528,0.6,0.079,3.4,17.2,10.5,6.4,0.9,0.7,9.2,14.4,0.4,1.2,1.6,0.053,-1.5,-1.2,-2.7,-0.2 247 | Torrey Craig,2,28,DEN,75,1503,20,2.1,4.8,0.442,0.8,2.5,0.324,1.3,2.3,0.569,0.526,0.7,0.9,0.7,1.2,2.3,3.5,1,0.5,0.6,0.6,2.3,5.7,10.4,0.547,0.519,0.193,6.4,12.6,9.5,6.3,1.2,2.7,10.1,12.4,1.4,1.7,3,0.096,-1,0.9,-0.1,0.7 248 | Andre Iguodala,2,35,GSW,68,1578,23.2,2.2,4.4,0.5,0.7,2.1,0.333,1.5,2.3,0.652,0.579,0.6,1,0.582,0.7,3,3.7,3.2,0.9,0.8,0.8,1.4,5.7,13.1,0.587,0.477,0.222,3.4,13.2,8.5,16.8,1.8,2.7,13.6,10.4,2.4,1.8,4.2,0.129,0.2,1.7,1.9,1.6 249 | Jakob Poeltl,3,23,SAS,77,1273,16.5,2.4,3.8,0.645,0,0,0,2.4,3.8,0.645,0.645,0.6,1.2,0.533,2.3,3,5.3,1.2,0.4,0.9,0.6,1.6,5.5,19.4,0.64,0,0.317,15.4,19.7,17.6,10,1.1,4.5,12.7,13.1,3.5,1.6,5.1,0.193,1.5,2.7,4.2,2 250 | Tim Frazier,1,28,TOT,59,1120,19,2,4.4,0.444,0.6,1.7,0.366,1.3,2.7,0.494,0.515,0.7,0.9,0.759,0.7,2.2,2.8,4.2,0.5,0.1,1.3,1.9,5.3,11.7,0.544,0.387,0.207,3.9,11.5,7.7,27.6,1.2,0.4,21.1,13.3,1.3,0.7,2,0.084,-1,-1.3,-2.3,-0.1 251 | Royce O'Neale,2,25,UTA,82,1671,20.4,2,4.2,0.475,0.8,2.1,0.386,1.2,2,0.569,0.574,0.4,0.5,0.762,0.3,3.2,3.5,1.5,0.7,0.3,0.9,2.1,5.2,9,0.589,0.513,0.122,1.5,16.7,9.2,10,1.5,1.1,16.2,11,0.7,2.5,3.3,0.094,-2,2.1,0.1,0.9 252 | Wesley Iwundu,2,24,ORL,68,1233,18.1,1.7,4,0.412,0.4,1.2,0.367,1.2,2.9,0.431,0.465,1.2,1.5,0.816,0.5,2.2,2.7,1.1,0.4,0.3,0.6,1.8,5,8.7,0.531,0.288,0.376,3.2,13,8,7.9,1.1,1.5,12.1,12.8,0.5,1.4,1.9,0.073,-3.4,0.7,-2.7,-0.2 253 | Anthony Tolliver,3,33,MIN,65,1079,16.6,1.5,4,0.382,1.2,3.3,0.377,0.3,0.7,0.409,0.539,0.7,0.9,0.783,0.2,2.5,2.7,0.7,0.3,0.3,0.6,1.4,5,8.6,0.571,0.83,0.232,1.5,16.2,8.8,5.5,0.8,1.7,11.2,12.5,0.6,0.5,1.2,0.052,-1.2,-1,-2.2,-0.1 254 | Jared Dudley,3,33,BRK,59,1220,20.7,1.7,4.1,0.423,0.9,2.6,0.351,0.8,1.5,0.545,0.533,0.5,0.8,0.696,0.6,2.1,2.6,1.4,0.6,0.3,0.7,2.2,4.9,7.8,0.554,0.632,0.192,2.9,10.4,6.7,9.2,1.4,1,14.2,10.4,0.6,1.2,1.8,0.07,-1.7,1,-0.7,0.4 255 | Nerlens Noel,3,24,OKC,77,1055,13.7,2.1,3.6,0.587,0,0,0,2.1,3.6,0.587,0.587,0.7,1,0.684,1.6,2.6,4.2,0.6,0.9,1.2,0.6,2.2,4.9,19.3,0.608,0,0.286,12.1,20,15.9,5.9,2.9,7.7,13.4,13.8,1.9,2.5,4.3,0.198,-1.6,5.5,3.9,1.6 256 | Alfonzo McKinnie,2,26,GSW,72,1003,13.9,1.9,3.8,0.487,0.6,1.6,0.356,1.3,2.2,0.586,0.564,0.4,0.7,0.563,1.1,2.3,3.4,0.4,0.3,0.2,0.4,1.9,4.7,11.2,0.569,0.429,0.175,9,16.9,13.1,4,0.9,1.3,9.2,13.9,1.2,0.9,2.1,0.1,-0.9,-1.5,-2.5,-0.1 257 | Bruce Brown,1,22,DET,74,1449,19.6,1.7,4.2,0.398,0.3,1.3,0.258,1.4,3,0.457,0.436,0.6,0.8,0.75,0.6,1.9,2.5,1.2,0.5,0.5,0.6,2.4,4.3,6.9,0.469,0.296,0.191,3.5,10.7,7,8.8,1.4,2.1,11.9,11.5,-0.1,1.6,1.5,0.048,-3.7,1.7,-2,0 258 | -------------------------------------------------------------------------------- /python-master-positional-clustering-NO-OUTPUTS.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "%matplotlib inline\n", 10 | "\n", 11 | "import matplotlib.pyplot as plt\n", 12 | "import numpy as np\n", 13 | "import pandas as pd\n", 14 | "from sklearn.cluster import KMeans\n", 15 | "from sklearn.decomposition import PCA\n", 16 | "from sklearn.preprocessing import StandardScaler\n", 17 | "from sklearn.metrics import silhouette_score" 18 | ] 19 | }, 20 | { 21 | "cell_type": "markdown", 22 | "metadata": {}, 23 | "source": [ 24 | "# A simple example of clustering" 25 | ] 26 | }, 27 | { 28 | "cell_type": "code", 29 | "execution_count": null, 30 | "metadata": {}, 31 | "outputs": [], 32 | "source": [ 33 | "df_example = pd.read_csv('clustering-example.csv')" 34 | ] 35 | }, 36 | { 37 | "cell_type": "code", 38 | "execution_count": null, 39 | "metadata": {}, 40 | "outputs": [], 41 | "source": [ 42 | "stl_leaders = df_example[0:5]\n", 43 | "blk_leaders = df_example[5:]" 44 | ] 45 | }, 46 | { 47 | "cell_type": "code", 48 | "execution_count": null, 49 | "metadata": {}, 50 | "outputs": [], 51 | "source": [ 52 | "plt.style.use('fivethirtyeight')\n", 53 | "\n", 54 | "stl_blk, ax = plt.subplots()\n", 55 | "\n", 56 | "ax.scatter(df_example['STL'], df_example['BLK'])\n", 57 | "\n", 58 | "ax.set_xlabel('STL/G')\n", 59 | "ax.set_ylabel('BLK/G')\n", 60 | "\n", 61 | "stl_blk.suptitle(\"Top 5 players in steals and blocks\", weight = 'bold', size = 18)\n", 62 | "\n", 63 | "stl_blk.text(x = -0.02, y = -0.08,\n", 64 | " s = '____________________________________________________________',\n", 65 | " fontsize = 14, color = 'grey', horizontalalignment='left')\n", 66 | "\n", 67 | "stl_blk.text(x = -0.02, y = -.14,\n", 68 | " s = 'https://dribbleanalytics.blog ',\n", 69 | " fontsize = 14, fontname = 'Rockwell', color = 'grey', horizontalalignment='left')\n", 70 | "\n", 71 | "stl_blk.savefig('stl-blk.png', dpi = 400, bbox_inches = 'tight')" 72 | ] 73 | }, 74 | { 75 | "cell_type": "code", 76 | "execution_count": null, 77 | "metadata": {}, 78 | "outputs": [], 79 | "source": [ 80 | "plt.style.use('fivethirtyeight')\n", 81 | "\n", 82 | "stl_blk_separated, ax = plt.subplots()\n", 83 | "\n", 84 | "ax.scatter(stl_leaders['STL'], stl_leaders['BLK'], label = 'STL leaders')\n", 85 | "ax.scatter(blk_leaders['STL'], blk_leaders['BLK'], label = 'BLK leaders')\n", 86 | "\n", 87 | "ax.legend(loc='best', prop={'size': 12, \"family\": \"Rockwell\"})\n", 88 | "\n", 89 | "ax.set_xlabel('STL/G')\n", 90 | "ax.set_ylabel('BLK/G')\n", 91 | "\n", 92 | "stl_blk_separated.suptitle(\"Top 5 players in steals and blocks\", weight = 'bold', size = 18)\n", 93 | "\n", 94 | "stl_blk_separated.text(x = -0.02, y = -0.08,\n", 95 | " s = '____________________________________________________________',\n", 96 | " fontsize = 14, color = 'grey', horizontalalignment='left')\n", 97 | "\n", 98 | "stl_blk_separated.text(x = -0.02, y = -.14,\n", 99 | " s = 'https://dribbleanalytics.blog ',\n", 100 | " fontsize = 14, fontname = 'Rockwell', color = 'grey', horizontalalignment='left')\n", 101 | "\n", 102 | "stl_blk_separated.savefig('stl-blk-separated.png', dpi = 400, bbox_inches = 'tight')" 103 | ] 104 | }, 105 | { 106 | "cell_type": "code", 107 | "execution_count": null, 108 | "metadata": {}, 109 | "outputs": [], 110 | "source": [ 111 | "kmeans = KMeans(n_clusters = 2, random_state = 0)\n", 112 | "\n", 113 | "x = np.column_stack((df_example['STL'], df_example['BLK']))\n", 114 | "\n", 115 | "kmeans.fit(x)\n", 116 | "\n", 117 | "y_kmeans = kmeans.predict(x)" 118 | ] 119 | }, 120 | { 121 | "cell_type": "code", 122 | "execution_count": null, 123 | "metadata": {}, 124 | "outputs": [], 125 | "source": [ 126 | "plt.style.use('fivethirtyeight')\n", 127 | "\n", 128 | "stl_blk_clustered, ax = plt.subplots()\n", 129 | "\n", 130 | "cluster_1 = []\n", 131 | "cluster_2 = []\n", 132 | "\n", 133 | "for i in range(len(y_kmeans)):\n", 134 | " if(y_kmeans[i] == 0):\n", 135 | " cluster_1.append(x[i])\n", 136 | " elif(y_kmeans[i] == 1):\n", 137 | " cluster_2.append(x[i])\n", 138 | " \n", 139 | "cluster_1 = np.vstack(cluster_1)\n", 140 | "cluster_2 = np.vstack(cluster_2)\n", 141 | "\n", 142 | "ax.scatter(cluster_1[:, 0], cluster_1[:, 1], label = \"Cluster 1\")\n", 143 | "ax.scatter(cluster_2[:, 0], cluster_2[:, 1], label = \"Cluster 2\")\n", 144 | "\n", 145 | "centers = kmeans.cluster_centers_\n", 146 | "ax.scatter(centers[:, 0], centers[:, 1], c = 'black', s = 200, alpha = .5, label = 'Cluster center')\n", 147 | "\n", 148 | "ax.legend(loc='best', prop={'size': 12, \"family\": \"Rockwell\"})\n", 149 | "\n", 150 | "ax.set_xlabel('STL/G')\n", 151 | "ax.set_ylabel('BLK/G')\n", 152 | "\n", 153 | "stl_blk_clustered.suptitle(\"Clustered steals and blocks leaders\", weight = 'bold', size = 18)\n", 154 | "\n", 155 | "stl_blk_clustered.text(x = -0.02, y = -0.08,\n", 156 | " s = '____________________________________________________________',\n", 157 | " fontsize = 14, color = 'grey', horizontalalignment='left')\n", 158 | "\n", 159 | "stl_blk_clustered.text(x = -0.02, y = -.14,\n", 160 | " s = 'https://dribbleanalytics.blog ',\n", 161 | " fontsize = 14, fontname = 'Rockwell', color = 'grey', horizontalalignment='left')\n", 162 | "\n", 163 | "stl_blk_clustered.savefig('stl-blk-clustered.png', dpi = 400, bbox_inches = 'tight')" 164 | ] 165 | }, 166 | { 167 | "cell_type": "markdown", 168 | "metadata": {}, 169 | "source": [ 170 | "Let's add a couple more features to this to see how we can differentiate the players differently" 171 | ] 172 | }, 173 | { 174 | "cell_type": "code", 175 | "execution_count": null, 176 | "metadata": {}, 177 | "outputs": [], 178 | "source": [ 179 | "kmeans = KMeans(n_clusters = 2, random_state = 0)\n", 180 | "\n", 181 | "x = np.column_stack((df_example['PTS'], df_example['TRB'], df_example['AST'], df_example['STL'], df_example['BLK']))\n", 182 | "\n", 183 | "kmeans.fit(x)\n", 184 | "\n", 185 | "y_kmeans = kmeans.predict(x)" 186 | ] 187 | }, 188 | { 189 | "cell_type": "code", 190 | "execution_count": null, 191 | "metadata": {}, 192 | "outputs": [], 193 | "source": [ 194 | "for i, j in zip(df_example['Player'], y_kmeans):\n", 195 | " print(i, j)" 196 | ] 197 | }, 198 | { 199 | "cell_type": "markdown", 200 | "metadata": {}, 201 | "source": [ 202 | "When we add other features to the cluster, the model clusters superstars together" 203 | ] 204 | }, 205 | { 206 | "cell_type": "markdown", 207 | "metadata": {}, 208 | "source": [ 209 | "# Let's cluster the top 50 players in PPG" 210 | ] 211 | }, 212 | { 213 | "cell_type": "code", 214 | "execution_count": null, 215 | "metadata": {}, 216 | "outputs": [], 217 | "source": [ 218 | "df_counting = pd.read_csv('counting-stats.csv')\n", 219 | "df_advanced = pd.read_csv('advanced-stats.csv')" 220 | ] 221 | }, 222 | { 223 | "cell_type": "code", 224 | "execution_count": null, 225 | "metadata": {}, 226 | "outputs": [], 227 | "source": [ 228 | "kmeans = KMeans(n_clusters = 3, random_state = 98)\n", 229 | "\n", 230 | "x = np.column_stack((df_counting['PTS'], df_advanced['USG%']))\n", 231 | "\n", 232 | "kmeans.fit(x)\n", 233 | "\n", 234 | "y_kmeans = kmeans.predict(x)" 235 | ] 236 | }, 237 | { 238 | "cell_type": "code", 239 | "execution_count": null, 240 | "metadata": {}, 241 | "outputs": [], 242 | "source": [ 243 | "for i, j in zip(df_counting['Player'], y_kmeans):\n", 244 | " print(i, j)" 245 | ] 246 | }, 247 | { 248 | "cell_type": "code", 249 | "execution_count": null, 250 | "metadata": {}, 251 | "outputs": [], 252 | "source": [ 253 | "plt.style.use('fivethirtyeight')\n", 254 | "\n", 255 | "pts_usg_clustered, ax = plt.subplots()\n", 256 | "\n", 257 | "cluster_1 = []\n", 258 | "cluster_2 = []\n", 259 | "cluster_3 = []\n", 260 | "\n", 261 | "for i in range(len(y_kmeans)):\n", 262 | " if(y_kmeans[i] == 0):\n", 263 | " cluster_1.append(x[i])\n", 264 | " elif(y_kmeans[i] == 1):\n", 265 | " cluster_2.append(x[i])\n", 266 | " elif(y_kmeans[i] == 2):\n", 267 | " cluster_3.append(x[i])\n", 268 | " \n", 269 | "cluster_1 = np.vstack(cluster_1)\n", 270 | "cluster_2 = np.vstack(cluster_2)\n", 271 | "cluster_3 = np.vstack(cluster_3)\n", 272 | "\n", 273 | "ax.scatter(cluster_1[:, 0], cluster_1[:, 1], label = \"Cluster 1 (secondary scorers)\")\n", 274 | "ax.scatter(cluster_2[:, 0], cluster_2[:, 1], label = \"Cluster 2 (primary scorers)\")\n", 275 | "ax.scatter(cluster_3[:, 0], cluster_3[:, 1], label = \"Cluster 3 (James Harden)\")\n", 276 | "\n", 277 | "centers = kmeans.cluster_centers_\n", 278 | "ax.scatter(centers[:, 0], centers[:, 1], c = 'black', s = 200, alpha = .5, label = 'Cluster center')\n", 279 | "\n", 280 | "ax.legend(loc='best', prop={'size': 12, \"family\": \"Rockwell\"})\n", 281 | "\n", 282 | "ax.set_xlabel('PPG')\n", 283 | "ax.set_ylabel('USG%')\n", 284 | "\n", 285 | "pts_usg_clustered.suptitle(\"Clustered points and usage\", weight = 'bold', size = 18)\n", 286 | "\n", 287 | "pts_usg_clustered.text(x = -0.02, y = -0.08,\n", 288 | " s = '____________________________________________________________',\n", 289 | " fontsize = 14, color = 'grey', horizontalalignment='left')\n", 290 | "\n", 291 | "pts_usg_clustered.text(x = -0.02, y = -.14,\n", 292 | " s = 'https://dribbleanalytics.blog ',\n", 293 | " fontsize = 14, fontname = 'Rockwell', color = 'grey', horizontalalignment='left')\n", 294 | "\n", 295 | "pts_usg_clustered.savefig('pts-usg-clustered.png', dpi = 400, bbox_inches = 'tight')" 296 | ] 297 | }, 298 | { 299 | "cell_type": "code", 300 | "execution_count": null, 301 | "metadata": {}, 302 | "outputs": [], 303 | "source": [ 304 | "kmeans = KMeans(n_clusters = 4, random_state = 99)\n", 305 | "\n", 306 | "x = np.column_stack((df_counting['AST'], df_advanced['USG%']))\n", 307 | "\n", 308 | "kmeans.fit(x)\n", 309 | "\n", 310 | "y_kmeans = kmeans.predict(x)" 311 | ] 312 | }, 313 | { 314 | "cell_type": "code", 315 | "execution_count": null, 316 | "metadata": {}, 317 | "outputs": [], 318 | "source": [ 319 | "for i, j in zip(df_counting['Player'], y_kmeans):\n", 320 | " print(i, j)" 321 | ] 322 | }, 323 | { 324 | "cell_type": "code", 325 | "execution_count": null, 326 | "metadata": {}, 327 | "outputs": [], 328 | "source": [ 329 | "plt.style.use('fivethirtyeight')\n", 330 | "\n", 331 | "ast_usg_clustered, ax = plt.subplots()\n", 332 | "\n", 333 | "cluster_1 = []\n", 334 | "cluster_2 = []\n", 335 | "cluster_3 = []\n", 336 | "cluster_4 = []\n", 337 | "\n", 338 | "for i in range(len(y_kmeans)):\n", 339 | " if(y_kmeans[i] == 2):\n", 340 | " cluster_1.append(x[i])\n", 341 | " elif(y_kmeans[i] == 1):\n", 342 | " cluster_2.append(x[i])\n", 343 | " elif(y_kmeans[i] == 0):\n", 344 | " cluster_3.append(x[i])\n", 345 | " elif(y_kmeans[i] == 3):\n", 346 | " cluster_4.append(x[i])\n", 347 | " \n", 348 | "cluster_1 = np.vstack(cluster_1)\n", 349 | "cluster_2 = np.vstack(cluster_2)\n", 350 | "cluster_3 = np.vstack(cluster_3)\n", 351 | "cluster_4 = np.vstack(cluster_4)\n", 352 | "\n", 353 | "ax.scatter(cluster_1[:, 0], cluster_1[:, 1], label = \"Cluster 1 (scorers)\")\n", 354 | "ax.scatter(cluster_2[:, 0], cluster_2[:, 1], label = \"Cluster 2 (passers)\")\n", 355 | "ax.scatter(cluster_3[:, 0], cluster_3[:, 1], label = \"Cluster 3 (stars)\")\n", 356 | "ax.scatter(cluster_4[:, 0], cluster_4[:, 1], label = \"Cluster 4 (James Harden)\")\n", 357 | "\n", 358 | "centers = kmeans.cluster_centers_\n", 359 | "ax.scatter(centers[:, 0], centers[:, 1], c = 'black', s = 200, alpha = .5, label = 'Cluster center')\n", 360 | "\n", 361 | "ax.legend(loc='best', prop={'size': 12, \"family\": \"Rockwell\"})\n", 362 | "\n", 363 | "ax.set_xlabel('AST')\n", 364 | "ax.set_ylabel('USG%')\n", 365 | "\n", 366 | "ast_usg_clustered.suptitle(\"Clustered assists and usage\", weight = 'bold', size = 18)\n", 367 | "\n", 368 | "ast_usg_clustered.text(x = -0.02, y = -0.08,\n", 369 | " s = '____________________________________________________________',\n", 370 | " fontsize = 14, color = 'grey', horizontalalignment='left')\n", 371 | "\n", 372 | "ast_usg_clustered.text(x = -0.02, y = -.14,\n", 373 | " s = 'https://dribbleanalytics.blog ',\n", 374 | " fontsize = 14, fontname = 'Rockwell', color = 'grey', horizontalalignment='left')\n", 375 | "\n", 376 | "ast_usg_clustered.savefig('ast-usg-clustered.png', dpi = 400, bbox_inches = 'tight')" 377 | ] 378 | }, 379 | { 380 | "cell_type": "markdown", 381 | "metadata": {}, 382 | "source": [ 383 | "# Now let's cluster NBA rotation players" 384 | ] 385 | }, 386 | { 387 | "cell_type": "code", 388 | "execution_count": null, 389 | "metadata": {}, 390 | "outputs": [], 391 | "source": [ 392 | "df_full_nba = pd.read_csv('full-nba-data.csv')" 393 | ] 394 | }, 395 | { 396 | "cell_type": "code", 397 | "execution_count": null, 398 | "metadata": {}, 399 | "outputs": [], 400 | "source": [ 401 | "df_full_nba.head()" 402 | ] 403 | }, 404 | { 405 | "cell_type": "code", 406 | "execution_count": null, 407 | "metadata": {}, 408 | "outputs": [], 409 | "source": [ 410 | "df_full_nba.columns.values" 411 | ] 412 | }, 413 | { 414 | "cell_type": "code", 415 | "execution_count": null, 416 | "metadata": {}, 417 | "outputs": [], 418 | "source": [ 419 | "features = ['Pos', 'FG', 'FGA', 'FG%', '3P', '3PA', '3P%', '2P', '2PA', '2P%', 'eFG%', 'FT', 'FTA', 'FT%', 'ORB', 'DRB', 'TRB',\n", 420 | " 'AST', 'STL', 'BLK', 'TOV', 'PF', 'PTS', 'PER', 'TS%', '3PAr', 'FTr', 'ORB%', 'DRB%', 'TRB%', 'AST%', 'STL%',\n", 421 | " 'BLK%', 'TOV%', 'USG%', 'OWS', 'DWS', 'WS', 'WS/48', 'OBPM', 'DBPM', 'BPM', 'VORP']" 422 | ] 423 | }, 424 | { 425 | "cell_type": "code", 426 | "execution_count": null, 427 | "metadata": {}, 428 | "outputs": [], 429 | "source": [ 430 | "x = df_full_nba.loc[:, features].values\n", 431 | "\n", 432 | "x = StandardScaler().fit_transform(x)" 433 | ] 434 | }, 435 | { 436 | "cell_type": "code", 437 | "execution_count": null, 438 | "metadata": {}, 439 | "outputs": [], 440 | "source": [ 441 | "pca_list = []\n", 442 | "\n", 443 | "for n_components in range(2, 11):\n", 444 | " pca = PCA(n_components = n_components)\n", 445 | " components = pca.fit_transform(x)\n", 446 | " pca_variance = sum(pca.explained_variance_ratio_)\n", 447 | " pca_list.append(pca_variance)\n", 448 | " print(\"For n_components = {}, explained variance ratio is {}\".format(n_components, pca_variance))" 449 | ] 450 | }, 451 | { 452 | "cell_type": "code", 453 | "execution_count": null, 454 | "metadata": {}, 455 | "outputs": [], 456 | "source": [ 457 | "plt.style.use('fivethirtyeight')\n", 458 | "\n", 459 | "pca_fig, ax = plt.subplots()\n", 460 | "\n", 461 | "ax.plot(range(2, 11), pca_list)\n", 462 | "\n", 463 | "ax.set_xlabel('Number of components')\n", 464 | "ax.set_ylabel('Explained variance ratio')\n", 465 | "\n", 466 | "ax.set_xticks(np.arange(2, 11, 1.0))\n", 467 | "\n", 468 | "pca_fig.suptitle(\"Finding the right number of components\", weight = 'bold', size = 18)\n", 469 | "\n", 470 | "pca_fig.text(x = -0.05, y = -0.08,\n", 471 | " s = '______________________________________________________________',\n", 472 | " fontsize = 14, color = 'grey', horizontalalignment='left')\n", 473 | "\n", 474 | "pca_fig.text(x = -0.05, y = -.14,\n", 475 | " s = 'https://dribbleanalytics.blog ',\n", 476 | " fontsize = 14, fontname = 'Rockwell', color = 'grey', horizontalalignment='left')\n", 477 | "\n", 478 | "pca_fig.savefig('pca-variance.png', dpi = 400, bbox_inches = 'tight')" 479 | ] 480 | }, 481 | { 482 | "cell_type": "code", 483 | "execution_count": null, 484 | "metadata": {}, 485 | "outputs": [], 486 | "source": [ 487 | "from numpy import diff\n", 488 | "\n", 489 | "dx = 1\n", 490 | "y = pca_list\n", 491 | "dy = diff(y)/dx\n", 492 | "print(dy)" 493 | ] 494 | }, 495 | { 496 | "cell_type": "code", 497 | "execution_count": null, 498 | "metadata": {}, 499 | "outputs": [], 500 | "source": [ 501 | "pca_deriv, ax = plt.subplots()\n", 502 | "\n", 503 | "ax.plot(range(3, 11), dy)\n", 504 | "\n", 505 | "ax.set_xlabel('Number of components')\n", 506 | "ax.set_ylabel('dy(explained variance)/dx')\n", 507 | "\n", 508 | "ax.set_xticks(np.arange(3, 11, 1.0))\n", 509 | "\n", 510 | "pca_deriv.suptitle(\"Finding the right number of components\", weight = 'bold', size = 18)\n", 511 | "\n", 512 | "pca_deriv.text(x = -0.05, y = -0.08,\n", 513 | " s = '______________________________________________________________',\n", 514 | " fontsize = 14, color = 'grey', horizontalalignment='left')\n", 515 | "\n", 516 | "pca_deriv.text(x = -0.05, y = -.14,\n", 517 | " s = 'https://dribbleanalytics.blog ',\n", 518 | " fontsize = 14, fontname = 'Rockwell', color = 'grey', horizontalalignment='left')\n", 519 | "\n", 520 | "pca_deriv.savefig('pca-deriv.png', dpi = 400, bbox_inches = 'tight')" 521 | ] 522 | }, 523 | { 524 | "cell_type": "code", 525 | "execution_count": null, 526 | "metadata": {}, 527 | "outputs": [], 528 | "source": [ 529 | "pca = PCA(n_components = 6)\n", 530 | "\n", 531 | "components = pca.fit_transform(x)\n", 532 | "\n", 533 | "pca_df = pd.DataFrame(data = components, columns = ['PC 1', 'PC 2', 'PC 3', 'PC 4', 'PC 5', 'PC 6'])\n", 534 | "\n", 535 | "pca_df['Player'] = df_full_nba['Player']\n", 536 | "pca_df = pca_df[['Player', 'PC 1', 'PC 2', 'PC 3', 'PC 4', 'PC 5', 'PC 6']]" 537 | ] 538 | }, 539 | { 540 | "cell_type": "code", 541 | "execution_count": null, 542 | "metadata": {}, 543 | "outputs": [], 544 | "source": [ 545 | "pca_df.head()" 546 | ] 547 | }, 548 | { 549 | "cell_type": "code", 550 | "execution_count": null, 551 | "metadata": {}, 552 | "outputs": [], 553 | "source": [ 554 | "print(pca.explained_variance_ratio_)\n", 555 | "print(sum(pca.explained_variance_ratio_))" 556 | ] 557 | }, 558 | { 559 | "cell_type": "code", 560 | "execution_count": null, 561 | "metadata": {}, 562 | "outputs": [], 563 | "source": [ 564 | "x = np.column_stack((pca_df['PC 1'], pca_df['PC 2'], pca_df['PC 3'], pca_df['PC 4'], pca_df['PC 5'], pca_df['PC 6']))\n", 565 | "\n", 566 | "silhouette = []\n", 567 | "\n", 568 | "for n_clusters in range(2, 21):\n", 569 | " kmeans = KMeans(n_clusters = n_clusters, random_state = 99)\n", 570 | " cluster_labels = kmeans.fit_predict(x)\n", 571 | " \n", 572 | " centers = kmeans.cluster_centers_\n", 573 | "\n", 574 | " score = silhouette_score(x, cluster_labels)\n", 575 | " silhouette.append(score)\n", 576 | " print(\"For n_clusters = {}, silhouette score is {}\".format(n_clusters, score))" 577 | ] 578 | }, 579 | { 580 | "cell_type": "code", 581 | "execution_count": null, 582 | "metadata": {}, 583 | "outputs": [], 584 | "source": [ 585 | "plt.style.use('fivethirtyeight')\n", 586 | "\n", 587 | "silhouette_fig, ax = plt.subplots()\n", 588 | "\n", 589 | "ax.plot(range(2, 21), silhouette)\n", 590 | "\n", 591 | "ax.set_xlabel('Number of clusters')\n", 592 | "ax.set_ylabel('Silhouette score')\n", 593 | "\n", 594 | "ax.set_xticks(np.arange(2, 21, 3.0))\n", 595 | "\n", 596 | "silhouette_fig.suptitle(\"Finding the right number of clusters\", weight = 'bold', size = 18)\n", 597 | "\n", 598 | "silhouette_fig.text(x = -0.05, y = -0.08,\n", 599 | " s = '______________________________________________________________',\n", 600 | " fontsize = 14, color = 'grey', horizontalalignment='left')\n", 601 | "\n", 602 | "silhouette_fig.text(x = -0.05, y = -.14,\n", 603 | " s = 'https://dribbleanalytics.blog ',\n", 604 | " fontsize = 14, fontname = 'Rockwell', color = 'grey', horizontalalignment='left')\n", 605 | "\n", 606 | "silhouette_fig.savefig('silhouette-score.png', dpi = 400, bbox_inches = 'tight')" 607 | ] 608 | }, 609 | { 610 | "cell_type": "code", 611 | "execution_count": null, 612 | "metadata": {}, 613 | "outputs": [], 614 | "source": [ 615 | "silhouette_diff = []\n", 616 | "\n", 617 | "for i in range(1, len(silhouette)):\n", 618 | " improvement = 1 - ((1 - silhouette[i]) / (1 - silhouette[i - 1]))\n", 619 | " silhouette_diff.append(improvement)\n", 620 | " print(\"For n_cluster = {}, percent improvement = {}\".format(i + 2, improvement))" 621 | ] 622 | }, 623 | { 624 | "cell_type": "code", 625 | "execution_count": null, 626 | "metadata": {}, 627 | "outputs": [], 628 | "source": [ 629 | "plt.style.use('fivethirtyeight')\n", 630 | "\n", 631 | "silhouette_imp_fig, ax = plt.subplots()\n", 632 | "\n", 633 | "ax.plot(range(3, 21), silhouette_diff)\n", 634 | "\n", 635 | "ax.set_xlabel('Number of clusters')\n", 636 | "ax.set_ylabel('% silhouette improvement')\n", 637 | "\n", 638 | "ax.set_xticks(np.arange(3, 21, 2.0))\n", 639 | "\n", 640 | "vals = ax.get_yticks()\n", 641 | "ax.set_yticklabels(['{:,.0%}'.format(x) for x in vals])\n", 642 | "\n", 643 | "silhouette_imp_fig.suptitle(\"Finding the right number of clusters\", weight = 'bold', size = 18)\n", 644 | "\n", 645 | "silhouette_imp_fig.text(x = -0.05, y = -0.08,\n", 646 | " s = '______________________________________________________________',\n", 647 | " fontsize = 14, color = 'grey', horizontalalignment='left')\n", 648 | "\n", 649 | "silhouette_imp_fig.text(x = -0.05, y = -.14,\n", 650 | " s = 'https://dribbleanalytics.blog ',\n", 651 | " fontsize = 14, fontname = 'Rockwell', color = 'grey', horizontalalignment='left')\n", 652 | "\n", 653 | "silhouette_imp_fig.savefig('silhouette-diff-score.png', dpi = 400, bbox_inches = 'tight')" 654 | ] 655 | }, 656 | { 657 | "cell_type": "code", 658 | "execution_count": null, 659 | "metadata": {}, 660 | "outputs": [], 661 | "source": [ 662 | "kmeans = KMeans(n_clusters = 12, random_state = 1)\n", 663 | "\n", 664 | "kmeans.fit(x)\n", 665 | "\n", 666 | "y_kmeans = kmeans.predict(x)" 667 | ] 668 | }, 669 | { 670 | "cell_type": "code", 671 | "execution_count": null, 672 | "metadata": {}, 673 | "outputs": [], 674 | "source": [ 675 | "df_cluster = pd.DataFrame()\n", 676 | "\n", 677 | "df_cluster['Player'] = df_full_nba['Player']\n", 678 | "df_cluster['Cluster'] = y_kmeans\n", 679 | "\n", 680 | "df_cluster.head()" 681 | ] 682 | }, 683 | { 684 | "cell_type": "code", 685 | "execution_count": null, 686 | "metadata": {}, 687 | "outputs": [], 688 | "source": [ 689 | "interest_stats = ['PTS', 'TRB', 'AST', 'STL', 'BLK', 'FG%', '3P%', 'FT%', 'USG%']\n", 690 | "\n", 691 | "def cluster_stats(cluster):\n", 692 | " \n", 693 | " print(df_full_nba[interest_stats].loc[df_cluster['Cluster'] == cluster].mean())" 694 | ] 695 | }, 696 | { 697 | "cell_type": "code", 698 | "execution_count": null, 699 | "metadata": {}, 700 | "outputs": [], 701 | "source": [ 702 | "df_cluster[df_cluster['Cluster'] == 11]" 703 | ] 704 | }, 705 | { 706 | "cell_type": "code", 707 | "execution_count": null, 708 | "metadata": {}, 709 | "outputs": [], 710 | "source": [ 711 | "cluster_stats(11)" 712 | ] 713 | }, 714 | { 715 | "cell_type": "code", 716 | "execution_count": null, 717 | "metadata": {}, 718 | "outputs": [], 719 | "source": [ 720 | "df_cluster[interest_stats] = df_full_nba[interest_stats]" 721 | ] 722 | }, 723 | { 724 | "cell_type": "code", 725 | "execution_count": null, 726 | "metadata": {}, 727 | "outputs": [], 728 | "source": [ 729 | "df_cluster['Cluster'] = df_cluster['Cluster'] + 1" 730 | ] 731 | }, 732 | { 733 | "cell_type": "code", 734 | "execution_count": null, 735 | "metadata": {}, 736 | "outputs": [], 737 | "source": [ 738 | "roles = ['3&D guard', 'Perimiter scorer', 'Rim runner', '???', 'Star big', 'Shooter', 'Star ball handler',\n", 739 | " 'Team-leading guard', 'Do it all big', 'Floor general', 'Inside big', '3&D forward']\n", 740 | "\n", 741 | "cluster_dict = dict(zip(list(range(1, 13)), roles))" 742 | ] 743 | }, 744 | { 745 | "cell_type": "code", 746 | "execution_count": null, 747 | "metadata": {}, 748 | "outputs": [], 749 | "source": [ 750 | "df_cluster['Role'] = df_cluster['Cluster'].map(cluster_dict)" 751 | ] 752 | }, 753 | { 754 | "cell_type": "code", 755 | "execution_count": null, 756 | "metadata": {}, 757 | "outputs": [], 758 | "source": [ 759 | "df_cluster.head()" 760 | ] 761 | }, 762 | { 763 | "cell_type": "code", 764 | "execution_count": null, 765 | "metadata": {}, 766 | "outputs": [], 767 | "source": [ 768 | "df_cluster = df_cluster[['Player', 'Cluster', 'Role', 'PTS', 'TRB', 'AST', 'STL', 'BLK', 'FG%', '3P%', 'FT%', 'USG%']]\n", 769 | "df_cluster.to_csv('clustered-nba.csv')" 770 | ] 771 | }, 772 | { 773 | "cell_type": "code", 774 | "execution_count": null, 775 | "metadata": {}, 776 | "outputs": [], 777 | "source": [ 778 | "df_avg = df_cluster.groupby('Role')[interest_stats].mean()" 779 | ] 780 | }, 781 | { 782 | "cell_type": "code", 783 | "execution_count": null, 784 | "metadata": {}, 785 | "outputs": [], 786 | "source": [ 787 | "df_avg" 788 | ] 789 | } 790 | ], 791 | "metadata": { 792 | "kernelspec": { 793 | "display_name": "Python 3", 794 | "language": "python", 795 | "name": "python3" 796 | }, 797 | "language_info": { 798 | "codemirror_mode": { 799 | "name": "ipython", 800 | "version": 3 801 | }, 802 | "file_extension": ".py", 803 | "mimetype": "text/x-python", 804 | "name": "python", 805 | "nbconvert_exporter": "python", 806 | "pygments_lexer": "ipython3", 807 | "version": "3.6.4" 808 | } 809 | }, 810 | "nbformat": 4, 811 | "nbformat_minor": 2 812 | } 813 | --------------------------------------------------------------------------------