Team and Opponent Stats Table Team | G | MP | FG | FGA | FG% | 3P | 3PA | 3P% | 2P | 2PA | 2P% | FT | FTA | FT% | ORB | DRB | TRB | AST | STL | BLK | TOV | PF | PTS |
Team | 46 | 10782 | 1770 | 3742 | .473 | 439 | 1284 | .342 | 1331 | 2458 | .541 | 786 | 1105 | .711 | 532 | 1373 | 1905 | 990 | 422 | 136 | 570 | 1089 | 4765 |
Opp | 46 | 10782 | | | | | | | | | | | | | | | | | | | | | |
Per Game Table Player | G | MP | FG | FGA | FG% | 3P | 3PA | 3P% | 2P | 2PA | 2P% | FT | FTA | FT% | ORB | DRB | TRB | AST | STL | BLK | TOV | PF | PTS |
Andrew Goudelock | 19 | 30.5 | 8.8 | 18.5 | .479 | 3.5 | 7.8 | .443 | 5.4 | 10.6 | .505 | 2.1 | 2.3 | .909 | 0.6 | 2.3 | 2.9 | 3.4 | 1.1 | 0.2 | 1.4 | 1.2 | 23.3 |
Cheng Jia | 46 | 21.4 | 3.2 | 6.6 | .483 | 0.4 | 1.1 | .367 | 2.8 | 5.5 | .506 | 1.8 | 2.3 | .769 | 1.7 | 3.8 | 5.5 | 0.7 | 0.5 | 0.6 | 1.1 | 2.9 | 8.5 |
Chunjun Zhang | 38 | 27.5 | 2.2 | 4.7 | .478 | 0.7 | 2.1 | .359 | 1.5 | 2.6 | .570 | 0.4 | 0.7 | .536 | 1.4 | 2.2 | 3.6 | 1.5 | 1.3 | 0.1 | 0.9 | 3.3 | 5.6 |
Donatas Motiejūnas | 35 | 33.6 | 11.3 | 20.4 | .555 | 1.1 | 3.4 | .317 | 10.2 | 17.0 | .603 | 4.0 | 7.6 | .528 | 3.3 | 10.7 | 13.9 | 4.1 | 1.9 | 0.9 | 2.9 | 2.6 | 27.7 |
HanLin Tao | 46 | 24.7 | 4.7 | 7.9 | .602 | 0.0 | 0.0 | | 4.7 | 7.9 | .602 | 2.3 | 3.0 | .765 | 2.1 | 3.6 | 5.7 | 0.7 | 0.6 | 0.6 | 0.7 | 2.8 | 11.7 |
Honghan Li | 37 | 13.9 | 1.1 | 3.8 | .286 | 0.5 | 2.3 | .233 | 0.5 | 1.5 | .370 | 0.4 | 0.5 | .765 | 0.4 | 0.7 | 1.1 | 0.8 | 0.3 | 0.0 | 0.4 | 1.4 | 3.1 |
JaKarr Sampson | 5 | 33.4 | 9.0 | 18.2 | .495 | 1.0 | 2.4 | .417 | 8.0 | 15.8 | .506 | 3.2 | 5.4 | .593 | 3.4 | 7.6 | 11.0 | 1.6 | 1.0 | 1.8 | 1.2 | 2.6 | 22.2 |
Ke Wu | 39 | 11.6 | 1.5 | 3.9 | .384 | 0.4 | 1.1 | .318 | 1.1 | 2.7 | .411 | 0.6 | 0.9 | .667 | 0.6 | 1.5 | 2.1 | 0.8 | 0.3 | 0.2 | 0.7 | 1.8 | 3.9 |
Nan Wu | 45 | 24.6 | 2.3 | 6.4 | .366 | 1.3 | 4.1 | .311 | 1.1 | 2.3 | .462 | 1.1 | 1.6 | .671 | 0.8 | 1.5 | 2.3 | 1.5 | 0.9 | 0.1 | 1.1 | 2.8 | 7.0 |
Pan Ning | 18 | 4.7 | 0.3 | 1.8 | .182 | 0.2 | 1.1 | .150 | 0.2 | 0.7 | .231 | 0.0 | 0.1 | .000 | 0.2 | 0.7 | 0.9 | 0.4 | 0.1 | 0.2 | 0.3 | 0.8 | 0.8 |
Zhang Qingpeng | 43 | 28.1 | 3.1 | 7.6 | .412 | 1.9 | 5.0 | .382 | 1.2 | 2.5 | .472 | 1.6 | 1.9 | .854 | 0.4 | 2.6 | 3.0 | 3.6 | 1.1 | 0.0 | 1.7 | 2.2 | 9.8 |
Ruheng Wang | 45 | 27.2 | 2.5 | 6.7 | .373 | 1.4 | 4.4 | .323 | 1.1 | 2.3 | .471 | 1.0 | 1.3 | .763 | 0.5 | 1.9 | 2.4 | 3.4 | 1.6 | 0.1 | 1.5 | 2.6 | 7.4 |
Ty Lawson | 22 | 34.4 | 8.7 | 16.8 | .520 | 2.0 | 5.4 | .361 | 6.8 | 11.4 | .596 | 7.1 | 8.4 | .848 | 0.4 | 3.5 | 3.9 | 9.0 | 1.7 | 0.0 | 2.5 | 1.7 | 26.5 |
Wen Yanxing | 10 | 5.1 | 0.2 | 1.3 | .154 | 0.0 | 0.3 | .000 | 0.2 | 1.0 | .200 | 0.0 | 0.0 | | 0.3 | 0.3 | 0.6 | 0.7 | 0.6 | 0.1 | 0.5 | 1.0 | 0.4 |
Zhu Rongzhen | 30 | 10.0 | 2.1 | 4.2 | .500 | 0.0 | 0.2 | .000 | 2.1 | 4.0 | .525 | 1.0 | 1.5 | .689 | 1.2 | 1.7 | 2.9 | 0.2 | 0.1 | 0.5 | 0.8 | 1.9 | 5.2 |
Totals Table Player | G | MP | FG | FGA | FG% | 3P | 3PA | 3P% | 2P | 2PA | 2P% | FT | FTA | FT% | ORB | DRB | TRB | AST | STL | BLK | TOV | PF | PTS |
Andrew Goudelock | 19 | 580 | 168 | 351 | .479 | 66 | 149 | .443 | 102 | 202 | .505 | 40 | 44 | .909 | 11 | 44 | 55 | 64 | 20 | 3 | 26 | 22 | 442 |
Cheng Jia | 46 | 983 | 146 | 302 | .483 | 18 | 49 | .367 | 128 | 253 | .506 | 83 | 108 | .769 | 76 | 175 | 251 | 32 | 22 | 28 | 50 | 133 | 393 |
Chunjun Zhang | 38 | 1046 | 85 | 178 | .478 | 28 | 78 | .359 | 57 | 100 | .570 | 15 | 28 | .536 | 52 | 85 | 137 | 56 | 51 | 2 | 34 | 125 | 213 |
Donatas Motiejūnas | 35 | 1177 | 396 | 714 | .555 | 38 | 120 | .317 | 358 | 594 | .603 | 140 | 265 | .528 | 114 | 374 | 488 | 145 | 66 | 30 | 100 | 91 | 970 |
HanLin Tao | 46 | 1136 | 218 | 362 | .602 | 0 | 0 | | 218 | 362 | .602 | 104 | 136 | .765 | 98 | 165 | 263 | 30 | 27 | 28 | 34 | 128 | 540 |
Honghan Li | 37 | 513 | 40 | 140 | .286 | 20 | 86 | .233 | 20 | 54 | .370 | 13 | 17 | .765 | 13 | 26 | 39 | 30 | 11 | 0 | 14 | 50 | 113 |
JaKarr Sampson | 5 | 167 | 45 | 91 | .495 | 5 | 12 | .417 | 40 | 79 | .506 | 16 | 27 | .593 | 17 | 38 | 55 | 8 | 5 | 9 | 6 | 13 | 111 |
Ke Wu | 39 | 451 | 58 | 151 | .384 | 14 | 44 | .318 | 44 | 107 | .411 | 24 | 36 | .667 | 22 | 58 | 80 | 31 | 10 | 6 | 26 | 71 | 154 |
Nan Wu | 45 | 1105 | 105 | 287 | .366 | 57 | 183 | .311 | 48 | 104 | .462 | 49 | 73 | .671 | 37 | 67 | 104 | 67 | 42 | 6 | 51 | 126 | 316 |
Pan Ning | 18 | 85 | 6 | 33 | .182 | 3 | 20 | .150 | 3 | 13 | .231 | 0 | 1 | .000 | 4 | 12 | 16 | 8 | 2 | 4 | 5 | 15 | 15 |
Zhang Qingpeng | 43 | 1209 | 134 | 325 | .412 | 83 | 217 | .382 | 51 | 108 | .472 | 70 | 82 | .854 | 18 | 113 | 131 | 154 | 46 | 1 | 73 | 94 | 421 |
Ruheng Wang | 45 | 1223 | 112 | 300 | .373 | 64 | 198 | .323 | 48 | 102 | .471 | 45 | 59 | .763 | 23 | 84 | 107 | 154 | 74 | 3 | 66 | 117 | 333 |
Ty Lawson | 22 | 756 | 192 | 369 | .520 | 43 | 119 | .361 | 149 | 250 | .596 | 156 | 184 | .848 | 9 | 77 | 86 | 198 | 38 | 1 | 55 | 37 | 583 |
Wen Yanxing | 10 | 51 | 2 | 13 | .154 | 0 | 3 | .000 | 2 | 10 | .200 | 0 | 0 | | 3 | 3 | 6 | 7 | 6 | 1 | 5 | 10 | 4 |
Zhu Rongzhen | 30 | 300 | 63 | 126 | .500 | 0 | 6 | .000 | 63 | 120 | .525 | 31 | 45 | .689 | 35 | 52 | 87 | 6 | 2 | 14 | 25 | 57 | 157 |
Per 36 Minutes Table Player | G | MP | FG | FGA | FG% | 3P | 3PA | 3P% | 2P | 2PA | 2P% | FT | FTA | FT% | ORB | DRB | TRB | AST | STL | BLK | TOV | PF | PTS |
Andrew Goudelock | 19 | 580 | 10.4 | 21.8 | .479 | 4.1 | 9.2 | .443 | 6.3 | 12.5 | .505 | 2.5 | 2.7 | .909 | 0.7 | 2.7 | 3.4 | 4.0 | 1.2 | 0.2 | 1.6 | 1.4 | 27.4 |
Cheng Jia | 46 | 983 | 5.3 | 11.1 | .483 | 0.7 | 1.8 | .367 | 4.7 | 9.3 | .506 | 3.0 | 4.0 | .769 | 2.8 | 6.4 | 9.2 | 1.2 | 0.8 | 1.0 | 1.8 | 4.9 | 14.4 |
Chunjun Zhang | 38 | 1046 | 2.9 | 6.1 | .478 | 1.0 | 2.7 | .359 | 2.0 | 3.4 | .570 | 0.5 | 1.0 | .536 | 1.8 | 2.9 | 4.7 | 1.9 | 1.8 | 0.1 | 1.2 | 4.3 | 7.3 |
Donatas Motiejūnas | 35 | 1177 | 12.1 | 21.8 | .555 | 1.2 | 3.7 | .317 | 10.9 | 18.2 | .603 | 4.3 | 8.1 | .528 | 3.5 | 11.4 | 14.9 | 4.4 | 2.0 | 0.9 | 3.1 | 2.8 | 29.7 |
HanLin Tao | 46 | 1136 | 6.9 | 11.5 | .602 | 0.0 | 0.0 | | 6.9 | 11.5 | .602 | 3.3 | 4.3 | .765 | 3.1 | 5.2 | 8.3 | 1.0 | 0.9 | 0.9 | 1.1 | 4.1 | 17.1 |
Honghan Li | 37 | 513 | 2.8 | 9.8 | .286 | 1.4 | 6.0 | .233 | 1.4 | 3.8 | .370 | 0.9 | 1.2 | .765 | 0.9 | 1.8 | 2.7 | 2.1 | 0.8 | 0.0 | 1.0 | 3.5 | 7.9 |
JaKarr Sampson | 5 | 167 | 9.7 | 19.6 | .495 | 1.1 | 2.6 | .417 | 8.6 | 17.0 | .506 | 3.4 | 5.8 | .593 | 3.7 | 8.2 | 11.9 | 1.7 | 1.1 | 1.9 | 1.3 | 2.8 | 23.9 |
Ke Wu | 39 | 451 | 4.6 | 12.1 | .384 | 1.1 | 3.5 | .318 | 3.5 | 8.5 | .411 | 1.9 | 2.9 | .667 | 1.8 | 4.6 | 6.4 | 2.5 | 0.8 | 0.5 | 2.1 | 5.7 | 12.3 |
Nan Wu | 45 | 1105 | 3.4 | 9.4 | .366 | 1.9 | 6.0 | .311 | 1.6 | 3.4 | .462 | 1.6 | 2.4 | .671 | 1.2 | 2.2 | 3.4 | 2.2 | 1.4 | 0.2 | 1.7 | 4.1 | 10.3 |
Pan Ning | 18 | 85 | 2.5 | 14.0 | .182 | 1.3 | 8.5 | .150 | 1.3 | 5.5 | .231 | 0.0 | 0.4 | .000 | 1.7 | 5.1 | 6.8 | 3.4 | 0.8 | 1.7 | 2.1 | 6.4 | 6.4 |
Zhang Qingpeng | 43 | 1209 | 4.0 | 9.7 | .412 | 2.5 | 6.5 | .382 | 1.5 | 3.2 | .472 | 2.1 | 2.4 | .854 | 0.5 | 3.4 | 3.9 | 4.6 | 1.4 | 0.0 | 2.2 | 2.8 | 12.5 |
Ruheng Wang | 45 | 1223 | 3.3 | 8.8 | .373 | 1.9 | 5.8 | .323 | 1.4 | 3.0 | .471 | 1.3 | 1.7 | .763 | 0.7 | 2.5 | 3.1 | 4.5 | 2.2 | 0.1 | 1.9 | 3.4 | 9.8 |
Ty Lawson | 22 | 756 | 9.1 | 17.6 | .520 | 2.0 | 5.7 | .361 | 7.1 | 11.9 | .596 | 7.4 | 8.8 | .848 | 0.4 | 3.7 | 4.1 | 9.4 | 1.8 | 0.0 | 2.6 | 1.8 | 27.8 |
Wen Yanxing | 10 | 51 | 1.4 | 9.2 | .154 | 0.0 | 2.1 | .000 | 1.4 | 7.1 | .200 | 0.0 | 0.0 | | 2.1 | 2.1 | 4.2 | 4.9 | 4.2 | 0.7 | 3.5 | 7.1 | 2.8 |
Zhu Rongzhen | 30 | 300 | 7.6 | 15.1 | .500 | 0.0 | 0.7 | .000 | 7.6 | 14.4 | .525 | 3.7 | 5.4 | .689 | 4.2 | 6.2 | 10.4 | 0.7 | 0.2 | 1.7 | 3.0 | 6.8 | 18.8 |
More 2019 Shandong Golden Stars Pages
International
More International Pages
Leagues
International
More International Pages
Leagues
We're Social...for Statheads
Every Sports Reference Social Media Account
Site Last Updated: Sunday, December 22, 3:28AM
Question, Comment, Feedback, or Correction?
Subscribe to our Free Email Newsletter
Subscribe to Stathead Basketball: Get your first month FREE
Your All-Access Ticket to the Basketball Reference Database
Do you have a sports website? Or write about sports? We have tools and resources that can help you use sports data. Find out more.