NAME POS GP MIN WP48 PoP48 WINS PTS REB AST TO BLK STL PF
Viacheslav Kravtsov C 25 224 .094 -0.2 0.44 16.5 9.6 1.9 3.0 1.9 1.1 6.9
Andre Drummond C 60 1243 .313 6.7 8.11 18.4 17.6 1.2 2.2 3.7 2.3 5.6
Jose Calderon PG 28 887 .234 4.2 4.32 17.6 3.8 10.0 2.8 0.1 1.6 2.2
Greg Monroe PF 81 2688 .140 1.3 7.85 23.2 13.9 5.0 4.2 1.0 1.9 3.4
Will Bynum PG 65 1219 -.002 -3.1 -0.05 25.0 3.8 9.1 4.9 0.2 1.8 5.0
Jonas Jerebko SF 49 892 .148 1.5 2.75 20.3 10.0 2.3 2.3 0.4 2.0 4.8
Jason Maxiell PF 72 1788 .052 -1.5 1.93 13.4 11.0 1.4 2.2 2.6 0.9 4.6
Tayshaun Prince SF 45 1457 .072 -0.8 2.20 17.4 6.9 3.7 1.8 0.4 0.7 1.5
Austin Daye SF 24 348 .124 0.8 0.90 16.8 8.7 2.9 1.8 1.1 0.7 5.9
Khris Middleton F 27 475 .008 -2.8 0.08 16.7 5.1 2.8 1.1 0.4 1.5 5.4
Kyle Singler SF 82 2293 .050 -1.5 2.39 15.1 6.9 1.6 2.1 0.8 1.2 4.5
Brandon Knight PG 75 2365 -.014 -3.5 -0.67 20.3 5.0 6.1 4.2 0.2 1.2 3.2
Rodney Stuckey SG 76 2171 .053 -1.4 2.39 19.4 4.7 6.0 3.0 0.4 1.1 2.8
Charlie Villanueva PF 69 1092 .010 -2.8 0.24 20.5 10.6 2.4 1.7 1.7 1.4 4.2
Kim English G 41 407 -.021 -3.7 -0.18 14.0 4.4 3.1 2.2 0.4 1.9 5.4
Corey Maggette F 18 257 -.148 -7.7 -0.79 17.7 4.7 3.5 3.2 0.4 1.1 7.8
Name FG% 2FG% 3FG% FT% eFG% TS% FGA 3FGA FTA
Viacheslav Kravtsov 71.7% 71.7% 0.0% 29.7% 71.7% 61.8% 9.9 0.0 7.9
Andre Drummond 60.8% 60.9% 50.0% 37.1% 61.0% 57.8% 13.2 0.1 6.1
Jose Calderon 52.7% 53.2% 52.0% 89.3% 63.5% 65.4% 12.8 5.3 1.5
Greg Monroe 48.6% 48.8% 0.0% 68.9% 48.6% 52.7% 18.9 0.1 7.0
Will Bynum 46.9% 49.4% 31.6% 80.9% 49.1% 53.2% 21.3 3.0 5.2
Jonas Jerebko 44.9% 50.2% 30.1% 77.3% 48.9% 53.1% 17.0 4.5 4.7
Jason Maxiell 44.6% 44.6% 0.0% 62.1% 44.6% 47.8% 12.3 0.0 3.9
Tayshaun Prince 44.4% 44.5% 43.4% 79.6% 46.8% 50.2% 15.9 1.7 3.1
Austin Daye 44.3% 38.6% 52.5% 83.3% 55.2% 58.1% 13.4 5.5 2.5
Khris Middleton 44.0% 50.0% 31.1% 84.4% 48.9% 53.2% 14.2 4.5 3.2
Kyle Singler 42.8% 46.4% 35.0% 80.6% 48.3% 51.7% 13.4 4.2 2.6
Brandon Knight 40.7% 43.0% 36.7% 73.3% 47.5% 51.1% 17.8 6.6 4.6
Rodney Stuckey 40.6% 44.0% 30.2% 78.3% 44.3% 50.5% 16.5 4.0 6.0
Charlie Villanueva 37.7% 41.5% 34.7% 55.1% 47.4% 48.1% 20.4 11.4 2.2
Kim English 37.5% 45.2% 28.0% 72.4% 43.8% 47.7% 13.2 5.9 3.4
Corey Maggette 35.5% 40.0% 23.8% 75.0% 38.8% 48.9% 14.2 3.9 9.0
  WP48 WINS PTS DRB ORB TRB AST TO BLK STL PF
DET 0.495 31.9 94.9 30.0 12.1 42.1 21.2 15.1 4.9 7.0 19.8
AVG 0.500 41.0 98.1 31.0 11.2 42.1 22.1 14.6 5.1 7.8 19.8
OPP 0.505 50.1 98.8 30.7 11.1 41.8 22.4 13.7 5.8 8.4 19.9
AVGOPP 0.500 41.0 98.1 31.0 11.2 42.1 22.1 14.6 5.1 7.8 19.8
  FG% 2FG% 3FG% FT% eFG% TS% FGA 3FGA FTA
DET 44.9% 47.4% 35.6% 69.9% 48.7% 52.1% 81.0 17.6 22.8
AVG 45.3% 48.3% 35.9% 75.3% 49.6% 53.5% 82.0 20.0 22.2

Wins Produced
Expected* Actual Forecast**
31.9-50.1 29-53 n/a

* The win-loss record that wins produced would have predicted based on players' WP48 so far (ignores previous seasons).

** future games only -- takes current record as given


Articles featuring the Detroit Pistons

Trade Machine Economics

So, yesterday a trade happened. I'm not going to talk a whole lot about the #BasketballReasons of the trade (other, than, perhaps to take a 5-minute break laughing myself silly at those of you who actually thought Toronto got better here) because I think Ben Gulker and Devin Digham both do a good job of that here and here. I just want to briefly talk about the economics.

Pistons: Win with Youth

From the Truehoop Bullets today:

The NBA Geek's Amnesty Guesses, Part 1

I'm calling them guesses, not predictions, because this way if I'm completely wrong, I won't look as stupid.