Trades Working Out?

What you will get in this article is kind of simple and easily comparable stuff. Don’t expect me to make judgments about how smart the player movements were. This study should be considered as a comparison tool which helps us have some insight whether the trades, on the paper, seem to help out teams or not! It was just a matter of me listing traded players one under the other and putting stats (for the same player) together.

Trades are being executed by GMs and coaches who are making decisions to make their team play better basketball. Not all of the players getting involved in a trade will react well and it’s not difficult to list a few reasons why trades don’t always work out with the way GMs and coaches think before making the movements. Here are the ones I could be able to to write

  • the physcology of not being the main men of trade,
  • getting assigned to a different role,
  • time needed for players in order to get adjusted to new teams’ pace&offensive and defensive sets
  • adaptation problems: New teammates, new city, social life, family issues etc.

Now let’s talk about the metrics used in this research:

I must point out the fact that this table only contains changes in playing times, ball usage, points, rebounds, and assists after the trades. Those stats are not enough themselves to make a statement about the trades worked out or not. It’s most likely about how the coaches has preferred to use new players on the court.

Since head coaches distribute total team possessions to players, -in other words, if you’re not Von Wafer– you won’t be allowed to use the ball as many as you want 🙂 Von Wafer? With attempting to shoot the ball 4-5 times in his 1.5 minutes of playing time, he is not the best trade thankfully! Now, I will name you a player whose name hasn’t been spelled so many times in the season. But he’s the champion of the trades work out research. Kirk Synder‘s stats tell us that the trade worked out very well for him and Minnesota. The table below contains the players with the most increased playing time in their new teams.

STATS WITH THE FORMER TEAM STATS WITH THE NEW TEAM
PLAYER TEAM GP MIN USAGE PER PTS RBD AST W/L TEAM GP MIN USAGE PER PTS RBD AST W/L
1 K.Snyder Hou 9 8.8 4.5 3.8 1.3 0.9 3-6 Min 14 26.6 9.8 14.5 8.4 4.0 1.9 7-7
2 D.West Sea 35 20.6 10.1 11.5 6.8 2.7 3.2 9-26 Cle 16 31.0 12.7 13.0 9.2 3.6 4.3 9-7
3 N.Fazekas Dal 6 2.8 1.3 0.7 0.7 0.2 3-2 Lac 9 11.3 4.1 18.9 3.4 4.4 0.4 1-8
4 M.Banks Pho 24 12.7 5.5 12.1 5.2 0.8 1.0 19-5 Mia 12 21.4 10.4 18.1 9.5 2.1 3.0 2-10
5 G.Giricek Phi 12 9.0 4.7 3.1 1.2 0.9 5-7 Pho 9 17.6 8.3 16.5 8.7 1.6 1.4 7-2
6 J.Crittenton Lal 22 7.6 4.1 3.3 1.0 0.8 18-4 Mem 20 15.6 7.8 10.9 6.3 2.5 0.8 4-16
7 R.Murray Det 19 18.1 11.6 15.7 7.5 1.9 3.4 13-6 Ind 11 22.3 14.4 18.5 12.4 2.4 2.5 6-5
8 S.Marion Pho 47 36.3 14.4 23.4 15.8 9.9 2.1 34-13 Mia 15 39.9 18.8 19.9 15.3 11.9 2.7 3-12
9 D.Harris Dal 39 30.1 16.7 21.4 14.4 2.3 5.3 28-11 Njn 13 33.7 20.1 18.3 16.1 3.2 6.2 4-9
10 L.Hughes Cle 41 29.9 15.9 13.7 12.3 3.5 2.3 24-17 Chi 14 32.8 18.3 16.5 14.6 3.9 4.1 5-9
11 M.Bibby Sac 15 31.4 17.5 15.9 13.5 3.7 5.0 8-7 Atl 19 33.9 18.5 16.0 13.7 2.8 6.9 8-11
12 D.Gooden Cle 52 30.4 14.0 14.6 11.3 8.3 1.0 30-22 Chi 14 32.1 15.3 21.3 14.1 9.2 1.8 5-9
13 W.Szczerbiak Sea 50 23.4 12.4 18.4 13.1 2.7 1.4 12-38 Cle 15 22.9 11.6 12.3 9.1 3.1 1.7 8-7
14 T.Hassell Dal 37 12.3 2.9 5.7 2.1 1.2 0.7 24-13 Njn 16 12.4 3.4 3.9 2.3 1.4 0.6 5-11
15 J.Dixon Tor 37 11.4 6.3 13.0 4.2 1.3 1.8 19-18 Det 10 11.3 5.8 11.0 4.4 1.3 1.4 8-2
16 S.O`Neal Mia 33 28.4 16.0 20.7 14.2 7.8 1.4 8-25 Pho 16 28.3 12.8 18.2 11.9 10.6 1.8 10-6
17 J.Smith Chi 50 22.7 12.0 19.8 11.2 5.3 0.9 20-30 Cle 16 22.1 8.6 17.7 7.8 5.6 0.9 9-7
18 J.Collins Njn 43 15.7 2.3 2.4 1.4 2.1 0.4 19-24 Mem 19 13.9 3.1 5.3 2.2 2.6 0.2 5-14
19 D.Marshall Cle 11 14.0 5.1 9.9 3.7 2.7 0.5 5-6 Sea 10 11.6 4.2 12.6 3.6 3.2 0.3 0-10
20 P.Gasol Mem 39 36.5 19.3 23.7 18.9 8.8 3.0 10-29 Lal 19 33.9 17.0 28.1 18.8 7.9 3.4 15-3
21 B.Jackson Nor 50 19.1 8.4 14.7 7.0 2.4 1.8 33-15 Hou 11 16.4 9.0 17.7 7.6 2.4 1.7 8-3
22 B.Wells Hou 51 21.8 11.8 16.6 9.2 5.1 1.6 31-20 Nor 9 18.9 10.7 23.5 9.8 3.4 0.8 5-4
23 J.Kidd Njn 51 36.9 19.0 18.6 11.3 8.1 10.4 23-28 Dal 17 33.9 14.8 19.7 8.4 6.4 9.3 9-8
24 S.Williams Atl 36 11.3 3.9 11.8 3.0 3.0 0.3 15-21 Sac 17 8.0 3.9 3.9 2.3 0.1 8-9
25 G.Giricek Uta 22 12.4 5.8 8.3 4.3 1.4 0.7 12-10 Phi 12 9.0 4.7 3.1 1.2 0.9 5-7
26 D.Diop Dal 52 17.0 3.6 16.0 3.0 5.2 0.5 34-18 Njn 17 13.2 3.5 12.7 2.2 4.4 0.4 6-11
27 B.Wallace Chi 50 32.3 8.0 14.0 5.1 8.8 1.8 19-31 Cle 14 28.0 6.1 14.1 4.9 8.1 0.6 9-5
28 F.Elson San 43 12.9 5.1 9.4 3.5 3.3 0.4 29-12 Sea 8 8.2 3.7 2.6 2.9 0.4 1-7
29 K.Korver Phi 25 26.1 11.5 12.4 10.0 2.9 1.3 12-13 Uta 39 21.2 9.1 17.1 10.0 1.9 1.3 30-9
30 S.Swift Mem 35 15.5 7.2 18.8 6.8 3.7 0.6 11-24 Njn 14 10.0 3.8 14.6 3.3 2.7 0.3 6-8
31 M.Allen Njn 48 15.7 6.5 12.0 5.4 2.7 0.6 21-27 Dal 16 10.4 3.0 16.9 3.1 2.2 0.5 9-7
32 K.Thomas Sea 42 25.0 7.8 18.5 7.5 8.8 1.3 13-29 San 16 18.7 6.4 15.4 5.0 5.4 0.6 10-6
33 D.Stoudamire Mem 29 21.4 9.8 13.9 7.3 2.4 3.9 8-21 San 22 14.4 6.7 6.0 3.7 1.5 1.7 16-6
34 S.Cassell Lac 38 25.4 15.7 19.7 12.8 2.8 4.7 14-24 Bos 7 18.2 9.7 6.8 5.6 1.9 2.3 6-1
35 M.James Hou 33 16.1 9.0 11.2 6.5 1.6 1.6 17-16 Nor 12 8.8 4.2 3.5 0.8 0.4 7-5
36 K.Brown Lal 23 21.9 7.4 11.6 5.7 5.7 1.2 15-8 Mem 13 12.2 3.8 11.8 2.5 3.3 0.9 2-11
37 A.Wright Njn 42 25.0 9.0 9.7 7.1 3.0 1.6 17-25 Dal 6 13.6 5.9 13.2 5.0 2.3 0.8 5-1
38 A.Johnson Atl 43 26.1 9.4 14.4 6.6 2.3 4.7 20-23 Sac 16 12.7 4.7 10.1 3.3 1.4 1.8 7-9

What about main men J-Kidd, Shaq, Pau Gasol and Matrix? J-Kidd is spending less time on the court with using the ball 4.19 fewer than he was doing it with the Nets. Despite having less playing time and using fewer possessions, Gasol plays more efficient basketball in Lakers uniform . Shaq’s playing time didn’t change but he is using 3.16 fewer balls than he was averaging in Miami. Shawn Marion seemed to fill the statsheet with getting more playing time and ball usage rights but his efficiency went significantly down (3.49) in Miami. The research showed that Marcus Banks led the traded players as he had his PER jumped from 12 to 18.

  • USAGE is number of possessions a player uses in his playing time in a game.

[USAGE FORMULA=(FGA+0.44*FTA+0.33 AST+TO)*(LEAGUE PACE/TEAM PACE)]

  • MIN is the average playing time
  • PER stands for Player Efficiency Rating, see the Top 100 Player List

S.Parker, T.Lue, A.Griffin, M.Ager, J.Magloire, T.Ratliff, S.Lasme, I.Newble and L.Wright couldn’t make it to the research as they have yet to play 5 games with their new teams.