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Trades Working Out?

What you will get in this article is kind of simple and easily comparable stuff. Don't expect me to make judgements 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 TEAMSTATS WITH THE NEW TEAM
PLAYERTEAMGPMINUSAGEPERPTSRBDASTW/LTEAMGPMINUSAGEPERPTSRBDASTW/L
1K.SnyderHou98.84.5 3.81.30.93-6Min1426.69.814.58.44.01.97-7
2D.WestSea3520.610.111.56.82.73.29-26Cle1631.012.713.09.23.64.39-7
3N.FazekasDal62.81.3 0.70.70.23-2Lac911.34.118.93.44.40.41-8
4M.BanksPho2412.75.512.15.20.81.019-5Mia1221.410.418.19.52.13.02-10
5G.GiricekPhi129.04.7 3.11.20.95-7Pho917.68.316.58.71.61.47-2
6J.CrittentonLal227.64.1 3.31.00.818-4Mem2015.67.810.96.32.50.84-16
7R.MurrayDet1918.111.615.77.51.93.413-6Ind1122.314.418.512.42.42.56-5
8S.MarionPho4736.314.423.415.89.92.134-13Mia1539.918.819.915.311.92.73-12
9D.HarrisDal3930.116.721.414.42.35.328-11Njn1333.720.118.316.13.26.24-9
10L.HughesCle4129.915.913.712.33.52.324-17Chi1432.818.316.514.63.94.15-9
11M.BibbySac1531.417.515.913.53.75.08-7Atl1933.918.516.013.72.86.98-11
12D.GoodenCle5230.414.014.611.38.31.030-22Chi1432.115.321.314.19.21.85-9
13W.SzczerbiakSea5023.412.418.413.12.71.412-38Cle1522.911.612.39.13.11.78-7
14T.HassellDal3712.32.95.72.11.20.724-13Njn1612.43.43.92.31.40.65-11
15J.DixonTor3711.46.313.04.21.31.819-18Det1011.35.811.04.41.31.48-2
16S.O`NealMia3328.416.020.714.27.81.48-25Pho1628.312.818.211.910.61.810-6
17J.SmithChi5022.712.019.811.25.30.920-30Cle1622.18.617.77.85.60.99-7
18J.CollinsNjn4315.72.32.41.42.10.419-24Mem1913.93.15.32.22.60.25-14
19D.MarshallCle1114.05.19.93.72.70.55-6Sea1011.64.212.63.63.20.30-10
20P.GasolMem3936.519.323.718.98.83.010-29Lal1933.917.028.118.87.93.415-3
21B.JacksonNor5019.18.414.77.02.41.833-15Hou1116.49.017.77.62.41.78-3
22B.WellsHou5121.811.816.69.25.11.631-20Nor918.910.723.59.83.40.85-4
23J.KiddNjn5136.919.018.611.38.110.423-28Dal1733.914.819.78.46.49.39-8
24S.WilliamsAtl3611.33.911.83.03.00.315-21Sac178.03.9 3.92.30.18-9
25G.GiricekUta2212.45.88.34.31.40.712-10Phi129.04.7 3.11.20.95-7
26D.DiopDal5217.03.616.03.05.20.534-18Njn1713.23.512.72.24.40.46-11
27B.WallaceChi5032.38.014.05.18.81.819-31Cle1428.06.114.14.98.10.69-5
28F.ElsonSan4312.95.19.43.53.30.429-12Sea88.23.7 2.62.90.41-7
29K.KorverPhi2526.111.512.410.02.91.312-13Uta3921.29.117.110.01.91.330-9
30S.SwiftMem3515.57.218.86.83.70.611-24Njn1410.03.814.63.32.70.36-8
31M.AllenNjn4815.76.512.05.42.70.621-27Dal1610.43.016.93.12.20.59-7
32K.ThomasSea4225.07.818.57.58.81.313-29San1618.76.415.45.05.40.610-6
33D.StoudamireMem2921.49.813.97.32.43.98-21San2214.46.76.03.71.51.716-6
34S.CassellLac3825.415.719.712.82.84.714-24Bos718.29.76.85.61.92.36-1
35M.JamesHou3316.19.011.26.51.61.617-16Nor128.84.2 3.50.80.47-5
36K.BrownLal2321.97.411.65.75.71.215-8Mem1312.23.811.82.53.30.92-11
37A.WrightNjn4225.09.09.77.13.01.617-25Dal613.65.913.25.02.30.85-1
38A.JohnsonAtl4326.19.414.46.62.34.720-23Sac1612.74.710.13.31.41.87-9

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.

Last Updated ( Monday, 01 September 2008 )
 
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