Very Quick Thoughts on the McGrady and Martin Trade

Posted on February 18, 2010 by


It was announced today (or maybe last night) that the Rockets and Kings have a deal involving Tracy McGrady and Kevin Martin.  Here is my first impression of this move (and I am ignoring completely what the Knicks might do today).

Once upon a time, McGrady was one of the most productive players in the game.  From 2000-01 to 2002-03 he posted the following WP48 [Wins Produced per 48 minutes] marks. 

2000-01: 0.279

2001-02: 0.303

2002-03: 0.325

But after peaking in 2003 (around the age of 23), McGrady’s production has tumbled.  In 2003-04 and 2004-05 his WP48 mark barely surpassed 0.200.  And while McGrady has been consistently above average (average WP48 is 0.100), his marks the past four years have been below 0.200.

2005-06: 0.152

2006-07: 0.186

2007-08: 0.110

2008-09: 0.163

Of course this year he has only played 46 minutes.   So at this point, McGrady was offering essentially nothing to the Rockets on the court. 

Today, though, it was announced that McGrady’s nothing has been traded for Kevin Martin.  Here is what Martin has done [with respect to WP48] across the past four year. 

2005-06: 0.160

2006-07: 0.199

2007-08: 0.192

2008-09: 0.115

In three of the past four years, Martin has offered more than McGrady.  Plus Martin is four years younger.  So it looks like the Rockets have turned a nothing into quite a something.

There are, though, some issues to consider.   Martin was only barely above average last year.  And this season, after just 22 games (he missed more than 30 due to injury), his WP48 stands at 0.100.  Obviously these numbers are not quite what we saw the last time Martin played 80 games in a season (2006-07).

Beyond questions about Martin’s ability to produce and stay healthy is the additional players included to make this trade happen.  The Rockets are sending Carl Landry and Joey Dorsey (plus cash) to the Kings for Kenny Thomas, Hilton Armstrong, and Sergio Rodriguez.  At the moment, Landry’s Wins Produced of 4.7 represents the third highest mark on the Rockets (Luis Scola and Kyle Lowry have eached produced 5.1 wins this season).  And Dorsey – in just 54 minutes – has posted a 0.304 WP48.  The loss of these two players leave the Rockets with Scola and Chuck Hayes as the only above average performers at power forward and center.  So although the transformation of McGrady into Martin could be quite a feat, the loss of Landry in the frontcourt is going to limit the positive effects of this trade. 

As for the Kings…Landry is already the most productive big man on the roster.  And with Tyreke Evans and Omri Casspi, it looks like the Kings now have a trio of productive players to build upon. 

Putting the whole picture together… it looks like the Kings are now a better team and Houston – Martin can return to form – could be somewhat better.  And now that I see this, I wish I had spent more of this quick post on the Kings (but that’s what you get when you write before you finish thinking about something).

Quick Update: The pieces added to this trade from the Knicks don’t really change the story.  Jordan Hill, Jared Jeffries, and Larry Hughes are all below average performers this year.  Hill, though, is a rookie.  So he might develop into something (although his college numbers weren’t encouraging).

Another quick update:  Forgot to note the draft picks.  If the Knicks continue to make poor choices (a real possibility) and therefore do not build a winner in the near future, this could be a very good deal for the Rockets. 

– DJ

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Our research on the NBA was summarized HERE.

The Technical Notes at provides substantially more information on the published research behind Wins Produced and Win Score

Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:

Simple Models of Player Performance

Wins Produced vs. Win Score

What Wins Produced Says and What It Does Not Say

Introducing PAWSmin — and a Defense of Box Score Statistics

Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.