Marty Burns Ranks the Best

Posted on February 15, 2008 by


This past week I have been traveling about the country.  So my attention to the Wages of Wins Journal has waned a bit. 

Thursday night, though, I finally got home.  And once I got home (and said hi to my wife and daughters), my thoughts turned back to this forum (at least, eventually).  All I needed was something to write about. 

A scan of my favorite sports sites and writers led to the following column by Marty Burns of

Aligning the stars: Ranking the players in NBA’s midseason showcase

There were 26 players named to the All-Star game – 10 starters chosen by fans, 14 players chosen as reserves by the coaches, and 2 players chosen as injury replacements.  Before reporting his rankings, Burns offered the following description of how these 26 players were listed:

The NBA All-Star Game is a chance for the league’s brightest individual talents to shine. With that in mind, we thought it would be fun to do a twist on Power Rankings and take a look at how this year’s All-Star selections stack up against each other. Keep in mind, this isn’t a breakdown of the MVP race or a ranking based on career achievements. It is simply a look at how these 26 All-Stars (24 original picks and two injury replacements) stand right now.

So Burns is looking at how these players “stand right now.”  Given this criterion, I thought it would be good to look at how these players rank in terms of Wins Produced at the midpoint of the 2007-08 season; and then compare the Wins Produced ranking to what Burns is saying. 

Okay, not sure this is fun.  But again, I am just looking for something to talk about on a Friday.

Table One:  Marty Burns vs. Wins Produced

Here is what leaps out at me when I make this comparison: Burns seems to believe that the Western Conference stars are much better than the stars from the East.  Of the top twelve players in the Burns rankings, nine come from the Western Conference. And since Kevin Garnett is not playing, the Eastern roster will only have two players – LeBron James and Dwight Howard – in the Burns top twelve. 

When we turn to Wins Produced, six of the top twelve are from the East.  In fact, six of the top eight in Wins Produced play in the East.  Yes, the quality of play is lower in the East.  Still, the East does have a number of players – Jason Kidd, Chauncey Billups, Caron Butler – who appear to be underrated by Burns.

Butler, like Garnett, is not playing.  Consequently, the average Eastern player falls short of the average player in the West.  The difference, though, is not that great.  The average Eastern star has a 0.223 WP48 [Wins Produced per 48 minutes].  In the West the average WP48 is 0.233.

What does all this mean?  Given the injuries to the East, I think the West should be favored.  But I would not be surprised if the Eastern stars pull off the upset. 

Let me close by noting that the sophomores did defeat the rookies 136 to 109 in the T-Mobile Rookie Challenge.  And this was the predicted outcome when we looked at Wins Produced.  Oh, and Andrea Bargnani – who I mentioned was a problem with the sophomore squad – played the least amount of minutes for the victors (but still played badly). 

What does all this tell us about the actual All-Star game?

First, the sample is only one, so we really can’t draw much of an inference.

And second, I am not sure I made an emphatic prediction about the All-Star game.  Looking over what I wrote…

– if the West wins I can claim that the numbers said this was the likely outcome.

– if the East wins I can claim that an upset was certainly possible.

So basically I can claim I was correct regardless of outcome.  Gotta like that kind of a prediction.

– DJ

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.