Assigning Blame in Atlanta and Boston

Posted on March 12, 2010 by


After 41 games the Atlanta Hawks and Boston Celtics posted the following marks:

Atlanta: 27 wins, 5.9 efficiency differential (offensive efficiency – defensive efficiency)

Boston: 28 wins, 6.4 differential

In the 22 games since this midpoint (as of Wednesday night), both teams have – as the following numbers indicate – performed somewhat worse. 

Atlanta: 13 wins, 2.7 differential

Boston: 12 wins, 0.7 differential

Clearly both teams have declined relative to what we saw after 41 games.  So what’s the problem?

A non-statistical approach might look at factors like teamwork, defensive intensity, and chemistry.  Player statistics, though, allow us be a bit more definitive.  Specifically, statistics allow us to separate a player from his teammates.  And that allows us to assign responsibility for the outcome we observe.

Let’s start with the Atlanta Hawks.  Tables One-Two provides two perspectives on this team.

Tables One-Two: The Atlanta Hawks after 63 games in 2009-10

Table One reports what the players for the Hawks have done across the entire season.  In addition, we see what the veteran players did in 2008-09.  As one can see, the story told since early in the season remains the same. Josh Smith – who has improved with respect to shooting efficiency, rebounds, assists, steals, and blocked shots – has increased his WP48 [Wins Produced per 48 minutes] from 0.116 to 0.284.

And as Table Two reports, Josh Smith is even better in the second half.  Since the midpoint, Josh Smith has posted a 0.305 WP48.  When we look at the remainder of the roster, for the most part we don’t see substantial changes in Wins Produced.  The lone exceptions are seen with respect to the production of Al Horford and Mike Bibby.  It appears those two players are the most responsible for the Hawks second-half decline.

Now let’s look at the Celtics. Unlike the Hawks – who have improved in 2009-10 (thanks primarily to Josh Smith) – the Celtics are winning less than their 2008-09 performance would suggest.  The veterans performance in 2008-09 suggests the Celtics should have already won 52 games this season.  Much of the twelve game drop-off – as Table Three indicates – can be linked to the production of Ray Allen, Eddie House, and Rasheed Wallace (three relatively old players).

Tables Three-Four: The Boston Celtics after 63 games in 2009-10

Since the midpoint, this decline has quickened.  Again, the team has only posted a 12-10 record across the past 22 games.  Virtually all of these wins can be linked to the play of Rajon Rondo, Kevin Garnett, and surprisingly, Ray Allen (who is not quite what he was last year, but is now closer).  Although this trio has played well, Paul Pierce, Kendrick Perkins, and Rasheed Wallace are offering much less. 

One could speculate as to why we see such declines.  Possible explanations include the problems of a small sample (although 22 games isn’t that small of a sample), injury, or age.  The best source for such explanations should be the coaches watching the players every day.  Answering the question “how productive are these players?”  serves to focus the attention of these coaches.

In talking to people in sports, though, one senses an unwillingness to be so focused.  In other words, coaches and teammates seem unwiling to single out individual players. It simply seems easier for people associated with the Celtics to say “well, we need to do better as a team.”  This approach, though, isn’t very helpful.   The data suggests the problems for this team are really linked to just three players (and for the Hawks it’s just two players).  For the Celtics to return to what we saw in the first half of the season it seems likely that the three players identified – and especially Paul Pierce — are going to have to produce more.  Yes, Paul Pierce really deserves the most blame for what we have seen in Boston since the midpoint.

– 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.