Repeating History in Portland

Posted on January 6, 2009 by


The Portland Trail Blazers came into existence in 1970.  In the team’s first four seasons success proved elusive.  Not only did the team fail to have a winning season, Portland never even managed to reach the 30 win threshold.  As is often the case in North American sports, failure is rewarded.  For the Blazers, the reward came in 1974 when Portland took Bill Walton with the first pick in the NBA draft.   

In Walton’s rookie season the Blazers managed to win 38 games and even score more points than their opponents.  The next season the team took a small step back, but the 1976-77 team – led in Wins Produced by Bill Walton – managed to both lead the league in efficiency differential (offensive efficiency minus defensive efficiency) and win the NBA title.  

Walton was hurt the next season and by the time he took the court again in 1979 he was wearing the uniform of the San Diego Clippers.  Without Walton, though, Portland still found some success.  After posting a negative efficiency differential in 1979-80, the Trail Blazers embarked on a string of 23 seasons where their efficiency differential was always in the positive range.  Although another championship proved elusive, no other franchise has been able to put together a longer streak of above average performances (at least not since 1973-74, the first year we can measure efficiency differential).

History Repeats

In 2003-04 this streak came to an end.  And over the next three seasons – just as we saw at the onset of this franchise – success proved elusive. The team only averaged 30.3 wins per season and Portland’s efficiency differential was always in the negative range.

Once again, such failure was rewarded.  In 2007 Portland selected Greg Oden with the number one pick in the NBA draft.  Unfortunately, Oden was injured in the summer of 2007 and missed the entire 2007-08 campaign. Despite losing Oden, Portland still managed to win half its games last season (although the team’s efficiency differential was in the negative range). 

Such success without Oden suggested that Portland was a team on the rise.  And in 2008-09 we see some evidence of this ascension.  After posting a -1.06 efficiency differential in 2007-08, Portland’s differential stands at 3.19 after 34 games in 2008-09.  Such a mark is consistent with a team that will win about 49 games.  In other words, after winning 41 games last year, Portland has so far improved by about eight games.  Yes, this is a leap forward although perhaps not quite the leap some people envisioned last summer.

When we look at the individual players we can identify who is responsible for Portland’s success.

Table One: The Portland Trail Blazers after 34 games in 2008-09

From Table One we see that Portland currently employs six players – Joel Przybilla, Brandon Roy, Rudy Fernandez, Steve Blake, Greg Oden, and Nicolas Batum — who are posting WP48 [Wins Produced per 48 minutes] marks that are above average (average is 0.100). Each of the veterans in this list has posted above average numbers in the past.  And although few expected Batum to make a significant contribution, the play of Oden and Fernandez during their rookie seasons is not unexpected.

Missing Lottery Picks

Virtually all of this team’s wins can be traced to this list of players.  If we look at the remainder of the roster we see a number of lottery picks, but not much productivity.  For example, LaMarcus Aldridge was selected with the second choice of the 2006 draft.  Thus far – as Table Two notes – Aldridge has yet to produce wins at an above average level.

Table Two: Evaluating LaMarcus Aldridge

When we look at the individual stats we see where Aldridge succeeds and fails.  Aldridge is very good at taking shots from the field. As a consequence, he’s an above producer of points.  He is also good at blocking shots and he avoids turnovers.  But he’s below average on the boards, he doesn’t get many assists, and he can’t get to the free throw line.  And when we look at the total package, as noted, he’s a below average performer.

A similar story can be told about Martell Webster, Channing Frye, and Ike Diogu.  Each of these players was taken in the lottery and each has yet to finish a season with an above average WP48 mark.  And thus far, Jerryd Bayless – the team’s 2008 lottery pick – has not impressed in limited minutes.

A Bright Future

Although we don’t know that the underperforming players will continue to offer disappointing levels of productivity, it seems likely that Portland will have to look elsewhere for additional wins.  Fortunately it looks like elsewhere is currently on the roster.  Four of the six above average players in Portland are under the age of 25.  This means that it is quite possible that these players will improve.  Perhaps the most likely candidate to improve is Greg Oden.  Oden is only21 years of age and has only played in 28 NBA games.  Although he has been above average thus far, one suspects he will get even better.

If that happens, Portland will once again be led by a big man who is not a prolific scorer, but is able to get rebounds.  Unfortunately, just like we saw with Walton, the new big man in town is also prone to injury.  Portland fans hope, though, that Oden can lead the Blazers to another title before injuries derail a promising career.  And if Oden is following the Walton schedule, that championship will come in Oden’s third year (or 2010-11).  Hopefully for Oden’s sake, another major injury doesn’t occur in 2011-12.

– DJ

The WoW Journal Comments Policy

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.