Today’s guest post — the WoW Journal NBA Forecast for 2008-09 – is by Erich Doerr . Erich first contacted me prior to the 2006 NBA Draft with a statistical preview in hand. Each subsequent year has seen improvement in the depth and breadth of his analysis. Outside of his basketball writing, Erich does consulting work for major software products by day and has started a fledgling sports-themed Open Source software initiative by night.
As the NBA season begins, each team begins with zero wins, zero losses, and playoff dreams. Where will these teams likely be six months from now? With helpful input from Dave Berri, I have developed a rudimentary model to predict team performance with Wins Produced.
Projecting the NBA field is difficult and there are many challenges to overcome, including player development models, minute allocation methods, and coaching changes. In particular, we have a number of choices when it comes to projecting Wins Produced. Should we just use last year’s performance? How about what a player did in prior seasons? And if these seasons are used, should the seasons before last year be weighted in some fashion? Obviously the answer to these questions will impact your projections.
And then there is the whole issue of allocating minutes. How many minutes a player ultimately see depends on the decisions of his coach and the player’s health. Neither of these factors is easy to forecast.
In sum, there are a host of challenges to overcome in making these projections. Here are some details on how these challenges were addressed.
This year’s Wins Produced team projections are the results of a Monte Carlo analysis on the NBA schedule and team based WP numbers. This method produced three sets of Wins Produced projections:
- Using last year’s minutes played and last year’s productivity
- Using Kevin Pelton’s projected minutes played with last year’s productivity and Berri’s rookie projections
- Using Pelton’s projected minutes played with a three year weighted average of productivity and Berri’s rookie projections.
- Using Pelton’s projected player statistics
Within the Monte Carlo model, division and playoff odds are generated, and the results are summarized here:
Other Statistical Prognostications
In the spirit of sabermetrics, I have roamed basketball’s statistical analyst community and gathered other projections for the coming season. There are many diverse opinions on the coming season, even within stat-favoring prognosticators, but certain themes emerge.
It’s important to note that there is a very high correlation between the projections of the various models. There are no two models that do not have at least a 0.80 correlation, and many have a correlation with another model in excess of 0.90.
Given the similarity in projections, it’s not surprising to see that all of the models cite Boston as the definitive top dog in the East, while the vast majority also like the Lakers out West. All expect the East’s winning percentage to improve over the West’s (.473 last season), but not overtake the lead.
The major difference between popular opinion and the stat heads would be Indiana’s forecast (this issue was noted in this forum last week). The Vegas line lists them at 35 wins, but all the included forecasts have Indian above 36 wins. In fact, one of the Wins Produced projections indicates Indiana may be a contender for a home court playoff series. By the stat-heads, Vegas’s Over/Under line is also too pessimistic on Boston and the Lakers.
At the other end of the league stands the teams that are not likely to make the playoffs. Of these, which teams are likely to top the draft boards? Last year, the top draft slots went to an injury-decimated Heat squad and a lottery lucky Chicago franchise. If these projections are to be believed, the odds should favor Memphis and Oklahoma City as the two clear cut cellar dwellers.
- Kevin Pelton is a former employee of the former Supersonics. He currently writes for BasketballProspectus.com and favors Wins Above Replacement Player as his metric of choice.
- John Hollinger brings statistical analysis to the masses via ESPN.com and ESPN’s Insider service. He created Player Efficiency Ratings (PER) and also studied economics in his undergraduate years.
- Mountain is a frequent commenter on the Wages of Wins Journal and a prominent member of the APBRmetrics forum.
- Accuscore is a budding sports statistical analysis company creating models and running Monte Carlo simulations across major sports. Their content regularly appears on ESPN.com.
- Wylie21Davis is a poster on APBR metrics and author for ArmchairGM.com.
- MikeG is a APBRmetrics poster.
Note that Accuscore and Kevin Pelton are not done releasing their season predictions at the time this post was published. I will update the projections as they become available and review the results after the season.
And finally I’d like to thank Dave Berri for his input and access to this forum. Thanks for reading and enjoy the games.
- Erich Doerr
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Our research on the NBA was summarized HERE.
Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:
Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.