Monday, June 17, 2013

Unsolved Mysteries: NBA Edition #10

The final question in Kevin Pelton's 10 questions to solve in the NBA is finally here!

Question 10:  How do we best predict the outcome of games or series?

We have relished the question and hopefully you have been following our website to see us actively publish our daily predictions in the NBA (winner and spread).  Many people ask how we do our predictions and maintain such high accuracies.  A few years ago I published an article that explains in high level detail how I do predictions in the NBA.  Since then, we have maintained a similar approach to predicting the winner of every game. 


First, we try to keep things simple.  It really comes down to how teams matchup -- through their basic stats.  The better shooting team will typically win games.  Combine that aspect with strong defense and you are almost a sure thing.  Typically, there are no surprises in the NBA -- standings are usually the same year after year (unless trades or injuries occur).  Was anyone surprised that Miami and OKC finished at the top?  Are we shocked to see the Spurs in the finals (after Westbrook went down)?  Although the Bobcats tried to mislead us at 7-5, did they not finish where they were supposed to?

Keeping to the idea of being simple, a lot can be explained on why a team wins through their box scores.  It takes a little craftiness to determine which box scores to use (home/away, last few games, vs conference, vs division, etc.).  Another aspect is to determine which statistics are important.  This can be accomplished through feature reduction by techniques such as principal component analysis or factor analysis.  Finally, a strong prediction algorithm (such as artificial neural networks) can take a seemingly impossible problem and make is simple. 

So, in short, I don't think this is a problem to solve.  We are doing it every day and have maintained an 81% accuracy in predicting the winner of every NBA game this season.  Most of our incorrect decisions came at the beginning (not enough data) of the season and at the end (injuries, rest) of the season.  Are there better stats out there to use -- maybe -- but why make a problem more difficult than necessary?

This concludes our examination into the 10 questions to solve.  We will start posting some work we are currently doing and information related to other sports.  Will the Spurs win in 6 -- our model says no...

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