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...

Unsolved Mysteries: NBA Edition #9

We have reached question 9 in Kevin Pelton's 10 questions to solve in the NBA

Question 9:  What is the market value for player performance?

Obviously this question is asked a lot especially when people wonder why athletes are paid millions of dollars to play a sport.  What warrants a high salary?  Is Lebron James really worth $50 million like he thinks (or $40 million according to Pelton)?  Are a lot of players overpaid?


I like Pelton's use of WARP (wins above replacement metric), but I don't think this necessarily encompasses all what a player is worth.  In addition to the number of wins a player can provide a team, there are the other aspects of revenue management that need to be included.  Such things are the ability to generate ticket sales, sponsorship opportunities (as we will start to see on backboards next year) and other revenue-generating circumstances. 

Are players paid what they are worth -- I think it really comes to a comparison to other players.  It's not the dollar amount that is of interest (although a GM or owner might say otherwise), but rather it is how much a player makes compared to others.  Lebron should have the highest salary in basketball, but chose not to in order to help form the Big 3.  Therefore, does it really matter if players are paid what they are worth (Chris Paul and Dwight Howard in 2013)?  It only really matters that players aren't overpaid (Kobe anyone?) and organizations aren't "losing" money on their supposed stars.  

If it came down to player performance through various statistics (personal and +/-) and WARP, sign me up!  Otherwise (and unfortunately) it seems to come down to perception, mania (Lin and Terry), agent skills and greed that drive salaries up and down -- and pure stats lose the battle here... 

Thursday, June 13, 2013

Unsolved Mysteries: NBA Edition #8

We are continuing on with Kevin Pelton's 10 questions to solve in the NBA

Question 8:  How do statistics translate from other leagues to the NBA?

Luck would have it we are looking at this exact problem.  We have been asked in the past if one could determine which players in the European leagues would do well in the NBA.  However, we are currently examining which players at the collegiate level will do well in the NBA.  I cannot yet get into the specifics, but we are able to determine with high accuracy which players fit into specified categories (level of NBA talent) based solely on box score data in college.

Pelton discusses the use of translations to determine how college players will do in the NBA.  He notes that while this is successfully used in baseball, the ability to translate statistics is much more difficult.  We are taking a somewhat different look at the problem. 

Every NBA player has been categorized based on their talent/success in the NBA.  This could be by statistics, influence or any number of subjective measures.  We then break these groups up by positions so that we do not measure centers the same as point guards (Pelton did the same).  Each position possesses their own unique set of statistics that explain each player (common techniques such as principal component analysis or factor analysis can be applied here). 

After capturing the right statistics for each group, we can then apply various prediction algorithms to determine which players belong in which groups.  The beauty behind our algorithms is that they "see" things we could easily have missed!

I look forward to sharing our results.  With this information, we take the guessing out of the draft and provide insight into the true floppers of the NBA. 

A fantastic question by Kevin Pelton -- which should be number 1 on the list.  If you claim to love Moneyball, this question should just scream potential to you! 

 

Unsolved Mysteries: NBA Edition #7

It seems only fitting that we examine question 7 of Kevin Pelton's 10 questions.

Question 7:  What role does coaching play in the success of teams and players?

The entire NBA nation might say a tremendous role since the Spurs' Popovich has shut down Lebron James with his "I dare you to shoot jumpers" defense.  So far, the King has been dethroned. 

Very little analytical work has been conducted on coaches, as pointed out by Pelton.  Coach tenures are very short in the NBA with the exception of several notables.  Next to Popovich (1996) and Doc Rivers (2004), the longest tenured coaches in the NBA are Spoelstra, Carlisle and Brooks since 2008.  Each of these coaches have made the NBA Finals. 

This fact alone shows some merit that the success of teams may rely on coaching.  However, are the players growing?  Are they getting better under direction?  Or do these teams just have good players?

Analytically, I do not see the value in pursuing this question.  Every coach approaches the game differently and every player accepts coaching advice in a different manner.  The key is finding the right coach that fits the system in place (Spoelstra is a decent candidate) or building a system around the right coach (Doc and Popovich).