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Can math help you understand basketball?

Last week in my Hoops Lab intro I discuss how Allen Iverson is becoming the poster child for using advanced stats to help measure how good a player really is.  The links I site in that write-up argue that you should give less credence to Iverson’s gaudy scoring average and more to newer stats that suggest that Iverson is in fact not as good as the players he has been traded for: Chauncey Billups and Andre’ Miller.  This was an extremely controversial thing to say two years ago before the Iverson/Miller trade, but the results of the two trades have more people willing to give these new stats a chance.

Historically, people have used some combination of traditional stats (i.e. points, rebounds, assists, etc.), team success, personal observations and “gut” feelings when deciding how to rank NBA players like Iverson and Billups.  These days, though, the emerging field of APBRmetrics (stats that seek to quantify basketball in similar ways to how the Moneyball guys quantified baseball) are helping many of us get a clearer idea of what makes “good” basketball.  Over the past few years I have gotten more and more into APBRmetrics, to the point now where I find myself as an advocate trying to convince the masses of their use.

Unfortunately, many don’t completely understand these stats and thus help prevent APBRmetrics from more wide-spread acceptance.  There are two main types of these people: One group believes that no advanced stat is good enough to explain a complicated sport like basketball and dismiss all attempts as useless (the skeptic).  The other school of thought is the opposite extreme, who attempt to use stats to make their arguments but they do it incorrectly and thus lead many skeptics to say “See!  Those stats are bogus!” (the ignorant know-it-all).

There are an awful lot of skeptics and the know-it-alls out there, and the only way to combat them is through information.  That’s where I come in.  Over a series of blogs, I’m going to break down a lot of the more popular APBRmetrics that are in use today.  I’ll talk about PER, +/-, Roland Rating, Wins Produced, Offense/Defense Rating, Win Scores, and any other measure that catches my eye.  I’m not going to get into the complex math behind them, but I will tell you exactly what each is measuring, how it should be used, and give some examples to make this clear.  Hopefully by the time this season ends, the five of you that read my blogs regularly will have a better understanding of how to use these non-traditional stats to rank and categorize players.

For today’s intro, though, are there any willing to sign their name in the comments as a skeptic, or as someone that would just like to know more about these stats?  Do you buy that a player like Iverson should be questioned by some abstract stat despite his third all-time NBA scoring average, or do you think this was just an isolated case where the advanced stats guys got lucky?  And finally, if there are any stats in particular that you’d like me to look at in the coming weeks, let me know in the comments and I’ll try to accommodate.

Comments

By: Dalton Del Don
On: 12/17/2008 5:40:00 PM		 I look forward to your future blogs. Basketball has always been behind MLB and NFL as far as in depth stats as you mention...After watching the Nuggets and Pistons play after that trade, it would be pretty difficult not to come to the conclusion C. Billups is a better basketball player than A. Iverson. Speaking of stats, A.I.'s impressive steal numbers might lead one to believe he is a solid defender, when in fact, he's simply atrocious during on the ball defense.
 
By: The Professor
On: 12/17/2008 10:49:00 PM		 Great point. The steals (and/or blocks) vs. actual good defense is another case that I'd like to make. Hopefully through things like defensive rating, defensive win shares and defensive efficiency (maybe even opponent PER as well) we can get a better handle on what really constitutes a great defender.
 
By: nayfel
On: 12/19/2008 8:58:00 AM		 I am in the minority, I enjoy basketball rottiserie better than baseball or football. I guess it's because everyone contributes to each category and that gives additional value to one category type guys. Anyways, I always like to use extended stats when reviewing bball data and I welcome these blogs.
 
By: paz840
On: 12/29/2008 9:11:00 AM		 I'm also looking forward to your future articles Prof. Basketball is one of favorite fantasy sports largely because of the multitude and complexity of statistics, and I have always been looking for and creating my own metrics to use to better analyze players.
 

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