Analytics No Easy Layup for the NBA


Daryl Morey gained notoriety a few years back as the first National Basketball Association general manager hired for his analytics prowess -- but is this man, with the number nerd's dream job, doing his current team or the league justice?

The freshly started 2012-13 season marks Morey's sixth with the Houston Rockets. And the MBA from MIT (where he also teaches an analytics course) has had teams with winning seasons for each of the previous five seasons. One of his teams even won a playoff series. Before Houston, he served as senior vice president of operations and information for the perennially successful Boston Celtics. He is but the seemingly most successful example of a growing group of analytics and statistics experts involved in pro basketball: At least 20 teams have analytics professionals on staff today.

And yet, despite the apparent growth and significance of "money ball" in the NBA, Morey isn't delivering on the analytics promise for the Rockets. He's had winning records for the last five seasons, but he's not been to the playoffs at all for the last three.

Most, if not all, NBA watchers have deemed his most recent off-season a cataclysm. He virtually declared the failure of his past five seasons by blowing up his team, trading Samuel Dalembert and Chase Budinger for draft picks. Purportedly, the plan was to continue maneuvering during draft time to get a coveted early first-round pick. Or Morey hoped to somehow land superstars Dwight Howard or Pau Gasol. None of this worked.

I won't bore you or myself with the details of who these players are or how NBA drafts work, and will instead make my point: Morey essentially trashed his work of the past five years to land a superstar. As anyone knows -- even casual pro basketball fans -- the way to winning in the NBA (let alone win a championship) is to have a superstar (or three in the Miami Heatís case). Morey made it plain that whatever analytics-based master plan he had been following for the past five years was not working.

He followed up his failure leading up to draft day with a couple of other possibly hugely disappointing (and apparently not well reasoned) moves. One was giving $25 million to last season's media darling, Jeremy Lin, from the New York Knicks. This despite having waived him at a rock-bottom price at the start of last season. Now, Morey is falling for one of the worst knee-jerk reactions an executive can have in any sport: Chase the free agent cashing in on fluky success. Again, is this his admission of past analytics failure?

His other mistake? After his failed draft maneuverings, Morey was left with three first-round draft picks, all in the middle of the round. In football, that would be amazing. In the NBA, it's a handicap. The Rockets are likely to have gotten three role players (not superstars), yet without the court space to develop their limited talents. There are only five players on the court at a time, and only so many minutes in a game.

What's worse, one of them, Royce White, is making headlines -- for missing parts of training camp and for his anxiety disorder and fear of flying, not for impressing people with his precociousness on the court. With White in particular, you have to wonder if Morey is chasing a dream that he saw in the data, without considering old-school scouting considerations like character and team cohesion.

Ultimately, Morey's failings will not discredit the work of analytics in basketball. After all, just as I am writing this, the 21st NBA team hired an analytics expert: the Philadelphia 76ers. But what it might show is that success in the NBA is a daunting challenge, and that analytics is just one weapon. In other words, you might not want to make a quant the boss. Or if you do, you might just want to also have a legitimate superstar (or three) on the court to make him look good.

Sports analytics -- do you love it or hate it? Share your opinion below.

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Re: Mad science -- ND
  • 11/12/2012 10:49:46 PM
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@SaneIT, he worked for the Boston Celtics before, and he plays a role with MIT's sports business center. I'd imagine that Money Ball has been around the NBA almost, if not as long, as in the MLB, except that unlike in baseball -- where it's a far more team sport driven by probabilities -- basketball games can be dominated by one or two players on the court.

Re: Mad science -- ND
  • 11/9/2012 6:54:12 AM
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That makes perfect sense.  I don't know much of the back story, did he work with other teams or the league as a whole or did the rest of the league pick up on what he was doing and imitate it?  In a closed market like a sports league I imagine that is one team is successful everyone else is going to try and figure out why.  I just wonder what his involvement was.

Re: Mad science -- ND
  • 11/8/2012 2:34:04 PM
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Broadway, his past success distinguished him, just like all other fields , notariety goes to the successful.

Re: Mad science -- ND
  • 11/8/2012 2:20:21 PM
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SaneIT, previously he was using tools unavailable or not identified by the other teams and now they have added it into their process, which evens the playing field. he must now expand or reinvent himself to regain an advantage.

Re: Mad science -- ND
  • 11/8/2012 1:11:00 PM
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And @rbaz and others, I don't want it to seem like Morey is the original basketball analytic. He is a major player in the space, and has been educating folks, but plenty of other analytics have been doing their own thing independent of him.

Re: Mad science -- ND
  • 11/8/2012 1:09:56 PM
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I think another thing is the quality and availability of data. Some data collection and sets are proprietary and accessed by a select few teams, but the NBA is also working to put data in every teams hands recently -- such as with the StatsCube, described by NBAStuffer as "a new data warehouse tool which the NBA has been developing over the last few years" and launched in 2009.

Re: Mad science -- ND
  • 11/8/2012 7:32:05 AM
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So you think that maybe he saturated the market and now there's not a niche for him to work in?  That does sound plausible, maybe they have worked enough inefficiencies out of the process that the real differences between the franchises are harder to or more expensive to fix, like signing super stars.

Re: Mad science -- ND
  • 11/7/2012 11:31:49 PM
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Broadway, maybe his previous success created greater and better competition. He essentially trained his competition in incorporating analytics to the process. To be fair some degree of luck must come to play as injuries and other factors are beyond measurement and control.

Re: Mad science -- ND
  • 11/7/2012 4:46:48 PM
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Matt, in responding to my Point piece, @mnorth had some great thoughts on this. I think they're worth duplicating here:

"Nearly a decade ago, Nicholas Carr published a controversial article in the Harvard Business Review called IT Doesn't Matter.  In the article, Carr essentially argues for the case presented by the villain Syndrome in Pixar's The Incredibles:  "When everyone's super, no one will be!"

When everyone has access to technology, then technology doesn't give you an edge.  When every team has a front office anaylitics department (or person ;-), it doesn't give that team a competitive advantage.  Effectively, that's what the argument is.

I think about the Moneyball story (via Michael Lewis/Brad Pitt).  When the Oakland A's made the playoffs this year, I think a lot of fans of the book/movie got a little romantic about the analytics that are now inseparably connected with that ball club's front office.  Many of us could envision the special edition DVD with just a black screen added before the credits roll: "Eight years later, the Oakland A's won the World Series."  

Alas, the Tigers dispatched the A's from the AL Divisional Series this fall, leaving romantic fans of both sports and analytics pining for some organization to satisfy our longing by winning a championship (and then attributing it to the data geeks in the office)."

Re: Mad science -- ND
  • 11/7/2012 2:55:36 PM
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@Beth, I have to agree that perhaps Morey's success in analytics in basketball has come back to bite him. He and others like him have been so successful over the last decade or so in bringing "Money Ball" to the NBA that now a majority of teams does it, and the benefit that teams gets from analytics is thus less than ever. That said, I do think he is also crumbling under stress and pressures.

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