The NBA draft this year provides a vivid real world test of whether very simple regressions can out-predict experts on a central business decision — the NBA draft.
Chris Doughty, a 2008 industrial and operations engineering graduate of the University of Michigan, pointed me to a cool regression analysis of the great John Hollinger. Using data from current NBA players, Hollinger sees how well the players’ college stats explain their subsequent performance in the NBA.
For example, here’s his analysis of the 2006 draft ranked in descending order of predicted play:
Hollinger’s regression analysis suggests that Rudy Gay, Marcus Williams, and newly minted NBA champion Rajon Rondo should have been the top three picks — where as the actual top three were Adam Morrison (who Hollinger rates as 14th best player), Brandon Roy, and Randy Foye.
Comparing the NBA success of his system’s predictions to the actual draft, Hollinger concludes, “while the system isn’t perfect, it’s a clear improvement on what actually took place.” Even armed with this statistical analysis, many teams continue to go with their gut.
But Hollinger goes further and applies his regression results to the current crop of players in the draft. Here are the regression’s rankings for this year’s draft:
A natural experiment is for us to wait a few years and see whether (once again?) the equation beats the expert.
It’s particularly interesting to see what happens to players like Darrell Arthur who had very different Hollinger and actual draft ratings. Hollinger ranked Arthur 3rd in projected PER (player efficiency rating) but Arthur was taken 27th. (Donte Greene, Kosta Koufus, Roy Hibbert, and Marreese Speights were also undervalued by the regression’s lights).
Instead of predicting the 3rd year PER, I’d also be interested in seeing how college stats predict the amount the player gets paid in his second NBA contract.
Regressions can also help assess which humans are the best prognosticators. Hollinger could also add the predictions of various long-time scouts into his regression and see which scouts best predict future NBA success of draft prospects.
and 
. You can also watch it on 
Umm those weren’t the top three picks in 2006.
The 2006 draft order was as follows: Andrea Bargnani, LaMarcus Aldridge, Morrison, Tyrus Thomas, Shelden Williams, Roy, Foye, Gay.
Oh and the reason for the discrepancy between that list is that is Hollinger’s list of “perimeter players,” thus excluding centers and power forwards. So no Bargnani, Aldridge, Thomas, Williams.
Might want to amend that first part to clarify that the screenshot you posted was actually of Hollinger’s top perimeter players, not overall players. Looking at both post players and guards, his 3rd-year predictions on some of the big men are a little more suspect. Still, I had seen both articles when they came out and thought they were both a fascinating read. As ESPN’s Bill Simmons has said for years, it seems like scouts over-emphasize workout numbers leading up to the draft and forget about high-level college performers, which Hollinger’s analysis seems to reemphasize, to me anyways.
Roy is better than everyone on that list. He should have been the top pick.
Did you know if you viewed that via the American Family Association’s OneNewsNow site “Rudy Gay” would be renamed “Rudy Homosexual”.
http://www.rightwingwatch.org/2008/06/the_dangers_of_1.html
Just sayin’
Way to go, Chris Doughty, 2008 IOE grad from UM.
GO BLUE!
One of the reasons Arthur slipped to 27th was related to questions about his health.
http://sports.aol.com/fanhouse/2008/06/30/darrell-arthur-blames-claritin-for-draft-slide/
I doubt this is reflected in Hollinger’s analysis, but it was certainly a factor in the team’s draft decisions.
#7 brings up a good point. There are other variables at play. Such as health risk, quantified, I guess, as the volatility of expected value. Do you want a guaranteed good player, or possibly great player? Depends on your current roster. Your draft could depend on this, or a lot of other variables, such as your revenue this year, age of your team, health of your team, locker-room atmosphere, etc. Not captured in the data. I don’t think a teams ONLY concern is the players future stats. If it were, drafting would be easy.
And by analogy, we’d all only be investing in mutual funds.