With 16 days left before the draft, teams are busily working out prospects, haggling with agents and breaking down game tape. Could there be an easier way? Last week we were talking about computer rating systems that purport to identify the best draft prospects, without the messy work of actually watching games, administering brain profile tests and trekking through rundown former Soviet airports. The two systems that have garnered the most attention were designed by Erich Doerr, a David Berri disciple, and ESPN’s John Hollinger. A good summation and explanation of the systems was posted here last year: http://www.knickerblogger.net/index.php/2007/06/26/draft-analysis-by-the-numbers/ The …continue reading
It is now official, Shaquille O’Neal has been dumped traded to the Phoenix Suns in exchange for Shawn Marion and Marcus Banks. I think we all, more or less, agree that this is a horrible trade for the Suns, trading the better, younger player on a team with the best record in the Western Conference for an older, worse player who, as a kicker, is not just injury prone, but currently injured. What I wonder, though, is this such a bad trade that it is even worse than any Isiah trade?
Learn all about what stats in the NBA are most useful. No calculators required.
One of the core tenets of basketball statistical analysis is the usage of per minute stats. When compared to per game stats, per minute stats are highly valuable in the evaluation of individuals. This is because per minute stats puts players of varying playing time on the same level. Using per game stats, starters will always dwarf bench players due to the extended time they get to accumulate various stats. Meanwhile per-minute stats allows to compare players independent of minutes, allowing for a more even approach in player evaluation. Recently a debate has come up on the validity and usefulness …continue reading
In Basketball on Paper, Dean Oliver devoted an entire chapter to comparing the individual rating systems of several NBA analysts. He argued something that I, and most people who do informed analysis, subscribe to: Any system of statistical analysis cannot only be internally consistent, but must also pass the “laugh test.” A statistical model can be built elegantly and beautifully and pass many confidence intervals within its own logical parameters, but if it’s results are absurd, then there’s obviously a need to return to the proverbial drawing board. Oliver thought of the “laugh test” as a litmus. It’s a very …continue reading
With the 2007 NBA draft almost upon us, there’s plenty of resources around the web for those craving more information regarding the draft. However I’ve stumbled across three that I thought were particularly interesting. The one thing all of these resources have in common is that they offer a statistical look at predicting incoming NBA players. For some time baseball fans have had a good amount of knowledge on what makes a good professional. College pitchers generally fared better than high schoolers. Minor league pitchers that had a good BB:K and HR:K ratios were more likely to succeed than those …continue reading