NEM is truly outrageous
The Dagger asks why North Carolina is currently hanging out in the mid-50s in the Pomeroy ratings. Pomeroy notes that it is still far too early to put much stock in the ratings, and I agree. But that still does not answer the question of why?
We can use the Net Efficiency Margin (cleverly abbreviated NEM) introduced last season to examine why, despite their high standing in the polls, the Heels are hanging with the likes of Pacific and UTSA. (No offense to Pacific and UTSA, but UNC has as many NCAA championships than those two have NCAA tournament wins.)
Read the full aforelinked introductory post for the details, but NEM essentially measures how a team performed in a given game compared to how an "average" Division I team would perform against that opponent. A NEM of 0 in a game means that a team (according to their offensive and defensive efficiency) performed exactly as an average Division I team would have against that opponent. A positive NEM means better-than-average performance, and a negative NEM means worse-than-average performance.
During the NCAA Tournament last year, I posted (thanks, of course, to Ken Pomeroy's womderful data) updated NEM rankings after each round (for example) and used NEM in my game previews. This season, I hope to use NEM more often during the regular season to answer questions like this.
The short answer to this particular question is that while the Heels have won several games against quality competition, their efficiency rating is suffering because of sub-par performances against the lower lower third of Division I.
|328||North Carolina Central||35.7|
This means that in three of their nine games, UNC played (from an efficiency stanpoint) like an average D-I team. Fortunately, those three opponents have an average Pomeroy rank (as of Dec. 7) of #277, so there was some margin for error. This inconsistency (look at that up-and-down in the first four games!) and playing to the level of the opponent is typical for a team as young as these Tar Heels, so do not read too much into the first month of results.