Sunday, October 17, 2010

The Robbie Hummel Effect (Revisited)

[Note: I made a minor change to this post on October 29th. I apologize for any confusion.]

By now I am sure you have all heard the news about a devastating ACL tear. Penn St. forward Sasa Borovnjak has torn his ACL and is out for the year. Oh wait, that is not the ACL tear that everyone is talking about? No, the news that has saddened college basketball fans everywhere is that Robbie Hummel is out for the season.

I’ve already presented the tempo free prediction for Purdue with Robbie Hummel:
Predicted Efficiency Rank = 5th Nationally
Predicted Adj Eff Margin = 25.4
Predicted Adj Off = 110.1
Predicted Adj Def = 84.8

One thing we can do is run the model again and see what it predicts if we do not count Robbie Hummel as a returning player this season.
Predicted Efficiency Rank = 24th Nationally
Predicted Adj Eff Margin = 19.4
Predicted Adj Off = 106.6
Predicted Adj Def = 87.1

Andy Katz has moved Purdue from 2nd to 23rd in his top 25, and my statistical model roughly agrees with that prognostication. But you may notice that these numbers are still better than Purdue’s splits without Hummel last season.

I think the key difference is that replacing a player like Hummel is a lot easier in October than in February. With this injury taking place in October, Purdue will still have a number of practices, exhibition games, and early season cupcakes to build a team without their star forward. Making this adjustment in February when their opponents were peaking was a very difficult adjustment for the team to make in such a short amount of time.

Regardless, Purdue may now be the 5th best team in a top-heavy Big Ten, and that is a shocking development for a team that was a Final Four favorite in most preseason publications.