EDIT NUSS: This is cool.

As the final seconds ticked off of the 31-pt defeat at the hands of the fake WSU this week, the realization that the basketball season is over for the Cougs hit me like a ton of bricks.  The two major college sports which generate the mountains of data that are followed by stats-geeks the world over are done for this academic year.  For the first time in nearly 8 months there will be no more new S&P+, FEI, Sagarin, or KenPom numbers flooding the interwebs on a daily basis.  This is a sad week indeed.

So in order to cheer myself at this, the conclusion of this basketball season I decided to delve into the one of the sillier expressions of statistics: Chernoff faces.  Chernoff faces are method for communicating a lot of different statistics in a single image.  The idea is that people are really good at gathering a lot of data from human faces and are easily able to distinguish tiny differences in expression.  Chernoff faces are an attempt to use that ability to its fullest potential by mapping statistics to aspects of a face, such as the size and shape of the eyes, nose, ears, etc.  This method of data visualization has never taken off, but is generally good for its novelty sake and even a mediocre attempt can get the random mathematician a story in the NY Times.

So what do the Cougs look like when they wear their stats on their faces?  Go ahead and take a look!

This is only showing the nine players for which KenPom kept stats this year.  I tried to lump together similar stats into the same facial feature.  For instance a big broad smile like that on Klay indicates that he is a very important offensive player;  taking a high percentages of the team shots (the width of the smile), with a high effective field goal percentage (height of the smile), and a high offensive rating (the strong upward curve of the smile.  Compare this with the small smile of Brock (or Capers) indicating that he is an efficient, but less used player, or Faisal's broad flat mouth, indicating a highly used player that isn't as efficient.  

Ultimately there is nothing super groundbreaking here, but a fun statistical diversion to contrast with the serious retrospectives that are sure to come in the following days and weeks.