[aothman]

If you're interested in this kind of stuff, Ken Pomeroy (kenpom.com) runs a fantastic basketball analytics site. He's a big proponent of what are called "tempo-free stats", which aim to filter out issues of playing speed from scoring (a team that plays quickly will score a lot of points, nearly independently of whether or not they are winning). Tempo-free stats instead count possessions; one interesting statistic is that the average team this year in college basketball produced 1.01 points per possession - such a tidy figure to emerge from the chaos.

In terms of predictions, one of the most interesting teams this year is Kansas (http://kenpom.com/team.php?team=Kansas). They've only lost twice but have a large number of narrow home wins. Depending on how your algorithm treats those wins they either look like a team that will struggle to reach the sweet 16 or like a potential national champion.

[danger]

One other issue that comes up is "garbage time". When a game isn't close (say in the last quarter of a blow-out), the stats are basically meaningless. Does Pomeroy have good ideas about how to deal with that?

[kenjackson]

Funny, I did tempo-free stats when I was about 10 years old -- decades ago. Although I didn't have access to actual possessions, I tried to base it, best off I could off of field goals attempted for individuals and at the team level, and do various extrapolations.

Seems like it is still a fun area, with much better data now. I just need the time.