For SportsIllustrated.com: Sweet 16 Matchup Issues

My latest is over at Luke Winn’s SI Tourney Blog. In it, I use adjusted efficiency data from Ken Pomeroy and adjusted box score data from TeamRankings.com’s possession-based college basketball game simulations to spotlight a few remaining teams that have matchup issues on defense. Summary: FSU should do great against VCU, Duke doesn’t want to see Kansas in the final, and Ohio State’s defense may be slightly overrated.

Final Four Characteristics

Just a short post to share something I noticed when digging through data last night…

In the Pomeroy Era (2004-09), there have been 24 Final Four teams.  All of them except 2006 George Mason and 2006 LSU fit the following critera:

• 30th or better in Adjusted Offensive Efficiency
• 30th or better in Adjusted Defensive Efficiency
• 15th or better in Pythagorean Rating
• 150th or better in defensive eFG%
• 150th or better in offensive 2PFG%
• 150th or better in defensive 2PFG%

Here are the teams in each region that fit these criteria:

• EAST: Kentucky, West Virginia, Wisconsin
• WEST: Syracuse, Kansas State, BYU
• MIDWEST: Kansas, Ohio State
• SOUTH:

Yes, I left the South blank on purpose.  Duke is disqualified due to their terrible shooting percentage within the arc (46.9%, 205th nationally).  However, they make up for this by being a fantastic offensive rebounding team (40%, 10th nationally), so given the lack of alternatives, I’d slot them in as the best fit in the South by these criteria.

Similarity Predictions

Since there were no tickets punched last night, I spent part of the evening developing an Excel workbook that makes game predictions based on how a team has performed in games against similar opponents.  I’ll use today’s game between Wisconsin and Illinois as an example.

First, I found the ten Wisconsin opponents whose offenses were most similar to Illinois, using the same method I’ve been using in the Tickets Punched series.  I then calculated Wisconsin’s individual game adjusted defensive efficiency against each of those opponents, using this equation (derived from the standard adjusted efficiency formula):

Wisc Game Adj Def Eff = [Opp Game Raw Off Eff] * [NCAA Ave Eff] / [Opp Season Adj Off Eff]

[NOTE: I actually treated HFA the same way Pomeroy does, but I didn’t want to make the equation look even messier]

Finally, I took a weighted average of those efficiencies, with the weight being the similarity score.  This gives me an adjusted defensive efficiency for Wisconsin that is specifically for games against offenses similar to Illinois.

I repeat the above process for Wisconsin’s offense, and Illinois's offense and defense, and the results all go into these pretty charts (where, as usual, green=good and red=bad):