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Skating Around the Bayesian Logistic Regression Markov Chain March Madness 2010 NCAA Men's Basketball Tournament Predictions

roadskater's picture

I'm no mathmetician, certainly, but music and basketball are two of my favorite applications of mathematics in understanding or perhaps delightfully confusing the world. I enjoyed studying physics in part because it gave meaning to math for me, even if I didn't understand it all still!

Being of late in Georgia I was very happy to see that http://mmod.ncaa.com is still offering up free, live, internet television of all the games. You can pick what to watch among the live games, and this allowed me to see the excellent Wake Forest University win over Texas, where the Demon Deacons were impressive in their handling of much of the game, particularly the first few minutes of the second half and the last minute or so of the game.

At the last minute, I had become entirely immersed in bracketology again (you can download my 2010 NCAA bracket below in the "attachments" section). With the NCAA Men's Basketball Tournament for 2010 starting in an hour or so, I started filling out a bracket on the ESPN site. I can't say that I have followed basketball much this year (with North Carolina having a nasty year), but I love college basketball, and filling out a bracket makes it more interesting for me. Soon after I was finished my bracket was already well busted, and I was hanging on for the evening games, hoping to recover.

My bracket was based largely on how teams did against top 25 teams, with a nod for playing more top 25 teams (where the nod was needed), and consideration for point differential (maybe tipping toward teams with a low average score but with a high point differential, since the tourney seems to have some low scoring games). None of this was scientific of course, but I avoided as much as possible my typical pulling for the Atlantic Coast Conference while picking teams. I knew I wanted to pick a 12 beats 5 upset if it looked like there was a reasonable one, and wasn't going let seeding in the tournament bother me in my picks.

Interesting first round picks were:

  • 9 N Iowa over 8 UNLV (correct)
  • 9 Wake Forest over 8 Texas (correct)
  • 11 Washington over 6 Marquette (correct)

Big misses for me were:

  • 3 Georgetown, whom I had selected to win 3, losing to 14 Ohio (14 over 3 wins are rare in the first round)
  • 6 Notre Dame, whom I had winning 2 games, losing to 11 Old Dominion, eventually falling to
  • 7 Richmond winning 3 games, but Richmond lost to 10 St. Mary's
  • 13 Murray St beating Vanderbilt was not a shocker for me but I still put down Vandy to win one, falling to 5 Butler (who did win their 5/12 match with UTEP

After Day 1 (half of the first round) my final four is still intact:

  • 1 Kansas beating
  • 1 Syracuse then beating
  • 3 New Mexico, the latter getting there by beating
  • 4 Purdue.

Early in the first day, my percentile rank had fallen to somewhere around 50, but by the end of the first day, it was up to 96.9%...but surely headed for a fall in coming days. But that's some of the sick hope of it all.

I really enjoyed seeing the "national bracket" here...(Kansas beats Syracuse, Kentucky beats Duke, Kansas beats Kentucky)...

...and the "who picked whom" which was really "who got picked to win in which round" here...

For the second round, I've picked these upsets:

  • 9 Louisville over 8 California
  • 11 Minnesota over 6 Xavier
  • 12 Utah State over 5 Texas A&M

There was a neat simulated games predicted bracket on the ESPN site called AccuScore, which I looked at after I made my picks. I made some notes and may share what I learn on that later (or not). Seems like a service aimed at selling picks to bettors. Just as selling advice about selling on eBay might be more profitible than selling on eBay, I imagine selling picks is more profitible than betting on them.

A more interesting computer predictive scheme (LRMC, or logistic regression/Markov chain, which I had heard of before and looked at after making my picks) actually PREDICTED THESE UPSETS:

  • 13 Murray State over 4 Vanderbilt
  • 11 Old Dominion over 6 Notre Dame
  • 10 St. Mary's over 7 Richmond
  • 9 Northern Iowa over UNLV

However it missed out by not predicting:

  • 14 Ohio beating 3 Georgetown
  • 6 Tennessee beating 11 San Diego State
  • 9 Wake Forest beating 8 Texas
  • 11 Washington beating 6 Marquette

Upsets it predicts for the 2nd day of round 1 are:

  • 10 Georgia Tech over 7 Oklahoma State (disclosure: the prediction routine was developed at GT)
  • 9 Florida State over 8 Gonzaga
  • 12 Utah State over 5 Texas A&M

To see the LRMC (logistic regression/Markov chain) bracket (this is not the very latest technique Joel Sokol et. al. are working on, which is Bayesian LRMC):

For more information on the LRMC system:

For a Bayesian LRMC sort, see the following (I didn't see a bracket based on the new BLRMC):

Note that both systems put BYU at 4th, very high for a 7 seed (remember there are four of each seed so this is like being ranked 25th-28th by the NCAA basketball committee), and Ohio State is 5 on BLRMC. California is 7th, high for an 8 seed (33rd-36th). Regardless, my bracket may be in for some hurtin'!

Math gone wild. The madness is watching basketball instead of going out to skate! But as madnesses go, it's a fun one.

Did you make a bracket? How's that working out for you? Care to make any bold predictions, or not so bold ones?


United States
39° 45' 50.4576" N, 86° 9' 47.8728" W
2010-ncaa-bracket-roadskater.pdf96.26 KB


dreeves's picture


Hi Blake,

You might like this thing I helped build at Yahoo: http://predictalot.com

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