Final Four Predictions

The Prediction Machine did pretty well on the Sweet Sixteen games.  I think it would have missed many of the Elite Eight games, but I didn't actually run it so we'll never know.  For the first two games of the Final Four:

#1 Florida vs. #7 Connecticut:  Florida by 5.5

I think most people would agree that Connecticut is the weakest of the Final Four teams.  Florida meanwhile has been rolling along quietly taking care of business.  Short of an abnormal shooting night from one or both of the teams, I don't think UConn has much chance in this game.

#2 Wisconsin vs. #8 Kentucky:  Toss-up

Before watching the Kentucky-Michigan game, I thought Wisconsin was playing the best basketball of any of the contenders.  Now I'm not so sure.  Kentucky has been nearly unstoppable on offense throughout the Tournament, and the fabled freshmen have been impervious to the pressure.  Still, the Wildcats may be vulnerable if they get stymied enough on offense (as they did a couple of times this year against Florida), and Bo Ryan's team is certainly capable of applying the defensive pressure.  But even so, Wisconsin is going to have to be very efficient on the offensive end to stay even with the Wildcats.

Adventures in Data Cleansing

According to the ESPN play-by-play data, the American University vs. Penn State game on 12/21/2009 was a blowout -- Penn State won 914-629.

Imagine if it had gone to OT!

Machine Madness Competitors: Monte McNair

Next up in our tour of Machine Madness competitors is Monte McNair.  Monte was in this contest last year as well, under the nom de plume "Predict the Madness". 

Monte attended Princeton but is also a lifelong Stanford fan, so he is enjoying their current Tournament run.  As a UCLA fan I'll try not to hold that against him.  At least he isn't a Cal fan.  Monte blogs (infrequently) about sports at Outside the Hashes.  He also runs a site called Ultimate Bracket Challenge that's worth checking out and bookmarking for next year.

Last year he did a posting over on the Number Crunching Life where he talked about his approach.  He uses a logistic regression based upon the location of the game, metrics for the team's offense and defense, and metrics of the team's opponents' averages for both offense and defense.  Unlike some approaches (like mine) that produce a predicted point spread, Monte's approach produces a confidence number.  Monte finished in the middle of the pack last year but is doing much better this year.  He's currently in second in this contest, and is doing quite well over on Kaggle, where he's currently in eleventh.

Monte has Villanova-Florida-Arizona-Louisville as his Final Four, with Arizona winning it all.  The current leader has Florida for champion, so if Arizona wins it all Monte will likely jump into first and win this contest.

Sweet Sixteen Analysis

Jeff Fogle over on Stats Intelligence has a nice post up analyzing the Sweet Sixteen matchups.  Unlike most analysis you'll see, this is actually grounded in the team statistics instead of some pundits vague intuitions.

Unfortunately for me, Jeff comes to the same conclusion I did about UCLA's chances against Florida:  not very good.  UCLA did beat Arizona (a team very similar to Florida) in the final of the Pac-12 Tournament, but Arizona was a little tired for that game, and UCLA enjoyed a tremendous advantage on the free throw line.  You never know what the officiating will be like in the Tournament, but I'll be very surprised if UCLA ends up with a significant advantage in that category. 

Machine March Madness Competitors: Eric Akers

Our next profile is Eric Akers.

Eric is a software engineer at a small biotech company, so he fits my mental profile of a Machine Madness competitor.  He went to Kansas and his education has focused on robotics, computer vision, and some machine learning.  Needless to say he's a big Jayhawks fan.

Sorry about that Stanford game, Eric.

He's also passionate about baseball (KC Royals fan, naturally) and is contemplating trying to predict baseball games.  It's a slippery slope, this prediction business.  For outside hobbies he's building an ASV (autonomous seasurface vehicle) and is looking at build a quadcopter.

Like many of the competitors, he got hooked into this via Number Crunching Life. One of his work colleagues did some number crunching to try to get an edge in the office pool, Eric got intrigued, Googled around and found Number Crunching Life and got sucked in.  Looking at the competitors from last year I don't see Eric's name, so I think this is his first year competing.

His algorithm uses Danny Tarlow's probabilistic matrix factorization method using the 2D model with a vector for both offense and defense. Data was taken from the Kaggle site. Stochastic gradient decent was used to train the model, but with aging added. After an initial training, the teams were ranked based on the offense and defense vectors, then training continued using a higher learning rate based on the rank of the opponent being faced.

Eric also entered the Kaggle competition and was as high as #7 at one point on the first day, but has since dropped to #224.  If he'd taken the opposite of his predictions he'd be in 25th place :-).

Right now Eric is in 6th place in the Machine Madness competition.  Eric has a Virginia-Louisville final predicted, with Louisville winning it all.  If that happens he'll certainly jump upwards in the standings!

Machine Madness Competitors: Brandon Kling

I thought it would be interesting to get a little insight into some of the Machine Madness competitors, and I'm starting off with Brandon Kling.

I frankly expected all the competitors to be data mining/AI geeks, but Brandon is a Commercial Real Estate broker/investor from Bloomfield, Michigan.  He went to Walsh College of Business, a private school in the suburbs about 1 hour north of Detroit, and -- given that Walsh College doesn't seem to field a basketball team -- is a die-hard University of Michigan fan.  He also plays a little basketball and volleyball himself.

This is his first year entering any sort of automated/algorithm based prediction models. He stumbled upon the Machine March Madness pages while looking for the historical best ways to predict the NCAA tournament brackets and got sucked into doing his own completely automated bracket. 

His method was pretty straightforward:

1. Teams with the higher BPI (Basketball Power Index) advance (unless the difference between seeds playing each other is 3 or less, then see #2)
2. If difference in seeds is 3 or less (i.e. 10v7 or 2vs3 or 1vs1), then disregard BPI and instead advance the team with the lower OPPONENT AVG PPG
3. Championship Game points -  (winning score = Championship Game winner's AVG PPG)  (losing score= Championship Game winner's OPPONENT AVG PPG)

In one sense his algorithm was more advanced than mine -- I just randomly filled in the tie-breaker game points!

Sadly, Brandon's in last place in the pool.   However, he's the only competitor with Virginia winning the Championship, so if that happens he'll move up quite a bit.  And of course his beloved Wolverines are still in the Tournament (at least until they play Tennessee :-) so he has that to be happy about!

Sweet Sixteen Predictions

Thursday Games

#10 Stanford vs. #11 Dayton:   Stanford by 3

The Sweet Sixteen surprise match-up.  My prediction for this game prior to the tournament had Stanford by 4, so Dayton has closed the gap but Stanford is still favored.  My subjective judgement agrees.  (Dayton's biggest fan for this game?  Wojo.)

#2 Wisconsin vs. #6 Baylor:  Wisconsin by 4

The needle hasn't  moved at all on this game.  Baylor has surprised some with their performance, but Creighton was probably over-rated at a three seed.  And let's not discount Wisconsin's beat-down of American and handling of Oregon.  I know many think that Baylor could surprise Wisconsin, but my own expectation is that Wisconsin will win handily.  I think Baylor will quickly get disheartened by the Wisconsin defense.

#1 Florida vs. #4 UCLA:  Florida by 4.5

The machine predictors generally rate Florida as the best team in the country, and after their dismantling of Pittsburgh it's easy to see why.  Prior to 2005 UCLA had never played Florida.  Since then, they've had the misfortune to meet them four times in the Tournament -- every time during a year when Florida was at its best.   As a UCLA fan, I don't like the matchups with the Florida players, and you can't expect them to shoot 55% from the field as they did against Stephen F. Austin.

#1 Arizona vs. #4 SDSU:  Arizona by 8

It feels like both of these teams have been playing well, but they've actually just won their tournament games about as expected.   SDSU was lucky to face North Dakota State instead of Oklahoma, or they might not be in this game.  This should be a straightforward victory for Arizona.

Friday Games

#2 Michigan vs. #11 Tennessee:  Tennessee by 3

The Prediction Machine had Tennessee as one of the most mis-seeded teams this year, and that has certainly borne out.  They've actually played significantly above the predictions, so they're now a 3 point favorite in this game (they were a 1 point favorite before the tourney began).  Michigan has played about as expected.  Tennessee may revert to form, but either way Michigan is facing a tougher challenge here than you'd expect from the seeding.

#3 Iowa State vs. #7 Connecticut:  Iowa State by 3

The Prediction Machine doesn't consider injuries, so this line should probably be a little tighter.  These are both mediocre, inconsistent teams, so I won't be surprised if either team wins big or if it's a 3OT thriller.

#4 Louisville vs. #8 Kentucky:  Louisville by 6

This is the only sub-regional that has played out (so far, anyway) exactly as the PM predicted.   The Kentucky-Wichita State game was a tremendously fun game to watch, but let's not overstate the value of a two point win over a very over-seeded #1.  UK beat Louisville solidly early in the year, but that was on UK's home court.  On the other hand, six points isn't a lock.  It's certainly going to be a hard-fought game, and could be an instant classic.

#1 Virginia vs. #4 Michigan State:  Michigan State by 2

Michigan State has the slight edge here, but Virginia's defense should keep them in the game.  I'll be surprised if this is a blow-out either way.