Tag Archives: March Madness

Predictions for tonight

The prediction for tonight: Kentucky over Kansas (54.6% of my simulations), but it should be close again (closer than the 6 to 6.5 point Vegas line). The simulations predict that the two teams are very close on most statistics, but Kentucky should rebound and shoot free throws slightly better and turn the ball over slightly less. We will see in 15 minutes!

The final four went almost exactly as my simulation predicted. Kentucky, who I predicted to win by 8.4, won by 8 points. Louisville did well on the offensive glass and limited their turnovers, but they fired up many bricks with their extra possessions (they were around 35% on twos and threes). Kentucky rebounded poorly but shot extremely well from the floor (57%, mostly on twos) and better from the line. Although I predicted an advantage for Kentucky shooting the ball, it wasn’t this big. They didn’t dominate the glass like I thought they would, so it’s a good thing they shot as well as they did.

In the nightcap, I had Ohio State and Kansas almost dead even. Kansas won by two points, and the game came down to the final shot. As I predicted, Kansas was better on the offensive glass. However, they turned the ball over quite a bit (I predicted the reverse), and the real difference in the game was Ohio State’s shooting. The simulations said they would shoot quite well. Instead, they shot about 35% on twos and threes, just like Louisville.  Kansas, on the other hand, shot about as expected and got the win.

I’ll have a tournament summary up tomorrow. It’s looking like a good performance for most of the prediction methods that I examined.

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Round 2 post for TeamRankings competition

My post for round 2 of TeamRankings blogging competition is up on their blog. I give a full explanation of my NCAA basketball simulation method and flesh out my predictions for tonight’s games.

Edit: The complete post can now be found below. I moved it here in case TeamRankings changes their links at a future date.

Breaking Down Match Ups: Sweet Sixteen Game Simulations

In round 1 of the Stat Geek Idol competition, I described a procedure to simulate NCAA basketball games based on the few team statistics that really matter: shooting percentages, shot selection, turnovers per play, and offensive rebound percentage. These are basically Dean Oliver’s four factors, though I go a little more in depth. For this round, I’ll break down the simulation procedure and apply it to the Sweet Sixteen match ups. But first, how have my simulations performed so far? For comparison, I list the number of teams correctly predicted to reach the second and third rounds by a few different methods (I give a full summary on my blog):

  • Take the higher seed: 22/32, 11/16
  • Take the higher RPI: 21/32, 9/16
  • Take the higher Pomeroy ranking: 22/32, 10/16
  • Take the higher Sagarin ranking: 23/32, 10/16
  • Take the team that wins majority of my simulations: 23/32, 9/16

If I forgive first round mistakes and recalculate second round match ups Continue reading