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The final eight teams are set in the NCAA Tournament. From the updated model results (method described in this previous post), of the four games in this round, only Kentucky’s match-up with Notre Dame has a high probability of one team winning (Kentucky at .794). The remaining three games are close to toss-ups.

Overall, Kentucky now has almost even odds to win the tournament. If Kentucky were to lose, Wisconsin, and the winner of the Duke and Gonzaga (the model thinks Duke with a .531 probability of winning) game would be next in line to be the favorite.

TeamSeedRegionB-T EffectProb Final 4Prob Final GameProb Winner
Kentucky1Midwest6.4890.7940.5900.477
Wisconsin1West5.3720.5990.2130.133
Duke1South5.1230.5310.3750.120
Gonzaga2South4.9770.4690.3210.104
Arizona2West4.9510.4020.1120.064
Notre Dame3Midwest4.7830.2060.0850.044
Louisville4East4.3380.5920.1990.043
Michigan St7East3.9420.4080.1050.017

  Posts

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March 11th, 2018

2018 NCAA Men’s College Basketball Division 1 Team Ratings

Team Rating Estimates Team ratings are based on a model factoring in team performance and team consistency. Ratings are produced by […]

March 11th, 2018

2018 NCAA Tournament Predictions

Just in time for the 2018 NCAA Men’s Basketball Tournament, I used a statistical model to assess team strength and […]

March 21st, 2017

Latest NCAA Tournament Predictions: Still No Overwhelming Favorite

The latest NCAA Tournament predictions are up and the chaos of the tournament is likely to continue. Although Gonzaga has […]

March 13th, 2017

2017 NCAA Tournament Prediction: Get Ready for Bracket Chaos

Just in time for the 2017 NCAA Men’s Basketball Tournament, I have put together a new statistical model to assess […]

March 6th, 2017

2017 NCAA Tournament Predictions

Just in time for the 2017 NCAA Men’s Basketball Tournament, I have put together a new statistical model to assess […]

November 8th, 2016

2017 Statistics Workshops: Diagnostic Modeling and Multilevel Longitudinal

Learn from instructors who wrote the book(s) on the topics! All workshops are given in a relaxed atmosphere with ample […]

November 1st, 2016

R Functions for Estimation of the LCDM in Mplus

The R functions are used to build, run, and parse Mplus syntax for estimation of the LCDM. The functions to […]

April 29th, 2016

An Introduction to Clustering and Classification Methods (EPSY 905; Spring 2016)

Multivariate Analysis (EPSY 905; Spring 2016): Week 14 Materials In-Class Lecture Materials: Lecture Slides R Files (zipped folder of all […]

April 24th, 2016

Principal Components Analysis and Exploratory Factor Analysis (EPSY 905; Spring, 2016)

Multivariate Analysis (EPSY 905; Spring 2016): Week 13 Materials In-Class Lecture Materials: Lecture Slides R Files (zipped folder of all […]

April 19th, 2016

Mixed Models Incorporate Repeated Measures and Multivariate ANOVA (EPSY 905; Spring 2016)

Multivariate Analysis (EPSY 905; Spring 2016): Week 12 Materials In-Class Lecture Materials: Lecture Slides R Files (zipped folder of all […]