Lesson 14: NCAA Men’s Basketball Final Four Predictions with Logistic Regression

March 29, 2016 at 9:49 pm  •  Posted in s16-busad360 by  •  2 Comments

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Wed, Mar 30


  • Logistic Regression
  • Exam 2 Corrections Due Mon Apr 4.


  • No lecture today; class cancelled.
  • Please spread the word to fellow students.


  • Build a Logistic Regression model to forecast the winner of the Final Four basketball games this Saturday.
  • This assignment won’t be easy. You will need to think about how to set up the problem and how to manipulate and organize the data to facilitate regression runs. Then you’ll need to figure out how to interpret your results. Take a shot and do your best.
  • Use this data sets for your analysis:
    • 2016 Game Results Data (Sheets)
    • Your dependent (y) variable is Column J labelled “Y Range”
    • You will have to decide on your independent (x) variables
    • You may use additional data if you think it would be useful (e.g., Tournament results, Win %, margin of victory, opponent seed, etc.)
  • Submit your work as follows:
    • Print Logistic Regression output for your model(s)
    • Specify your projected winner and estimated win probability for both games.
      • For Example, write something like this:
        • “Oklahoma over Villanova, 57% probability of win.”
        • “North Carolina over Syracuse, 63% probability of win”
    • Be sure your name is on all paper(s) submitted
    • Submit to Kim Wharton (or assistant) upstairs in HSB 200
    • Due before 5pm on Friday, April 1 (this is not an April Fool’s Joke; ask for a time stamp)
      • Bonus 1: Tweet your results to me @justinholman
      • Bonus 2: Create a blog post to share results
    • This assignment will count toward a portion of your Exam 3 grade
  • Is this the coolest assignment ever or what?

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