Bracketeering update: Mascot randomness is beating the pants off RPI after round 2

  1. March Madness Bracketeering
  2. Applied Bracketeering: Modeling March Madness
  3. Bracketeering update: Mascot randomness is beating the pants off RPI after round 2
  4. Applied Bracketeering: So, who saw that final four coming?
  5. Applied bracketeering wrapup: Highly-rated team wins in shocking finale
  6. Applied Bracketeering: Does our model also work for the NCAA Women’s tournament?
  7. Applied Bracketeering, 2018 Edition: Do streaks matter?
  8. Applied Bracketeering, 2018: Streaky Clean
  9. Bracketeering Sweet 16 update: The Infallible Braculator agrees to never speak of this past weekend again
  10. Bracketeering Final Four update: Round of the Usual Suspects (and Loyola)
  11. Bracketeering Finale: Much ado about nothing or A tale of four regions
  12. What countries punch above their demographic weight at the World Cup (and can this be predictive)?
  13. World Cup Predictions: in a bonkers first round of games, even the best models get just over 50%
  14. World Cup Predictions: Most models underestimate the chance of a tie.
  15. World Cup Predictions: Knockout round madness
  16. World Cup Predictions: The final countdown
  17. World Cup predictions wrap-up: Vive le France!
  18. The Insufferable Braculator™ Strikes Again. Can your NCAA Women’s Tourney predictions beat it?
  19. The Insufferable Braculator models NCAA Women’s basketball, chapter 2: Concerning chalk

By: Richard W. Sharp

The question

So, after a very chalk first round and a bonkers-insane second round, how are our models doing vs. the NCAA’s officially-sanctioned rankings (now powered by magical numbers!)?

Quite good!


Early returns

  • RPI is as terrible as we thought it was.
  • The mascot noise models are doing substantially better in terms of peak performance (remember, we added noise to maximize our chances to win pools, not just to do respectably on average).

Here’s how the brackets we highlighted before the tourney are doing after 2 rounds of games. Remember, we’re using a simple scoring system, where each 1st round game is worth 1 point, each 2nd round game 2, 3rd round game 4, etc.



Stand-alone brackets

Here are several single brackets (as opposed to models run many times and averaged) in order of decreasing score. An upset is any game in which the team with the better seed loses. 

  1. Seeds (although RPI is officially used “to aid in the selecting and seeding” process, apparently cooler heads prevailed)
    • Correct: 38
    • Points: 50
    • Upsets called: None, by definition
  2. Sagarin with mascot weighting #14, (bracket.ranker_SAG.mascot_14.csv – this is the one that really counts. We entered it in an actual pool)
    • Correct: 37
    • Points: 47
    • Upsets called: 1
  3. RPI
    • Correct: 35
    • Points: 46
    • Upsets called: 0
  4. Obama’s bracket
    • Correct: 33
    • Points: 43
    • Upsets called: 3

Randomized bracket sets

The brackets we posted on GIT were created by adding either random noise or mascot-weighted noise to some standard model. For each set of brackets listed below, we report the performance of the brackets at or above the 90th percentile in each group. If we play random brackets from these strategies year after year, we should expect to generate one this good in every ten entries.

  1. Mascot-weighted composite
    • 90th pct. Correct: 39
    • 90th pct. Points: 51
    • Most common Sweet Sixteen at 90th pct. 
      • East
        • Villanova (1) vs. Florida (4) | Duke (2) vs. Baylor (3)
      • Midwest
        • Kansas (1) vs. Purdue (4) | Louisville (2) vs. Oregon (3)
      • South
        • North Carolina (1) vs. Butler (4) | Kentucky (2) vs. UCLA (3)
      • West
        • Gonzaga (1) vs. Notre Dame (5) | Arizona (2) vs. Maryland (6)
  2. Mascot-weighted Sagarin
    • 90th pct. Correct: 38
    • 90th pct. Points: 49
    • Most common Sweet Sixteen at 90th pct.
      • East
        • Villanova (1) vs. Florida (4) | Duke (2) vs. Baylor (3)
      • Midwest
        • Kansas (1) vs. Iowa St. (5) | Louisville (2) vs. Oregon (3)
      • South
        • North Carolina (1) vs. Butler (4) | Kentucky (2) vs. UCLA (3)
      • West
        • Gonzaga (1) vs. West Virginia (4) | Arizona (2) vs. Florida St. (3)
  3. Sagarin with standard deviation 5 noise
    • 90th pct. Correct: 38
    • 90th pct. Points: 49
    • Most common Sweet Sixteen at 90th pct.
      • East
        • Villanova (1) vs. Florida (4) | Duke (2) vs. Baylor (3)
      • Midwest
        • Kansas (1) vs. Purdue (4) | Louisville (2) vs. Oregon (3)
      • South
        • North Carolina (1) vs. Butler (4) | Kentucky (2) vs. UCLA (3)
      • West
        • Gonzaga (1) vs. West Virginia (4) | Arizona (2) vs. Florida St. (3)
  4. RPI with standard deviation 5 random noise
    • 90th pct. Correct: 36
    • 90th pct. Points: 48
    • Most common Sweet Sixteen at 90th pct.
      • East
        • Villanova (1) vs. Florida (4) | Duke (2) vs. Baylor (3)
      • Midwest
        • Kansas (1) vs. Purdue (4) | Louisville (2) vs. Oregon (3)
      • South
        • North Carolina (1) vs. Butler (4) | Kentucky (2) vs. UCLA (3)
      • West
        • Gonzaga (1) vs. West Virginia (4) | Arizona (2) vs. Florida St. (3)
  5. Model composite with standard deviation 5 random noise
    • 90th pct. Correct: 36
    • 90th pct. Points: 46
    • Most common Sweet Sixteen at 90th pct.
      • East
        • Villanova (1) vs. Florida (4) | Duke (2) vs. Baylor(3)
      • Midwest
        • Kansas (1) vs. Purdue (4) | Louisville (2) vs. Oregon (3)
      • South
        • North Carolina (1) vs. Butler (4) | Kentucky (2) vs. UCLA (3)
      • West
        • Gonzaga (1) vs. West Virginia (4) | Arizona (2) vs. Florida St. (3)

Coming up

We all take a deep breath, re-introduce ourselves to our families and pets, and then prep for the Sweet 16!

We’ll post another update after the elite 8 games are finished on March 28th.

About The Author

Richard is a Seattle area data scientist who builds predictive models and the services that deliver them. He earned a PhD in Applied and Computational Math from Princeton University, and left academia for the dark side of science (industry) in 2010, following his wife to the land of flannel. Fan of coffee, beer, backpacking and puns. Enjoys a day on the lake fishing, and, better, cooking up the catch for a crowd.

No Comments on "Bracketeering update: Mascot randomness is beating the pants off RPI after round 2"

Leave a Comment