#195 Minnesota-B (3-6)

avg: 468.5  •  sd: 245.12  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
2 Carleton College** Loss 0-15 1963.52 Ignored Apr 12th Western North Central D I Womens Conferences 2025
132 Iowa Loss 5-9 297.79 Apr 12th Western North Central D I Womens Conferences 2025
132 Iowa Loss 5-9 297.79 Apr 12th Western North Central D I Womens Conferences 2025
215 Minnesota-Duluth Win 7-6 393.78 Apr 12th Western North Central D I Womens Conferences 2025
2 Carleton College** Loss 0-15 1963.52 Ignored Apr 26th North Central D I College Womens Regionals 2025
92 Iowa State** Loss 1-15 512.02 Ignored Apr 26th North Central D I College Womens Regionals 2025
215 Minnesota-Duluth Loss 6-7 143.78 Apr 26th North Central D I College Womens Regionals 2025
215 Minnesota-Duluth Win 11-7 735.67 Apr 27th North Central D I College Womens Regionals 2025
217 Wisconsin-Milwaukee Win 9-4 861.14 Apr 27th North Central D I College Womens Regionals 2025
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
The uncertainty of the mean is equal to the standard deviation of the set of game ratings, divided by the square root of the number of games. We treated a team’s ranking as a normally distributed random variable, with the USAU ranking as the mean and the uncertainty of the ranking as the standard deviation
What's the algorithm again?
  1. Calculate uncertainy for USAU ranking averge
  2. Model ranking as a normal distribution around USAU averge with standard deviation equal to uncertainty
  3. Simulate seasons by drawing a rank for each team from their distribution. Note the teams in the top 16 (club) or top 20 (college)
  4. Sum the fractions for each region for how often each of it's teams appeared in the top 16 (club) or top 20 (college)
  5. Subtract one from each fraction for "autobids"
  6. Award remainings bids to the regions with the highest remaining fraction, subtracting one from the fraction each time a bid is awarded
Is there a longer explanation of all this?
There is an article on Ulitworld written by Scott Dunham and I that gives a little more context (though it probably was the thing that linked you here)