#24 Minnesota (16-7)

avg: 1823.12  •  sd: 74.58  •  top 16/20: 13%

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# Opponent Result Game Rating Status Date Event
108 Alabama-Huntsville** Win 13-3 1623.86 Ignored Feb 15th Queen City Tune Up 2025
80 Case Western Reserve** Win 13-2 1801.55 Ignored Feb 15th Queen City Tune Up 2025
9 North Carolina Loss 4-13 1522.91 Feb 15th Queen City Tune Up 2025
29 Georgia Loss 7-8 1601.12 Feb 16th Queen City Tune Up 2025
37 William & Mary Loss 7-8 1477.87 Feb 16th Queen City Tune Up 2025
45 American Win 9-7 1821.75 Mar 29th East Coast Invite 2025
97 Lehigh** Win 15-2 1690.28 Ignored Mar 29th East Coast Invite 2025
25 Northeastern Win 11-9 2051.74 Mar 29th East Coast Invite 2025
22 Ohio State Loss 8-9 1768.06 Mar 29th East Coast Invite 2025
70 Carnegie Mellon Win 15-5 1879.15 Mar 30th East Coast Invite 2025
29 Georgia Win 11-8 2091.72 Mar 30th East Coast Invite 2025
21 Virginia Loss 6-7 1776.06 Mar 30th East Coast Invite 2025
2 Carleton College Loss 7-12 2048.3 Apr 12th Western North Central D I Womens Conferences 2025
92 Iowa State Win 10-7 1501.4 Apr 12th Western North Central D I Womens Conferences 2025
92 Iowa State** Win 10-4 1711.73 Ignored Apr 12th Western North Central D I Womens Conferences 2025
214 Minnesota-Duluth** Win 15-1 868.17 Ignored Apr 12th Western North Central D I Womens Conferences 2025
130 Iowa** Win 15-3 1426.07 Ignored Apr 26th North Central D I College Womens Regionals 2025
98 Wisconsin-Eau Claire** Win 15-3 1685.78 Ignored Apr 26th North Central D I College Womens Regionals 2025
145 Wisconsin-La Crosse** Win 15-3 1324.19 Ignored Apr 26th North Central D I College Womens Regionals 2025
216 Wisconsin-Milwaukee** Win 15-0 860.38 Ignored Apr 26th North Central D I College Womens Regionals 2025
2 Carleton College** Loss 3-15 1968.81 Ignored Apr 27th North Central D I College Womens Regionals 2025
95 Marquette** Win 14-3 1694.02 Ignored Apr 27th North Central D I College Womens Regionals 2025
35 Wisconsin Win 12-9 1979.17 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)