#40 Minnesota (14-7)

avg: 1713.8  •  sd: 76.29  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
158 Case Western Reserve** Win 15-1 1434.5 Ignored Feb 10th Queen City Tune Up 2024
61 Florida Win 13-10 1821.58 Feb 10th Queen City Tune Up 2024
8 Tufts Loss 8-15 1790.89 Feb 10th Queen City Tune Up 2024
21 Northeastern Loss 5-15 1359.88 Feb 10th Queen City Tune Up 2024
41 South Carolina Win 9-5 2228 Feb 11th Queen City Tune Up 2024
19 Georgia Loss 7-12 1507.66 Feb 11th Queen City Tune Up 2024
99 Chicago Win 9-2 1819.77 Mar 30th Old Capitol Open 2024
83 Kansas Win 7-5 1671.14 Mar 30th Old Capitol Open 2024
205 Minnesota-Duluth** Win 10-0 993.13 Ignored Mar 30th Old Capitol Open 2024
35 St Olaf Loss 3-7 1178.48 Mar 31st Old Capitol Open 2024
100 Davenport Win 8-2 1819.44 Mar 31st Old Capitol Open 2024
59 Purdue Win 8-0 2116.42 Mar 31st Old Capitol Open 2024
3 Carleton College** Loss 2-13 2022 Ignored Apr 13th Western North Central D I Womens Conferences 2024
96 Iowa State Win 10-4 1853.51 Apr 13th Western North Central D I Womens Conferences 2024
96 Iowa State Win 13-3 1853.51 Apr 13th Western North Central D I Womens Conferences 2024
205 Minnesota-Duluth** Win 13-0 993.13 Ignored Apr 13th Western North Central D I Womens Conferences 2024
178 Wisconsin-La Crosse** Win 15-2 1268.92 Ignored Apr 27th North Central D I College Womens Regionals 2024
26 Wisconsin Loss 9-13 1458.61 Apr 27th North Central D I College Womens Regionals 2024
3 Carleton College** Loss 6-15 2022 Ignored Apr 28th North Central D I College Womens Regionals 2024
102 Iowa Win 15-3 1812.27 Apr 28th North Central D I College Womens Regionals 2024
96 Iowa State Win 15-12 1554 Apr 28th North Central D I College Womens Regionals 2024
**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)