#26 Wisconsin (13-13)

avg: 1877.17  •  sd: 55.32  •  top 16/20: 3.4%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
41 South Carolina Loss 10-13 1370.8 Feb 10th Queen City Tune Up 2024
2 Vermont** Loss 5-15 2077.17 Ignored Feb 10th Queen City Tune Up 2024
51 Virginia Win 14-9 2051.56 Feb 10th Queen City Tune Up 2024
36 William & Mary Win 10-8 2022.55 Feb 10th Queen City Tune Up 2024
21 Northeastern Loss 7-8 1834.88 Feb 11th Queen City Tune Up 2024
22 Pittsburgh Loss 10-14 1535.51 Feb 11th Queen City Tune Up 2024
11 Brigham Young Loss 10-13 1927.9 Mar 16th NW Challenge 2024
13 Victoria Loss 8-12 1712.21 Mar 16th NW Challenge 2024
4 Oregon Loss 6-13 1969.05 Mar 16th NW Challenge 2024
28 California Loss 9-13 1437.95 Mar 17th NW Challenge 2024
15 Western Washington Loss 9-13 1714.17 Mar 17th NW Challenge 2024
46 Whitman Win 13-6 2240.31 Mar 17th NW Challenge 2024
71 Columbia Win 13-4 2007.82 Mar 30th East Coast Invite 2024
8 Tufts Loss 3-9 1755.7 Mar 30th East Coast Invite 2024
51 Virginia Win 12-8 2018.84 Mar 30th East Coast Invite 2024
44 Yale Win 15-2 2246.48 Mar 30th East Coast Invite 2024
2 Vermont** Loss 5-15 2077.17 Ignored Mar 31st East Coast Invite 2024
12 Michigan Loss 6-11 1652.99 Mar 31st East Coast Invite 2024
49 Ohio Win 10-8 1869.37 Mar 31st East Coast Invite 2024
178 Wisconsin-La Crosse** Win 13-3 1268.92 Ignored Apr 13th Lake Superior D I Womens Conferences 2024
161 Wisconsin-Milwaukee** Win 13-5 1417.87 Ignored Apr 13th Lake Superior D I Womens Conferences 2024
127 Wisconsin-Eau Claire** Win 13-5 1641.07 Ignored Apr 13th Lake Superior D I Womens Conferences 2024
40 Minnesota Win 13-9 2132.37 Apr 27th North Central D I College Womens Regionals 2024
161 Wisconsin-Milwaukee** Win 15-3 1417.87 Ignored Apr 27th North Central D I College Womens Regionals 2024
3 Carleton College** Loss 4-15 2022 Ignored Apr 28th North Central D I College Womens Regionals 2024
96 Iowa State Win 15-7 1853.51 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)