#129 Winona State (12-7)

avg: 1098.99  •  sd: 61.67  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
152 Iowa Loss 6-8 664.47 Mar 1st Midwest Throwdown 2025
97 Iowa State Loss 4-6 963.83 Mar 1st Midwest Throwdown 2025
181 Truman State Win 6-3 1286.65 Mar 1st Midwest Throwdown 2025
219 Wisconsin-B** Win 7-1 1015 Ignored Mar 1st Midwest Throwdown 2025
181 Truman State Win 10-2 1339.96 Mar 2nd Midwest Throwdown 2025
128 Saint Louis Win 8-7 1235.83 Mar 2nd Midwest Throwdown 2025
94 Wisconsin-Eau Claire Loss 2-11 743.8 Mar 2nd Midwest Throwdown 2025
103 Loyola-Chicago Win 6-4 1632.6 Mar 22nd Meltdown 2025
45 Missouri** Loss 2-10 1227.88 Ignored Mar 22nd Meltdown 2025
205 Wheaton (Illinois) Win 8-3 1120.72 Mar 22nd Meltdown 2025
187 St Olaf-B Win 10-1 1268.07 Mar 22nd Meltdown 2025
103 Loyola-Chicago Loss 2-8 666.99 Mar 23rd Meltdown 2025
187 St Olaf-B Win 6-1 1268.07 Mar 23rd Meltdown 2025
75 Chicago Loss 3-8 917.69 Mar 29th Old Capitol Open 2025
123 Northwestern Loss 7-8 1017.51 Mar 29th Old Capitol Open 2025
148 Wisconsin-La Crosse Win 8-6 1278.57 Mar 29th Old Capitol Open 2025
200 Grinnell Win 8-6 872.31 Mar 30th Old Capitol Open 2025
152 Iowa Win 9-3 1564.96 Mar 30th Old Capitol Open 2025
223 Minnesota-Duluth Win 11-6 912.52 Mar 30th Old Capitol Open 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)