#200 Northern Iowa (13-12)

avg: 1121.31  •  sd: 54.75  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
313 Kansas-B Win 12-10 905.38 Feb 17th Dust Bowl 2024
41 Oklahoma Christian Loss 6-11 1306.18 Feb 17th Dust Bowl 2024
190 Texas-Dallas Loss 6-9 739.77 Feb 17th Dust Bowl 2024
356 Wichita State Win 11-7 955.98 Feb 17th Dust Bowl 2024
356 Wichita State Win 13-9 907.65 Feb 18th Dust Bowl 2024
228 Oklahoma State Loss 8-10 759.57 Feb 18th Dust Bowl 2024
263 Illinois State Win 13-6 1498.19 Mar 23rd Free State Classic
313 Kansas-B Win 11-2 1267.26 Mar 23rd Free State Classic
243 Nebraska Win 9-8 1108.44 Mar 23rd Free State Classic
337 Wisconsin-Stevens Point Win 11-2 1165.68 Mar 23rd Free State Classic
243 Nebraska Win 13-6 1583.44 Mar 24th Free State Classic
228 Oklahoma State Loss 10-11 897.23 Mar 24th Free State Classic
110 Davenport Loss 9-10 1342.57 Mar 30th Old Capitol Open 2024
49 Michigan State** Loss 3-11 1178.48 Ignored Mar 30th Old Capitol Open 2024
320 Washington University-B Win 13-2 1251.34 Mar 30th Old Capitol Open 2024
193 Grinnell Loss 4-9 554.63 Mar 31st Old Capitol Open 2024
122 Minnesota-B Loss 2-12 800.63 Mar 31st Old Capitol Open 2024
299 Minnesota-C Win 8-6 1019.09 Mar 31st Old Capitol Open 2024
305 Creighton Win 9-4 1294.2 Apr 13th West Plains D I Mens Conferences 2024
63 Iowa Loss 3-13 1086.69 Apr 13th West Plains D I Mens Conferences 2024
107 Iowa State Loss 7-13 918.6 Apr 13th West Plains D I Mens Conferences 2024
243 Nebraska Win 11-6 1530.13 Apr 13th West Plains D I Mens Conferences 2024
243 Nebraska Win 15-7 1583.44 Apr 27th North Central D I College Mens Regionals 2024
94 Wisconsin-Eau Claire Loss 10-15 1081.1 Apr 27th North Central D I College Mens Regionals 2024
105 Wisconsin-Milwaukee Loss 7-15 884.87 Apr 27th North Central D I College Mens 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)