#194 John Brown (9-11)

avg: 1085.63  •  sd: 59.38  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
187 Nebraska Win 7-6 1243.9 Feb 22nd Dust Bowl 2025
272 Oklahoma Win 10-9 930.29 Feb 22nd Dust Bowl 2025
201 Saint Louis Win 9-8 1185.04 Feb 22nd Dust Bowl 2025
130 North Texas Loss 5-12 730.22 Feb 23rd Dust Bowl 2025
258 Colorado State-B Loss 8-12 403.32 Mar 29th Free State Classic 2025
322 Kansas State Win 15-4 1201.16 Mar 29th Free State Classic 2025
191 Oklahoma State Loss 8-14 564.37 Mar 29th Free State Classic 2025
163 Truman State Loss 11-12 1097.22 Mar 29th Free State Classic 2025
159 Kansas Win 12-11 1357.13 Mar 30th Free State Classic 2025
322 Kansas State Win 15-6 1201.16 Mar 30th Free State Classic 2025
284 Harding Win 13-9 1180 Apr 12th Ozarks D III Mens Conferences 2025
87 Missouri S&T Loss 9-13 1089.01 Apr 12th Ozarks D III Mens Conferences 2025
163 Truman State Loss 11-12 1097.22 Apr 12th Ozarks D III Mens Conferences 2025
57 Oklahoma Christian Loss 3-13 1073.33 Apr 12th Ozarks D III Mens Conferences 2025
163 Truman State Win 10-8 1484.88 Apr 13th Ozarks D III Mens Conferences 2025
87 Missouri S&T Loss 8-14 971.55 Apr 13th Ozarks D III Mens Conferences 2025
89 Colorado College Loss 11-12 1371.88 Apr 26th South Central D III College Mens Regionals 2025
118 Colorado Mines Loss 9-14 898.79 Apr 26th South Central D III College Mens Regionals 2025
231 Air Force Win 13-12 1067.02 Apr 27th South Central D III College Mens Regionals 2025
87 Missouri S&T Loss 12-13 1382.58 Apr 27th South Central D III College Mens Regionals 2025
**Blowout Eligible

FAQ

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
  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
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)