#201 Saint Louis (7-19)

avg: 1060.04  •  sd: 57.54  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
122 Clemson Win 11-10 1486.6 Feb 8th Bulldog Brawl
284 Harding Win 13-7 1318.97 Feb 8th Bulldog Brawl
151 Lipscomb Loss 4-13 672.07 Feb 8th Bulldog Brawl
117 Mississippi State Loss 6-13 775.25 Feb 8th Bulldog Brawl
196 Kennesaw State Loss 8-11 717.04 Feb 9th Bulldog Brawl
117 Mississippi State Loss 13-15 1161.07 Feb 9th Bulldog Brawl
93 Southern Illinois-Edwardsville Loss 6-15 887.63 Feb 9th Bulldog Brawl
194 John Brown Loss 8-9 960.63 Feb 22nd Dust Bowl 2025
187 Nebraska Win 13-5 1718.9 Feb 22nd Dust Bowl 2025
272 Oklahoma Win 9-5 1334.35 Feb 22nd Dust Bowl 2025
87 Missouri S&T Loss 5-7 1179.44 Feb 23rd Dust Bowl 2025
176 Northern Iowa Win 8-4 1735.64 Feb 23rd Dust Bowl 2025
100 Alabama Loss 8-13 969.44 Mar 29th Huck Finn 2025
73 Iowa State Loss 6-14 1001.89 Mar 29th Huck Finn 2025
121 Northwestern Loss 8-11 997.74 Mar 29th Huck Finn 2025
79 Notre Dame Loss 6-15 971.71 Mar 29th Huck Finn 2025
100 Alabama Loss 8-11 1099.99 Mar 30th Huck Finn 2025
153 Kentucky Loss 9-10 1140.58 Mar 30th Huck Finn 2025
96 Missouri Loss 2-8 877.57 Mar 30th Huck Finn 2025
309 Washington University-B Win 15-13 855.14 Apr 12th Ozarks D I Mens Conferences 2025
12 Washington University** Loss 6-15 1504.3 Ignored Apr 12th Ozarks D I Mens Conferences 2025
159 Kansas Loss 6-9 813.57 Apr 13th Ozarks D I Mens Conferences 2025
96 Missouri Loss 10-13 1149.43 Apr 13th Ozarks D I Mens Conferences 2025
225 Arkansas Win 12-8 1417.46 Apr 26th South Central D I College Mens Regionals 2025
116 Denver Loss 3-13 784.14 Apr 26th South Central D I College Mens Regionals 2025
96 Missouri Loss 4-11 877.57 Apr 27th South Central D I College Mens Regionals 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)