#161 Rice (8-7)

avg: 1111.8  •  sd: 51.81  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
35 Missouri Loss 6-12 1207.51 Feb 25th Dust Bowl 2023
252 Texas-B Win 11-5 1330 Feb 25th Dust Bowl 2023
93 Iowa Loss 5-12 826.29 Feb 25th Dust Bowl 2023
264 Oklahoma State Win 10-7 1070.9 Feb 25th Dust Bowl 2023
35 Missouri** Loss 3-8 1186.83 Ignored Feb 26th Dust Bowl 2023
92 Missouri S&T Loss 7-8 1304.82 Feb 26th Dust Bowl 2023
217 Texas-Dallas Win 8-7 997.96 Feb 26th Dust Bowl 2023
156 Wichita State Win 8-7 1252.46 Feb 26th Dust Bowl 2023
271 Texas A&M-B Win 13-6 1232.68 Mar 11th Centex Tier 2
186 Texas State Loss 10-12 759.72 Mar 11th Centex Tier 2
302 Houston** Win 13-3 1041.66 Ignored Mar 11th Centex Tier 2
252 Texas-B Win 13-6 1330 Mar 12th Centex Tier 2
143 Colorado-B Loss 10-15 729.13 Mar 12th Centex Tier 2
93 Iowa Loss 12-15 1125.8 Mar 12th Centex Tier 2
249 Texas-San Antonio Win 15-4 1336.79 Mar 12th Centex Tier 2
**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)