#93 Iowa (13-7)

avg: 1426.29  •  sd: 60.97  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
35 Missouri Loss 8-10 1524.16 Feb 25th Dust Bowl 2023
252 Texas-B Win 12-6 1309.31 Feb 25th Dust Bowl 2023
161 Rice Win 12-5 1711.8 Feb 25th Dust Bowl 2023
264 Oklahoma State** Win 11-4 1281.23 Ignored Feb 25th Dust Bowl 2023
96 Arkansas Loss 8-9 1296.49 Feb 26th Dust Bowl 2023
92 Missouri S&T Loss 9-10 1304.82 Feb 26th Dust Bowl 2023
193 North Texas Win 9-7 1254.18 Feb 26th Dust Bowl 2023
217 Texas-Dallas Win 11-2 1472.96 Feb 26th Dust Bowl 2023
264 Oklahoma State Win 13-7 1238.77 Mar 11th Centex Tier 2
336 Trinity** Win 13-1 814.33 Ignored Mar 11th Centex Tier 2
193 North Texas Win 12-5 1574.85 Mar 11th Centex Tier 2
96 Arkansas Win 15-14 1546.49 Mar 12th Centex Tier 2
161 Rice Win 15-12 1412.3 Mar 12th Centex Tier 2
48 Iowa State Loss 7-15 1046.34 Mar 12th Centex Tier 2
183 Minnesota-B Win 9-7 1290.3 Mar 25th Old Capitol Open
94 Saint Louis Win 13-6 2024.8 Mar 25th Old Capitol Open
64 St. Olaf Loss 7-8 1443 Mar 25th Old Capitol Open
121 Michigan Tech Win 12-7 1813.81 Mar 26th Old Capitol Open
94 Saint Louis Loss 9-10 1299.8 Mar 26th Old Capitol Open
64 St. Olaf Loss 6-11 1021.3 Mar 26th Old Capitol Open
**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)