#146 Kansas (7-5)

avg: 1168.89  •  sd: 87.41  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
271 Texas A&M-B Win 13-1 1232.68 Feb 25th Dust Bowl 2023
254 Oklahoma Win 9-6 1136.04 Feb 25th Dust Bowl 2023
207 Illinois State Win 13-5 1510.86 Feb 25th Dust Bowl 2023
28 Oklahoma Christian Loss 6-13 1243.49 Feb 25th Dust Bowl 2023
217 Texas-Dallas Loss 6-9 454.39 Feb 26th Dust Bowl 2023
193 North Texas Win 11-5 1574.85 Feb 26th Dust Bowl 2023
156 Wichita State Win 9-7 1406.8 Feb 26th Dust Bowl 2023
246 Northern Iowa Win 8-5 1202.45 Mar 4th Midwest Throwdown 2023
341 Iowa State-B** Win 13-0 770.62 Ignored Mar 4th Midwest Throwdown 2023
75 Grinnell Loss 6-9 1068.2 Mar 4th Midwest Throwdown 2023
148 Minnesota-Duluth Loss 9-11 911.81 Mar 5th Midwest Throwdown 2023
48 Iowa State Loss 6-11 1099.65 Mar 5th Midwest Throwdown 2023
**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)