#32 Oklahoma Christian (14-3)

avg: 1627.39  •  sd: 86.04  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
111 John Brown Win 11-9 1377.54 Feb 5th JPC Just Plain Chilly
278 Oklahoma** Win 13-3 949.76 Ignored Feb 5th JPC Just Plain Chilly
259 Oklahoma State** Win 13-2 1067.69 Ignored Feb 5th JPC Just Plain Chilly
150 Kansas Win 13-6 1561.07 Feb 25th Dust Bowl 2023
271 Texas A&M-B** Win 13-1 1007.6 Ignored Feb 25th Dust Bowl 2023
198 Illinois State Win 10-6 1242.11 Feb 25th Dust Bowl 2023
278 Oklahoma** Win 12-5 949.76 Ignored Feb 25th Dust Bowl 2023
93 Arkansas Win 12-9 1586.42 Feb 26th Dust Bowl 2023
60 Missouri Win 8-7 1519.56 Feb 26th Dust Bowl 2023
102 Missouri S&T Win 11-6 1722.55 Feb 26th Dust Bowl 2023
12 Carleton College Loss 10-11 1738.49 Mar 18th Centex 2023
4 Texas Loss 2-13 1421.51 Mar 18th Centex 2023
44 Colorado College Win 12-11 1614.81 Mar 18th Centex 2023
50 Virginia Win 8-5 1897.2 Mar 18th Centex 2023
13 Tufts Loss 12-15 1557.68 Mar 19th Centex 2023
28 Georgia Tech Win 14-13 1797.79 Mar 19th Centex 2023
29 Wisconsin Win 14-11 1980 Mar 19th Centex 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)