#53 Kentucky (9-5)

avg: 1185.8  •  sd: 74.8  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
105 North Carolina-Asheville Win 9-8 868.35 Jan 25th Carolina Kickoff 2020
17 North Carolina-Wilmington Loss 6-9 1149.69 Jan 25th Carolina Kickoff 2020
78 Indiana Win 11-7 1416.15 Jan 25th Carolina Kickoff 2020
102 Florida State Win 11-5 1375.44 Jan 25th Carolina Kickoff 2020
1 North Carolina** Loss 2-15 1611.98 Ignored Jan 26th Carolina Kickoff 2020
58 North Carolina-Charlotte Win 11-9 1363.2 Jan 26th Carolina Kickoff 2020
54 Duke Loss 11-13 952.91 Jan 26th Carolina Kickoff 2020
121 Saint Louis Win 13-6 1179.43 Feb 8th Chattanooga Classic 2020
89 Mississippi State Win 10-3 1471.83 Feb 8th Chattanooga Classic 2020
79 Georgia State Loss 7-9 664.68 Feb 8th Chattanooga Classic 2020
84 Missouri Win 12-4 1497.07 Feb 8th Chattanooga Classic 2020
121 Saint Louis** Win 15-6 1179.43 Ignored Feb 9th Chattanooga Classic 2020
49 Tennessee-Chattanooga Win 11-9 1453.3 Feb 9th Chattanooga Classic 2020
33 Alabama-Huntsville Loss 8-13 845.01 Feb 9th Chattanooga Classic 2020
**Blowout Eligible

FAQ

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
  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
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)