#74 Cincinnati (5-9)

avg: 1361.2  •  sd: 91.13  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
82 Central Florida Win 13-10 1665.41 Feb 2nd Florida Warm Up 2024
14 Texas Loss 9-11 1687.43 Feb 2nd Florida Warm Up 2024
20 Northeastern Loss 6-13 1230.32 Feb 2nd Florida Warm Up 2024
101 Cornell Loss 11-13 995.73 Feb 3rd Florida Warm Up 2024
2 Georgia** Loss 5-13 1672.81 Ignored Feb 3rd Florida Warm Up 2024
33 Wisconsin Loss 11-14 1332.16 Feb 4th Florida Warm Up 2024
57 Auburn Loss 6-13 847.19 Feb 24th Easterns Qualifier 2024
169 Rutgers Win 13-7 1509.17 Feb 24th Easterns Qualifier 2024
56 Emory Loss 10-13 1119.43 Feb 24th Easterns Qualifier 2024
28 North Carolina-Wilmington Loss 7-12 1213.99 Feb 24th Easterns Qualifier 2024
50 Alabama Loss 6-15 901.57 Feb 25th Easterns Qualifier 2024
68 James Madison Win 12-9 1722.26 Feb 25th Easterns Qualifier 2024
106 Notre Dame Win 15-12 1510.81 Feb 25th Easterns Qualifier 2024
61 William & Mary Win 11-4 2032.01 Feb 25th Easterns Qualifier 2024
**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)