#263 Georgia-B (5-8)

avg: 822.37  •  sd: 78.3  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
168 Charleston Loss 5-9 678.82 Mar 15th Southerns 2025
359 Georgia College Win 8-5 846.34 Mar 15th Southerns 2025
233 Georgia Southern Win 10-8 1197.93 Mar 15th Southerns 2025
188 Georgia Tech-B Loss 6-8 817.31 Mar 15th Southerns 2025
188 Georgia Tech-B Loss 5-9 588.75 Mar 15th Southerns 2025
106 Appalachian State** Loss 3-13 849.49 Ignored Mar 29th Needle in a Ho Stack 2025
172 East Carolina Loss 4-10 584.39 Mar 29th Needle in a Ho Stack 2025
228 Embry-Riddle Loss 6-11 415.11 Mar 29th Needle in a Ho Stack 2025
359 Georgia College Win 13-6 992.73 Mar 29th Needle in a Ho Stack 2025
228 Embry-Riddle Win 13-7 1519.34 Mar 30th Needle in a Ho Stack 2025
370 Morehouse Win 11-4 914.4 Mar 30th Needle in a Ho Stack 2025
203 North Carolina State-B Loss 7-10 666.07 Mar 30th Needle in a Ho Stack 2025
188 Georgia Tech-B Loss 9-15 602.33 Apr 19th Southeast Dev Mens Conferences 2025
**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)