#232 Georgia Southern (8-9)

avg: 678.26  •  sd: 62.07  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
104 Alabama Loss 2-13 638.96 Feb 22nd Mardi Gras XXXVII
258 Trinity Loss 10-11 454.39 Feb 22nd Mardi Gras XXXVII
269 Jacksonville State Win 9-7 814.64 Feb 22nd Mardi Gras XXXVII
270 Texas State Win 11-8 890.14 Feb 22nd Mardi Gras XXXVII
130 Charleston Loss 4-13 523.67 Mar 15th Southerns 2025
130 Charleston Loss 5-15 523.67 Mar 15th Southerns 2025
345 Georgia College Win 12-4 722.42 Mar 15th Southerns 2025
345 Georgia College Win 13-6 722.42 Mar 15th Southerns 2025
196 Georgia Tech-B Loss 5-12 239.54 Mar 15th Southerns 2025
260 Georgia-B Loss 8-10 304.52 Mar 15th Southerns 2025
252 Embry-Riddle Win 10-7 980.1 Mar 23rd Needle in a Ho Stack 2025
184 East Carolina Loss 8-12 448.55 Mar 29th Needle in a Ho Stack 2025
65 Tennessee** Loss 3-13 853.54 Ignored Mar 29th Needle in a Ho Stack 2025
199 North Carolina State-B Win 10-9 942.07 Mar 29th Needle in a Ho Stack 2025
130 Charleston Loss 7-15 523.67 Mar 30th Needle in a Ho Stack 2025
184 East Carolina Win 11-8 1255.32 Mar 30th Needle in a Ho Stack 2025
257 East Tennessee State Win 15-13 794.42 Mar 30th Needle in a Ho Stack 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)