#184 Georgia State (7-9)

avg: 1134.51  •  sd: 79.28  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
122 Clemson Loss 7-12 841.08 Mar 1st Joint Summit 2025
330 South Carolina-B Win 13-5 1175.32 Mar 1st Joint Summit 2025
198 North Carolina-B Loss 9-12 730.82 Mar 1st Joint Summit 2025
188 Georgia Tech-B Win 12-10 1355.93 Mar 1st Joint Summit 2025
122 Clemson Loss 1-11 761.6 Mar 2nd Joint Summit 2025
198 North Carolina-B Loss 10-15 622.58 Mar 2nd Joint Summit 2025
101 Berry Win 15-14 1587.45 Mar 15th Tally Classic XIX
126 Central Florida Loss 8-13 850.32 Mar 15th Tally Classic XIX
71 Florida Loss 9-12 1264.88 Mar 15th Tally Classic XIX
132 Florida State Win 10-9 1452.53 Mar 15th Tally Classic XIX
18 Georgia** Loss 4-13 1438.84 Ignored Apr 12th Southern Appalachian D I Mens Conferences 2025
98 Tennessee-Chattanooga Win 10-8 1734.89 Apr 12th Southern Appalachian D I Mens Conferences 2025
82 Tennessee Loss 6-9 1127.4 Apr 12th Southern Appalachian D I Mens Conferences 2025
303 Tennessee Tech Win 10-7 1061.46 Apr 12th Southern Appalachian D I Mens Conferences 2025
233 Georgia Southern Win 15-12 1235.75 Apr 13th Southern Appalachian D I Mens Conferences 2025
82 Tennessee Loss 5-15 945.96 Apr 13th Southern Appalachian D I 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)