#246 Georgia Southern (4-12)

avg: 970.37  •  sd: 68.91  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
78 Carleton College-CHOP** Loss 5-13 1004.23 Ignored Mar 16th Southerns 2024
248 Florida-B Loss 9-11 714.66 Mar 16th Southerns 2024
265 Georgia College Loss 9-12 544.24 Mar 16th Southerns 2024
248 Florida-B Win 15-5 1563.86 Mar 17th Southerns 2024
261 Georgia Tech-B Loss 11-14 590.94 Mar 17th Southerns 2024
346 Coastal Carolina Win 9-6 949.59 Mar 23rd Needle in a Ho Stack 2024
114 Davidson Loss 7-10 1047.61 Mar 23rd Needle in a Ho Stack 2024
214 North Carolina-B Loss 8-9 948.8 Mar 24th Needle in a Ho Stack 2024
241 Wake Forest Win 9-6 1405.55 Mar 24th Needle in a Ho Stack 2024
251 North Carolina State-B Loss 8-9 817.94 Mar 24th Needle in a Ho Stack 2024
306 High Point Win 12-9 1037.87 Mar 24th Needle in a Ho Stack 2024
54 Emory** Loss 4-15 1155.32 Ignored Apr 13th Southern Appalachian D I Mens Conferences 2024
28 Georgia Tech** Loss 3-15 1388.02 Ignored Apr 13th Southern Appalachian D I Mens Conferences 2024
99 Tennessee-Chattanooga Loss 3-15 918.93 Apr 13th Southern Appalachian D I Mens Conferences 2024
98 Georgia State Loss 4-15 920.82 Apr 14th Southern Appalachian D I Mens Conferences 2024
99 Tennessee-Chattanooga Loss 8-11 1153.33 Apr 14th Southern Appalachian D I Mens Conferences 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)