#247 Georgia Southern (4-15)

avg: 413.37  •  sd: 60.44  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
90 Alabama** Loss 3-13 623.49 Ignored Jan 28th T Town Throwdown1
102 Central Florida** Loss 4-15 554.49 Ignored Jan 28th T Town Throwdown1
141 LSU Loss 5-13 379.7 Jan 28th T Town Throwdown1
308 North Florida** Win 13-5 370.08 Ignored Jan 28th T Town Throwdown1
254 Alabama-B Win 8-7 495.08 Jan 29th T Town Throwdown1
221 Florida-B Loss 6-13 -58.31 Jan 29th T Town Throwdown1
225 Jacksonville State Loss 7-10 137.11 Jan 29th T Town Throwdown1
107 Chicago Loss 8-11 760.41 Mar 11th Tally Classic XVII
141 LSU Loss 4-13 379.7 Mar 11th Tally Classic XVII
115 Florida State** Loss 5-13 485.76 Ignored Mar 11th Tally Classic XVII
79 Notre Dame** Loss 5-13 689.15 Ignored Mar 11th Tally Classic XVII
211 Alabama-Birmingham Loss 12-14 387.14 Mar 12th Tally Classic XVII
102 Central Florida** Loss 4-15 554.49 Ignored Mar 12th Tally Classic XVII
60 Appalachian State** Loss 3-13 757.46 Ignored Mar 18th College Southerns XXI
151 Carleton College-CHOP Loss 7-13 401.34 Mar 18th College Southerns XXI
221 Florida-B Win 11-6 1088.38 Mar 18th College Southerns XXI
148 East Carolina Loss 4-14 364.09 Mar 19th College Southerns XXI
207 Georgia-B Loss 3-14 31.28 Mar 19th College Southerns XXI
264 Georgia Tech-B Win 11-10 410.49 Mar 19th College Southerns XXI
**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)