#84 Elon (15-4)

avg: 1576.44  •  sd: 37.53  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
86 Cedarville Loss 9-11 1306.31 Feb 17th Commonwealth Cup Weekend 1 2024
214 North Carolina-B Win 13-7 1631.33 Feb 17th Commonwealth Cup Weekend 1 2024
254 Michigan-B** Win 13-5 1528.81 Ignored Feb 17th Commonwealth Cup Weekend 1 2024
86 Cedarville Win 11-10 1680.52 Feb 18th Commonwealth Cup Weekend 1 2024
104 Liberty Win 11-9 1739.93 Feb 18th Commonwealth Cup Weekend 1 2024
64 Maryland Loss 7-8 1552.89 Feb 18th Commonwealth Cup Weekend 1 2024
274 Air Force** Win 13-3 1450.51 Ignored Mar 2nd FCS D III Tune Up 2024
88 Berry Loss 12-13 1426.68 Mar 2nd FCS D III Tune Up 2024
198 Messiah Win 13-9 1547.56 Mar 2nd FCS D III Tune Up 2024
123 Oberlin Win 13-12 1521.72 Mar 2nd FCS D III Tune Up 2024
232 Butler Win 13-6 1610.21 Mar 3rd FCS D III Tune Up 2024
168 Kenyon Win 13-11 1481.2 Mar 3rd FCS D III Tune Up 2024
173 Xavier Win 13-10 1561.57 Mar 3rd FCS D III Tune Up 2024
209 Christopher Newport Win 14-5 1681.48 Apr 20th Atlantic Coast D III Mens Conferences 2024
179 North Carolina-Asheville Win 15-3 1799.53 Apr 20th Atlantic Coast D III Mens Conferences 2024
176 Navy Win 15-7 1812.43 Apr 20th Atlantic Coast D III Mens Conferences 2024
209 Christopher Newport Win 13-8 1577.64 Apr 21st Atlantic Coast D III Mens Conferences 2024
114 Davidson Loss 10-12 1199.15 Apr 21st Atlantic Coast D III Mens Conferences 2024
306 High Point** Win 15-3 1292.5 Ignored Apr 21st Atlantic Coast D III 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)