#223 Elon (4-12)

avg: 383.22  •  sd: 88.72  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
71 William & Mary Loss 6-13 726.62 Feb 9th Ultimate Galentines Celebration 2019
274 Wooster Win 13-3 385.82 Feb 9th Ultimate Galentines Celebration 2019
203 Wake Forest Loss 12-13 383.51 Feb 9th Ultimate Galentines Celebration 2019
153 Virginia Tech Loss 4-13 260.33 Feb 9th Ultimate Galentines Celebration 2019
259 East Carolina Win 13-2 673.16 Feb 10th Ultimate Galentines Celebration 2019
27 Delaware** Loss 3-13 1214.9 Ignored Feb 23rd Commonwealth Cup 2019
51 Florida State** Loss 1-13 908.35 Ignored Feb 23rd Commonwealth Cup 2019
135 Princeton Loss 3-13 342.48 Feb 23rd Commonwealth Cup 2019
93 Kennesaw State Loss 7-13 630.51 Feb 23rd Commonwealth Cup 2019
209 North Carolina-B Loss 5-13 -113.56 Feb 24th Commonwealth Cup 2019
271 Virginia-B Win 10-5 390.44 Feb 24th Commonwealth Cup 2019
284 Miami (Ohio)** Win 13-5 7.25 Ignored Mar 9th Mash Up 2019
63 New Hampshire** Loss 5-12 814.87 Ignored Mar 9th Mash Up 2019
122 Georgia College Loss 7-11 556.32 Mar 9th Mash Up 2019
212 SUNY-Fredonia Loss 6-10 -17.35 Mar 10th Mash Up 2019
170 Vermont-B Loss 6-8 435.11 Mar 10th Mash Up 2019
**Blowout Eligible

FAQ

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
  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
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)