#215 East Carolina (10-15)

avg: 1065.59  •  sd: 78.34  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
217 George Washington Win 10-6 1554.66 Feb 24th Monument Melee
202 George Mason Loss 6-8 815.83 Feb 24th Monument Melee
170 Villanova Loss 6-9 833.4 Feb 24th Monument Melee
204 Virginia Commonwealth Loss 7-10 718.31 Feb 25th Monument Melee
202 George Mason Win 8-7 1241.33 Feb 25th Monument Melee
217 George Washington Win 11-10 1183.5 Feb 25th Monument Melee
196 Charleston Win 8-3 1733.53 Mar 16th Southerns 2024
224 Georgia-B Loss 7-9 760.02 Mar 16th Southerns 2024
418 Wisconsin-Eau Claire-B** Win 13-2 600 Ignored Mar 16th Southerns 2024
196 Charleston Win 9-2 1733.53 Mar 17th Southerns 2024
224 Georgia-B Loss 7-9 760.02 Mar 17th Southerns 2024
304 Luther College Win 12-6 1274.28 Mar 17th Southerns 2024
86 Cedarville Loss 3-13 955.52 Mar 23rd Needle in a Ho Stack 2024
251 North Carolina State-B Win 8-7 1067.94 Mar 23rd Needle in a Ho Stack 2024
265 Georgia College Win 12-1 1489.6 Mar 24th Needle in a Ho Stack 2024
104 Liberty Loss 2-12 890.72 Mar 24th Needle in a Ho Stack 2024
214 North Carolina-B Win 11-6 1620.49 Mar 24th Needle in a Ho Stack 2024
164 Kennesaw State Loss 6-10 772.97 Mar 24th Needle in a Ho Stack 2024
146 Clemson Loss 8-9 1193.35 Apr 13th Carolina D I Mens Conferences 2024
50 Duke** Loss 4-15 1172.52 Ignored Apr 13th Carolina D I Mens Conferences 2024
27 North Carolina-Wilmington** Loss 4-12 1395.28 Ignored Apr 13th Carolina D I Mens Conferences 2024
2 North Carolina** Loss 3-15 1886.33 Ignored Apr 13th Carolina D I Mens Conferences 2024
72 Appalachian State Loss 7-14 1045.76 Apr 14th Carolina D I Mens Conferences 2024
196 Charleston Loss 8-11 767.92 Apr 14th Carolina D I Mens Conferences 2024
241 Wake Forest Loss 4-14 386.99 Apr 14th Carolina 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)