#184 East Carolina (14-13)

avg: 889.71  •  sd: 56.83  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
180 American Win 10-9 1030.74 Jan 25th Mid Atlantic Warm Up 2025
75 Carnegie Mellon Loss 7-9 1091.91 Jan 25th Mid Atlantic Warm Up 2025
101 Yale Loss 7-13 704.95 Jan 25th Mid Atlantic Warm Up 2025
64 James Madison Loss 6-11 910.69 Jan 25th Mid Atlantic Warm Up 2025
122 Boston University Loss 10-13 839.64 Jan 26th Mid Atlantic Warm Up 2025
298 Navy Win 15-4 988.51 Jan 26th Mid Atlantic Warm Up 2025
179 Pennsylvania Loss 8-13 415.74 Jan 26th Mid Atlantic Warm Up 2025
180 American Win 12-6 1485.05 Feb 22nd Monument Melee 2025
247 George Washington Win 11-4 1225.89 Feb 22nd Monument Melee 2025
324 Villanova** Win 13-2 860.06 Ignored Feb 22nd Monument Melee 2025
272 Virginia Commonwealth Win 9-8 636.33 Feb 23rd Monument Melee 2025
157 Johns Hopkins Win 10-9 1130.84 Feb 23rd Monument Melee 2025
159 George Mason Loss 10-12 759.65 Feb 23rd Monument Melee 2025
180 American Loss 9-12 560.37 Mar 22nd Atlantic Coast Open 2025
171 Dickinson Win 9-8 1078.2 Mar 22nd Atlantic Coast Open 2025
81 North Carolina-Charlotte Loss 6-12 742.95 Mar 22nd Atlantic Coast Open 2025
357 George Washington-B** Win 15-0 628.03 Ignored Mar 22nd Atlantic Coast Open 2025
139 Florida State Win 14-13 1208.69 Mar 23rd Atlantic Coast Open 2025
159 George Mason Win 10-9 1122.77 Mar 23rd Atlantic Coast Open 2025
138 RIT Loss 9-15 577.44 Mar 23rd Atlantic Coast Open 2025
199 North Carolina State-B Win 8-7 942.07 Mar 29th Needle in a Ho Stack 2025
232 Georgia Southern Win 12-8 1119.41 Mar 29th Needle in a Ho Stack 2025
65 Tennessee Loss 7-13 896.01 Mar 29th Needle in a Ho Stack 2025
260 Georgia-B Win 10-4 1167.19 Mar 29th Needle in a Ho Stack 2025
94 Tennessee-Chattanooga Loss 11-12 1154.56 Mar 30th Needle in a Ho Stack 2025
232 Georgia Southern Loss 8-11 312.65 Mar 30th Needle in a Ho Stack 2025
187 North Carolina-B Loss 5-11 264.39 Mar 30th Needle in a Ho Stack 2025
**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)