#78 Richmond (11-10)

avg: 1348.03  •  sd: 54.17  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
122 Boston University Win 13-8 1663.94 Jan 25th Mid Atlantic Warm Up 2025
60 Michigan State Loss 5-13 886.35 Jan 25th Mid Atlantic Warm Up 2025
138 RIT Win 13-5 1692.92 Jan 25th Mid Atlantic Warm Up 2025
272 Virginia Commonwealth** Win 13-4 1111.33 Ignored Jan 25th Mid Atlantic Warm Up 2025
39 Cincinnati Loss 10-12 1391.92 Jan 26th Mid Atlantic Warm Up 2025
66 Dartmouth Win 11-10 1577.25 Jan 26th Mid Atlantic Warm Up 2025
159 George Mason Win 11-10 1122.77 Jan 26th Mid Atlantic Warm Up 2025
52 William & Mary Loss 8-13 1055.33 Jan 26th Mid Atlantic Warm Up 2025
149 Davidson Win 13-7 1612.28 Feb 28th D III River City Showdown 2025
163 Messiah Win 13-7 1539.13 Mar 1st D III River City Showdown 2025
125 Puget Sound Win 11-7 1607.5 Mar 1st D III River City Showdown 2025
54 Carleton College-CHOP Loss 10-11 1413.06 Mar 2nd D III River City Showdown 2025
99 Oberlin Loss 9-11 1016.89 Mar 2nd D III River City Showdown 2025
80 Rochester Loss 9-13 921.92 Mar 2nd D III River City Showdown 2025
144 Bates Win 13-8 1555.72 Mar 29th Easterns 2025
206 Christopher Newport Win 13-3 1378.26 Mar 29th Easterns 2025
171 Dickinson Win 13-5 1553.2 Mar 29th Easterns 2025
46 Middlebury Loss 10-13 1269.65 Mar 29th Easterns 2025
70 Franciscan Loss 11-12 1285.69 Mar 30th Easterns 2025
34 Lewis & Clark Loss 7-12 1138.79 Mar 30th Easterns 2025
46 Middlebury Loss 10-13 1269.65 Mar 30th Easterns 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)