#206 George Washington (7-11)

avg: 803.3  •  sd: 74.48  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
189 East Carolina Loss 6-10 365.88 Feb 24th Monument Melee
184 George Mason Win 9-8 1001.05 Feb 24th Monument Melee
166 Villanova Loss 7-11 491.65 Feb 24th Monument Melee
280 Drexel Win 13-7 1031.16 Feb 25th Monument Melee
189 East Carolina Loss 10-11 737.04 Feb 25th Monument Melee
175 Maryland-Baltimore County Loss 8-9 803 Feb 25th Monument Melee
84 Appalachian State Loss 6-9 908.24 Mar 2nd Oak Creek Challenge 2024
130 Towson Loss 3-13 516.83 Mar 2nd Oak Creek Challenge 2024
165 RIT Loss 7-13 407.76 Mar 2nd Oak Creek Challenge 2024
280 Drexel Win 13-6 1073.63 Mar 3rd Oak Creek Challenge 2024
156 Johns Hopkins Loss 6-11 472.34 Mar 3rd Oak Creek Challenge 2024
152 West Chester Loss 8-13 530.41 Mar 3rd Oak Creek Challenge 2024
224 American Win 13-11 960.59 Mar 30th Atlantic Coast Open 2024
231 Christopher Newport Win 15-6 1312.61 Mar 30th Atlantic Coast Open 2024
252 Dickinson Win 15-1 1210.43 Mar 30th Atlantic Coast Open 2024
126 Lehigh Loss 5-15 545.39 Mar 30th Atlantic Coast Open 2024
208 Virginia Commonwealth Win 14-8 1321.41 Mar 31st Atlantic Coast Open 2024
156 Johns Hopkins Loss 8-15 454.23 Mar 31st Atlantic Coast Open 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)