#357 George Washington-B (7-10)

avg: 28.03  •  sd: 73.5  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
388 American-B Win 9-5 108.33 Feb 22nd Monument Melee 2025
352 Georgetown-B Loss 5-8 -356.62 Feb 22nd Monument Melee 2025
374 Richmond-B Win 11-9 141.85 Feb 22nd Monument Melee 2025
388 American-B Win 11-8 -55.12 Feb 23rd Monument Melee 2025
352 Georgetown-B Win 13-7 654.52 Feb 23rd Monument Melee 2025
180 American** Loss 5-14 305.74 Ignored Mar 22nd Atlantic Coast Open 2025
171 Dickinson** Loss 2-15 353.2 Ignored Mar 22nd Atlantic Coast Open 2025
184 East Carolina** Loss 0-15 289.71 Ignored Mar 22nd Atlantic Coast Open 2025
81 North Carolina-Charlotte** Loss 1-15 722.26 Ignored Mar 22nd Atlantic Coast Open 2025
388 American-B Win 11-10 -295.73 Mar 23rd Atlantic Coast Open 2025
276 Virginia Tech-B Loss 5-15 -122.41 Mar 23rd Atlantic Coast Open 2025
379 William & Mary-B Win 10-8 108.06 Mar 29th Fishbowl 2025
291 Virginia-B Loss 5-10 -161.52 Mar 29th Fishbowl 2025
230 West Virginia** Loss 5-13 85.38 Ignored Mar 29th Fishbowl 2025
378 Maryland-B Win 11-7 315.67 Mar 29th Fishbowl 2025
351 James Madison-B Loss 9-10 -19.41 Mar 30th Fishbowl 2025
230 West Virginia** Loss 5-15 85.38 Ignored Mar 30th Fishbowl 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)