#155 Washington-B (11-10)

avg: 1300  •  sd: 60.98  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
255 Cal State-Long Beach Win 13-8 1418.95 Feb 3rd Stanford Open 2024
354 California-Santa Cruz-B Win 11-6 1038.02 Feb 3rd Stanford Open 2024
169 Puget Sound Loss 6-12 672.83 Feb 3rd Stanford Open 2024
361 Oregon State-B** Win 13-3 1040.58 Ignored Mar 2nd PLU Mens BBQ
355 Portland State** Win 13-3 1091.18 Ignored Mar 2nd PLU Mens BBQ
365 Seattle Win 13-6 1031.55 Mar 2nd PLU Mens BBQ
160 Washington State Win 11-9 1533.12 Mar 2nd PLU Mens BBQ
169 Puget Sound Loss 8-10 989.47 Mar 3rd PLU Mens BBQ
239 Reed Win 13-9 1407.92 Mar 3rd PLU Mens BBQ
160 Washington State Loss 4-7 787.76 Mar 3rd PLU Mens BBQ
21 British Columbia** Loss 3-15 1449.89 Ignored Apr 13th Cascadia D I Mens Conferences 2024
177 British Columbia -B Win 12-11 1334.1 Apr 13th Cascadia D I Mens Conferences 2024
19 Oregon State** Loss 4-15 1498.46 Ignored Apr 13th Cascadia D I Mens Conferences 2024
177 British Columbia -B Win 14-12 1430.06 Apr 14th Cascadia D I Mens Conferences 2024
361 Oregon State-B** Win 15-4 1040.58 Ignored Apr 14th Cascadia D I Mens Conferences 2024
66 Western Washington Loss 2-15 1073.44 Apr 14th Cascadia D I Mens Conferences 2024
21 British Columbia Loss 6-13 1449.89 May 4th Northwest D I College Mens Regionals 2024
19 Oregon State Loss 10-13 1770.32 May 4th Northwest D I College Mens Regionals 2024
40 Victoria Loss 2-13 1257.48 May 4th Northwest D I College Mens Regionals 2024
160 Washington State Win 13-10 1612.06 May 4th Northwest D I College Mens Regionals 2024
58 Utah Valley Loss 7-13 1180.01 May 5th Northwest D I College Mens Regionals 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)