#22 Western Washington (12-8)

avg: 1849.96  •  sd: 49.12  •  top 16/20: 43%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
5 Oregon Loss 9-15 1678.15 Jan 25th Pac Con 2025
10 Oregon State Loss 12-15 1681.18 Jan 25th Pac Con 2025
121 Simon Fraser Win 14-13 1295.02 Jan 25th Pac Con 2025
175 Cal Poly-Humboldt** Win 15-1 1536.36 Ignored Jan 26th Pac Con 2025
10 Oregon State Loss 12-15 1681.18 Jan 26th Pac Con 2025
189 Oregon State-B** Win 15-6 1463.35 Ignored Jan 26th Pac Con 2025
14 California Win 11-10 2094.23 Mar 8th Stanford Invite 2025 Mens
33 California-Santa Barbara Win 11-10 1785.93 Mar 8th Stanford Invite 2025 Mens
123 Wisconsin-Milwaukee** Win 13-4 1746.99 Ignored Mar 8th Stanford Invite 2025 Mens
12 British Columbia Win 11-10 2096.97 Mar 9th Stanford Invite 2025 Mens
41 California-San Diego Win 13-9 2040.03 Mar 9th Stanford Invite 2025 Mens
9 California-Santa Cruz Loss 11-13 1792.34 Mar 9th Stanford Invite 2025 Mens
8 Brigham Young Loss 13-14 1945.56 Mar 21st Northwest Challenge 2025 mens
41 California-San Diego Win 15-11 2002.63 Mar 22nd Northwest Challenge 2025 mens
10 Oregon State Loss 14-15 1856.68 Mar 22nd Northwest Challenge 2025 mens
55 UCLA Win 15-13 1749.42 Mar 22nd Northwest Challenge 2025 mens
23 Victoria Loss 13-15 1634.24 Mar 22nd Northwest Challenge 2025 mens
33 California-Santa Barbara Win 15-11 2042.09 Mar 23rd Northwest Challenge 2025 mens
10 Oregon State Loss 13-15 1767.5 Mar 23rd Northwest Challenge 2025 mens
23 Victoria Win 14-13 1973.42 Mar 23rd Northwest Challenge 2025 mens
**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)