#168 Washington State (14-5)

avg: 953.98  •  sd: 73.85  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
18 Oregon State Loss 10-15 1415.7 Jan 27th Trouble in Corvegas
356 Oregon State-B** Win 15-5 591.5 Ignored Jan 27th Trouble in Corvegas
339 Portland State** Win 15-1 705.28 Ignored Jan 27th Trouble in Corvegas
63 Western Washington Loss 9-15 906.75 Jan 27th Trouble in Corvegas
349 Cal Poly-Humboldt Win 15-7 627.1 Jan 28th Trouble in Corvegas
339 Portland State Win 15-10 558.89 Jan 28th Trouble in Corvegas
63 Western Washington Loss 12-15 1121.74 Jan 28th Trouble in Corvegas
341 Boise State Win 15-7 696.53 Feb 24th Palouse Open 2024
159 Gonzaga Loss 7-12 482.36 Feb 24th Palouse Open 2024
291 Idaho Win 15-4 1005.33 Feb 24th Palouse Open 2024
279 Whitworth Win 15-5 1079.7 Feb 24th Palouse Open 2024
159 Gonzaga Win 10-5 1576.77 Feb 25th Palouse Open 2024
279 Whitworth Win 11-4 1079.7 Feb 25th Palouse Open 2024
284 Pacific Lutheran Win 13-4 1030.87 Mar 2nd PLU Mens BBQ
339 Portland State Win 12-7 625.79 Mar 2nd PLU Mens BBQ
345 Seattle** Win 12-5 654.9 Ignored Mar 2nd PLU Mens BBQ
186 Washington-B Loss 9-11 616.2 Mar 2nd PLU Mens BBQ
190 Portland Win 11-8 1227.36 Mar 3rd PLU Mens BBQ
186 Washington-B Win 7-4 1361.57 Mar 3rd PLU Mens BBQ
**Blowout Eligible

FAQ

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
  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
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)