#335 Willamette (2-9)

avg: 570.54  •  sd: 83.33  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
178 Portland Loss 6-13 608.77 Mar 2nd PLU Mens BBQ
169 Puget Sound** Loss 4-13 652.14 Ignored Mar 2nd PLU Mens BBQ
276 Whitworth Loss 5-10 272.23 Mar 2nd PLU Mens BBQ
361 Oregon State-B Loss 10-11 315.58 Mar 3rd PLU Mens BBQ
355 Portland State Win 13-11 720.03 Mar 3rd PLU Mens BBQ
169 Puget Sound Loss 9-11 1002.93 Apr 13th Northwest D III Mens Conferences 2024
239 Reed Loss 5-11 389.35 Apr 13th Northwest D III Mens Conferences 2024
365 Seattle Win 8-4 996.36 Apr 13th Northwest D III Mens Conferences 2024
81 Lewis & Clark** Loss 2-11 987.48 Ignored Apr 13th Northwest D III Mens Conferences 2024
365 Seattle Loss 14-15 306.55 Apr 14th Northwest D III Mens Conferences 2024
276 Whitworth Loss 11-15 464.97 Apr 14th Northwest D III Mens Conferences 2024
**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)