#355 Portland State (3-18)

avg: 491.18  •  sd: 121.54  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
338 Cal Poly-Humboldt Win 12-10 801.69 Jan 27th Trouble in Corvegas
361 Oregon State-B Win 15-11 821.74 Jan 27th Trouble in Corvegas
160 Washington State** Loss 1-15 683.92 Ignored Jan 27th Trouble in Corvegas
66 Western Washington** Loss 5-15 1073.44 Ignored Jan 27th Trouble in Corvegas
19 Oregon State** Loss 2-15 1498.46 Ignored Jan 28th Trouble in Corvegas
19 Oregon State** Loss 0-15 1498.46 Ignored Jan 28th Trouble in Corvegas
160 Washington State Loss 10-15 830.31 Jan 28th Trouble in Corvegas
361 Oregon State-B Loss 8-10 177.91 Mar 2nd PLU Mens BBQ
291 Pacific Lutheran Loss 4-13 148.55 Mar 2nd PLU Mens BBQ
160 Washington State Loss 7-12 763.4 Mar 2nd PLU Mens BBQ
155 Washington-B** Loss 3-13 700 Ignored Mar 2nd PLU Mens BBQ
276 Whitworth Loss 8-12 404.98 Mar 3rd PLU Mens BBQ
335 Willamette Loss 11-13 341.7 Mar 3rd PLU Mens BBQ
169 Puget Sound** Loss 2-13 652.14 Ignored Mar 31st PDX Round Robin 2024
169 Puget Sound** Loss 3-13 652.14 Ignored Mar 31st PDX Round Robin 2024
7 Oregon** Loss 0-15 1730.08 Ignored Apr 13th Cascadia D I Mens Conferences 2024
361 Oregon State-B Win 15-10 894.18 Apr 13th Cascadia D I Mens Conferences 2024
66 Western Washington** Loss 2-15 1073.44 Ignored Apr 13th Cascadia D I Mens Conferences 2024
22 Washington** Loss 0-15 1433.49 Ignored Apr 13th Cascadia D I Mens Conferences 2024
177 British Columbia -B Loss 7-13 651.57 Apr 14th Cascadia D I Mens Conferences 2024
361 Oregon State-B Loss 7-15 -159.42 Apr 14th Cascadia D I 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)