#361 Oregon State-B (3-18)

avg: 440.58  •  sd: 117.41  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
338 Cal Poly-Humboldt Loss 8-15 -1.25 Jan 27th Trouble in Corvegas
19 Oregon State** Loss 0-15 1498.46 Ignored Jan 27th Trouble in Corvegas
160 Washington State** Loss 5-15 683.92 Ignored Jan 27th Trouble in Corvegas
355 Portland State Loss 11-15 110.02 Jan 27th Trouble in Corvegas
338 Cal Poly-Humboldt Loss 10-12 325.44 Jan 28th Trouble in Corvegas
66 Western Washington** Loss 1-15 1073.44 Ignored Jan 28th Trouble in Corvegas
235 Claremont Loss 3-13 395.21 Feb 3rd Stanford Open 2024
178 Portland Loss 7-12 688.26 Feb 3rd Stanford Open 2024
124 San Jose State** Loss 4-13 792.34 Ignored Feb 3rd Stanford Open 2024
291 Pacific Lutheran Loss 7-10 358.88 Mar 2nd PLU Mens BBQ
355 Portland State Win 10-8 753.85 Mar 2nd PLU Mens BBQ
365 Seattle Loss 9-10 306.55 Mar 2nd PLU Mens BBQ
155 Washington-B** Loss 3-13 700 Ignored Mar 2nd PLU Mens BBQ
335 Willamette Win 11-10 695.54 Mar 3rd PLU Mens BBQ
276 Whitworth Loss 2-13 246.13 Mar 3rd PLU Mens BBQ
7 Oregon** Loss 1-15 1730.08 Ignored Apr 13th Cascadia D I Mens Conferences 2024
22 Washington** Loss 3-15 1433.49 Ignored Apr 13th Cascadia D I Mens Conferences 2024
355 Portland State Loss 10-15 37.58 Apr 13th Cascadia D I Mens Conferences 2024
66 Western Washington** Loss 5-15 1073.44 Ignored Apr 13th Cascadia D I Mens Conferences 2024
155 Washington-B** Loss 4-15 700 Ignored Apr 14th Cascadia D I Mens Conferences 2024
355 Portland State Win 15-7 1091.18 Apr 14th Cascadia D I Mens Conferences 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)