#154 Oregon State (1-17)

avg: 859.31  •  sd: 121.7  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
48 Colorado College** Loss 2-13 1013.36 Ignored Feb 10th DIII Grand Prix
75 Lewis & Clark Loss 6-8 1074.59 Feb 10th DIII Grand Prix
43 Portland Loss 5-11 1061.6 Feb 10th DIII Grand Prix
46 Whitman Loss 5-11 1040.31 Feb 10th DIII Grand Prix
37 Carleton College-Eclipse** Loss 2-10 1149.41 Ignored Feb 11th DIII Grand Prix
118 Puget Sound Loss 5-7 781.91 Feb 11th DIII Grand Prix
118 Puget Sound Loss 6-8 809.56 Feb 24th PLU Womens BBQ 2024
43 Portland** Loss 2-13 1061.6 Ignored Feb 24th PLU Womens BBQ 2024
189 Pacific Lutheran Win 12-1 1166.31 Feb 24th PLU Womens BBQ 2024
118 Puget Sound Loss 3-10 510.05 Feb 25th PLU Womens BBQ 2024
10 Washington** Loss 5-15 1658.08 Ignored Apr 13th Cascadia D I Womens Conferences 2024
15 Western Washington** Loss 4-15 1532.74 Ignored Apr 14th Cascadia D I Womens Conferences 2024
11 Brigham Young** Loss 3-13 1656.04 Ignored May 4th Northwest D I College Womens Regionals 2024
116 Montana Loss 7-11 645.99 May 4th Northwest D I College Womens Regionals 2024
4 Oregon** Loss 1-13 1969.05 Ignored May 4th Northwest D I College Womens Regionals 2024
10 Washington** Loss 4-13 1658.08 Ignored May 4th Northwest D I College Womens Regionals 2024
25 Utah** Loss 1-13 1286.02 Ignored May 5th Northwest D I College Womens Regionals 2024
13 Victoria** Loss 0-13 1553.37 Ignored May 5th Northwest D I College Womens Regionals 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)