#52 Oregon State (15-9)

avg: 1464.09  •  sd: 68.86  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
63 British Columbia-B Win 8-7 1456.04 Feb 1st Stanford Open Womens
165 Cal Poly-SLO-B Win 13-7 1193.58 Feb 1st Stanford Open Womens
46 Carleton College-Eclipse Win 9-8 1670.04 Feb 1st Stanford Open Womens
63 British Columbia-B Win 10-7 1720.7 Feb 2nd Stanford Open Womens
141 Stanford-B Win 8-5 1198.95 Feb 2nd Stanford Open Womens
68 Santa Clara Loss 9-11 1050.86 Feb 2nd Stanford Open Womens
76 Portland Win 9-7 1503.31 Feb 2nd Stanford Open Womens
73 Colorado College Win 10-6 1764.98 Feb 8th DIII Grand Prix 2025
66 Lewis & Clark Win 12-10 1552.38 Feb 8th DIII Grand Prix 2025
113 Puget Sound Win 12-5 1569.45 Feb 8th DIII Grand Prix 2025
42 Whitman Loss 7-13 1010.62 Feb 8th DIII Grand Prix 2025
46 Carleton College-Eclipse Loss 10-12 1306.91 Feb 9th DIII Grand Prix 2025
133 Claremont** Win 13-5 1423.43 Ignored Feb 9th DIII Grand Prix 2025
76 Portland Loss 10-12 985.85 Feb 9th DIII Grand Prix 2025
219 Cal Poly-Humboldt** Win 13-2 829.91 Ignored Mar 8th PACcon
250 Lewis & Clark -B** Win 11-2 575.28 Ignored Mar 8th PACcon
18 Western Washington Loss 10-12 1728.5 Mar 8th PACcon
66 Lewis & Clark Win 11-10 1439.25 Mar 9th PACcon
168 Pacific Lutheran Win 11-7 1086.81 Mar 9th PACcon
18 Western Washington Loss 5-13 1366.62 Mar 9th PACcon
6 Oregon Loss 11-14 1906.55 Apr 3rd Cascadia D I Womens Conferences 2025
63 British Columbia-B Win 12-8 1772.19 Apr 12th Cascadia D I Womens Conferences 2025
7 Washington Loss 8-15 1624.49 Apr 12th Cascadia D I Womens Conferences 2025
16 Victoria Loss 6-15 1385.9 Apr 12th Cascadia D I Womens Conferences 2025
**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)