#58 California-Santa Cruz (11-12)

avg: 1366.65  •  sd: 57.73  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
21 Vermont Loss 8-9 1800.53 Jan 25th Santa Barbara Invite 2020
36 Brigham Young Loss 10-11 1442.15 Jan 25th Santa Barbara Invite 2020
10 California-Santa Barbara Loss 8-13 1545.73 Jan 25th Santa Barbara Invite 2020
22 Northwestern Loss 7-13 1232.21 Jan 25th Santa Barbara Invite 2020
39 Cal Poly-SLO Loss 5-10 983.08 Jan 26th Santa Barbara Invite 2020
59 Washington University Win 9-8 1486.69 Jan 26th Santa Barbara Invite 2020
124 California-San Diego-B Win 10-4 1508.98 Feb 1st Presidents’ Day Qualifier Women
142 Colorado-B Win 12-4 1395 Feb 1st Presidents’ Day Qualifier Women
125 Chico State Win 10-6 1405.12 Feb 1st Presidents’ Day Qualifier Women
100 Cal State-Long Beach Loss 9-10 939.93 Feb 2nd Presidents’ Day Qualifier Women
124 California-San Diego-B Win 8-4 1473.79 Feb 2nd Presidents’ Day Qualifier Women
96 Occidental Win 11-9 1337.71 Feb 2nd Presidents’ Day Qualifier Women
157 Humboldt State** Win 13-1 1219.64 Ignored Feb 8th Stanford Open 2020
175 Lewis & Clark Win 13-6 1098.88 Feb 8th Stanford Open 2020
86 San Diego State University Win 13-4 1774.11 Feb 8th Stanford Open 2020
140 Santa Clara Win 7-5 1130.23 Feb 9th Stanford Open 2020
27 California-Davis Win 6-5 1870.47 Feb 9th Stanford Open 2020
14 UCLA Loss 6-9 1569.72 Mar 7th Stanford Invite 2020
13 Pittsburgh Loss 6-10 1498.65 Mar 7th Stanford Invite 2020
1 Carleton College** Loss 2-13 1914.9 Ignored Mar 7th Stanford Invite 2020
39 Cal Poly-SLO Loss 5-11 956.98 Mar 8th Stanford Invite 2020
29 California Loss 6-9 1261.96 Mar 8th Stanford Invite 2020
23 Minnesota Loss 3-13 1183.65 Mar 8th Stanford Invite 2020
**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)