#17 California-Santa Cruz (14-11)

avg: 2078.47  •  sd: 79.06  •  top 16/20: 88.7%

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# Opponent Result Game Rating Status Date Event
5 Stanford Loss 9-13 2101.32 Jan 27th Santa Barbara Invite 2024
11 Brigham Young Win 13-11 2484.88 Jan 27th Santa Barbara Invite 2024
9 California-Santa Barbara Win 12-10 2564.53 Jan 27th Santa Barbara Invite 2024
13 Victoria Loss 12-15 1852.87 Jan 27th Santa Barbara Invite 2024
20 California-Davis Win 10-7 2371.1 Jan 28th Santa Barbara Invite 2024
3 Carleton College Loss 10-15 2168.39 Jan 28th Santa Barbara Invite 2024
10 Washington Loss 8-14 1722.05 Jan 28th Santa Barbara Invite 2024
11 Brigham Young Loss 9-10 2131.04 Mar 2nd Stanford Invite 2024
28 California Win 9-6 2275.08 Mar 2nd Stanford Invite 2024
7 Colorado Loss 7-10 2036.58 Mar 2nd Stanford Invite 2024
53 Texas Win 9-4 2161.29 Mar 2nd Stanford Invite 2024
5 Stanford Loss 6-13 1919.88 Mar 3rd Stanford Invite 2024
14 California-San Diego Win 9-8 2267.18 Mar 3rd Stanford Invite 2024
9 California-Santa Barbara Loss 7-11 1859.51 Mar 3rd Stanford Invite 2024
72 Santa Clara** Win 14-3 1996.79 Ignored Apr 13th NorCal D I Womens Conferences 2024
248 Cal Poly-Humboldt** Win 15-2 600 Ignored Apr 13th NorCal D I Womens Conferences 2024
20 California-Davis Loss 7-10 1591.77 Apr 13th NorCal D I Womens Conferences 2024
28 California Win 10-9 1981.51 Apr 14th NorCal D I Womens Conferences 2024
67 Nevada-Reno Win 11-9 1689.13 Apr 14th NorCal D I Womens Conferences 2024
72 Santa Clara** Win 15-1 1996.79 Ignored Apr 27th Southwest D I College Womens Regionals 2024
5 Stanford Loss 3-15 1919.88 Apr 27th Southwest D I College Womens Regionals 2024
20 California-Davis Win 12-8 2422.59 Apr 27th Southwest D I College Womens Regionals 2024
28 California Win 12-7 2377.03 Apr 28th Southwest D I College Womens Regionals 2024
20 California-Davis Win 12-8 2422.59 Apr 28th Southwest D I College Womens Regionals 2024
14 California-San Diego Loss 9-13 1723.62 Apr 28th Southwest 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)