#37 California (6-7)

avg: 1752.36  •  sd: 105.51  •  top 16/20: 0.6%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
94 Arizona State Win 8-4 1700.39 Feb 1st Presidents Day Qualifiers 2025
13 Cal Poly-SLO Loss 1-11 1670.8 Feb 1st Presidents Day Qualifiers 2025
195 California-San Diego-C** Win 13-0 637.15 Ignored Feb 1st Presidents Day Qualifiers 2025
48 California-Irvine Win 7-6 1801.72 Feb 1st Presidents Day Qualifiers 2025
139 Arizona** Win 11-3 1359.35 Ignored Feb 2nd Presidents Day Qualifiers 2025
23 UCLA Loss 5-11 1359.3 Feb 2nd Presidents Day Qualifiers 2025
48 California-Irvine Win 8-5 2130.32 Feb 2nd Presidents Day Qualifiers 2025
8 California-San Diego Loss 6-11 1809.88 Mar 1st Stanford Invite 2025 Womens
10 Washington Loss 10-13 2016.41 Mar 1st Stanford Invite 2025 Womens
29 Pittsburgh Win 10-9 1929.85 Mar 1st Stanford Invite 2025 Womens
15 California-Santa Barbara Loss 7-12 1640.81 Mar 1st Stanford Invite 2025 Womens
23 UCLA Loss 6-9 1540.74 Mar 2nd Stanford Invite 2025 Womens
34 Wisconsin Loss 7-8 1641.57 Mar 2nd Stanford Invite 2025 Womens
**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)