#55 Southern California (6-11)

avg: 1556.09  •  sd: 45.11  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
23 Cal Poly-SLO Loss 8-12 1530.13 Feb 3rd Stanford Open 2024
- Stanford-B** Win 13-0 1160.45 Ignored Feb 3rd Stanford Open 2024
19 Colorado State Loss 9-12 1767.84 Feb 17th Presidents Day Invite 2024
9 California-Santa Barbara** Loss 5-15 1821.8 Ignored Feb 17th Presidents Day Invite 2024
23 Cal Poly-SLO Loss 6-11 1424.59 Feb 17th Presidents Day Invite 2024
69 California-San Diego-B Win 11-8 1787.98 Feb 18th Presidents Day Invite 2024
32 UCLA Loss 8-11 1486.26 Feb 18th Presidents Day Invite 2024
24 California-Davis Loss 8-11 1605.48 Feb 18th Presidents Day Invite 2024
113 Denver Win 10-6 1560.98 Feb 19th Presidents Day Invite 2024
69 California-San Diego-B Win 10-8 1685.04 Feb 19th Presidents Day Invite 2024
27 Utah Loss 9-13 1503.36 Mar 16th Womens Centex 2024
36 Texas-Dallas Loss 10-12 1555.38 Mar 16th Womens Centex 2024
37 Washington University Loss 9-13 1350.08 Mar 16th Womens Centex 2024
21 Ohio State Loss 5-13 1482.16 Mar 16th Womens Centex 2024
113 Denver Win 14-4 1664.82 Mar 16th Womens Centex 2024
60 Colorado College Win 11-9 1767.63 Mar 17th Womens Centex 2024
33 Central Florida Loss 3-11 1219.58 Mar 17th Womens Centex 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)