#27 California-Davis (7-8)

avg: 1661.5  •  sd: 69.36  •  top 16/20: 4.2%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
1 Carleton College** Loss 6-15 1859.36 Ignored Jan 27th Santa Barbara Invite 2024
39 Cal Poly-SLO Win 10-7 1888.09 Jan 27th Santa Barbara Invite 2024
8 Washington Loss 6-10 1636.35 Jan 27th Santa Barbara Invite 2024
36 Utah Win 12-6 2099.08 Jan 27th Santa Barbara Invite 2024
7 Stanford Loss 6-13 1567.85 Jan 28th Santa Barbara Invite 2024
13 California-Santa Cruz Loss 7-10 1512.48 Jan 28th Santa Barbara Invite 2024
17 Victoria Loss 8-9 1730.03 Jan 28th Santa Barbara Invite 2024
108 Denver** Win 14-2 1248.32 Ignored Feb 17th Presidents Day Invite 2024
5 Oregon Loss 4-12 1631.59 Feb 17th Presidents Day Invite 2024
26 California-San Diego Loss 9-12 1323.24 Feb 17th Presidents Day Invite 2024
62 Southern California Win 11-8 1579.72 Feb 18th Presidents Day Invite 2024
30 UCLA Win 9-7 1886.82 Feb 18th Presidents Day Invite 2024
74 California-San Diego-B Win 11-6 1581.48 Feb 18th Presidents Day Invite 2024
39 Cal Poly-SLO Win 9-2 2098.43 Feb 19th Presidents Day Invite 2024
30 UCLA Loss 6-9 1188.91 Feb 19th Presidents Day Invite 2024
**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)