#17 UCLA (10-5)

avg: 1764.85  •  sd: 68.78  •  top 16/20: 78.7%

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# Opponent Result Game Rating Status Date Event
39 California-San Diego Win 13-12 1637.06 Jan 27th Santa Barbara Invite 2024
18 Brigham Young Loss 12-14 1525.65 Jan 27th Santa Barbara Invite 2024
79 Northwestern Win 15-5 1790.94 Jan 27th Santa Barbara Invite 2024
16 Washington Win 12-9 2113.61 Jan 27th Santa Barbara Invite 2024
3 Cal Poly-SLO Loss 7-15 1530.36 Jan 28th Santa Barbara Invite 2024
11 California Loss 11-13 1627.1 Jan 28th Santa Barbara Invite 2024
27 Utah Win 11-10 1755.38 Jan 28th Santa Barbara Invite 2024
48 California-Santa Barbara Win 11-8 1758.81 Feb 17th Presidents Day Invite 2024
32 Victoria Loss 8-12 1124.14 Feb 17th Presidents Day Invite 2024
6 Oregon Loss 10-14 1562.26 Feb 17th Presidents Day Invite 2024
41 California-Santa Cruz Win 13-9 1909.24 Feb 18th Presidents Day Invite 2024
64 Stanford Win 12-5 1873.73 Feb 18th Presidents Day Invite 2024
28 Utah State Win 11-6 2149.58 Feb 18th Presidents Day Invite 2024
39 California-San Diego Win 15-4 2112.06 Feb 19th Presidents Day Invite 2024
28 Utah State Win 11-8 1968.5 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)