#87 Southern California (3-11)

avg: 1179.21  •  sd: 79.99  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
33 Dartmouth Loss 6-13 994.51 Jan 25th Santa Barbara Invite 2020
4 Cal Poly-SLO** Loss 3-13 1478.61 Ignored Jan 25th Santa Barbara Invite 2020
31 Utah Loss 9-13 1186.49 Jan 25th Santa Barbara Invite 2020
51 Tulane Win 13-10 1739.48 Jan 25th Santa Barbara Invite 2020
49 Case Western Reserve Loss 9-11 1170.01 Jan 26th Santa Barbara Invite 2020
69 Victoria Loss 9-13 900.24 Jan 26th Santa Barbara Invite 2020
6 Oregon** Loss 5-15 1460.76 Ignored Feb 15th Presidents Day Invite 2020
37 California-San Diego Loss 5-11 970.96 Feb 15th Presidents Day Invite 2020
30 California-Santa Cruz Loss 6-14 1006.84 Feb 15th Presidents Day Invite 2020
48 California-Davis Loss 5-11 820.41 Feb 16th Presidents Day Invite 2020
24 California-Santa Barbara Loss 4-12 1066.89 Feb 16th Presidents Day Invite 2020
31 Utah Loss 4-12 1005.06 Feb 16th Presidents Day Invite 2020
138 San Diego State Win 15-2 1520.15 Feb 17th Presidents Day Invite 2020
57 Illinois Win 12-9 1725.25 Feb 17th Presidents Day Invite 2020
**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)