#108 Southern California (8-13)

avg: 1072.45  •  sd: 72.18  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
32 Brigham Young** Loss 4-13 1110.48 Ignored Jan 26th Santa Barbara Invite 2019
24 Washington** Loss 5-13 1272.59 Ignored Jan 26th Santa Barbara Invite 2019
48 California-Santa Cruz Loss 6-13 920.82 Jan 26th Santa Barbara Invite 2019
90 Colorado State Loss 7-11 750.23 Jan 27th Santa Barbara Invite 2019
84 Victoria Loss 5-10 671.46 Jan 27th Santa Barbara Invite 2019
14 Colorado** Loss 2-13 1446.85 Ignored Feb 16th Presidents Day Invite 2019
12 Minnesota** Loss 0-12 1469.71 Ignored Feb 16th Presidents Day Invite 2019
29 Northwestern** Loss 2-7 1167.62 Ignored Feb 17th Presidents Day Invite 2019
23 California Loss 4-7 1421.76 Feb 17th Presidents Day Invite 2019
86 San Diego State Loss 2-7 642.2 Feb 17th Presidents Day Invite 2019
136 Occidental Win 8-5 1391.76 Mar 2nd 2019 Claremont Ultimate Classic
158 Claremont Win 13-4 1426.85 Mar 2nd 2019 Claremont Ultimate Classic
158 Claremont Win 11-9 1076.06 Mar 2nd 2019 Claremont Ultimate Classic
237 North Texas** Win 10-2 859.68 Ignored Mar 23rd Womens College Centex 2019
173 Baylor Win 12-5 1322.32 Mar 23rd Womens College Centex 2019
278 Texas-B** Win 13-0 259.35 Ignored Mar 23rd Womens College Centex 2019
80 St Olaf Win 10-9 1396.04 Mar 23rd Womens College Centex 2019
99 MIT Loss 7-9 848.14 Mar 24th Womens College Centex 2019
132 Boston University Win 8-7 1104.62 Mar 24th Womens College Centex 2019
59 Duke Loss 7-10 1056.3 Mar 24th Womens College Centex 2019
102 LSU Loss 4-7 623.27 Mar 24th Womens College Centex 2019
**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)