#38 Southern California (11-11)

avg: 1633.89  •  sd: 68.51  •  top 16/20: 0.7%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
74 Washington University Win 13-7 1976.02 Jan 27th Santa Barbara Invitational 2018
53 UCLA Win 13-8 2030.58 Jan 27th Santa Barbara Invitational 2018
15 Stanford Loss 12-13 1760.63 Jan 27th Santa Barbara Invitational 2018
25 Victoria Win 15-14 1856.74 Jan 27th Santa Barbara Invitational 2018
143 California-San Diego Win 13-8 1657.08 Jan 28th Santa Barbara Invitational 2018
5 Washington Loss 10-13 1723.26 Jan 28th Santa Barbara Invitational 2018
20 Cal Poly-SLO Loss 9-13 1424.55 Jan 28th Santa Barbara Invitational 2018
67 Utah Win 13-10 1786.11 Jan 28th Santa Barbara Invitational 2018
211 Utah State Win 13-7 1465.37 Feb 17th Presidents Day Invitational Tournament 2018
32 California Win 12-11 1820.8 Feb 17th Presidents Day Invitational Tournament 2018
24 Western Washington Win 13-12 1867.07 Feb 17th Presidents Day Invitational Tournament 2018
55 Oregon State Loss 9-12 1172.81 Feb 18th Presidents Day Invitational Tournament 2018
65 California-Santa Barbara Win 13-9 1880.94 Feb 18th Presidents Day Invitational Tournament 2018
19 Colorado Loss 7-11 1384.06 Feb 18th Presidents Day Invitational Tournament 2018
5 Washington Win 11-6 2598.1 Feb 19th Presidents Day Invitational Tournament 2018
24 Western Washington Loss 9-10 1617.07 Feb 19th Presidents Day Invitational Tournament 2018
17 Colorado State Loss 9-13 1451.19 Mar 24th NW Challenge 2018
18 Brigham Young Loss 7-13 1295.85 Mar 24th NW Challenge 2018
63 Tulane Loss 9-10 1338.68 Mar 24th NW Challenge 2018
43 British Columbia Loss 10-13 1266.5 Mar 24th NW Challenge 2018
55 Oregon State Win 14-11 1831.52 Mar 25th NW Challenge 2018
32 California Loss 11-14 1382.46 Mar 25th NW Challenge 2018
**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)