#54 California-Davis (7-7)

avg: 1478.06  •  sd: 106.49  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
76 Puget Sound Win 13-4 1947.71 Feb 8th Stanford Open 2020
75 Nevada-Reno Loss 9-11 1111.48 Feb 8th Stanford Open 2020
148 Sonoma State Win 11-7 1474.7 Feb 8th Stanford Open 2020
46 Arizona Loss 1-10 958.84 Feb 9th Stanford Open 2020
89 Carleton College-GoP Win 8-3 1878.33 Feb 9th Stanford Open 2020
126 Chico State Loss 5-6 997.43 Feb 9th Stanford Open 2020
4 Cal Poly-SLO** Loss 3-14 1578.18 Ignored Feb 15th Presidents Day Invite 2020
57 Illinois Loss 9-12 1107.54 Feb 15th Presidents Day Invite 2020
37 Oklahoma State Loss 7-15 1020.27 Feb 15th Presidents Day Invite 2020
28 California-Santa Barbara Win 10-8 1979.16 Feb 16th Presidents Day Invite 2020
42 Utah Loss 8-12 1158.69 Feb 16th Presidents Day Invite 2020
90 Southern California Win 11-5 1870.22 Feb 16th Presidents Day Invite 2020
160 San Diego State Win 14-4 1590.19 Feb 17th Presidents Day Invite 2020
57 Illinois Win 15-7 2052.91 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)