#119 UCLA-B (9-4)

avg: 1036.67  •  sd: 106.5  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
275 Cal Poly SLO-B** Win 12-0 330.79 Ignored Feb 2nd Presidents Day Qualifiers Women
246 California-B Win 7-3 780.65 Feb 2nd Presidents Day Qualifiers Women
107 Chico State Loss 7-9 797.05 Feb 2nd Presidents Day Qualifiers Women
187 California-San Diego-B Win 12-3 1198.15 Feb 2nd Presidents Day Qualifiers Women
77 Cal State-Long Beach Win 10-8 1544.48 Feb 3rd Presidents Day Qualifiers Women
39 California-Davis Loss 6-12 1013.97 Feb 3rd Presidents Day Qualifiers Women
39 California-Davis Loss 1-10 993.28 Feb 3rd Presidents Day Qualifiers Women
107 Chico State Loss 2-10 476.39 Feb 3rd Presidents Day Qualifiers Women
275 Cal Poly SLO-B** Win 12-3 330.79 Ignored Feb 17th Santa Clara RAGE Presidents Day Tournament 2019
246 California-B** Win 13-2 780.65 Ignored Feb 17th Santa Clara RAGE Presidents Day Tournament 2019
176 Santa Clara Win 9-5 1207.09 Feb 17th Santa Clara RAGE Presidents Day Tournament 2019
176 Santa Clara Win 10-6 1174.19 Feb 18th Santa Clara RAGE Presidents Day Tournament 2019
250 California-Davis-B** Win 8-2 747.51 Ignored Feb 18th Santa Clara RAGE Presidents Day Tournament 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)