#142 Colorado-B (7-8)

avg: 795  •  sd: 68.19  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
183 Arizona Loss 7-8 320.82 Feb 1st Presidents’ Day Qualifier Women
124 California-San Diego-B Loss 6-7 783.98 Feb 1st Presidents’ Day Qualifier Women
58 California-Santa Cruz Loss 4-12 766.65 Feb 1st Presidents’ Day Qualifier Women
125 Chico State Loss 5-9 379.91 Feb 1st Presidents’ Day Qualifier Women
196 California-B Win 8-5 755.66 Feb 2nd Presidents’ Day Qualifier Women
204 California-Davis-B Win 10-4 830.13 Feb 2nd Presidents’ Day Qualifier Women
171 California-Irvine Win 8-4 1090.47 Feb 2nd Presidents’ Day Qualifier Women
218 North Texas** Win 11-1 666.58 Ignored Feb 22nd Big D in lil d 2020 Women
77 Texas State Loss 4-10 640.46 Feb 22nd Big D in lil d 2020 Women
119 Rice Loss 5-9 413.07 Feb 22nd Big D in lil d 2020 Women
87 Texas A&M Loss 7-8 1036.1 Feb 22nd Big D in lil d 2020 Women
190 Arkansas Win 7-3 987.72 Feb 23rd Big D in lil d 2020 Women
51 Texas-Dallas Loss 4-9 829.97 Feb 23rd Big D in lil d 2020 Women
184 Texas Christian Win 10-5 1017.09 Feb 23rd Big D in lil d 2020 Women
119 Rice Win 7-5 1270.27 Feb 23rd Big D in lil d 2020 Women
**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)