#113 Oklahoma (9-8)

avg: 1052.65  •  sd: 65.74  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
195 Texas A&M Win 11-2 1168.44 Feb 16th Big D in lil d Women
102 LSU Loss 7-9 840.1 Feb 16th Big D in lil d Women
120 Arizona State Win 8-6 1327.66 Feb 16th Big D in lil d Women
109 Texas State Win 8-7 1189.56 Feb 17th Big D in lil d Women
120 Arizona State Loss 5-8 573.57 Feb 17th Big D in lil d Women
102 LSU Loss 5-8 665.83 Feb 17th Big D in lil d Women
243 Colorado-B** Win 11-4 790.79 Ignored Mar 10th Dust Bowl 2019
174 Tulsa Win 15-8 1285.61 Mar 10th Dust Bowl 2019
181 Arkansas Win 15-9 1144.67 Mar 10th Dust Bowl 2019
88 John Brown Loss 12-13 1101.55 Mar 10th Dust Bowl 2019
206 Texas-San Antonio Win 13-3 1102.39 Mar 23rd Womens College Centex 2019
199 Miami Win 11-4 1153.62 Mar 23rd Womens College Centex 2019
101 Trinity Loss 5-8 672.13 Mar 23rd Womens College Centex 2019
43 Georgia Tech Loss 4-15 955.59 Mar 24th Womens College Centex 2019
99 MIT Loss 8-9 1002.48 Mar 24th Womens College Centex 2019
132 Boston University Loss 8-9 854.62 Mar 24th Womens College Centex 2019
109 Texas State Win 9-2 1664.56 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)