#110 Texas State (14-5)

avg: 833.98  •  sd: 89.07  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
181 North Texas** Win 12-1 592.38 Ignored Feb 4th Antifreeze
114 Rice Win 11-5 1397.12 Feb 4th Antifreeze
200 Texas-B** Win 9-2 80.81 Ignored Feb 4th Antifreeze
20 Texas-Dallas** Loss 2-8 1019.7 Ignored Feb 4th Antifreeze
143 Sam Houston Win 8-4 1056.68 Feb 5th Antifreeze
87 Trinity Win 8-7 1112.74 Feb 5th Antifreeze
20 Texas-Dallas Loss 7-9 1340.36 Feb 5th Antifreeze
138 Alabama Win 10-5 1127.74 Feb 25th Mardi Gras XXXV
163 Jacksonville State Win 11-6 807.72 Feb 25th Mardi Gras XXXV
168 LSU** Win 9-2 829.32 Ignored Feb 25th Mardi Gras XXXV
85 Central Florida Loss 5-7 673.42 Feb 26th Mardi Gras XXXV
87 Trinity Win 9-4 1587.74 Feb 26th Mardi Gras XXXV
152 Illinois Win 12-9 738.52 Mar 18th Womens Centex1
107 Iowa Loss 7-11 380.09 Mar 18th Womens Centex1
176 Colorado-B Win 9-6 524.8 Mar 18th Womens Centex1
114 Rice Loss 6-13 197.12 Mar 18th Womens Centex1
152 Illinois Win 7-2 993.16 Mar 19th Womens Centex1
168 LSU Win 13-10 557.46 Mar 19th Womens Centex1
173 Texas-San Antonio** Win 15-4 771.58 Ignored Mar 19th Womens Centex1
**Blowout Eligible


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)