#22 Texas-Dallas (18-1)

avg: 1623.85  •  sd: 133.14  •  top 16/20: 42.2%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
198 North Texas** Win 10-4 574.76 Ignored Feb 4th Antifreeze
112 Rice** Win 13-3 1401.42 Ignored Feb 4th Antifreeze
106 Texas State** Win 8-2 1439.68 Ignored Feb 4th Antifreeze
217 Texas-B** Win 13-1 65.84 Ignored Feb 4th Antifreeze
112 Rice** Win 11-3 1401.42 Ignored Feb 5th Antifreeze
106 Texas State Win 9-7 1119.02 Feb 5th Antifreeze
63 Kansas Win 10-7 1538.28 Feb 25th Dust Bowl 2023
174 Missouri State** Win 11-2 848.07 Ignored Feb 25th Dust Bowl 2023
131 Nebraska** Win 10-3 1223.16 Ignored Feb 25th Dust Bowl 2023
52 Arkansas Win 10-3 1896.29 Feb 26th Dust Bowl 2023
63 Kansas Win 8-3 1748.62 Feb 26th Dust Bowl 2023
207 Oklahoma** Win 11-2 434.8 Ignored Feb 26th Dust Bowl 2023
78 Central Florida** Win 13-2 1612.53 Ignored Mar 18th Womens Centex1
56 Georgia Tech Win 13-2 1826.21 Mar 18th Womens Centex1
47 Washington University Win 12-6 1934.47 Mar 18th Womens Centex1
56 Georgia Tech Win 11-9 1475.42 Mar 19th Womens Centex1
73 Boston University Win 15-6 1656.8 Mar 19th Womens Centex1
68 Northwestern Win 10-7 1504.73 Mar 19th Womens Centex1
15 Middlebury Loss 9-12 1461.18 Mar 19th Womens Centex1
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)