#130 North Texas (17-12)

avg: 1192.13  •  sd: 58.73  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
68 Baylor Loss 7-9 1175.48 Feb 3rd Big D in Little d Open 2018
82 Oklahoma State Loss 10-14 1008.49 Feb 3rd Big D in Little d Open 2018
351 Texas-Arlington** Win 10-4 963.48 Ignored Feb 3rd Big D in Little d Open 2018
200 Rice Win 9-8 1057.65 Feb 3rd Big D in Little d Open 2018
379 Southern Methodist** Win 13-0 837.65 Ignored Feb 3rd Big D in Little d Open 2018
170 Kansas State Win 13-6 1659.64 Feb 4th Big D in Little d Open 2018
287 Central Arkansas Win 15-3 1241.28 Feb 4th Big D in Little d Open 2018
199 Stephen F Austin Loss 13-14 809.47 Feb 4th Big D in Little d Open 2018
70 Arkansas Loss 7-11 972.64 Feb 24th Dust Bowl 2018
139 Luther Win 6-5 1293.04 Feb 24th Dust Bowl 2018
82 Oklahoma State Loss 6-11 860.5 Feb 24th Dust Bowl 2018
27 Texas State Loss 6-11 1174.46 Feb 24th Dust Bowl 2018
89 John Brown Win 7-6 1507.31 Feb 25th Dust Bowl 2018
123 Nebraska Win 13-10 1578.58 Feb 25th Dust Bowl 2018
200 Rice Win 13-8 1428.81 Feb 25th Dust Bowl 2018
27 Texas State Loss 4-15 1121.16 Feb 25th Dust Bowl 2018
68 Baylor Loss 6-13 854.82 Mar 10th Mens Centex 2018
114 Minnesota-Duluth Loss 10-13 952.93 Mar 10th Mens Centex 2018
217 Texas Christian Win 12-10 1126.43 Mar 10th Mens Centex 2018
297 Trinity University Win 13-7 1151.08 Mar 10th Mens Centex 2018
112 Texas Tech Win 11-8 1650.69 Mar 11th Mens Centex 2018
26 Texas-Dallas Loss 6-15 1129.02 Mar 11th Mens Centex 2018
100 Arizona Win 8-5 1789.08 Mar 24th Trouble in Vegas 2018
202 Utah Valley Win 10-9 1057.09 Mar 24th Trouble in Vegas 2018
129 Claremont Win 11-6 1742.56 Mar 24th Trouble in Vegas 2018
159 Colorado-B Loss 4-8 529.75 Mar 24th Trouble in Vegas 2018
111 Arizona State Win 7-6 1414.21 Mar 25th Trouble in Vegas 2018
128 Colorado School of Mines Loss 5-9 674.8 Mar 25th Trouble in Vegas 2018
202 Utah Valley Win 9-7 1211.43 Mar 25th Trouble in Vegas 2018
**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)