#245 Texas-Dallas (6-12)

avg: 901.38  •  sd: 70.29  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
176 Northern Iowa Loss 10-12 932.71 Feb 22nd Dust Bowl 2025
57 Oklahoma Christian Loss 7-9 1393.99 Feb 22nd Dust Bowl 2025
275 Texas Tech Win 8-7 913.22 Feb 22nd Dust Bowl 2025
309 Washington University-B Win 10-9 765.96 Feb 22nd Dust Bowl 2025
191 Oklahoma State Loss 5-11 500.4 Feb 23rd Dust Bowl 2025
225 Arkansas Loss 8-9 851.3 Mar 15th Mens Centex 2025
86 Colorado-B Loss 10-11 1384.79 Mar 15th Mens Centex 2025
191 Oklahoma State Loss 9-10 975.4 Mar 15th Mens Centex 2025
332 Texas A&M-B Win 11-6 1119.68 Mar 15th Mens Centex 2025
189 Baylor Loss 11-15 726.53 Mar 16th Mens Centex 2025
220 Texas-B Win 15-13 1214.84 Mar 16th Mens Centex 2025
293 Trinity Loss 7-11 261.74 Mar 16th Mens Centex 2025
394 Stephen F Austin** Win 12-4 737.93 Ignored Apr 12th North Texas D I Mens Conferences 2025
183 Tarleton State Loss 6-12 569.06 Apr 12th North Texas D I Mens Conferences 2025
189 Baylor Win 9-8 1232.7 Apr 13th North Texas D I Mens Conferences 2025
183 Tarleton State Loss 10-14 749.67 Apr 13th North Texas D I Mens Conferences 2025
42 Colorado State** Loss 3-15 1184.76 Ignored Apr 26th South Central D I College Mens Regionals 2025
159 Kansas Loss 9-12 886.77 Apr 26th South Central D I College Mens Regionals 2025
**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)