#176 Colorado State-B (15-7)

avg: 1026.62  •  sd: 60.3  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
274 Arkansas State Win 11-6 1248 Feb 24th Dust Bowl 2018
99 Missouri S&T Loss 8-11 972.27 Feb 24th Dust Bowl 2018
96 Missouri State Loss 7-11 883.6 Feb 24th Dust Bowl 2018
305 Oklahoma-B Loss 6-7 436.22 Feb 24th Dust Bowl 2018
287 Central Arkansas Win 15-5 1241.28 Feb 24th Dust Bowl 2018
284 Tulsa Win 11-10 771.62 Feb 24th Dust Bowl 2018
99 Missouri S&T Loss 10-15 884.28 Feb 25th Dust Bowl 2018
199 Stephen F Austin Win 12-9 1279.84 Feb 25th Dust Bowl 2018
343 Texas-B Win 13-7 952.49 Mar 10th Mens Centex 2018
411 Texas State -B** Win 13-2 524.42 Ignored Mar 10th Mens Centex 2018
258 Texas A&M-C Win 13-6 1355.2 Mar 10th Mens Centex 2018
200 Rice Win 13-12 1057.65 Mar 11th Mens Centex 2018
297 Trinity University Win 12-10 831.68 Mar 11th Mens Centex 2018
199 Stephen F Austin Win 13-11 1163.31 Mar 11th Mens Centex 2018
235 Arizona State-B Loss 8-9 677.66 Mar 24th Trouble in Vegas 2018
186 Cal Poly-Pomona Win 9-7 1262.44 Mar 24th Trouble in Vegas 2018
333 California-Davis-B Win 13-7 988.01 Mar 24th Trouble in Vegas 2018
332 California-San Diego-B Win 10-5 1016.08 Mar 24th Trouble in Vegas 2018
53 UCLA Loss 4-9 934.42 Mar 24th Trouble in Vegas 2018
129 Claremont Loss 5-11 595.86 Mar 25th Trouble in Vegas 2018
128 Colorado School of Mines Win 9-8 1328.86 Mar 25th Trouble in Vegas 2018
202 Utah Valley Win 11-4 1532.09 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)