#244 Colorado-B (9-9)

avg: 877.2  •  sd: 78.6  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
169 Chico State Loss 8-9 959.3 Feb 2nd Presidents Day Qualifiers Men
444 California-Irvine-B** Win 13-0 12.99 Ignored Feb 2nd Presidents Day Qualifiers Men
407 California-Santa Barbara-B** Win 13-1 784.86 Ignored Feb 2nd Presidents Day Qualifiers Men
414 UCLA-B** Win 13-5 731.49 Ignored Feb 2nd Presidents Day Qualifiers Men
254 Cal Poly-Pomona Win 10-7 1229.85 Feb 3rd Presidents Day Qualifiers Men
164 Arizona State Loss 5-11 503.22 Feb 3rd Presidents Day Qualifiers Men
100 California-Santa Cruz Loss 10-13 1030.63 Feb 3rd Presidents Day Qualifiers Men
328 Caltech Win 11-7 1031.67 Feb 3rd Presidents Day Qualifiers Men
229 Missouri Win 13-6 1513.85 Mar 10th Dust Bowl 2019
179 Nebraska Loss 0-15 458.84 Mar 10th Dust Bowl 2019
- Central Arkansas Win 15-9 770.08 Mar 10th Dust Bowl 2019
80 Oklahoma Loss 8-12 1010.81 Mar 10th Dust Bowl 2019
170 Colorado-Denver Loss 5-13 483.91 Mar 16th Air Force Invite 2019
341 Colorado-Colorado Springs Win 13-3 1127.82 Mar 16th Air Force Invite 2019
123 New Mexico Loss 3-13 679.41 Mar 17th Air Force Invite 2019
75 Air Force** Loss 4-13 877.54 Ignored Mar 17th Air Force Invite 2019
382 Air Force-B Win 13-2 906.13 Mar 17th Air Force Invite 2019
125 Colorado School of Mines Loss 3-11 678.32 Mar 17th Air Force Invite 2019
**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)