#170 Colorado-Denver (11-6)

avg: 1083.91  •  sd: 74.22  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
125 Colorado School of Mines Loss 5-13 678.32 Feb 23rd Denver Round Robin 2019
406 Colorado School of Mines - B** Win 13-4 787.01 Ignored Feb 23rd Denver Round Robin 2019
273 Colorado State-B Win 13-6 1375.73 Feb 23rd Denver Round Robin 2019
238 Denver Win 13-3 1497.8 Feb 23rd Denver Round Robin 2019
75 Air Force Loss 6-13 877.54 Mar 16th Air Force Invite 2019
244 Colorado-B Win 13-5 1477.2 Mar 16th Air Force Invite 2019
341 Colorado-Colorado Springs Win 12-3 1127.82 Mar 16th Air Force Invite 2019
382 Air Force-B Win 11-5 906.13 Mar 17th Air Force Invite 2019
307 Colorado Mesa Win 11-9 889.9 Mar 17th Air Force Invite 2019
125 Colorado School of Mines Win 11-10 1403.32 Mar 17th Air Force Invite 2019
123 New Mexico Loss 2-13 679.41 Mar 23rd Trouble in Vegas 2019
133 Utah State Loss 9-13 826.71 Mar 23rd Trouble in Vegas 2019
216 Occidental Win 13-7 1484.87 Mar 23rd Trouble in Vegas 2019
202 Northern Arizona Win 12-11 1098.07 Mar 23rd Trouble in Vegas 2019
116 Nevada-Reno Loss 11-13 1064.88 Mar 24th Trouble in Vegas 2019
265 Cal State-Long Beach Win 13-5 1400.7 Mar 24th Trouble in Vegas 2019
184 California-B Loss 9-13 613.95 Mar 24th Trouble in Vegas 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)