#74 Denver (14-3)

avg: 1321.88  •  sd: 95.96  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
118 Arizona Win 11-7 1506.61 Jan 26th New Year Fest 2019
120 Arizona State Win 10-6 1523.33 Jan 26th New Year Fest 2019
277 Arizona-B** Win 13-0 271.45 Ignored Jan 26th New Year Fest 2019
230 New Mexico Win 10-5 894.57 Jan 26th New Year Fest 2019
73 Northern Arizona Loss 8-10 1062.15 Jan 27th New Year Fest 2019
73 Northern Arizona Win 10-5 1898.71 Jan 27th New Year Fest 2019
86 San Diego State Win 11-4 1842.2 Jan 27th New Year Fest 2019
138 Oregon State Win 10-7 1323.83 Feb 2nd Big Sky Brawl 2019
152 Montana State Win 9-5 1390.81 Feb 2nd Big Sky Brawl 2019
30 Utah Loss 8-10 1496.2 Feb 2nd Big Sky Brawl 2019
138 Oregon State Win 12-6 1513.48 Feb 3rd Big Sky Brawl 2019
152 Montana State Win 8-6 1162.24 Feb 3rd Big Sky Brawl 2019
123 Boise State Loss 8-9 894.37 Feb 3rd Big Sky Brawl 2019
116 Air Force Win 8-4 1612.02 Mar 16th Air Force Invite 2019
202 Colorado School of Mines Win 8-6 832.23 Mar 16th Air Force Invite 2019
175 Kansas Win 11-6 1263.94 Mar 16th Air Force Invite 2019
116 Air Force Win 10-9 1172.21 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)