#94 Denver (17-4)

avg: 1255.85  •  sd: 67.87  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
330 Arizona State-C** Win 11-1 691 Ignored Jan 25th New Year Fest 2020
228 Colorado State-B Win 11-4 1339.97 Jan 25th New Year Fest 2020
149 Brigham Young-B Win 11-9 1256.63 Jan 25th New Year Fest 2020
179 Grand Canyon Win 11-6 1471.42 Jan 25th New Year Fest 2020
44 Utah State Loss 7-11 1121.71 Jan 25th New Year Fest 2020
86 Arizona State-B-B Win 9-8 1422.07 Jan 26th New Year Fest 2020
165 New Mexico Win 11-9 1222.18 Jan 26th New Year Fest 2020
44 Utah State Loss 8-12 1147.45 Jan 26th New Year Fest 2020
208 Colorado School of Mines Win 13-7 1371.68 Feb 22nd Dust Bowl 2020
154 Pacific Lutheran Win 14-7 1582.32 Feb 22nd Dust Bowl 2020
- Harding Win 15-8 954.74 Feb 22nd Dust Bowl 2020
93 Rice Win 11-10 1385.8 Feb 23rd Dust Bowl 2020
37 Oklahoma State Loss 10-14 1221.57 Feb 23rd Dust Bowl 2020
87 Texas State Win 13-12 1411.68 Feb 23rd Dust Bowl 2020
100 Truman State Win 11-9 1458.93 Feb 23rd Dust Bowl 2020
162 Air Force Loss 6-13 382.13 Mar 7th Air Force Invite 2020
282 Colorado Mesa University** Win 13-3 1044.84 Ignored Mar 7th Air Force Invite 2020
344 Colorado School of Mines-B** Win 13-0 576.85 Ignored Mar 7th Air Force Invite 2020
205 Colorado-Colorado Springs Win 13-7 1378.28 Mar 7th Air Force Invite 2020
162 Air Force Win 9-6 1400.69 Mar 8th Air Force Invite 2020
166 Colorado College Win 11-9 1222.06 Mar 8th Air Force Invite 2020
**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)