#181 Colorado-B (9-9)

avg: 916.83  •  sd: 75.92  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
148 Sonoma State Win 8-7 1132.81 Feb 1st 2020 Mens Presidents Day Qualifier
159 California-Irvine Win 9-7 1270.88 Feb 1st 2020 Mens Presidents Day Qualifier
294 Southern California-B Win 13-0 989.77 Feb 1st 2020 Mens Presidents Day Qualifier
126 Chico State Win 8-5 1576.04 Feb 1st 2020 Mens Presidents Day Qualifier
121 Arizona State Loss 5-9 601.55 Feb 2nd 2020 Mens Presidents Day Qualifier
253 Caltech Win 9-6 1034.33 Feb 2nd 2020 Mens Presidents Day Qualifier
68 Occidental Loss 4-10 785.25 Feb 2nd 2020 Mens Presidents Day Qualifier
152 John Brown Loss 11-14 691.85 Feb 22nd Dust Bowl 2020
234 Baylor Win 13-7 1271.72 Feb 22nd Dust Bowl 2020
87 Texas State Loss 5-15 686.68 Feb 22nd Dust Bowl 2020
152 John Brown Loss 10-15 551.59 Feb 23rd Dust Bowl 2020
105 Kansas Loss 13-15 984.49 Feb 23rd Dust Bowl 2020
100 Truman State Loss 11-15 828.56 Feb 23rd Dust Bowl 2020
166 Colorado College Win 12-9 1318.22 Mar 7th Air Force Invite 2020
208 Colorado School of Mines Win 11-9 1063.36 Mar 7th Air Force Invite 2020
336 University of Denver-B** Win 13-3 637.43 Ignored Mar 7th Air Force Invite 2020
166 Colorado College Loss 9-10 847.86 Mar 8th Air Force Invite 2020
205 Colorado-Colorado Springs Loss 5-13 220.75 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)