#208 Colorado School of Mines (6-6)

avg: 814.15  •  sd: 70.54  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
199 Texas Christian Loss 10-15 381.48 Feb 22nd Dust Bowl 2020
100 Truman State Loss 8-13 713.57 Feb 22nd Dust Bowl 2020
37 Oklahoma State Loss 7-15 1020.27 Feb 22nd Dust Bowl 2020
94 Denver Loss 7-13 698.32 Feb 22nd Dust Bowl 2020
226 Texas A&M-B Win 15-9 1256.44 Feb 23rd Dust Bowl 2020
202 Missouri State Win 14-12 1046.13 Feb 23rd Dust Bowl 2020
166 Colorado College Loss 7-10 583.19 Mar 7th Air Force Invite 2020
181 Colorado-B Loss 9-11 667.62 Mar 7th Air Force Invite 2020
336 University of Denver-B** Win 13-3 637.43 Ignored Mar 7th Air Force Invite 2020
285 Colorado-Denver Win 13-4 1030.31 Mar 7th Air Force Invite 2020
282 Colorado Mesa University Win 8-6 745.33 Mar 8th Air Force Invite 2020
344 Colorado School of Mines-B** Win 13-1 576.85 Ignored 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)