#117 Colorado Mines (12-6)

avg: 1189.25  •  sd: 63.55  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
95 Claremont Win 13-7 1833.17 Feb 8th DIII Grand Prix 2025
125 Puget Sound Loss 10-13 812.47 Feb 8th DIII Grand Prix 2025
34 Lewis & Clark Loss 5-13 1059.3 Feb 8th DIII Grand Prix 2025
53 Whitman Loss 7-12 1027.77 Feb 8th DIII Grand Prix 2025
242 Reed Win 13-6 1240.47 Feb 9th DIII Grand Prix 2025
273 Pacific Lutheran** Win 13-5 1085.92 Ignored Feb 9th DIII Grand Prix 2025
167 Brigham Young-B Win 11-9 1217.46 Mar 1st Snow Melt 2025
76 Colorado College Win 13-12 1494.71 Mar 1st Snow Melt 2025
261 Colorado State-B** Win 13-5 1164.61 Ignored Mar 1st Snow Melt 2025
338 Colorado Mesa** Win 15-1 783.72 Ignored Mar 2nd Snow Melt 2025
165 Montana State Win 14-10 1373.16 Mar 2nd Snow Melt 2025
34 Lewis & Clark Loss 11-13 1430.46 Mar 2nd Snow Melt 2025
250 Illinois State Win 13-9 1031.15 Mar 29th Old Capitol Open 2025
178 Minnesota-B Win 12-11 1045.73 Mar 29th Old Capitol Open 2025
253 DePaul** Win 13-4 1188.06 Ignored Mar 29th Old Capitol Open 2025
155 Grinnell Win 12-8 1461.04 Mar 30th Old Capitol Open 2025
156 Wisconsin-La Crosse Loss 10-11 893.24 Mar 30th Old Capitol Open 2025
123 Wisconsin-Milwaukee Loss 5-7 818.85 Mar 30th Old Capitol Open 2025
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)