#69 Colorado Mines (16-3)

avg: 1369.4  •  sd: 115.26  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
310 Arizona State-B** Win 13-2 902.77 Ignored Jan 27th New Year Fest 40
193 Northern Arizona Win 13-6 1450.58 Jan 27th New Year Fest 40
327 Denver-B** Win 13-4 789.75 Ignored Jan 27th New Year Fest 40
45 Utah Valley Win 12-10 1771.03 Jan 27th New Year Fest 40
109 Denver Win 11-8 1562.45 Jan 28th New Year Fest 40
45 Utah Valley Loss 9-13 1114.34 Jan 28th New Year Fest 40
178 Brigham Young-B Win 10-8 1175.56 Mar 2nd Snow Melt 2024
171 Montana State Win 13-8 1443.66 Mar 2nd Snow Melt 2024
93 Colorado-B Win 11-9 1515.31 Mar 2nd Snow Melt 2024
135 Kansas Win 14-10 1505.94 Mar 3rd Snow Melt 2024
45 Utah Valley Win 15-13 1747.08 Mar 3rd Snow Melt 2024
93 Colorado-B Win 14-12 1487.06 Mar 3rd Snow Melt 2024
370 Northwestern-B** Win 13-1 394.7 Ignored Mar 30th Old Capitol Open 2024
383 Wisconsin-Milwaukee-B** Win 13-0 -142.26 Ignored Mar 30th Old Capitol Open 2024
140 Minnesota-B Win 11-8 1443.65 Mar 30th Old Capitol Open 2024
260 Illinois State Win 13-6 1158.62 Mar 30th Old Capitol Open 2024
124 Macalester Loss 7-8 1021.58 Mar 31st Old Capitol Open 2024
102 Davenport Loss 7-10 827.6 Mar 31st Old Capitol Open 2024
170 Minnesota-Duluth Win 13-5 1550.77 Mar 31st Old Capitol Open 2024
**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)