#187 Colorado-B (3-12)

avg: 497.88  •  sd: 95.65  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
180 Arizona Loss 6-8 237.1 Jan 25th New Year Fest 2025
114 Arizona State Loss 5-11 355.88 Jan 25th New Year Fest 2025
78 Grand Canyon Loss 6-11 673.21 Jan 25th New Year Fest 2025
106 San Diego State Loss 6-9 621.15 Jan 25th New Year Fest 2025
114 Arizona State Loss 3-11 355.88 Jan 26th New Year Fest 2025
242 Arizona-B Win 7-5 372.36 Jan 26th New Year Fest 2025
114 Arizona State Loss 8-13 459.72 Mar 1st Snow Melt 2025
73 Colorado College** Loss 0-15 668.82 Ignored Mar 1st Snow Melt 2025
193 Colorado Mines Win 11-7 940.89 Mar 1st Snow Melt 2025
107 Denver Loss 2-15 431.18 Mar 1st Snow Melt 2025
180 Arizona Loss 8-9 412.6 Mar 2nd Snow Melt 2025
251 Colorado College-B Win 12-3 561.56 Mar 2nd Snow Melt 2025
4 Colorado** Loss 3-15 1727.97 Ignored Apr 12th Rocky Mountain D I Womens Conferences 2025
54 Colorado State** Loss 0-15 855.89 Ignored Apr 12th Rocky Mountain D I Womens Conferences 2025
107 Denver Loss 1-9 431.18 Apr 12th Rocky Mountain D I Womens Conferences 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)