#377 Denver-B (1-15)

avg: 264.69  •  sd: 105.22  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
156 Brigham Young-B** Loss 2-13 643.68 Ignored Jan 25th New Year Fest 2025
109 San Diego State** Loss 2-13 828.77 Ignored Jan 25th New Year Fest 2025
269 Grand Canyon-B Loss 6-12 228.08 Jan 25th New Year Fest 2025
116 Denver** Loss 2-13 784.14 Ignored Jan 26th New Year Fest 2025
249 Northern Arizona** Loss 2-13 285.56 Ignored Jan 26th New Year Fest 2025
156 Brigham Young-B** Loss 1-13 643.68 Ignored Mar 1st Snow Melt 2025
279 California-B Loss 5-12 177.31 Mar 1st Snow Melt 2025
89 Colorado College** Loss 4-13 896.88 Ignored Mar 1st Snow Melt 2025
258 Colorado State-B Loss 5-10 270.58 Mar 1st Snow Melt 2025
360 Colorado Mesa Loss 10-11 266.52 Mar 2nd Snow Melt 2025
391 Colorado Mines-B Win 12-10 394.25 Mar 2nd Snow Melt 2025
360 Colorado Mesa Loss 11-12 266.52 Apr 12th Rocky Mountain D I Mens Conferences 2025
42 Colorado State** Loss 0-15 1184.76 Ignored Apr 12th Rocky Mountain D I Mens Conferences 2025
86 Colorado-B** Loss 4-15 909.79 Ignored Apr 12th Rocky Mountain D I Mens Conferences 2025
258 Colorado State-B Loss 5-15 244.48 Apr 13th Rocky Mountain D I Mens Conferences 2025
116 Denver** Loss 4-15 784.14 Ignored Apr 13th Rocky Mountain D I Mens 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)