#259 Colorado State-B (7-15)

avg: 840.19  •  sd: 65.45  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
154 Brigham Young-B Loss 9-13 825.98 Mar 1st Snow Melt 2025
281 California-B Win 9-8 886.82 Mar 1st Snow Melt 2025
117 Colorado Mines Loss 5-13 763.26 Mar 1st Snow Melt 2025
378 Denver-B Win 10-5 838 Mar 1st Snow Melt 2025
357 Colorado Mesa Win 13-9 822.21 Mar 2nd Snow Melt 2025
137 Montana State Loss 10-15 851.73 Mar 2nd Snow Melt 2025
114 Denver Loss 1-15 775.42 Mar 2nd Snow Melt 2025
160 Kansas Loss 3-15 617.19 Mar 29th Free State Classic 2025
324 Kansas State Win 14-8 1123.19 Mar 29th Free State Classic 2025
191 Oklahoma State Loss 5-15 483.79 Mar 29th Free State Classic 2025
195 John Brown Win 12-8 1510.79 Mar 29th Free State Classic 2025
164 Truman State Loss 2-15 607.14 Mar 30th Free State Classic 2025
160 Kansas Loss 4-15 617.19 Mar 30th Free State Classic 2025
191 Oklahoma State Loss 7-9 804.46 Mar 30th Free State Classic 2025
4 Colorado** Loss 4-15 1737.87 Ignored Apr 12th Rocky Mountain D I Mens Conferences 2025
114 Denver Loss 7-11 908.52 Apr 12th Rocky Mountain D I Mens Conferences 2025
357 Colorado Mesa Win 15-8 968.45 Apr 13th Rocky Mountain D I Mens Conferences 2025
86 Colorado-B** Loss 5-15 893.4 Ignored Apr 13th Rocky Mountain D I Mens Conferences 2025
378 Denver-B Win 15-5 864.1 Apr 13th Rocky Mountain D I Mens Conferences 2025
11 Washington University** Loss 3-15 1482.57 Ignored Apr 26th South Central D I College Mens Regionals 2025
97 Missouri Loss 7-14 877.09 Apr 26th South Central D I College Mens Regionals 2025
114 Denver Loss 3-13 775.42 Apr 27th South Central D I College Mens Regionals 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)