#281 California-B (10-19)

avg: 761.82  •  sd: 35.81  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
94 Cal Poly-CCWR** Loss 2-13 874.67 Feb 1st Pres Day Quals men
46 Stanford** Loss 4-13 1141.55 Ignored Feb 1st Pres Day Quals men
175 California-Davis Loss 6-13 562.65 Feb 1st Pres Day Quals men
94 Cal Poly-CCWR** Loss 3-13 874.67 Feb 2nd Pres Day Quals men
217 Cal Poly-Pomona Loss 6-13 396.29 Feb 2nd Pres Day Quals men
352 California-San Diego-B Win 12-9 765.95 Feb 2nd Pres Day Quals men
202 Cal Poly-Humboldt Loss 1-13 447.02 Feb 8th Stanford Open Mens
126 San Jose State Loss 7-11 873.3 Feb 8th Stanford Open Mens
237 Loyola Marymount Win 12-10 1145.36 Feb 9th Stanford Open Mens
279 Chico State Win 10-9 891.49 Feb 9th Stanford Open Mens
163 Washington-B Loss 8-13 715.74 Feb 9th Stanford Open Mens
154 Brigham Young-B Loss 3-13 644.54 Mar 1st Snow Melt 2025
89 Colorado College** Loss 5-13 885.28 Ignored Mar 1st Snow Melt 2025
378 Denver-B Win 12-5 864.1 Mar 1st Snow Melt 2025
259 Colorado State-B Loss 8-9 715.19 Mar 1st Snow Melt 2025
36 Lewis & Clark** Loss 2-15 1197.06 Ignored Mar 2nd Snow Melt 2025
114 Denver** Loss 6-15 775.42 Ignored Mar 2nd Snow Melt 2025
391 Colorado Mines-B Win 14-7 736.88 Mar 2nd Snow Melt 2025
202 Cal Poly-Humboldt Loss 9-13 628.45 Mar 15th Silicon Valley Rally 2025
126 San Jose State Loss 6-10 844.03 Mar 15th Silicon Valley Rally 2025
174 California-Santa Cruz-B Loss 5-10 589.09 Mar 15th Silicon Valley Rally 2025
279 Chico State Win 9-8 891.49 Mar 15th Silicon Valley Rally 2025
174 California-Santa Cruz-B Loss 5-10 589.09 Mar 16th Silicon Valley Rally 2025
279 Chico State Win 9-8 891.49 Mar 16th Silicon Valley Rally 2025
120 Cal Poly-SLO-B Loss 8-13 851.91 Apr 12th Southwest Dev Mens Conferences 2025
379 San Diego State-B Win 12-5 850.94 Apr 12th Southwest Dev Mens Conferences 2025
301 California-Santa Barbara-B Win 9-7 949.9 Apr 12th Southwest Dev Mens Conferences 2025
318 Arizona State-B Win 13-11 831.82 Apr 13th Southwest Dev Mens Conferences 2025
214 UCLA-B Loss 9-14 533.93 Apr 13th Southwest Dev 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)