#120 Cal Poly-SLO-B (14-8)

avg: 1348.07  •  sd: 58.94  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
16 British Columbia** Loss 2-13 1430.23 Ignored Jan 25th Santa Barbara Invite 2025
54 UCLA Loss 5-13 1083.5 Jan 25th Santa Barbara Invite 2025
32 California-Santa Barbara Loss 5-13 1236.17 Jan 26th Santa Barbara Invite 2025
379 San Diego State-B** Win 13-2 850.94 Ignored Feb 1st Pres Day Quals men
174 California-Santa Cruz-B Win 10-8 1425.65 Feb 1st Pres Day Quals men
138 California-Irvine Win 12-8 1741.44 Feb 1st Pres Day Quals men
214 UCLA-B Win 12-8 1448.95 Feb 2nd Pres Day Quals men
46 Stanford Loss 9-11 1492.34 Feb 2nd Pres Day Quals men
262 Nevada-Reno Win 13-6 1422.12 Feb 8th Stanford Open Mens
333 Cal State-Long Beach** Win 13-4 1165.67 Ignored Feb 8th Stanford Open Mens
108 British Columbia -B Loss 9-11 1169.8 Feb 9th Stanford Open Mens
251 Portland Win 13-6 1464.06 Feb 9th Stanford Open Mens
109 San Diego State Win 12-7 1931.3 Feb 9th Stanford Open Mens
301 California-Santa Barbara-B** Win 13-2 1270.56 Ignored Apr 12th Southwest Dev Mens Conferences 2025
379 San Diego State-B** Win 13-2 850.94 Ignored Apr 12th Southwest Dev Mens Conferences 2025
281 California-B Win 13-8 1257.98 Apr 12th Southwest Dev Mens Conferences 2025
174 California-Santa Cruz-B Win 15-9 1678.46 Apr 13th Southwest Dev Mens Conferences 2025
41 California-San Diego Loss 5-15 1172.27 Apr 26th Southwest D I College Mens Regionals 2025
175 California-Davis Loss 11-12 1037.65 Apr 26th Southwest D I College Mens Regionals 2025
126 San Jose State Win 15-14 1465.19 Apr 26th Southwest D I College Mens Regionals 2025
109 San Diego State Loss 9-15 895.31 Apr 26th Southwest D I College Mens Regionals 2025
214 UCLA-B Win 15-10 1461.4 Apr 27th Southwest 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)