#120 Arizona State (8-12)

avg: 1365.92  •  sd: 52.22  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
84 Southern California Loss 3-13 919.35 Feb 15th Vice Presidents Day Invite 2025
216 Cal Poly-Pomona Win 7-6 1140.56 Feb 15th Vice Presidents Day Invite 2025
65 Grand Canyon Loss 6-11 1098.35 Feb 15th Vice Presidents Day Invite 2025
237 Loyola Marymount Win 11-6 1472.07 Feb 16th Vice Presidents Day Invite 2025
124 San Jose State Loss 8-9 1233.94 Feb 16th Vice Presidents Day Invite 2025
89 Colorado College Loss 8-9 1371.88 Mar 15th Mens Centex 2025
58 Illinois Loss 7-9 1393.61 Mar 15th Mens Centex 2025
117 Mississippi State Loss 8-9 1250.25 Mar 15th Mens Centex 2025
183 Tarleton State Win 12-4 1748.38 Mar 15th Mens Centex 2025
70 Dartmouth Loss 12-15 1318.01 Mar 16th Mens Centex 2025
73 Iowa State Loss 11-15 1220.72 Mar 16th Mens Centex 2025
130 North Texas Win 13-9 1748.79 Mar 16th Mens Centex 2025
186 Arizona Win 12-11 1245 Apr 13th Desert D I Mens Conferences 2025
65 Grand Canyon Loss 7-11 1178.16 Apr 13th Desert D I Mens Conferences 2025
249 Northern Arizona Win 15-7 1485.56 Apr 13th Desert D I Mens Conferences 2025
6 Cal Poly-SLO** Loss 5-15 1667.97 Ignored Apr 26th Southwest D I College Mens Regionals 2025
109 San Diego State Win 12-9 1774.14 Apr 26th Southwest D I College Mens Regionals 2025
46 Stanford Loss 7-15 1165.36 Apr 26th Southwest D I College Mens Regionals 2025
127 Santa Clara Win 13-11 1570.45 Apr 26th Southwest D I College Mens Regionals 2025
84 Southern California Loss 11-13 1290.51 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)