#73 San Diego State (14-7)

avg: 1723.73  •  sd: 71.86  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
111 California-Irvine Win 11-7 1900.23 Feb 3rd 2018 Presidents Day Qualifying Tournament
120 California-San Diego-B Win 11-6 1925.4 Feb 3rd 2018 Presidents Day Qualifying Tournament
17 California-Santa Barbara Loss 5-13 1720.26 Feb 3rd 2018 Presidents Day Qualifying Tournament
63 Arizona Loss 7-10 1396.56 Feb 3rd 2018 Presidents Day Qualifying Tournament
164 UCLA-B Win 10-6 1602.45 Feb 4th 2018 Presidents Day Qualifying Tournament
120 California-San Diego-B Win 12-3 1978.7 Feb 4th 2018 Presidents Day Qualifying Tournament
100 Arizona State Loss 6-9 1087.67 Feb 4th 2018 Presidents Day Qualifying Tournament
87 California-Santa Cruz Win 7-6 1712.75 Feb 10th Stanford Open 2018
105 Chico State Loss 6-8 1178.85 Feb 10th Stanford Open 2018
118 Lewis & Clark Win 11-8 1762.06 Feb 10th Stanford Open 2018
147 Humboldt State Win 9-6 1611.13 Feb 10th Stanford Open 2018
67 Puget Sound Win 8-7 1893.81 Feb 11th Stanford Open 2018
61 California-Davis Loss 6-10 1321.76 Feb 11th Stanford Open 2018
77 Brown Loss 5-7 1360.78 Feb 11th Stanford Open 2018
98 Northern Arizona Loss 5-7 1195.71 Mar 24th Trouble in Vegas 2018
120 California-San Diego-B Win 10-2 1978.7 Mar 24th Trouble in Vegas 2018
200 Nevada-Reno** Win 10-1 1483.18 Ignored Mar 24th Trouble in Vegas 2018
63 Arizona Win 9-5 2315.29 Mar 24th Trouble in Vegas 2018
111 California-Irvine Win 9-2 2033.34 Mar 25th Trouble in Vegas 2018
105 Chico State Win 13-2 2079.34 Mar 25th Trouble in Vegas 2018
100 Arizona State Win 8-6 1806.73 Mar 25th Trouble in Vegas 2018
**Blowout Eligible

FAQ

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
  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
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)