#65 Liberty (12-8)

avg: 1314.23  •  sd: 74.83  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
12 Virginia** Loss 1-13 1435.27 Ignored Jan 25th Winta Binta Vinta Fest 2020
32 William & Mary Loss 7-12 1120.06 Jan 25th Winta Binta Vinta Fest 2020
166 West Virginia Win 11-6 1102.03 Jan 25th Winta Binta Vinta Fest 2020
107 Georgetown Win 10-6 1530.65 Jan 26th Winta Binta Vinta Fest 2020
12 Virginia** Loss 2-14 1435.27 Ignored Jan 26th Winta Binta Vinta Fest 2020
32 William & Mary Loss 7-9 1361.23 Jan 26th Winta Binta Vinta Fest 2020
79 Temple Loss 9-10 1101.54 Feb 15th Commonwealth Cup 2020 Weekend 1
219 Michigan-B** Win 13-1 663.75 Ignored Feb 15th Commonwealth Cup 2020 Weekend 1
139 Mary Washington Win 10-3 1406.2 Feb 15th Commonwealth Cup 2020 Weekend 1
34 James Madison Loss 5-13 1032.11 Feb 16th Commonwealth Cup 2020 Weekend 1
101 Connecticut Win 8-6 1359.25 Feb 16th Commonwealth Cup 2020 Weekend 1
37 Boston University Win 10-9 1683.66 Feb 16th Commonwealth Cup 2020 Weekend 1
24 Ohio Loss 2-12 1183.41 Feb 16th Commonwealth Cup 2020 Weekend 1
85 Haverford/Bryn Mawr Loss 7-9 904.74 Mar 7th Mash Up 2020
170 Rhode Island** Win 13-4 1128.84 Ignored Mar 7th Mash Up 2020
110 Cincinnati Win 9-5 1551.71 Mar 7th Mash Up 2020
194 SUNY-Fredonia** Win 9-3 917.47 Ignored Mar 7th Mash Up 2020
155 Vermont-B Win 10-5 1230.63 Mar 8th Mash Up 2020
85 Haverford/Bryn Mawr Win 13-6 1784.08 Mar 8th Mash Up 2020
231 RIT** Win 13-3 463.86 Ignored Mar 8th Mash Up 2020
**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)