#47 Vice (11-9)

avg: 948.25  •  sd: 66.55  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
69 PLOW Win 10-8 803.21 Jul 15th Boston Invite 2023
24 Sage Loss 4-13 883.57 Jul 15th Boston Invite 2023
42 Wave Loss 8-11 671.83 Jul 15th Boston Invite 2023
- Vintage Loss 8-9 1036.15 Jul 15th Boston Invite 2023
86 Versa** Win 12-4 763.15 Ignored Aug 5th Philly Open 2023
42 Wave Win 10-9 1162.44 Aug 5th Philly Open 2023
94 Dissent** Win 12-3 626.69 Ignored Aug 5th Philly Open 2023
63 Pine Baroness Win 11-7 1163.56 Aug 5th Philly Open 2023
73 Incline Win 10-8 732.95 Aug 6th Philly Open 2023
37 Agency Loss 7-10 759.41 Aug 6th Philly Open 2023
86 Versa** Win 13-1 763.15 Ignored Sep 9th 2023 Womens East New England Sectional Championship
57 Salty Win 13-7 1396.23 Sep 9th 2023 Womens East New England Sectional Championship
74 Frolic Win 12-8 899.89 Sep 9th 2023 Womens East New England Sectional Championship
22 Siege Loss 7-13 983.95 Sep 9th 2023 Womens East New England Sectional Championship
95 Ignite** Win 13-5 624.41 Ignored Sep 23rd 2023 Northeast Womens Regional Championship
5 Brute Squad** Loss 1-13 1702.83 Ignored Sep 23rd 2023 Northeast Womens Regional Championship
57 Salty Win 11-10 963.69 Sep 23rd 2023 Northeast Womens Regional Championship
8 6ixers** Loss 1-15 1505.93 Ignored Sep 23rd 2023 Northeast Womens Regional Championship
18 Starling Ultimate Loss 7-15 1074.5 Sep 24th 2023 Northeast Womens Regional Championship
39 Brooklyn Book Club Loss 7-11 616.3 Sep 24th 2023 Northeast Womens Regional Championship
**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)