#86 Versa (1-15)

avg: 163.15  •  sd: 108.98  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
- Tempest Loss 4-13 -78.36 Jul 15th Boston Invite 2023
39 Brooklyn Book Club** Loss 2-13 483.2 Ignored Jul 15th Boston Invite 2023
59 Virginia Rebellion Loss 2-12 135.23 Jul 15th Boston Invite 2023
73 Incline Loss 7-10 80.62 Aug 5th Philly Open 2023
47 Vice** Loss 4-12 348.25 Ignored Aug 5th Philly Open 2023
37 Agency** Loss 3-13 549.08 Ignored Aug 5th Philly Open 2023
42 Wave** Loss 1-13 437.44 Ignored Aug 6th Philly Open 2023
94 Dissent Win 9-7 306.03 Aug 6th Philly Open 2023
63 Pine Baroness Loss 4-11 96.66 Aug 6th Philly Open 2023
74 Frolic Loss 7-9 179.4 Sep 9th 2023 Womens East New England Sectional Championship
22 Siege** Loss 2-13 941.48 Ignored Sep 9th 2023 Womens East New England Sectional Championship
47 Vice** Loss 1-13 348.25 Ignored Sep 9th 2023 Womens East New England Sectional Championship
57 Salty Loss 6-10 342.53 Sep 9th 2023 Womens East New England Sectional Championship
8 6ixers** Loss 0-13 1505.93 Ignored Sep 23rd 2023 Northeast Womens Regional Championship
69 PLOW Loss 5-13 -59.45 Sep 23rd 2023 Northeast Womens Regional Championship
69 PLOW Loss 7-8 415.55 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)