#52 Deadly Viper Assassination Squad (7-16)

avg: 793.57  •  sd: 61.56  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
24 Wicked** Loss 6-15 892.17 Ignored Jun 16th Fort Collins Summer Solstice 2018
38 Jackwagon Loss 14-15 956.53 Jun 16th Fort Collins Summer Solstice 2018
- Colorado Cutthroat Win 15-6 1070.07 Jun 16th Fort Collins Summer Solstice 2018
47 Trainwreck Loss 12-14 617.23 Jun 17th Fort Collins Summer Solstice 2018
50 Cold Cuts Win 15-9 1333.75 Jun 17th Fort Collins Summer Solstice 2018
25 Colorado Small Batch** Loss 3-15 847.1 Ignored Jun 17th Fort Collins Summer Solstice 2018
33 Rampage Loss 3-13 563.46 Aug 18th Ski Town Classic 2018
72 Seattle END Win 13-5 908.59 Aug 18th Ski Town Classic 2018
38 Jackwagon Loss 6-9 662.97 Aug 18th Ski Town Classic 2018
47 Trainwreck Loss 7-10 448.52 Aug 19th Ski Town Classic 2018
69 Viva Win 13-6 985.9 Aug 19th Ski Town Classic 2018
68 Seven Devils Win 13-5 1016.4 Aug 19th Ski Town Classic 2018
32 FAB Loss 3-13 590.7 Sep 8th Nor Cal Womens Sectional Championship 2018
2 Fury** Loss 0-13 1760.71 Ignored Sep 8th Nor Cal Womens Sectional Championship 2018
- Tempo** Win 13-5 600 Ignored Sep 8th Nor Cal Womens Sectional Championship 2018
23 LOL** Loss 5-13 910.22 Ignored Sep 8th Nor Cal Womens Sectional Championship 2018
32 FAB Loss 8-11 825.09 Sep 9th Nor Cal Womens Sectional Championship 2018
- Tempo** Win 15-5 600 Ignored Sep 9th Nor Cal Womens Sectional Championship 2018
33 Rampage Loss 11-12 1038.46 Sep 22nd Southwest Womens Regional Championship 2018
23 LOL** Loss 5-15 910.22 Ignored Sep 22nd Southwest Womens Regional Championship 2018
8 Nightlock** Loss 4-15 1320.39 Ignored Sep 22nd Southwest Womens Regional Championship 2018
32 FAB Loss 8-15 625.89 Sep 23rd Southwest Womens Regional Championship 2018
33 Rampage Loss 8-15 598.65 Sep 23rd Southwest Womens Regional Championship 2018
**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)