#105 Jackpot (13-8)

avg: 1085.69  •  sd: 74.16  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
90 Mutiny Loss 8-10 903.02 Jul 7th Swan Boat 2018
244 Mixchief** Win 13-4 577.14 Ignored Jul 7th Swan Boat 2018
225 Big Bend** Win 13-4 951.82 Ignored Jul 7th Swan Boat 2018
- Bold City Win 13-4 1175.94 Jul 7th Swan Boat 2018
90 Mutiny Loss 10-15 712.08 Jul 8th Swan Boat 2018
- Bold City Win 15-10 1029.54 Jul 8th Swan Boat 2018
42 Mixfits Loss 9-13 1055.96 Aug 11th HoDown%20ShowDown%20XXII
219 Carolina Reign Win 13-7 983 Aug 11th HoDown%20ShowDown%20XXII
82 Method Win 13-9 1651.18 Aug 11th HoDown%20ShowDown%20XXII
54 JLP Loss 6-13 725.88 Aug 11th HoDown%20ShowDown%20XXII
192 RnB Win 15-14 743.78 Aug 12th HoDown%20ShowDown%20XXII
82 Method Loss 11-13 1003.78 Aug 12th HoDown%20ShowDown%20XXII
54 JLP Win 13-12 1450.88 Aug 12th HoDown%20ShowDown%20XXII
151 LoveShack Win 15-13 1070.61 Aug 12th HoDown%20ShowDown%20XXII
90 Mutiny Win 9-8 1290.68 Sep 8th Florida Mixed Sectional Championship 2018
27 Weird Loss 7-13 1020.32 Sep 8th Florida Mixed Sectional Championship 2018
244 Mixchief** Win 13-3 577.14 Ignored Sep 8th Florida Mixed Sectional Championship 2018
225 Big Bend** Win 13-2 951.82 Ignored Sep 8th Florida Mixed Sectional Championship 2018
90 Mutiny Loss 12-13 1040.68 Sep 9th Florida Mixed Sectional Championship 2018
27 Weird Loss 9-12 1232.48 Sep 9th Florida Mixed Sectional Championship 2018
- Bold City Win 13-3 1175.94 Sep 9th Florida Mixed Sectional Championship 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)