#123 Satellite (16-11)

avg: 701.15  •  sd: 61.54  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
170 Bird Patrol** Win 13-3 625.47 Ignored Jul 21st Layout for Summer 2018
100 Babe Loss 10-11 708.2 Jul 21st Layout for Summer 2018
154 Black Market II Win 9-7 586.17 Jul 21st Layout for Summer 2018
139 Kentucky Flying Circus Win 13-10 853.65 Jul 21st Layout for Summer 2018
- BromINtum Loss 9-12 13.38 Jul 22nd Layout for Summer 2018
139 Kentucky Flying Circus Win 10-7 915.17 Jul 22nd Layout for Summer 2018
154 Black Market II Loss 8-9 181.83 Jul 22nd Layout for Summer 2018
- Kettering** Win 13-1 600 Ignored Aug 4th Heavyweights 2018
146 Dirty D Win 13-7 970.77 Aug 4th Heavyweights 2018
70 Imperial Loss 9-11 781.36 Aug 4th Heavyweights 2018
- Baemaker Win 13-5 894.85 Aug 5th Heavyweights 2018
121 BlackER Market Win 13-8 1202.62 Aug 5th Heavyweights 2018
112 Enigma Win 12-10 1002.56 Aug 5th Heavyweights 2018
124 Wisconsin Hops Win 13-11 925.19 Aug 18th Cooler Classic 30
152 Green Bay Quackers Win 13-9 750.93 Aug 18th Cooler Classic 30
149 Chimney Win 13-9 765.59 Aug 18th Cooler Classic 30
136 Pipeline Win 13-10 908.96 Aug 18th Cooler Classic 30
56 Haymaker Loss 6-15 530.27 Aug 19th Cooler Classic 30
117 THE BODY Win 15-11 1112.1 Aug 19th Cooler Classic 30
124 Wisconsin Hops Loss 8-9 571.35 Aug 19th Cooler Classic 30
119 MomINtuM Loss 8-10 449.67 Sep 8th Central Plains Mens Sectional Championship 2018
56 Haymaker Loss 4-13 530.27 Sep 8th Central Plains Mens Sectional Championship 2018
- BlackEST Market Win 13-6 799.92 Sep 8th Central Plains Mens Sectional Championship 2018
26 Brickyard** Loss 3-13 798.84 Ignored Sep 8th Central Plains Mens Sectional Championship 2018
170 Bird Patrol** Win 15-2 625.47 Ignored Sep 9th Central Plains Mens Sectional Championship 2018
121 BlackER Market Loss 8-15 141.65 Sep 9th Central Plains Mens Sectional Championship 2018
116 Greater Gary Goblins X Loss 11-12 616.16 Sep 9th Central Plains Mens 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)