#104 Black Lung (11-12)

avg: 808.72  •  sd: 56.67  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
97 Rush Hour Win 13-7 1408.71 Jul 21st Club Terminus 2018
15 Chain Lightning Loss 6-13 1092.74 Jul 21st Club Terminus 2018
165 War Machine Win 13-6 703.5 Jul 21st Club Terminus 2018
66 Bullet Loss 10-12 803.46 Jul 22nd Club Terminus 2018
23 Freaks** Loss 5-13 901.12 Ignored Jul 22nd Club Terminus 2018
61 Tanasi Loss 6-13 495.92 Jul 22nd Club Terminus 2018
106 Battleship Win 13-10 1106.02 Aug 18th Trestlemania III
108 Swamp Horse Win 13-11 1000.29 Aug 18th Trestlemania III
128 Vicious Cycle Win 13-3 1248.1 Aug 18th Trestlemania III
114 Cockfight Win 12-11 888.48 Aug 18th Trestlemania III
71 UpRoar Loss 9-13 604.65 Aug 19th Trestlemania III
102 H.O.G. Ultimate Win 13-11 1056.35 Aug 19th Trestlemania III
149 Chimney Win 13-6 947.03 Sep 8th East Plains Mens Sectional Championship 2018
36 CLE Smokestack Loss 5-13 699.63 Sep 8th East Plains Mens Sectional Championship 2018
65 Mango Tree Loss 6-13 444.17 Sep 8th East Plains Mens Sectional Championship 2018
146 Dirty D Win 11-10 538.23 Sep 9th East Plains Mens Sectional Championship 2018
136 Pipeline Win 10-8 843.48 Sep 9th East Plains Mens Sectional Championship 2018
51 BroCats Loss 1-15 589.85 Sep 9th East Plains Mens Sectional Championship 2018
26 Brickyard Loss 8-13 902.68 Sep 22nd Great Lakes Mens Regional Championship 2018
56 Haymaker Loss 5-13 530.27 Sep 22nd Great Lakes Mens Regional Championship 2018
121 BlackER Market Loss 7-10 316.79 Sep 22nd Great Lakes Mens Regional Championship 2018
116 Greater Gary Goblins X Win 15-10 1194.76 Sep 23rd Great Lakes Mens Regional Championship 2018
90 Omen Loss 14-16 692.74 Sep 23rd Great Lakes Mens Regional 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)