#149 Chimney (4-15)

avg: 347.03  •  sd: 75.47  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
127 Dynasty Loss 9-11 402.76 Jul 7th Motown Throwdown 2018
31 Black Market** Loss 4-11 746.73 Ignored Jul 7th Motown Throwdown 2018
- Torontosaurus Rex Win 11-6 405.99 Jul 7th Motown Throwdown 2018
48 Four** Loss 5-15 616.08 Ignored Jul 7th Motown Throwdown 2018
154 Black Market II Win 15-9 822.31 Jul 8th Motown Throwdown 2018
127 Dynasty Loss 12-15 351.47 Jul 8th Motown Throwdown 2018
- COAT Win 15-6 871.89 Jul 8th Motown Throwdown 2018
123 Satellite Loss 9-13 282.59 Aug 18th Cooler Classic 30
152 Green Bay Quackers Loss 8-13 -163.8 Aug 18th Cooler Classic 30
124 Wisconsin Hops Loss 9-13 277.78 Aug 18th Cooler Classic 30
95 Scythe Loss 6-15 279.07 Aug 19th Cooler Classic 30
121 BlackER Market Loss 12-14 485.5 Aug 19th Cooler Classic 30
152 Green Bay Quackers Loss 11-13 103.52 Aug 19th Cooler Classic 30
36 CLE Smokestack** Loss 2-13 699.63 Ignored Sep 8th East Plains Mens Sectional Championship 2018
104 Black Lung Loss 6-13 208.72 Sep 8th East Plains Mens Sectional Championship 2018
146 Dirty D Win 11-7 880.13 Sep 8th East Plains Mens Sectional Championship 2018
100 Babe Loss 8-15 268.39 Sep 9th East Plains Mens Sectional Championship 2018
136 Pipeline Loss 6-11 34.12 Sep 9th East Plains Mens Sectional Championship 2018
65 Mango Tree** Loss 3-13 444.17 Ignored Sep 9th East 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)