#36 Kansas City Smokestack (17-7)

avg: 1641.9  •  sd: 55.59  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
57 Fungi Win 10-7 1882.21 Jun 24th Colorado Summer Solstice 2023
49 Shrimp Win 11-10 1680.23 Jun 24th Colorado Summer Solstice 2023
41 Johnny Walker Win 15-8 2176.56 Jun 24th Colorado Summer Solstice 2023
57 Fungi Loss 10-11 1367.54 Jun 25th Colorado Summer Solstice 2023
49 Shrimp Win 12-11 1680.23 Jun 25th Colorado Summer Solstice 2023
41 Johnny Walker Loss 11-14 1298.41 Jun 25th Colorado Summer Solstice 2023
176 Battery** Win 13-4 1417.3 Ignored Jul 15th TCT Select Flight West 2023
76 Haymaker Win 15-1 1977.16 Jul 15th TCT Select Flight West 2023
58 Skipjack Win 15-9 2006.19 Jul 15th TCT Select Flight West 2023
11 Furious George Loss 10-14 1658.74 Jul 16th TCT Select Flight West 2023
69 Clutch Win 13-12 1535.39 Jul 16th TCT Select Flight West 2023
70 OAT Win 10-9 1524.46 Jul 16th TCT Select Flight West 2023
96 Bux Win 9-6 1707.43 Aug 19th Cooler Classic 34
90 HouSE Win 13-5 1896.54 Aug 19th Cooler Classic 34
29 Mallard Loss 9-13 1309.7 Aug 19th Cooler Classic 34
17 STL Lounar Loss 9-15 1393.87 Aug 20th Cooler Classic 34
76 Haymaker Win 15-7 1977.16 Aug 20th Cooler Classic 34
46 DeMo Win 15-12 1864.14 Aug 20th Cooler Classic 34
131 NOx Win 13-6 1638.61 Sep 9th 2023 Mens West Plains Sectional Shampionship
214 Meadowlark** Win 13-5 1148.73 Ignored Sep 9th 2023 Mens West Plains Sectional Shampionship
46 DeMo Win 13-11 1792.49 Sep 9th 2023 Mens West Plains Sectional Shampionship
17 STL Lounar Loss 4-15 1309.35 Sep 10th 2023 Mens West Plains Sectional Shampionship
103 Scythe Win 14-13 1328.08 Sep 10th 2023 Mens West Plains Sectional Shampionship
46 DeMo Loss 8-9 1438.65 Sep 10th 2023 Mens West Plains Sectional Shampionship
**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)