#103 Scythe (12-8)

avg: 1203.08  •  sd: 49.23  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
147 DINGWOP Win 12-7 1460.63 Jun 24th Spirit of the Plains
233 BeMo Win 13-6 1010.9 Jun 24th Spirit of the Plains
73 Knights of Ni Loss 9-13 967.28 Jun 24th Spirit of the Plains
204 Loaded Panda Win 12-6 1221.6 Jun 24th Spirit of the Plains
148 Minnesota Superior A Loss 9-10 804.49 Jun 25th Spirit of the Plains
192 Minnesota Superior B Win 11-8 1093.87 Jun 25th Spirit of the Plains
46 DeMo Loss 4-13 963.65 Jun 25th Spirit of the Plains
77 BARNSTORM Loss 8-11 1009.14 Aug 26th Ragna Rock 2023
172 Memphis Pharaohs Win 13-8 1321.43 Aug 26th Ragna Rock 2023
208 Grit** Win 13-5 1190.49 Ignored Aug 26th Ragna Rock 2023
116 Atlanta Arson Loss 8-10 881.22 Aug 27th Ragna Rock 2023
172 Memphis Pharaohs Win 13-6 1425.27 Aug 27th Ragna Rock 2023
149 Rawhide Win 13-10 1255.17 Aug 27th Ragna Rock 2023
17 STL Lounar Loss 6-13 1309.35 Sep 9th 2023 Mens West Plains Sectional Shampionship
143 STL Moonar Win 13-8 1462.93 Sep 9th 2023 Mens West Plains Sectional Shampionship
131 NOx Win 15-12 1339.1 Sep 9th 2023 Mens West Plains Sectional Shampionship
204 Loaded Panda Win 13-10 970.43 Sep 9th 2023 Mens West Plains Sectional Shampionship
143 STL Moonar Win 13-8 1462.93 Sep 10th 2023 Mens West Plains Sectional Shampionship
36 Kansas City Smokestack Loss 13-14 1516.9 Sep 10th 2023 Mens West Plains Sectional Shampionship
46 DeMo Loss 5-15 963.65 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)