#73 Knights of Ni (16-5)

avg: 1385.85  •  sd: 48.84  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
147 DINGWOP Win 13-7 1497.65 Jun 24th Spirit of the Plains
233 BeMo** Win 13-2 1010.9 Ignored Jun 24th Spirit of the Plains
192 Minnesota Superior B Win 13-6 1328.26 Jun 24th Spirit of the Plains
103 Scythe Win 13-9 1621.65 Jun 24th Spirit of the Plains
148 Minnesota Superior A Win 10-5 1503.39 Jun 25th Spirit of the Plains
204 Loaded Panda Win 13-8 1138.45 Jun 25th Spirit of the Plains
46 DeMo Loss 9-12 1218.28 Jun 25th Spirit of the Plains
130 Diesel Win 13-9 1459.23 Jul 8th Heavyweights 2023
143 STL Moonar Win 13-6 1566.77 Jul 8th Heavyweights 2023
135 Trident II Win 13-5 1623.67 Jul 8th Heavyweights 2023
191 DCVIII Win 13-6 1335.58 Jul 8th Heavyweights 2023
98 Riverside Win 12-11 1403.58 Jul 9th Heavyweights 2023
17 STL Lounar Loss 5-13 1309.35 Jul 9th Heavyweights 2023
90 HouSE Loss 9-13 877.98 Jul 9th Heavyweights 2023
245 Milwaukee Revival** Win 13-2 800.48 Ignored Sep 9th 2023 Mens Northwest Plains Sectional Championship
127 Nomads Win 13-8 1547.18 Sep 9th 2023 Mens Northwest Plains Sectional Championship
191 DCVIII** Win 13-5 1335.58 Ignored Sep 9th 2023 Mens Northwest Plains Sectional Championship
175 Dinkytown Doughboys Win 15-10 1273.8 Sep 10th 2023 Mens Northwest Plains Sectional Championship
19 Sub Zero Loss 6-15 1265.58 Sep 10th 2023 Mens Northwest Plains Sectional Championship
29 Mallard Loss 11-13 1499.42 Sep 10th 2023 Mens Northwest Plains Sectional Championship
127 Nomads Win 15-11 1432.19 Sep 10th 2023 Mens Northwest Plains Sectional Championship
**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)