#131 NOx (15-12)

avg: 1038.61  •  sd: 54.3  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
78 Drought Loss 3-15 774.11 Jun 24th Colorado Summer Solstice 2023
224 Mycellium Win 15-3 1090.07 Jun 24th Colorado Summer Solstice 2023
49 Shrimp Loss 5-15 955.23 Jun 24th Colorado Summer Solstice 2023
174 Colorado Cutthroat: Youth Club U-20 Boys Win 9-8 947.65 Jun 25th Colorado Summer Solstice 2023
171 Sonoran Dog Loss 8-10 565.54 Jun 25th Colorado Summer Solstice 2023
178 COSmic U-20 Boys Win 13-8 1308.4 Jun 25th Colorado Summer Solstice 2023
98 Riverside Loss 4-13 678.58 Jul 8th Heavyweights 2023
179 Timber Win 13-7 1368.08 Jul 8th Heavyweights 2023
63 I-69 Loss 6-13 849.32 Jul 8th Heavyweights 2023
201 Trident III Win 13-11 905.33 Jul 8th Heavyweights 2023
143 STL Moonar Win 13-7 1524.3 Jul 9th Heavyweights 2023
179 Timber Win 13-5 1410.55 Jul 9th Heavyweights 2023
55 Colonels Loss 11-13 1274.85 Jul 9th Heavyweights 2023
143 STL Moonar Loss 7-9 687.44 Aug 19th Cooler Classic 34
219 THE BODY Win 13-4 1131.59 Aug 19th Cooler Classic 34
192 Minnesota Superior B Win 12-7 1248.77 Aug 19th Cooler Classic 34
159 Choice City Hops Win 13-9 1303.21 Aug 19th Cooler Classic 34
170 Rubicon Rapids Win 9-8 955.18 Aug 20th Cooler Classic 34
147 DINGWOP Win 15-9 1455.6 Aug 20th Cooler Classic 34
135 Trident II Loss 12-15 723.18 Aug 20th Cooler Classic 34
36 Kansas City Smokestack Loss 6-13 1041.9 Sep 9th 2023 Mens West Plains Sectional Shampionship
46 DeMo Loss 6-13 963.65 Sep 9th 2023 Mens West Plains Sectional Shampionship
214 Meadowlark Win 13-7 1106.26 Sep 9th 2023 Mens West Plains Sectional Shampionship
103 Scythe Loss 12-15 902.59 Sep 9th 2023 Mens West Plains Sectional Shampionship
143 STL Moonar Loss 8-15 401.96 Sep 10th 2023 Mens West Plains Sectional Shampionship
204 Loaded Panda Win 14-5 1242.29 Sep 10th 2023 Mens West Plains Sectional Shampionship
204 Loaded Panda Win 15-5 1242.29 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)