#219 THE BODY (2-15)

avg: 531.59  •  sd: 64.95  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
147 DINGWOP Loss 1-7 340.12 Jun 18th Spirit of the Plains
233 BeMo Win 9-8 535.9 Jun 18th Spirit of the Plains
127 Nomads Loss 5-13 451.02 Jun 24th Spirit of the Plains
135 Trident II Loss 2-13 423.67 Jun 24th Spirit of the Plains
148 Minnesota Superior A Loss 6-13 329.49 Jun 24th Spirit of the Plains
46 DeMo** Loss 1-13 963.65 Ignored Jun 25th Spirit of the Plains
143 STL Moonar Loss 8-10 704.11 Aug 19th Cooler Classic 34
159 Choice City Hops Loss 12-13 759.65 Aug 19th Cooler Classic 34
131 NOx Loss 4-13 438.61 Aug 19th Cooler Classic 34
192 Minnesota Superior B Loss 11-13 499.42 Aug 20th Cooler Classic 34
204 Loaded Panda Win 14-11 955.62 Aug 20th Cooler Classic 34
156 NOMAD Loss 9-11 640.75 Aug 20th Cooler Classic 34
175 Dinkytown Doughboys Loss 11-13 591.36 Sep 9th 2023 Mens Northwest Plains Sectional Championship
19 Sub Zero** Loss 4-13 1265.58 Ignored Sep 9th 2023 Mens Northwest Plains Sectional Championship
156 NOMAD Loss 6-13 289.95 Sep 9th 2023 Mens Northwest Plains Sectional Championship
170 Rubicon Rapids Loss 8-13 334.02 Sep 10th 2023 Mens Northwest Plains Sectional Championship
191 DCVIII Loss 12-14 514.63 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)