#115 Bomb Squad (16-6)

avg: 1144.34  •  sd: 57.26  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
180 SUPA FC Win 11-9 1038.59 Jul 8th MOB Open 2023
186 Town Hall Stars Win 10-7 1143.96 Jul 8th MOB Open 2023
91 Helots Win 11-9 1544.09 Jul 8th MOB Open 2023
52 Oakgrove Boys Loss 5-15 927.68 Jul 8th MOB Open 2023
133 BAG Win 10-9 1159.3 Aug 5th Philly Open 2023
209 Long Island Riff Raff Win 13-6 1189.54 Aug 5th Philly Open 2023
177 JAWN Win 8-6 1112.93 Aug 5th Philly Open 2023
91 Helots Loss 8-9 1169.88 Aug 6th Philly Open 2023
94 Magma Bears Win 13-9 1709.79 Aug 6th Philly Open 2023
52 Oakgrove Boys Loss 6-11 980.99 Aug 6th Philly Open 2023
235 Adelphos** Win 13-2 974.59 Ignored Aug 26th The Incident 2023
189 Dirty Laundry Win 12-5 1348.17 Aug 26th The Incident 2023
252 Deepfake** Win 13-1 649.62 Ignored Aug 26th The Incident 2023
163 Crossfire Win 13-8 1355.53 Aug 26th The Incident 2023
102 Harvey Cats Loss 7-14 624.31 Aug 27th The Incident 2023
163 Crossfire Win 13-12 984.38 Aug 27th The Incident 2023
157 Winc City Fog of War Win 11-9 1138.21 Sep 9th 2023 Mens Capital Sectional Championship
227 Brackish** Win 12-5 1077.16 Ignored Sep 9th 2023 Mens Capital Sectional Championship
183 Bearfax Win 11-6 1329.69 Sep 9th 2023 Mens Capital Sectional Championship
83 Red Wolves Loss 4-15 747.98 Sep 10th 2023 Mens Capital Sectional Championship
161 MOB Ultimate Win 15-3 1464.78 Sep 10th 2023 Mens Capital Sectional Championship
95 Puzzles Loss 10-14 890.4 Sep 10th 2023 Mens Capital 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)