#133 BAG (7-9)

avg: 1034.3  •  sd: 81.68  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
109 Ascension Loss 9-10 1043.78 Jul 15th Boston Invite 2023
169 MBTA Loss 8-10 567.95 Jul 15th Boston Invite 2023
94 Magma Bears Loss 6-13 691.23 Jul 15th Boston Invite 2023
154 Odyssey Win 13-2 1494.28 Jul 15th Boston Invite 2023
177 JAWN Win 9-8 937.44 Aug 5th Philly Open 2023
209 Long Island Riff Raff Win 13-2 1189.54 Aug 5th Philly Open 2023
115 Bomb Squad Loss 9-10 1019.34 Aug 5th Philly Open 2023
94 Magma Bears Win 10-7 1680.89 Aug 6th Philly Open 2023
91 Helots Loss 5-10 720.98 Aug 6th Philly Open 2023
84 Pittsburgh Stealers Win 10-8 1590.34 Aug 6th Philly Open 2023
32 Scoop** Loss 6-15 1075.57 Ignored Sep 9th 2023 Mens East New England Sectional Championship
163 Crossfire Win 14-11 1172.71 Sep 9th 2023 Mens East New England Sectional Championship
7 DiG** Loss 5-15 1567.51 Ignored Sep 9th 2023 Mens East New England Sectional Championship
71 Big Wrench Loss 6-12 815.7 Sep 9th 2023 Mens East New England Sectional Championship
154 Odyssey Loss 11-13 665.44 Sep 10th 2023 Mens East New England Sectional Championship
163 Crossfire Win 11-10 984.38 Sep 10th 2023 Mens East New England 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)