#198 Capitol City Chaos (1-19)

avg: 696.2  •  sd: 56.85  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
134 Dyno Loss 3-11 426.16 Jun 24th Huntsville Huckfest
144 Music City Mafia Loss 5-11 365.1 Jun 24th Huntsville Huckfest
56 Little Red Wagon Loss 5-11 897.91 Jun 24th Huntsville Huckfest
89 Second Nature Loss 7-13 742.07 Jun 24th Huntsville Huckfest
172 Memphis Pharaohs Loss 8-11 459.66 Jun 24th Huntsville Huckfest
37 Alliance** Loss 3-11 1027.37 Ignored Jun 25th Huntsville Huckfest
207 Villains Loss 8-9 474.94 Jun 25th Huntsville Huckfest
116 Atlanta Arson Loss 10-11 1018.89 Aug 5th Trestlemania V
124 Battleship Loss 8-10 798.26 Aug 5th Trestlemania V
64 Hooch Loss 6-11 901.87 Aug 5th Trestlemania V
56 Little Red Wagon** Loss 5-13 897.91 Ignored Aug 5th Trestlemania V
144 Music City Mafia Win 10-9 1090.1 Aug 6th Trestlemania V
56 Little Red Wagon** Loss 5-12 897.91 Ignored Aug 6th Trestlemania V
150 Nashville Mudcats Loss 6-9 507.63 Aug 6th Trestlemania V
146 Ronin Loss 7-12 430.99 Sep 9th 2023 Mens Gulf Coast Sectional Championship
124 Battleship Loss 9-12 715.56 Sep 9th 2023 Mens Gulf Coast Sectional Championship
89 Second Nature Loss 10-13 971.46 Sep 9th 2023 Mens Gulf Coast Sectional Championship
172 Memphis Pharaohs Loss 9-13 406.7 Sep 9th 2023 Mens Gulf Coast Sectional Championship
37 Alliance Loss 6-13 1027.37 Sep 10th 2023 Mens Gulf Coast Sectional Championship
172 Memphis Pharaohs Loss 9-13 406.7 Sep 10th 2023 Mens Gulf Coast 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)