#108 Swamp Horse (12-18)

avg: 771.45  •  sd: 43.51  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
107 BaNC Win 13-12 900.64 Jun 16th ATL Classic 2018
114 Cockfight Win 13-12 888.48 Jun 16th ATL Classic 2018
75 Omen Loss 7-12 472.23 Jun 16th ATL Classic 2018
- ATLiens Loss 10-11 673.36 Jun 16th ATL Classic 2018
71 UpRoar Loss 9-13 604.65 Jun 17th ATL Classic 2018
55 Ironmen Loss 9-12 806.85 Jun 17th ATL Classic 2018
102 H.O.G. Ultimate Loss 11-13 598.67 Jun 17th ATL Classic 2018
168 Tyranny** Win 13-2 660.32 Ignored Jul 7th Swan Boat 2018
- Shrimp Boat Win 12-7 625.85 Jul 7th Swan Boat 2018
137 Space Coast Ultimate Loss 11-12 439.97 Jul 7th Swan Boat 2018
75 Omen Loss 8-13 496.58 Jul 7th Swan Boat 2018
128 Vicious Cycle Win 15-9 1163.58 Jul 8th Swan Boat 2018
75 Omen Loss 10-13 664.6 Jul 8th Swan Boat 2018
133 Holy City Heathens Win 15-8 1171.21 Jul 8th Swan Boat 2018
34 Lost Boys Loss 8-13 813.03 Jul 21st Club Terminus 2018
55 Ironmen Loss 8-12 711.07 Jul 21st Club Terminus 2018
107 BaNC Loss 6-8 475.15 Jul 22nd Club Terminus 2018
37 Brickhouse Loss 7-13 730.68 Jul 22nd Club Terminus 2018
98 Southern Hospitality Win 13-9 1267.61 Jul 22nd Club Terminus 2018
101 Memphis Belle Win 9-6 1248.44 Jul 22nd Club Terminus 2018
106 Battleship Win 12-10 1016 Aug 18th Trestlemania III
104 Black Lung Loss 11-13 579.88 Aug 18th Trestlemania III
128 Vicious Cycle Win 13-4 1248.1 Aug 18th Trestlemania III
114 Cockfight Loss 11-12 638.48 Aug 18th Trestlemania III
102 H.O.G. Ultimate Loss 9-10 702.51 Aug 19th Trestlemania III
140 ScooberDivers Win 15-9 1038.52 Sep 8th Florida Mens Sectional Championship 2018
137 Space Coast Ultimate Win 14-8 1101.01 Sep 8th Florida Mens Sectional Championship 2018
75 Omen Loss 4-10 392.74 Sep 8th Florida Mens Sectional Championship 2018
44 El Niño Loss 9-15 729.52 Sep 9th Florida Mens Sectional Championship 2018
128 Vicious Cycle Loss 9-15 132.62 Sep 9th Florida Mens Sectional Championship 2018
**Blowout Eligible

FAQ

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
  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
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)