#127 Rougaroux (11-15)

avg: 905.97  •  sd: 65.97  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
36 Freaks Loss 3-13 875.4 Jun 15th ATL Classic 2019
86 Bullet Loss 9-13 688.13 Jun 15th ATL Classic 2019
85 ATLiens Loss 5-13 509.18 Jun 15th ATL Classic 2019
117 Rush Hour ATL Loss 5-13 368.19 Jun 15th ATL Classic 2019
120 baNC Win 10-6 1432.38 Jun 16th ATL Classic 2019
117 Rush Hour ATL Loss 9-10 843.19 Jun 16th ATL Classic 2019
108 H.O.G. Ultimate Win 12-9 1358.36 Jul 20th 2019 Club Terminus
102 Charleston Heat Stroke Win 12-10 1272.58 Jul 20th 2019 Club Terminus
120 baNC Loss 6-13 336.22 Jul 20th 2019 Club Terminus
143 Space Cowboys Loss 11-13 599.09 Jul 20th 2019 Club Terminus
199 Villains Win 13-7 1033.48 Jul 21st 2019 Club Terminus
117 Rush Hour ATL Win 13-9 1386.75 Jul 21st 2019 Club Terminus
152 Predator Loss 7-10 376.96 Jul 21st 2019 Club Terminus
86 Bullet Loss 8-13 610.54 Aug 17th Mudbowl 2019
28 Clutch** Loss 3-13 912.24 Ignored Aug 17th Mudbowl 2019
67 Ironmen Loss 7-13 680.62 Aug 17th Mudbowl 2019
86 Bullet Win 13-11 1335.54 Aug 18th Mudbowl 2019
117 Rush Hour ATL Loss 9-11 718.98 Aug 18th Mudbowl 2019
140 ScooberDivers Win 13-6 1441.82 Aug 18th Mudbowl 2019
36 Freaks Loss 7-13 917.87 Sep 7th Gulf Coast Mens Club Sectional Championship 2019
221 Traffic** Win 13-2 862.31 Ignored Sep 7th Gulf Coast Mens Club Sectional Championship 2019
203 War Machine Win 13-1 1039.03 Sep 7th Gulf Coast Mens Club Sectional Championship 2019
67 Ironmen Loss 8-10 975.49 Sep 7th Gulf Coast Mens Club Sectional Championship 2019
166 Barefoot Win 10-4 1279.12 Sep 8th Gulf Coast Mens Club Sectional Championship 2019
187 Rampage Win 13-11 766.39 Sep 8th Gulf Coast Mens Club Sectional Championship 2019
67 Ironmen Loss 6-13 638.16 Sep 8th Gulf Coast Mens Club Sectional Championship 2019
**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)