#221 Traffic (2-14)

avg: 262.31  •  sd: 88.15  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
37 Tanasi** Loss 3-13 875.25 Ignored Jul 20th 2019 Club Terminus
117 Rush Hour ATL** Loss 2-13 368.19 Ignored Jul 20th 2019 Club Terminus
120 baNC Loss 6-13 336.22 Jul 20th 2019 Club Terminus
108 H.O.G. Ultimate Loss 7-10 623.33 Jul 21st 2019 Club Terminus
142 Space Coast Ultimate Loss 5-13 239.44 Jul 21st 2019 Club Terminus
203 War Machine Win 11-10 564.03 Jul 21st 2019 Club Terminus
183 Battleship Loss 12-13 431.85 Aug 17th Mudbowl 2019
117 Rush Hour ATL** Loss 5-13 368.19 Ignored Aug 17th Mudbowl 2019
203 War Machine Loss 9-12 93.66 Aug 17th Mudbowl 2019
187 Rampage Win 12-8 978.71 Aug 18th Mudbowl 2019
183 Battleship Loss 5-13 -43.15 Aug 18th Mudbowl 2019
203 War Machine Loss 9-13 20.46 Aug 18th Mudbowl 2019
36 Freaks** Loss 1-13 875.4 Ignored Sep 7th Gulf Coast Mens Club Sectional Championship 2019
127 Rougaroux** Loss 2-13 305.97 Ignored Sep 7th Gulf Coast Mens Club Sectional Championship 2019
203 War Machine Loss 3-11 -160.97 Sep 7th Gulf Coast Mens Club Sectional Championship 2019
187 Rampage Loss 5-9 8.49 Sep 7th 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)