#140 Space Coast Ultimate (10-9)

avg: 833.66  •  sd: 49.52  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
142 ScooberDivers Loss 9-11 578.18 Jul 13th Swan Boat 2019
113 Omen Loss 8-10 704.16 Jul 13th Swan Boat 2019
217 Tyranny Win 11-8 688.98 Jul 13th Swan Boat 2019
133 Vicious Cycle Loss 10-11 756.97 Jul 13th Swan Boat 2019
203 Scootlyfe Win 15-7 1035.85 Jul 14th Swan Boat 2019
124 Swamp Horse Win 9-6 1333.94 Jul 14th Swan Boat 2019
217 Tyranny Win 11-6 870.06 Jul 14th Swan Boat 2019
81 Bullet Loss 5-13 526.43 Jul 20th 2019 Club Terminus
151 Predator Win 11-10 891.7 Jul 20th 2019 Club Terminus
202 War Machine Win 11-7 903.06 Jul 20th 2019 Club Terminus
86 ATLiens Loss 10-11 989.94 Jul 20th 2019 Club Terminus
120 Rush Hour ATL Win 9-8 1072.33 Jul 21st 2019 Club Terminus
223 Traffic Win 13-5 862.59 Jul 21st 2019 Club Terminus
151 Predator Loss 8-10 504.04 Jul 21st 2019 Club Terminus
217 Tyranny Win 13-7 880.9 Sep 7th Florida Mens Club Sectional Championship 2019
49 El Niño Loss 9-13 929.42 Sep 7th Florida Mens Club Sectional Championship 2019
190 UpRoar Claws Win 13-6 1129.12 Sep 7th Florida Mens Club Sectional Championship 2019
113 Omen Loss 10-13 638.68 Sep 7th Florida Mens Club Sectional Championship 2019
124 Swamp Horse Loss 11-14 602.04 Sep 8th Florida 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)