#139 Kentucky Flying Circus (3-16)

avg: 525.5  •  sd: 71.35  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
123 Satellite Loss 10-13 373.01 Jul 21st Layout for Summer 2018
- BromINtum Win 13-8 854.91 Jul 21st Layout for Summer 2018
- Illinois Youth Ultimate - u20 Loss 6-11 -22.28 Jul 21st Layout for Summer 2018
119 MomINtuM Loss 5-13 112.34 Jul 21st Layout for Summer 2018
123 Satellite Loss 7-10 311.49 Jul 22nd Layout for Summer 2018
100 Babe Loss 8-13 337.04 Jul 22nd Layout for Summer 2018
161 Ironside Win 9-2 807.16 Jul 22nd Layout for Summer 2018
112 Enigma Loss 5-6 639.44 Aug 25th Indy Invite Club 2018
26 Brickyard Loss 5-11 798.84 Aug 25th Indy Invite Club 2018
51 BroCats** Loss 4-11 589.85 Ignored Aug 26th Indy Invite Club 2018
90 Omen Loss 5-11 301.03 Aug 26th Indy Invite Club 2018
119 MomINtuM Loss 5-8 258.73 Aug 26th Indy Invite Club 2018
65 Mango Tree Loss 8-11 678.56 Aug 26th Indy Invite Club 2018
100 Babe Loss 9-11 583.99 Sep 8th East Plains Mens Sectional Championship 2018
112 Enigma Loss 8-10 501.77 Sep 8th East Plains Mens Sectional Championship 2018
90 Omen Loss 10-11 776.03 Sep 8th East Plains Mens Sectional Championship 2018
159 Midnight Meat Train Win 11-4 835.84 Sep 8th East Plains Mens Sectional Championship 2018
51 BroCats** Loss 4-11 589.85 Ignored Sep 9th East Plains Mens Sectional Championship 2018
48 Four** Loss 2-11 616.08 Ignored Sep 9th East Plains 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)