#13 Furious George (18-1)

avg: 1879.83  •  sd: 66.93  •  top 16/20: 88.1%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
93 Dark Star Win 13-6 1677.26 Jun 22nd Eugene Summer Solstice 2019
196 Komori** Win 13-3 1082.3 Ignored Jun 22nd Eugene Summer Solstice 2019
121 Green River Swordfish Win 13-7 1497.72 Jun 22nd Eugene Summer Solstice 2019
45 Red Dawn Win 13-7 1935.86 Jun 22nd Eugene Summer Solstice 2019
19 Voodoo Win 15-6 2335.56 Jun 23rd Eugene Summer Solstice 2019
15 Rhino Slam! Win 16-15 1978.54 Jun 23rd Eugene Summer Solstice 2019
43 CITYWIDE Special Win 13-5 2001.95 Jul 27th TCT Select Flight Invite East 2019
41 MKE Win 13-4 2010.84 Jul 27th TCT Select Flight Invite East 2019
36 Nitro Win 13-8 1959.57 Jul 27th TCT Select Flight Invite East 2019
23 CLE Smokestack Win 13-7 2193.2 Jul 28th TCT Select Flight Invite East 2019
24 Brickhouse Win 13-10 1896.35 Jul 28th TCT Select Flight Invite East 2019
8 GOAT Win 13-7 2554.76 Jul 28th TCT Select Flight Invite East 2019
53 Ghost Train Win 11-7 1777.75 Sep 7th Washington Mens Club Sectional Championship 2019
- Waste Management Squad** Win 11-3 1214.59 Ignored Sep 7th Washington Mens Club Sectional Championship 2019
89 SOUF** Win 11-1 1705.59 Ignored Sep 7th Washington Mens Club Sectional Championship 2019
71 DNA Win 11-9 1438.22 Sep 7th Washington Mens Club Sectional Championship 2019
83 Seattle Blacklist** Win 15-2 1726.02 Ignored Sep 8th Washington Mens Club Sectional Championship 2019
19 Voodoo Loss 12-15 1435.06 Sep 8th Washington Mens Club Sectional Championship 2019
89 SOUF** Win 15-3 1705.59 Ignored Sep 8th Washington 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)