#33 Freaks (19-7)

avg: 1499.59  •  sd: 57.92  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
81 Bullet Win 12-5 1726.43 Jun 15th ATL Classic 2019
126 Rougaroux Win 13-3 1505.03 Jun 15th ATL Classic 2019
120 Rush Hour ATL Win 13-7 1504.86 Jun 15th ATL Classic 2019
86 ATLiens Win 13-7 1672.47 Jun 15th ATL Classic 2019
81 Bullet Win 11-10 1251.43 Jun 16th ATL Classic 2019
49 El Niño Loss 11-12 1222.98 Jun 16th ATL Classic 2019
139 Space Cowboys** Win 11-3 1434.13 Ignored Jul 6th Huntsville Huckfest 2019
37 Lost Boys Loss 4-11 861.09 Jul 6th Huntsville Huckfest 2019
120 Rush Hour ATL Win 11-4 1547.33 Jul 6th Huntsville Huckfest 2019
202 War Machine** Win 11-3 1036.17 Ignored Jul 6th Huntsville Huckfest 2019
212 Gentlemen's Club** Win 11-1 984.5 Ignored Jul 7th Huntsville Huckfest 2019
192 Trent's Team Win 11-5 1118.85 Jul 7th Huntsville Huckfest 2019
106 H.O.G. Ultimate Win 15-10 1460.73 Jul 7th Huntsville Huckfest 2019
35 Tanasi Win 15-6 2073.63 Jul 7th Huntsville Huckfest 2019
2 Truck Stop Loss 8-15 1604.76 Aug 2nd 2019 US Open Club Championship
3 PoNY Loss 8-15 1603.21 Aug 2nd 2019 US Open Club Championship
7 Chicago Machine Win 14-13 2133.98 Aug 3rd 2019 US Open Club Championship
10 DiG Loss 7-15 1367.04 Aug 17th TCT Elite Select Challenge 2019
11 Johnny Bravo Loss 8-15 1333.9 Aug 17th TCT Elite Select Challenge 2019
30 Black Market I Loss 11-13 1306.54 Aug 17th TCT Elite Select Challenge 2019
63 Guerrilla Win 9-8 1382.1 Aug 18th TCT Elite Select Challenge 2019
202 War Machine** Win 13-3 1036.17 Ignored Sep 7th Gulf Coast Mens Club Sectional Championship 2019
223 Traffic** Win 13-1 862.59 Ignored Sep 7th Gulf Coast Mens Club Sectional Championship 2019
126 Rougaroux Win 13-7 1462.56 Sep 7th Gulf Coast Mens Club Sectional Championship 2019
168 Barefoot** Win 13-3 1273.23 Ignored Sep 7th Gulf Coast Mens Club Sectional Championship 2019
66 Ironmen Win 11-7 1695.05 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)