#6 Revolver (16-5)

avg: 2038.57  •  sd: 60.69  •  top 16/20: 100%

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# Opponent Result Game Rating Status Date Event
14 Chain Lightning Win 13-12 1943.1 Jul 13th TCT Pro Elite Challenge 2019
5 Chicago Machine Win 13-11 2315.95 Jul 13th TCT Pro Elite Challenge 2019
19 Voodoo Win 13-11 1920.03 Jul 13th TCT Pro Elite Challenge 2019
5 Chicago Machine Win 13-9 2505.68 Jul 14th TCT Pro Elite Challenge 2019
12 Doublewide Loss 11-13 1626.67 Jul 14th TCT Pro Elite Challenge 2019
15 Rhino Slam! Win 13-7 2375.12 Jul 14th TCT Pro Elite Challenge 2019
7 Sub Zero Win 15-11 2366.87 Aug 2nd 2019 US Open Club Championship
3 Ring of Fire Loss 11-15 1787.83 Aug 3rd 2019 US Open Club Championship
109 Green River Swordfish** Win 11-4 1612.08 Ignored Sep 21st Southwest Club Mens Regional Championship 2019
70 Sundowners** Win 11-3 1828.1 Ignored Sep 21st Southwest Club Mens Regional Championship 2019
61 Battery Win 11-6 1825.99 Sep 21st Southwest Club Mens Regional Championship 2019
119 DOGGPOUND** Win 11-1 1537.89 Ignored Sep 21st Southwest Club Mens Regional Championship 2019
9 SoCal Condors Win 13-10 2222.08 Sep 22nd Southwest Club Mens Regional Championship 2019
55 OAT** Win 13-5 1921.73 Ignored Sep 22nd Southwest Club Mens Regional Championship 2019
3 Ring of Fire Loss 9-15 1653.51 Oct 24th USA Ultimate National Championships 2019
12 Doublewide Win 15-14 1980.51 Oct 24th USA Ultimate National Championships 2019
15 Rhino Slam! Win 15-10 2271.19 Oct 24th USA Ultimate National Championships 2019
7 Sub Zero Win 15-12 2286.2 Oct 25th USA Ultimate National Championships 2019
5 Chicago Machine Loss 13-15 1872.93 Oct 25th USA Ultimate National Championships 2019
9 SoCal Condors Win 15-13 2108.12 Oct 25th USA Ultimate National Championships 2019
2 Truck Stop Loss 12-15 1880.53 Oct 26th USA Ultimate National Championships 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)