#43 Birdfruit (14-12)

avg: 1517.79  •  sd: 60.12  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
82 Pegasus Win 11-4 1845.6 Jun 15th Northwest Mixer 2019
87 Garbage Win 12-10 1443.49 Jun 15th Northwest Mixer 2019
28 Lights Out Win 11-7 2110.5 Jun 15th Northwest Mixer 2019
11 Lochsa Loss 8-10 1621.08 Jun 15th Northwest Mixer 2019
3 Seattle Mixtape Loss 2-11 1483.72 Jun 15th Northwest Mixer 2019
31 XIST Win 12-9 1971.29 Jul 13th TCT Pro Elite Challenge 2019
12 Blackbird Loss 9-13 1461.16 Jul 13th TCT Pro Elite Challenge 2019
18 Columbus Cocktails Loss 11-12 1637.6 Jul 13th TCT Pro Elite Challenge 2019
7 Mischief Loss 7-10 1537.85 Jul 14th TCT Pro Elite Challenge 2019
20 Polar Bears Loss 6-10 1259.9 Jul 14th TCT Pro Elite Challenge 2019
32 NOISE Loss 10-11 1486.8 Jul 14th TCT Pro Elite Challenge 2019
52 Mesteño Win 13-12 1566.75 Aug 17th Northwest Fruit Bowl 2019
26 Public Enemy Loss 7-12 1177.78 Aug 17th Northwest Fruit Bowl 2019
19 The Chad Larson Experience Loss 11-12 1634.72 Aug 17th Northwest Fruit Bowl 2019
24 MOONDOG Loss 6-13 1110.43 Aug 17th Northwest Fruit Bowl 2019
29 Lotus Loss 8-13 1146.92 Aug 18th Northwest Fruit Bowl 2019
51 Minnesota Star Power Win 11-10 1584.03 Aug 18th Northwest Fruit Bowl 2019
52 Mesteño Win 13-4 2041.75 Aug 18th Northwest Fruit Bowl 2019
82 Pegasus Loss 7-11 778.7 Sep 7th Washington Mixed Club Sectional Championship 2019
121 Bulleit Train Win 11-4 1685.56 Sep 7th Washington Mixed Club Sectional Championship 2019
114 Surge Win 11-4 1708.9 Sep 7th Washington Mixed Club Sectional Championship 2019
188 Seven Hills** Win 11-2 1323.52 Ignored Sep 7th Washington Mixed Club Sectional Championship 2019
245 Mola Mola** Win 11-0 1053.96 Ignored Sep 7th Washington Mixed Club Sectional Championship 2019
82 Pegasus Win 11-10 1370.6 Sep 8th Washington Mixed Club Sectional Championship 2019
152 Fable Win 14-8 1458.05 Sep 8th Washington Mixed Club Sectional Championship 2019
87 Garbage Win 14-7 1788.25 Sep 8th Washington Mixed 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)