#155 Goose Lee (9-12)

avg: 913.21  •  sd: 67.73  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
132 Liquid Hustle Loss 7-11 556.93 Jul 6th Motown Throwdown 2019
33 Hybrid Loss 7-11 1133.67 Jul 6th Motown Throwdown 2019
236 Skyhawks Win 11-6 1030.63 Jul 6th Motown Throwdown 2019
73 Petey's Pirates Loss 9-12 929.32 Jul 7th Motown Throwdown 2019
132 Liquid Hustle Win 11-6 1570.52 Jul 7th Motown Throwdown 2019
160 EMU Loss 9-13 476.35 Jul 7th Motown Throwdown 2019
182 Rocket LawnChair Win 10-6 1265.86 Jul 7th Motown Throwdown 2019
89 FlyTrap Loss 6-12 621.4 Aug 10th HoDown ShowDown 23 GOAT
103 Tyrannis Win 11-10 1285.03 Aug 10th HoDown ShowDown 23 GOAT
47 Huntsville Outlaws Loss 7-13 915.89 Aug 10th HoDown ShowDown 23 GOAT
175 Moonshine Win 11-9 1031.04 Aug 10th HoDown ShowDown 23 GOAT
165 APEX Loss 8-13 348.95 Aug 11th HoDown ShowDown 23 GOAT
89 FlyTrap Loss 8-9 1075.71 Aug 11th HoDown ShowDown 23 GOAT
40 Murmur** Loss 6-15 940.03 Ignored Aug 11th HoDown ShowDown 23 GOAT
73 Petey's Pirates Loss 11-14 961.35 Sep 7th East Plains Mixed Club Sectional Championship 2019
257 Derby City Thunder Win 13-6 977.02 Sep 7th East Plains Mixed Club Sectional Championship 2019
249 Second Wind Win 13-10 750.96 Sep 7th East Plains Mixed Club Sectional Championship 2019
58 Toast Loss 7-13 827.55 Sep 7th East Plains Mixed Club Sectional Championship 2019
170 Thunderpants the Magic Dragon Loss 10-15 353.58 Sep 8th East Plains Mixed Club Sectional Championship 2019
187 Pixel Win 12-8 1182.11 Sep 8th East Plains Mixed Club Sectional Championship 2019
205 Pi+ Win 15-9 1191.69 Sep 8th East Plains 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)