#190 LORD (11-13)

avg: 665.35  •  sd: 56.32  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
160 APEX Win 13-6 1428.62 Jun 22nd Summer Glazed Daze 2019
102 Tyrannis Loss 9-13 693.61 Jun 22nd Summer Glazed Daze 2019
173 Piedmont United Win 13-7 1315.16 Jun 22nd Summer Glazed Daze 2019
77 Ant Madness Loss 6-12 642.3 Jun 23rd Summer Glazed Daze 2019
221 District Cocktails Win 10-7 933.4 Jun 23rd Summer Glazed Daze 2019
165 Possum Loss 7-13 247.99 Jun 23rd Summer Glazed Daze 2019
267 Baltimore BENCH Win 13-7 809.07 Jul 13th Battle for the Beltway 2019
89 HVAC Loss 8-13 656.3 Jul 13th Battle for the Beltway 2019
221 District Cocktails Win 9-8 668.74 Jul 13th Battle for the Beltway 2019
291 Swing Vote** Win 13-3 508.67 Ignored Jul 13th Battle for the Beltway 2019
102 Tyrannis Loss 7-14 529.29 Jul 14th Battle for the Beltway 2019
128 Legion Loss 10-12 753.53 Jul 14th Battle for the Beltway 2019
153 Buffalo Lake Effect Loss 3-13 259.03 Aug 3rd Philly Open 2019
92 The Bandits Loss 9-13 715.79 Aug 3rd Philly Open 2019
209 TBD Loss 9-13 183.04 Aug 3rd Philly Open 2019
271 Tropics Ultimate Win 11-8 608.32 Aug 3rd Philly Open 2019
267 Baltimore BENCH Win 15-10 705.15 Aug 4th Philly Open 2019
232 Buffalo Brain Freeze Win 11-6 999.77 Aug 4th Philly Open 2019
62 8 Bit Heroes** Loss 2-13 688.07 Ignored Sep 7th Capital Mixed Club Sectional Championship 2019
77 Ant Madness Loss 3-13 621.61 Sep 7th Capital Mixed Club Sectional Championship 2019
215 Espionage Loss 11-12 453.33 Sep 7th Capital Mixed Club Sectional Championship 2019
274 WhirlyNegs Win 13-8 709.44 Sep 7th Capital Mixed Club Sectional Championship 2019
102 Tyrannis Loss 7-15 512.17 Sep 8th Capital Mixed Club Sectional Championship 2019
242 Pandatime Win 15-12 712.51 Sep 8th Capital 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)