#233 Stormborn (8-17)

avg: 450.35  •  sd: 52.8  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
136 Crucible Loss 6-13 331.51 Jun 22nd Summer Glazed Daze 2019
236 RnB Loss 7-13 -124.5 Jun 22nd Summer Glazed Daze 2019
74 Petey's Pirates** Loss 5-13 629.88 Ignored Jun 22nd Summer Glazed Daze 2019
100 NC Galaxy Loss 7-13 558.87 Jun 23rd Summer Glazed Daze 2019
136 Crucible Loss 3-13 331.51 Jun 23rd Summer Glazed Daze 2019
160 APEX Loss 6-9 410.05 Jun 23rd Summer Glazed Daze 2019
273 Rampage Win 13-7 789.56 Jun 23rd Summer Glazed Daze 2019
215 Espionage Win 10-8 841 Jul 13th Battle for the Beltway 2019
102 Tyrannis** Loss 5-13 512.17 Ignored Jul 13th Battle for the Beltway 2019
128 Legion Loss 3-13 391.65 Jul 13th Battle for the Beltway 2019
267 Baltimore BENCH Win 14-9 725.41 Jul 14th Battle for the Beltway 2019
221 District Cocktails Loss 8-11 178.13 Jul 14th Battle for the Beltway 2019
291 Swing Vote Win 12-8 349.82 Jul 14th Battle for the Beltway 2019
91 Garbage Plates** Loss 4-13 535.45 Ignored Aug 3rd Philly Open 2019
179 Unlimited Swipes Loss 10-11 598.99 Aug 3rd Philly Open 2019
242 Pandatime Win 13-10 740.16 Aug 3rd Philly Open 2019
144 Philly Twist Loss 4-13 292.41 Aug 3rd Philly Open 2019
267 Baltimore BENCH Win 13-11 480.38 Aug 4th Philly Open 2019
232 Buffalo Brain Freeze Loss 10-13 124.94 Aug 4th Philly Open 2019
106 Fireball Loss 9-11 846.44 Sep 7th Capital Mixed Club Sectional Championship 2019
128 Legion Loss 1-13 391.65 Sep 7th Capital Mixed Club Sectional Championship 2019
242 Pandatime Loss 6-11 -134.68 Sep 7th Capital Mixed Club Sectional Championship 2019
55 Sparkle Ponies** Loss 5-13 741.29 Ignored Sep 7th Capital Mixed Club Sectional Championship 2019
267 Baltimore BENCH Win 13-8 747.7 Sep 8th Capital Mixed Club Sectional Championship 2019
274 WhirlyNegs Win 12-10 451.41 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)