#270 Baltimore BENCH (4-21)

avg: 292.64  •  sd: 65.23  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
223 District Cocktails Loss 6-12 8.6 Jul 13th Battle for the Beltway 2019
191 LORD Loss 7-13 156.37 Jul 13th Battle for the Beltway 2019
291 Swing Vote Win 10-5 521.81 Jul 13th Battle for the Beltway 2019
85 HVAC** Loss 4-13 631.84 Ignored Jul 13th Battle for the Beltway 2019
237 Stormborn Loss 9-14 7.77 Jul 14th Battle for the Beltway 2019
216 Espionage Loss 4-15 18.95 Jul 14th Battle for the Beltway 2019
94 Soft Boiled** Loss 2-13 581.95 Ignored Aug 3rd Philly Open 2019
178 Mashed Loss 10-11 654.24 Aug 3rd Philly Open 2019
96 Birds** Loss 2-13 578.39 Ignored Aug 3rd Philly Open 2019
191 LORD Loss 10-15 260.3 Aug 4th Philly Open 2019
237 Stormborn Loss 11-13 252.8 Aug 4th Philly Open 2019
269 Tropics Ultimate Loss 8-9 168.3 Aug 4th Philly Open 2019
115 Rat City** Loss 1-13 505.67 Ignored Aug 24th The Incident 2019 Age of Ultimatron
266 I-79 Loss 7-9 36.13 Aug 24th The Incident 2019 Age of Ultimatron
86 Eat Lightning** Loss 2-13 621.84 Ignored Aug 24th The Incident 2019 Age of Ultimatron
142 Philly Twist** Loss 2-13 352.29 Ignored Aug 24th The Incident 2019 Age of Ultimatron
264 Albany Airbenders Win 12-6 911.16 Aug 25th The Incident 2019 Age of Ultimatron
293 Turnstyle Win 11-5 439.57 Aug 25th The Incident 2019 Age of Ultimatron
199 HAOS Loss 4-11 96.95 Aug 25th The Incident 2019 Age of Ultimatron
242 RnB Loss 7-13 -92.46 Sep 7th Capital Mixed Club Sectional Championship 2019
23 Rally** Loss 0-13 1111.34 Ignored Sep 7th Capital Mixed Club Sectional Championship 2019
90 Fleet Loss 7-12 676.63 Sep 7th Capital Mixed Club Sectional Championship 2019
115 Rat City** Loss 4-13 505.67 Ignored Sep 7th Capital Mixed Club Sectional Championship 2019
281 Nottoway Flatball Club Win 13-8 681.12 Sep 8th Capital Mixed Club Sectional Championship 2019
237 Stormborn Loss 8-13 -14.52 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)