#247 Pandatime (4-16)

avg: 447.97  •  sd: 71.5  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
173 Alt Stacks Loss 3-13 192.17 Jul 13th Ow My Knee
180 Varsity Loss 8-11 407.16 Jul 13th Ow My Knee
237 Stormborn Loss 10-13 153.5 Aug 3rd Philly Open 2019
91 Garbage Plates** Loss 2-13 596.12 Ignored Aug 3rd Philly Open 2019
142 Philly Twist Loss 3-13 352.29 Aug 3rd Philly Open 2019
177 Unlimited Swipes Loss 3-13 180.86 Aug 3rd Philly Open 2019
216 Espionage Loss 8-15 54.14 Aug 4th Philly Open 2019
96 Birds** Loss 3-11 578.39 Ignored Aug 24th The Incident 2019 Age of Ultimatron
264 Albany Airbenders Win 11-7 798.74 Aug 24th The Incident 2019 Age of Ultimatron
112 Stoke** Loss 5-13 513.57 Ignored Aug 24th The Incident 2019 Age of Ultimatron
194 Nautilus Loss 2-13 103.4 Aug 24th The Incident 2019 Age of Ultimatron
177 Unlimited Swipes Loss 4-12 180.86 Aug 25th The Incident 2019 Age of Ultimatron
266 I-79 Win 11-7 782.36 Aug 25th The Incident 2019 Age of Ultimatron
216 Espionage Loss 8-13 122.79 Aug 25th The Incident 2019 Age of Ultimatron
237 Stormborn Win 11-6 1028.33 Sep 7th Capital Mixed Club Sectional Championship 2019
46 Sparkle Ponies** Loss 1-13 890.21 Ignored Sep 7th Capital Mixed Club Sectional Championship 2019
136 Fireball Loss 7-13 443.62 Sep 7th Capital Mixed Club Sectional Championship 2019
131 Legion Loss 1-13 429.65 Sep 7th Capital Mixed Club Sectional Championship 2019
191 LORD Loss 12-15 413.41 Sep 8th Capital Mixed Club Sectional Championship 2019
223 District Cocktails Win 20-0 1187.92 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)