#211 Stackcats (7-18)

avg: 518.98  •  sd: 61.27  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
38 Columbus Cocktails** Loss 4-11 900.3 Ignored Jul 7th Motown Throwdown 2018
171 North Coast Loss 6-11 204.02 Jul 7th Motown Throwdown 2018
134 Petey's Pirates Loss 2-11 357.75 Jul 7th Motown Throwdown 2018
172 Los Heros Loss 8-9 619.78 Jul 7th Motown Throwdown 2018
196 Thunderpants the Magic Dragon Loss 9-15 78.98 Jul 8th Motown Throwdown 2018
223 Petey's Scallywags Win 11-10 485.69 Jul 8th Motown Throwdown 2018
186 Jabba Loss 10-12 412.07 Jul 8th Motown Throwdown 2018
185 Boomtown Pandas Loss 6-10 154.35 Aug 4th Heavyweights 2018
186 Jabba Win 11-10 775.2 Aug 4th Heavyweights 2018
97 tHUMP** Loss 5-13 539.88 Ignored Aug 4th Heavyweights 2018
217 Mastodon Loss 8-9 358.04 Aug 5th Heavyweights 2018
230 EDM Win 13-4 904.08 Aug 5th Heavyweights 2018
235 Skyhawks Win 13-2 844.51 Aug 5th Heavyweights 2018
233 ALTimate Brews Loss 9-13 -130.21 Aug 18th Cooler Classic 30
146 Prion Loss 9-10 760.02 Aug 18th Cooler Classic 30
145 Pandamonium Loss 12-13 760.38 Aug 18th Cooler Classic 30
249 LudICRous** Win 12-5 379.2 Ignored Aug 18th Cooler Classic 30
233 ALTimate Brews Win 15-6 888.36 Aug 19th Cooler Classic 30
191 Coalition Ultimate Loss 13-14 494.68 Aug 19th Cooler Classic 30
229 Pushovers-C Win 15-8 883.08 Aug 19th Cooler Classic 30
146 Prion Loss 5-13 285.02 Sep 8th Central Plains Mixed Sectional Championship 2018
68 Nothing's Great Again Loss 6-13 681.31 Sep 8th Central Plains Mixed Sectional Championship 2018
137 ELevate Loss 3-12 341.87 Sep 8th Central Plains Mixed Sectional Championship 2018
77 Tequila Mockingbird** Loss 4-10 652.9 Ignored Sep 8th Central Plains Mixed Sectional Championship 2018
172 Los Heros Loss 10-12 506.66 Sep 9th Central Plains Mixed Sectional Championship 2018
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)