#101 Tyrannis (16-8)

avg: 1112.39  •  sd: 75.83  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
42 Mixfits Win 11-10 1599.53 Jun 23rd Summer Glazed Daze 2018
41 Storm Win 10-9 1604.16 Jun 23rd Summer Glazed Daze 2018
63 Rowdy Loss 8-11 923.11 Jun 23rd Summer Glazed Daze 2018
224 Stormborn** Win 13-3 957.45 Ignored Jun 23rd Summer Glazed Daze 2018
212 Mixed Results Win 13-4 1114.05 Jun 24th Summer Glazed Daze 2018
56 Murmur Win 12-10 1559.29 Jun 24th Summer Glazed Daze 2018
100 FlyTrap Loss 12-14 893.41 Jun 24th Summer Glazed Daze 2018
18 Loco** Loss 3-15 1134.4 Ignored Jun 24th Summer Glazed Daze 2018
149 Crucible Win 13-4 1479.71 Aug 11th Chesapeake Open 2018
144 Rat City Win 11-6 1437.26 Aug 11th Chesapeake Open 2018
163 Stoke Win 10-3 1396.61 Aug 11th Chesapeake Open 2018
95 Ant Madness Loss 9-12 801.91 Aug 11th Chesapeake Open 2018
179 LORD Win 12-8 1122.37 Aug 12th Chesapeake Open 2018
114 Buffalo Lake Effect Win 11-6 1588.43 Aug 12th Chesapeake Open 2018
126 American Hyperbole Win 11-8 1347.87 Aug 12th Chesapeake Open 2018
156 Heavy Flow Win 11-6 1386.26 Sep 8th Capital Mixed Sectional Championship 2018
95 Ant Madness Loss 5-7 819.14 Sep 8th Capital Mixed Sectional Championship 2018
179 LORD Win 11-5 1281.22 Sep 8th Capital Mixed Sectional Championship 2018
239 Pandatime** Win 11-2 767.17 Ignored Sep 8th Capital Mixed Sectional Championship 2018
232 Baltimore BENCH** Win 11-1 889.24 Ignored Sep 8th Capital Mixed Sectional Championship 2018
- Fireball Loss 6-10 730.34 Sep 9th Capital Mixed Sectional Championship 2018
132 HVAC Loss 6-12 383.22 Sep 9th Capital Mixed Sectional Championship 2018
173 Fake Newport News Loss 7-9 462.23 Sep 9th Capital Mixed Sectional Championship 2018
156 Heavy Flow Win 10-9 964.56 Sep 9th Capital Mixed Sectional Championship 2018
**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)