#153 APEX (10-11)

avg: 853.35  •  sd: 99.86  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
79 8 Bit Heroes Loss 7-12 722.7 Jun 23rd Summer Glazed Daze 2018
219 Carolina Reign Win 13-6 1025.47 Jun 23rd Summer Glazed Daze 2018
18 Loco Loss 10-13 1406.26 Jun 23rd Summer Glazed Daze 2018
54 JLP Loss 6-13 725.88 Jun 23rd Summer Glazed Daze 2018
156 Heavy Flow Win 9-0 1439.56 Jun 24th Summer Glazed Daze 2018
78 Malice in Wonderland Loss 6-13 643.54 Jun 24th Summer Glazed Daze 2018
224 Stormborn Win 13-9 776.02 Jun 24th Summer Glazed Daze 2018
176 ThunderCats Win 13-7 1263.86 Jun 24th Summer Glazed Daze 2018
207 District Cocktails Win 10-9 660.79 Jul 21st SunRise Open 2018
95 Ant Madness Loss 4-13 547.28 Jul 21st SunRise Open 2018
243 SPACE INVADERS** Win 13-2 620.63 Ignored Jul 21st SunRise Open 2018
156 Heavy Flow Loss 9-13 420.99 Jul 22nd SunRise Open 2018
132 HVAC Loss 8-13 466.37 Jul 22nd SunRise Open 2018
63 Rowdy Loss 5-15 688.72 Jul 22nd SunRise Open 2018
56 Murmur Loss 5-10 747.27 Sep 8th East Coast Mixed Sectional Championship 2018
188 Hairy Otter Win 10-9 766.26 Sep 8th East Coast Mixed Sectional Championship 2018
238 Strictly Bidness** Win 13-5 787.41 Ignored Sep 8th East Coast Mixed Sectional Championship 2018
151 LoveShack Win 12-9 1201.8 Sep 8th East Coast Mixed Sectional Championship 2018
84 'Shine Loss 6-12 642.15 Sep 9th East Coast Mixed Sectional Championship 2018
54 JLP Loss 9-13 907.31 Sep 9th East Coast Mixed Sectional Championship 2018
177 OutKast Win 11-5 1297.14 Sep 9th East Coast 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)