#61 Notorious C.L.E. (7-13)

avg: 596.45  •  sd: 69.51  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
42 Pine Baroness Loss 5-15 422.63 Jul 14th Old Line Classic 2018
64 Suffrage Win 9-8 632.05 Jul 14th Old Line Classic 2018
53 Backhanded Loss 4-15 130.82 Jul 14th Old Line Classic 2018
79 DINO** Win 14-4 123.43 Ignored Jul 14th Old Line Classic 2018
67 Broad City Win 13-11 665.76 Jul 15th Old Line Classic 2018
- DC Rogue Win 10-8 475.39 Jul 15th Old Line Classic 2018
29 Virginia Rebellion** Loss 4-13 756.45 Ignored Aug 11th Chesapeake Open 2018
45 Outbreak Loss 9-13 485.21 Aug 11th Chesapeake Open 2018
56 Brooklyn Book Club Loss 6-11 146.91 Aug 11th Chesapeake Open 2018
35 Hot Metal Loss 5-13 537.96 Aug 11th Chesapeake Open 2018
53 Backhanded Loss 8-10 468.15 Aug 12th Chesapeake Open 2018
56 Brooklyn Book Club Loss 8-13 197.45 Aug 12th Chesapeake Open 2018
55 Sureshot Loss 9-12 349.27 Sep 15th East Plains Womens Sectional Championship 2018
75 Autonomous Win 13-1 735.98 Sep 15th East Plains Womens Sectional Championship 2018
57 Helix Win 15-11 1053.57 Sep 22nd Great Lakes Womens Regional Championship 2018
55 Sureshot Loss 9-10 569.64 Sep 22nd Great Lakes Womens Regional Championship 2018
31 Indy Rogue Loss 6-13 603.99 Sep 22nd Great Lakes Womens Regional Championship 2018
10 Nemesis** Loss 2-13 1224.48 Ignored Sep 22nd Great Lakes Womens Regional Championship 2018
55 Sureshot Win 14-8 1230.67 Sep 23rd Great Lakes Womens Regional Championship 2018
31 Indy Rogue Loss 11-15 822.83 Sep 23rd Great Lakes Womens Regional 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)