#64 Suffrage (9-16)

avg: 507.05  •  sd: 75.51  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
41 Frolic Win 14-13 1164.54 Jun 23rd Boston Invite 2018
56 Brooklyn Book Club Loss 8-9 568.61 Jun 23rd Boston Invite 2018
- Tempest Loss 13-15 463.8 Jun 23rd Boston Invite 2018
- Salt City Spirit Win 15-10 350.4 Jun 24th Boston Invite 2018
67 Broad City Win 11-10 561.92 Jun 24th Boston Invite 2018
- Tempest Loss 3-15 77.98 Jun 24th Boston Invite 2018
67 Broad City Win 10-9 561.92 Jul 14th Old Line Classic 2018
79 DINO** Win 13-5 123.43 Ignored Jul 14th Old Line Classic 2018
61 Notorious C.L.E. Loss 8-9 471.45 Jul 14th Old Line Classic 2018
42 Pine Baroness Loss 8-13 526.47 Jul 15th Old Line Classic 2018
53 Backhanded Loss 9-14 256.95 Jul 15th Old Line Classic 2018
51 Vice Loss 3-11 195.41 Aug 11th Philly Open 2018
67 Broad City Loss 7-12 -83.59 Aug 11th Philly Open 2018
76 Boomslang Win 13-2 651.28 Aug 11th Philly Open 2018
79 DINO** Win 13-0 123.43 Ignored Aug 11th Philly Open 2018
29 Virginia Rebellion** Loss 3-15 756.45 Ignored Sep 8th Capital Womens Sectional Championship 2018
17 Grit** Loss 1-15 1122.02 Ignored Sep 8th Capital Womens Sectional Championship 2018
53 Backhanded Win 11-8 1096.43 Sep 8th Capital Womens Sectional Championship 2018
17 Grit** Loss 3-13 1122.02 Ignored Sep 22nd Mid Atlantic Womens Regional Championship 2018
42 Pine Baroness Loss 7-13 465.1 Sep 22nd Mid Atlantic Womens Regional Championship 2018
67 Broad City Win 13-9 855.48 Sep 22nd Mid Atlantic Womens Regional Championship 2018
35 Hot Metal** Loss 4-13 537.96 Ignored Sep 22nd Mid Atlantic Womens Regional Championship 2018
43 Green Means Go Loss 4-14 396.6 Sep 23rd Mid Atlantic Womens Regional Championship 2018
5 Scandal** Loss 3-15 1503.1 Ignored Sep 23rd Mid Atlantic Womens Regional Championship 2018
53 Backhanded Loss 8-11 365.21 Sep 23rd Mid Atlantic 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)