#52 TOX6ix (6-7)

avg: 978.2  •  sd: 72.56  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
98 DINO** Win 15-0 425.45 Ignored Jun 1st New York Warmup Womens Sanctioned Games 2019
- PPF** Win 15-6 884.82 Ignored Jun 1st New York Warmup Womens Sanctioned Games 2019
66 Hot Metal Win 11-8 1085.25 Jun 2nd New York Warmup Womens Sanctioned Games 2019
42 Frolic Loss 10-13 836.71 Jun 22nd Boston Invite 2019
11 Siege** Loss 2-13 1313.69 Ignored Jun 22nd Boston Invite 2019
40 Pine Baroness Loss 6-13 609.04 Jun 22nd Boston Invite 2019
37 Vintage Loss 8-13 720.09 Jun 22nd Boston Invite 2019
54 Venus Win 11-10 1081.73 Jun 23rd Boston Invite 2019
58 Agency Win 10-8 1124.4 Jun 23rd Boston Invite 2019
24 Salty Loss 9-14 989.83 Jun 23rd Boston Invite 2019
39 Stella Loss 9-12 866.54 Sep 7th Upstate New York Womens Club Sectional Championship 2019
43 Rebel Rebel Win 11-9 1400.08 Sep 7th Upstate New York Womens Club Sectional Championship 2019
43 Rebel Rebel Loss 9-11 901.66 Sep 7th Upstate New York Womens Club Sectional Championship 2019
**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)