#66 Hot Metal (6-21)

avg: 719.64  •  sd: 56.59  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
- PPF Win 12-6 864.13 Jun 1st New York Warmup Womens Sanctioned Games 2019
98 DINO** Win 15-0 425.45 Ignored Jun 2nd New York Warmup Womens Sanctioned Games 2019
52 TOX6ix Loss 8-11 612.59 Jun 2nd New York Warmup Womens Sanctioned Games 2019
16 Iris** Loss 5-14 1151.91 Ignored Jun 2nd New York Warmup Womens Sanctioned Games 2019
54 Venus Loss 8-12 515.58 Jun 22nd Boston Invite 2019
41 Vice Loss 5-13 575.88 Jun 22nd Boston Invite 2019
19 BENT** Loss 6-15 1093.55 Ignored Jun 22nd Boston Invite 2019
16 Iris** Loss 2-13 1151.91 Ignored Jun 22nd Boston Invite 2019
79 Versa Win 13-6 991.03 Jun 23rd Boston Invite 2019
48 Brooklyn Book Club Loss 8-13 586.02 Jun 23rd Boston Invite 2019
44 Tempest Loss 8-14 608.24 Jun 23rd Boston Invite 2019
73 Ignite Loss 7-10 227.06 Jun 23rd Boston Invite 2019
30 Colorado Small Batch** Loss 5-12 797.71 Ignored Jul 27th TCT Select Flight Invite East 2019
55 Dish Win 13-8 1371.84 Jul 27th TCT Select Flight Invite East 2019
39 Stella Loss 5-13 611.9 Jul 27th TCT Select Flight Invite East 2019
20 Pop** Loss 5-13 1033.37 Ignored Jul 27th TCT Select Flight Invite East 2019
38 FAB Loss 9-10 1090.76 Jul 28th TCT Select Flight Invite East 2019
46 Indy Rogue Loss 7-13 542.63 Jul 28th TCT Select Flight Invite East 2019
41 Vice Loss 6-13 575.88 Aug 10th Chesapeake Open 2019
69 Broad City Loss 6-10 164.52 Aug 10th Chesapeake Open 2019
40 Pine Baroness Loss 10-12 970.92 Aug 10th Chesapeake Open 2019
26 Virginia Rebellion Loss 11-15 1066.54 Aug 11th Chesapeake Open 2019
58 Agency Loss 11-13 632.89 Aug 11th Chesapeake Open 2019
69 Broad City Win 9-8 785.68 Aug 11th Chesapeake Open 2019
69 Broad City Win 12-10 898.81 Sep 7th Founders Womens Club Sectional Championship 2019
65 Eliza Furnace Loss 10-11 600.78 Sep 7th Founders Womens Club Sectional Championship 2019
40 Pine Baroness Loss 7-15 609.04 Sep 7th Founders 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)