#39 Brooklyn Book Club (16-9)

avg: 1083.2  •  sd: 60.31  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
42 Wave Loss 9-10 912.44 Jun 24th Scuffletown Throwdown 2023
37 Agency Loss 5-13 549.08 Jun 24th Scuffletown Throwdown 2023
65 Warhawks Win 13-8 1152.89 Jun 24th Scuffletown Throwdown 2023
55 Shiver Win 11-8 1236.26 Jun 24th Scuffletown Throwdown 2023
59 Virginia Rebellion Win 8-4 1300.03 Jun 25th Scuffletown Throwdown 2023
94 Dissent** Win 12-3 626.69 Ignored Jun 25th Scuffletown Throwdown 2023
55 Shiver Win 7-4 1366.81 Jun 25th Scuffletown Throwdown 2023
86 Versa** Win 13-2 763.15 Ignored Jul 15th Boston Invite 2023
- Tempest Win 13-4 1121.64 Jul 15th Boston Invite 2023
24 Sage Loss 4-12 883.57 Jul 15th Boston Invite 2023
83 Autonomous** Win 15-3 876.44 Ignored Jul 29th TCT Select Flight East 2023
66 Banshee Win 9-7 905.3 Jul 29th TCT Select Flight East 2023
31 Rival Win 8-7 1491.44 Jul 29th TCT Select Flight East 2023
34 Indy Rogue Loss 10-12 948.21 Jul 30th TCT Select Flight East 2023
54 Stellar Win 12-7 1397.45 Jul 30th TCT Select Flight East 2023
32 Crush City Loss 7-14 730.51 Jul 30th TCT Select Flight East 2023
7 BENT** Loss 5-15 1531.43 Ignored Sep 9th 2023 Womens Metro NY Sectional Championship
- Remember When Win 15-9 1071.78 Sep 9th 2023 Womens Metro NY Sectional Championship
95 Ignite** Win 15-4 624.41 Ignored Sep 9th 2023 Womens Metro NY Sectional Championship
8 6ixers** Loss 4-13 1505.93 Ignored Sep 23rd 2023 Northeast Womens Regional Championship
69 PLOW Win 13-7 1098.08 Sep 23rd 2023 Northeast Womens Regional Championship
74 Frolic Win 14-9 932.6 Sep 23rd 2023 Northeast Womens Regional Championship
5 Brute Squad** Loss 3-15 1702.83 Ignored Sep 23rd 2023 Northeast Womens Regional Championship
47 Vice Win 11-7 1415.15 Sep 24th 2023 Northeast Womens Regional Championship
22 Siege Loss 9-15 1026 Sep 24th 2023 Northeast Womens Regional Championship
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)