#48 Wild Card (10-11)

avg: 1441.83  •  sd: 45.64  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
16 'Shine Loss 12-15 1520.13 Jun 24th FROGS
49 Jughandle Loss 13-15 1192.59 Jun 24th FROGS
70 League of Shadows Loss 11-13 1018.16 Jun 24th FROGS
6 XIST Loss 5-15 1414.52 Jun 24th FROGS
40 Pittsburgh Port Authority Loss 12-14 1307.95 Jun 25th FROGS
14 Slow Loss 4-13 1224.04 Jul 15th Boston Invite 2023
57 Greater Baltimore Anthem Win 11-9 1567.35 Jul 15th Boston Invite 2023
68 Heat Wave Win 9-8 1383.05 Jul 15th Boston Invite 2023
70 League of Shadows Win 10-7 1636.67 Jul 15th Boston Invite 2023
9 Red Flag Loss 4-13 1341.57 Aug 26th Northwest Fruit Bowl 2023
47 Donuts Win 13-12 1568.38 Aug 26th Northwest Fruit Bowl 2023
41 BW Ultimate Loss 10-11 1375.27 Aug 26th Northwest Fruit Bowl 2023
26 Loco Loss 8-13 1200.37 Aug 26th Northwest Fruit Bowl 2023
41 BW Ultimate Loss 9-12 1154.91 Aug 27th Northwest Fruit Bowl 2023
54 Lights Out Win 13-12 1468.13 Aug 27th Northwest Fruit Bowl 2023
199 Rainbow** Win 13-4 1154.13 Ignored Sep 9th 2023 Mixed East New England Sectional Championship
45 Darkwing Win 15-9 1973.61 Sep 9th 2023 Mixed East New England Sectional Championship
76 Obscure Win 13-7 1749.18 Sep 9th 2023 Mixed East New England Sectional Championship
70 League of Shadows Win 11-10 1372 Sep 9th 2023 Mixed East New England Sectional Championship
8 Sprocket Loss 8-15 1386.08 Sep 10th 2023 Mixed East New England Sectional Championship
52 The Buoy Association Win 13-11 1612.38 Sep 10th 2023 Mixed East New England Sectional 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)