#71 Jackwagon (5-13)

avg: 497.72  •  sd: 66.12  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
- Molly Blue** Loss 5-15 715.87 Jun 24th Colorado Summer Solstice 2023
85 Colorado Cutthroat: Youth Club U-20 Girls Loss 6-7 128.81 Jun 24th Colorado Summer Solstice 2023
49 Trainwreck Loss 4-11 334.06 Jun 24th Colorado Summer Solstice 2023
20 Wildfire** Loss 3-11 960.61 Ignored Jul 15th TCT Select Flight West 2023
45 Rampage Loss 6-11 427.05 Jul 15th TCT Select Flight West 2023
100 Just Add Water Win 9-5 347.91 Jul 15th TCT Select Flight West 2023
68 Venom Loss 6-9 136.93 Jul 16th TCT Select Flight West 2023
38 FAB** Loss 3-11 519.26 Ignored Jul 16th TCT Select Flight West 2023
87 Haboob Win 10-6 652.87 Jul 16th TCT Select Flight West 2023
25 Colorado Small Batch** Loss 4-13 859.47 Ignored Sep 9th 2023 Womens Rocky Mountain Sectional Championship
70 COSMOS Loss 5-10 -71.58 Sep 9th 2023 Womens Rocky Mountain Sectional Championship
49 Trainwreck Loss 1-13 334.06 Sep 9th 2023 Womens Rocky Mountain Sectional Championship
85 Colorado Cutthroat: Youth Club U-20 Girls Win 10-5 827.71 Sep 9th 2023 Womens Rocky Mountain Sectional Championship
32 Crush City Loss 5-11 713.39 Sep 23rd 2023 South Central Womens Regional
40 Hayride Loss 4-6 712.13 Sep 23rd 2023 South Central Womens Regional
64 TWISTED Loss 5-7 361.6 Sep 23rd 2023 South Central Womens Regional
82 Venom Win 10-6 774.83 Sep 24th 2023 South Central Womens Regional
91 Firewheel Win 15-2 674.38 Sep 24th 2023 South Central Womens Regional
**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)