#27 Underground (18-12)

avg: 1425.92  •  sd: 57.62  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
51 Seven Devils Win 11-1 1507.19 Jun 24th Summer Solstice 2023
33 Seattle END Win 11-2 1874.73 Jun 24th Summer Solstice 2023
77 Portland Rain Check** Win 11-1 1010.41 Ignored Jun 24th Summer Solstice 2023
50 Drift Win 9-6 1333.51 Jun 24th Summer Solstice 2023
28 Oregon Downpour Win 13-3 2008.63 Jun 25th Summer Solstice 2023
9 Schwa** Loss 5-13 1501.71 Ignored Jun 25th Summer Solstice 2023
4 Molly Brown** Loss 3-15 1734.03 Ignored Jul 8th TCT Pro Elite Challenge West 2023
11 Seattle Riot Loss 7-15 1384.62 Jul 8th TCT Pro Elite Challenge West 2023
13 Nightlock Loss 7-11 1364.63 Jul 8th TCT Pro Elite Challenge West 2023
10 Traffic** Loss 2-15 1501.06 Ignored Jul 9th TCT Pro Elite Challenge West 2023
25 Colorado Small Batch Loss 8-10 1196.8 Jul 9th TCT Pro Elite Challenge West 2023
77 Portland Rain Check** Win 15-4 1010.41 Ignored Jul 9th TCT Pro Elite Challenge West 2023
13 Nightlock Loss 6-10 1335.37 Aug 19th TCT Elite Select Challenge 2023
16 Grit Loss 9-11 1440.93 Aug 19th TCT Elite Select Challenge 2023
34 Indy Rogue Win 15-4 1786.34 Aug 19th TCT Elite Select Challenge 2023
25 Colorado Small Batch Win 9-8 1584.47 Aug 20th TCT Elite Select Challenge 2023
30 Tabby Rosa Loss 6-9 965.67 Aug 20th TCT Elite Select Challenge 2023
29 Pop Win 12-11 1527.13 Aug 20th TCT Elite Select Challenge 2023
50 Drift Win 15-7 1514.94 Sep 9th 2023 Womens Washington Sectional Championship
77 Portland Rain Check** Win 15-2 1010.41 Ignored Sep 9th 2023 Womens Washington Sectional Championship
84 Seattle Soul** Win 15-1 869.19 Ignored Sep 9th 2023 Womens Washington Sectional Championship
53 Hucklebears Win 15-5 1477.79 Sep 10th 2023 Womens Washington Sectional Championship
33 Seattle END Loss 8-14 738.69 Sep 10th 2023 Womens Washington Sectional Championship
11 Seattle Riot Loss 4-13 1384.62 Sep 23rd 2023 Northwest Womens Regional Championship
56 Eugene Further Win 13-5 1445.32 Sep 23rd 2023 Northwest Womens Regional Championship
84 Seattle Soul** Win 13-1 869.19 Ignored Sep 23rd 2023 Northwest Womens Regional Championship
51 Seven Devils Win 13-3 1507.19 Sep 23rd 2023 Northwest Womens Regional Championship
50 Drift Win 15-7 1514.94 Sep 24th 2023 Northwest Womens Regional Championship
19 Dark Sky Loss 8-14 1045.21 Sep 24th 2023 Northwest Womens Regional Championship
33 Seattle END Win 11-7 1741.62 Sep 24th 2023 Northwest 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)