#10 Red Flag (21-3)

avg: 1876.21  •  sd: 50.82  •  top 16/20: 96.2%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
57 Steamboat Win 11-9 1588.61 Jul 29th TCT Select Flight East 2023
73 Northern Comfort** Win 14-6 1794.2 Ignored Jul 29th TCT Select Flight East 2023
30 Waterloo Win 14-6 2215.31 Jul 29th TCT Select Flight East 2023
25 MOONDOG Win 14-9 2122.15 Jul 30th TCT Select Flight East 2023
5 Cleveland Crocs Loss 11-13 1707.67 Jul 30th TCT Select Flight East 2023
51 Classy Win 12-11 1508.8 Jul 30th TCT Select Flight East 2023
45 Wild Card Win 13-4 2057.53 Aug 26th Northwest Fruit Bowl 2023
36 BW Ultimate Win 13-6 2111.22 Aug 26th Northwest Fruit Bowl 2023
24 Loco Win 13-9 2089.41 Aug 26th Northwest Fruit Bowl 2023
23 Oregon Scorch Loss 12-13 1551.76 Aug 27th Northwest Fruit Bowl 2023
51 Classy Win 13-8 1879.96 Aug 27th Northwest Fruit Bowl 2023
26 Sunshine Win 13-5 2247.42 Aug 27th Northwest Fruit Bowl 2023
129 TT** Win 13-4 1502.69 Ignored Sep 9th 2023 Mixed Washington Sectional Championship
72 Grit City Win 13-9 1613.94 Sep 9th 2023 Mixed Washington Sectional Championship
77 Bullet Train Win 15-7 1762.69 Sep 9th 2023 Mixed Washington Sectional Championship
58 Lights Out Win 15-5 1911.04 Sep 9th 2023 Mixed Washington Sectional Championship
34 Spoke Win 14-10 1943.03 Sep 10th 2023 Mixed Washington Sectional Championship
53 Quick Draw Win 12-9 1695.92 Sep 23rd 2023 Northwest Mixed Regional Championship
127 Squid Inc.** Win 15-6 1515.93 Ignored Sep 23rd 2023 Northwest Mixed Regional Championship
25 MOONDOG Win 15-10 2101.88 Sep 23rd 2023 Northwest Mixed Regional Championship
58 Lights Out Win 15-10 1764.65 Sep 23rd 2023 Northwest Mixed Regional Championship
11 Seattle Mixtape Loss 11-15 1492.86 Sep 24th 2023 Northwest Mixed Regional Championship
23 Oregon Scorch Win 15-13 1890.94 Sep 24th 2023 Northwest Mixed Regional Championship
25 MOONDOG Win 15-9 2163.76 Sep 24th 2023 Northwest Mixed 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)