#78 Northern Comfort (10-8)

avg: 1188.75  •  sd: 55.55  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
9 Red Flag** Loss 6-14 1341.57 Ignored Jul 29th TCT Select Flight East 2023
50 Steamboat Loss 8-13 894.34 Jul 29th TCT Select Flight East 2023
27 Waterloo Loss 5-13 1086.05 Jul 29th TCT Select Flight East 2023
46 Revival Loss 6-15 853.7 Jul 30th TCT Select Flight East 2023
53 Roma Ultima Loss 8-12 907.72 Jul 30th TCT Select Flight East 2023
70 League of Shadows Loss 11-13 1018.16 Jul 30th TCT Select Flight East 2023
132 Mousetrap Win 12-11 1023.86 Aug 19th Cooler Classic 34
245 Underdogs** Win 13-3 674.21 Ignored Aug 19th Cooler Classic 34
155 Madison United Mixed Ultimate Win 10-4 1417.14 Aug 19th Cooler Classic 34
188 Melt Win 13-3 1210.23 Aug 19th Cooler Classic 34
117 Spectre Win 13-8 1506.61 Aug 20th Cooler Classic 34
30 Chicago Parlay Loss 4-15 1063.97 Aug 20th Cooler Classic 34
92 Mad Udderburn Loss 11-13 871.31 Aug 20th Cooler Classic 34
228 Dinosaur Fancy** Win 15-6 908.16 Ignored Sep 9th 2023 Mixed Northwest Plains Sectional Championship
164 Pandamonium Win 15-8 1339.12 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
64 Minnesota Star Power Win 15-14 1408.35 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
111 Bird Win 15-10 1476.13 Sep 10th 2023 Mixed Northwest Plains Sectional Championship
56 No Touching! Win 11-10 1449.26 Sep 10th 2023 Mixed Northwest Plains 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)