#109 Pushovers (10-7)

avg: 1025.51  •  sd: 59.45  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
63 Pegasus Loss 10-13 931.28 Jul 15th TCT Select Flight West 2023
49 Donuts Loss 9-15 881.03 Jul 15th TCT Select Flight West 2023
33 Tower Loss 5-15 948.37 Jul 15th TCT Select Flight West 2023
169 Octonauts Win 12-7 1252.5 Jul 16th TCT Select Flight West 2023
58 Lights Out Loss 9-13 892.48 Jul 16th TCT Select Flight West 2023
145 Madison United Mixed Ultimate Loss 9-13 405.65 Aug 19th Cooler Classic 34
159 Pandamonium Win 11-8 1151.46 Aug 19th Cooler Classic 34
203 Locomotion Win 13-3 1113.55 Aug 19th Cooler Classic 34
131 Stackcats Win 11-10 1015.78 Aug 19th Cooler Classic 34
128 Mousetrap Win 13-9 1333.52 Aug 20th Cooler Classic 34
145 Madison United Mixed Ultimate Loss 11-12 699.22 Aug 20th Cooler Classic 34
182 Melt Win 13-3 1220.06 Aug 20th Cooler Classic 34
182 Melt Win 13-7 1177.59 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
179 Frostbite Win 13-4 1246.15 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
209 Mastodon Win 13-7 1020.9 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
76 Bantr Win 13-11 1412.89 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
103 Bird Loss 9-13 618.97 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)