#45 Rampage (12-9)

avg: 973.75  •  sd: 69.61  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
20 Wildfire Loss 3-9 960.61 Jul 15th TCT Select Flight West 2023
38 FAB Loss 5-10 545.37 Jul 15th TCT Select Flight West 2023
71 Jackwagon Win 11-6 1044.42 Jul 15th TCT Select Flight West 2023
100 Just Add Water** Win 11-0 418.85 Ignored Jul 15th TCT Select Flight West 2023
68 Venom Win 13-4 1155.5 Jul 16th TCT Select Flight West 2023
32 Crush City Loss 8-13 817.23 Aug 19th Ski Town Classic 2023
79 Swell Win 12-7 870.16 Aug 19th Ski Town Classic 2023
84 Seattle Soul Win 8-4 834 Aug 19th Ski Town Classic 2023
52 Void Cat Rewind Win 7-2 1493.58 Aug 20th Ski Town Classic 2023
19 Dark Sky** Loss 4-13 981.24 Ignored Aug 20th Ski Town Classic 2023
58 Fiasco Win 10-4 1389.62 Aug 20th Ski Town Classic 2023
68 Venom Win 13-8 1051.66 Sep 9th 2023 Womens SoCal Sectional Championship
20 Wildfire Loss 6-10 1064.45 Sep 9th 2023 Womens SoCal Sectional Championship
87 Haboob** Win 12-5 756.71 Ignored Sep 9th 2023 Womens SoCal Sectional Championship
100 Just Add Water** Win 13-1 418.85 Ignored Sep 9th 2023 Womens SoCal Sectional Championship
20 Wildfire Loss 7-13 1003.08 Sep 23rd 2023 Southwest Womens Regional Championship
6 Flipside** Loss 6-15 1667.63 Ignored Sep 23rd 2023 Southwest Womens Regional Championship
87 Haboob** Win 13-3 756.71 Ignored Sep 23rd 2023 Southwest Womens Regional Championship
89 Tempo** Win 13-1 738.45 Ignored Sep 23rd 2023 Southwest Womens Regional Championship
52 Void Cat Rewind Loss 11-14 580.24 Sep 24th 2023 Southwest Womens Regional Championship
38 FAB Loss 10-11 994.26 Sep 24th 2023 Southwest 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)