#13 Slow (16-6)

avg: 1849.58  •  sd: 44.53  •  top 16/20: 92.9%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
68 Heat Wave** Win 13-3 1836.17 Ignored Jul 15th Boston Invite 2023
65 League of Shadows** Win 13-5 1848.69 Ignored Jul 15th Boston Invite 2023
45 Wild Card Win 13-4 2057.53 Jul 15th Boston Invite 2023
59 Greater Baltimore Anthem Win 13-6 1909.03 Jul 15th Boston Invite 2023
19 Public Enemy Loss 9-13 1319.96 Aug 19th TCT Elite Select Challenge 2023
12 'Shine Win 15-13 2065.26 Aug 19th TCT Elite Select Challenge 2023
5 Cleveland Crocs Loss 10-11 1811.51 Aug 19th TCT Elite Select Challenge 2023
35 Impact Win 15-8 2081.9 Aug 20th TCT Elite Select Challenge 2023
17 Lawless Win 14-10 2161.89 Aug 20th TCT Elite Select Challenge 2023
12 'Shine Win 13-9 2269.65 Aug 20th TCT Elite Select Challenge 2023
16 Hybrid Loss 13-14 1698.85 Sep 2nd TCT Pro Championships 2023
20 Toro Win 13-12 1862.48 Sep 2nd TCT Pro Championships 2023
3 AMP Loss 8-11 1702.24 Sep 2nd TCT Pro Championships 2023
8 NOISE Loss 7-15 1293.89 Sep 3rd TCT Pro Championships 2023
21 Love Tractor Loss 10-12 1468.91 Sep 3rd TCT Pro Championships 2023
20 Toro Win 14-12 1958.44 Sep 4th TCT Pro Championships 2023
56 LAX-Senior Win 13-10 1668.87 Sep 23rd 2023 Northeast Mixed Regional Championship
55 Garbage Plates Win 13-7 1899.8 Sep 23rd 2023 Northeast Mixed Regional Championship
7 XIST Win 15-12 2221.35 Sep 23rd 2023 Northeast Mixed Regional Championship
44 The Buoy Association Win 14-9 1947.88 Sep 23rd 2023 Northeast Mixed Regional Championship
48 Townies Win 13-11 1631.7 Sep 24th 2023 Northeast Mixed Regional Championship
6 Sprocket Win 12-11 2049.96 Sep 24th 2023 Northeast 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)