#9 Space Force (11-5)

avg: 1890.7  •  sd: 77.01  •  top 16/20: 92.5%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
14 Rally Loss 11-13 1604.9 Jul 15th TCT Pro Elite Challenge East 2023
5 Cleveland Crocs Win 15-9 2451.99 Jul 15th TCT Pro Elite Challenge East 2023
22 Storm Win 12-7 2209.86 Jul 15th TCT Pro Elite Challenge East 2023
29 RAMP Loss 12-13 1497.75 Jul 16th TCT Pro Elite Challenge East 2023
35 Impact Win 14-11 1830.43 Aug 19th TCT Elite Select Challenge 2023
21 Love Tractor Win 13-8 2203.19 Aug 19th TCT Elite Select Challenge 2023
15 Mischief Win 13-7 2388.41 Aug 19th TCT Elite Select Challenge 2023
19 Public Enemy Win 11-9 1987.73 Aug 20th TCT Elite Select Challenge 2023
1 shame. Loss 12-15 1866.72 Aug 20th TCT Elite Select Challenge 2023
15 Mischief Win 10-8 2093.55 Aug 20th TCT Elite Select Challenge 2023
69 Too Much Fun Win 11-6 1763.97 Sep 23rd 2023 Southeast Mixed Regional Championship
98 FlyTrap** Win 13-4 1653.4 Ignored Sep 23rd 2023 Southeast Mixed Regional Championship
93 Crown Peach** Win 12-4 1678.61 Ignored Sep 23rd 2023 Southeast Mixed Regional Championship
89 B-Unit** Win 15-5 1702.7 Ignored Sep 24th 2023 Southeast Mixed Regional Championship
22 Storm Loss 13-14 1564.35 Sep 24th 2023 Southeast Mixed Regional Championship
20 Toro Loss 12-15 1436.99 Sep 24th 2023 Southeast 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)