#160 Moontower (6-11)

avg: 800.68  •  sd: 56.46  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
222 Replay Win 11-2 952.42 Jul 15th Boston Invite 2023
74 Deadweight Loss 7-11 741.58 Jul 15th Boston Invite 2023
177 Eat Lightning Win 11-6 1219.19 Jul 15th Boston Invite 2023
135 Harfang ultimate Loss 11-13 653.19 Jul 15th Boston Invite 2023
236 Rampage Win 15-3 825.56 Aug 12th HoDown Showdown 2023
75 Brunch Club Loss 8-11 827.33 Aug 12th HoDown Showdown 2023
85 Too Much Fun Loss 8-15 585.71 Aug 12th HoDown Showdown 2023
126 Barefoot Loss 11-15 585.96 Aug 13th HoDown Showdown 2023
107 FlyTrap Loss 11-15 657.67 Aug 13th HoDown Showdown 2023
152 Verdant Win 15-9 1339.98 Aug 13th HoDown Showdown 2023
94 Risky Business Loss 9-11 839.07 Sep 9th 2023 Mixed Texas Sectional Championship
229 Scoober Heroes Win 13-5 906.56 Sep 9th 2023 Mixed Texas Sectional Championship
27 Waterloo** Loss 3-13 1086.05 Ignored Sep 9th 2023 Mixed Texas Sectional Championship
139 Goosebumps Loss 9-11 621.24 Sep 9th 2023 Mixed Texas Sectional Championship
25 Public Enemy** Loss 4-13 1110.07 Ignored Sep 10th 2023 Mixed Texas Sectional Championship
229 Scoober Heroes Win 13-7 864.09 Sep 10th 2023 Mixed Texas Sectional Championship
139 Goosebumps Loss 10-13 542.31 Sep 10th 2023 Mixed Texas 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)