#72 KnoxFusion (7-11)

avg: 493.2  •  sd: 115.4  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
96 Y'all Win 15-6 595.64 Jun 17th SCINNY1
34 Indy Rogue** Loss 6-15 586.34 Ignored Jun 17th SCINNY1
92 Sureshot Win 15-6 647.83 Jun 17th SCINNY1
103 Bullseye** Win 15-6 100.11 Ignored Jun 17th SCINNY1
96 Y'all Win 14-8 531.67 Jun 18th SCINNY1
34 Indy Rogue** Loss 4-15 586.34 Ignored Jun 18th SCINNY1
102 Solstice** Win 15-2 281.02 Ignored Jun 18th SCINNY1
23 Flight** Loss 5-14 939.4 Ignored Jul 15th TCT Pro Elite Challenge East 2023
12 Nemesis** Loss 4-15 1331.46 Ignored Jul 15th TCT Pro Elite Challenge East 2023
2 Phoenix** Loss 2-15 1879.74 Ignored Jul 15th TCT Pro Elite Challenge East 2023
29 Pop** Loss 5-14 802.13 Ignored Jul 16th TCT Pro Elite Challenge East 2023
75 Calypso Loss 10-12 216.73 Aug 12th HoDown Showdown 2023
44 Juice Box Loss 5-15 388.44 Aug 12th HoDown Showdown 2023
46 San Antonio Problems Win 12-9 1304.67 Aug 12th HoDown Showdown 2023
55 Shiver Loss 6-12 291.34 Aug 12th HoDown Showdown 2023
67 Magma Win 11-10 723.14 Aug 13th HoDown Showdown 2023
67 Magma Loss 3-7 -1.86 Aug 13th HoDown Showdown 2023
67 Magma Loss 9-12 252.78 Sep 10th 2023 Womens East Coast 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)