#119 Tennessee Folklore (6-10)

avg: 1100.59  •  sd: 55.86  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
37 Alliance Loss 5-11 1027.37 Jul 8th Club Terminus 2023
64 Hooch Loss 5-13 848.57 Jul 8th Club Terminus 2023
138 Queen City Kings Win 11-8 1360.76 Jul 8th Club Terminus 2023
134 Dyno Loss 10-11 901.16 Jul 9th Club Terminus 2023
85 Space Cowboys Loss 10-13 984.16 Jul 9th Club Terminus 2023
150 Nashville Mudcats Win 11-8 1291.81 Jul 9th Club Terminus 2023
35 baNC Loss 9-15 1128.86 Aug 12th HoDown Showdown 2023
40 Cash Crop 2 Loss 6-15 1020.37 Aug 12th HoDown Showdown 2023
101 Triumph Loss 11-15 831.56 Aug 12th HoDown Showdown 2023
138 Queen City Kings Win 10-9 1120.15 Aug 13th HoDown Showdown 2023
89 Second Nature Win 14-13 1424.6 Aug 13th HoDown Showdown 2023
116 Atlanta Arson Loss 11-12 1018.89 Sep 9th 2023 Mens East Coast Sectional Championship
28 Tanasi** Loss 5-13 1132.45 Ignored Sep 9th 2023 Mens East Coast Sectional Championship
248 Power Point Ultimate** Win 13-4 737.63 Ignored Sep 9th 2023 Mens East Coast Sectional Championship
64 Hooch Loss 6-13 848.57 Sep 9th 2023 Mens East Coast Sectional Championship
144 Music City Mafia Win 15-8 1529.91 Sep 10th 2023 Mens 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)