#144 Music City Mafia (8-14)

avg: 965.1  •  sd: 61.24  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
37 Alliance Loss 9-11 1378.17 Jun 24th Huntsville Huckfest
134 Dyno Win 10-9 1151.16 Jun 24th Huntsville Huckfest
198 Capitol City Chaos Win 11-5 1296.2 Jun 24th Huntsville Huckfest
172 Memphis Pharaohs Win 11-7 1292.16 Jun 24th Huntsville Huckfest
124 Battleship Win 11-6 1607.62 Jun 25th Huntsville Huckfest
56 Little Red Wagon Loss 5-11 897.91 Jun 25th Huntsville Huckfest
89 Second Nature Loss 10-11 1174.6 Jun 25th Huntsville Huckfest
37 Alliance Loss 6-9 1208.81 Aug 5th Trestlemania V
134 Dyno Loss 8-10 763.49 Aug 5th Trestlemania V
150 Nashville Mudcats Win 7-6 1051.2 Aug 5th Trestlemania V
93 Charleston Heat Stroke Loss 5-12 691.36 Aug 5th Trestlemania V
198 Capitol City Chaos Loss 9-10 571.2 Aug 6th Trestlemania V
85 Space Cowboys Loss 10-15 858.7 Aug 12th HoDown Showdown 2023
30 Delirium** Loss 5-15 1078.68 Ignored Aug 12th HoDown Showdown 2023
61 Lost Boys Loss 3-15 865.93 Aug 12th HoDown Showdown 2023
89 Second Nature Loss 9-15 784.12 Aug 13th HoDown Showdown 2023
138 Queen City Kings Win 13-12 1120.15 Aug 13th HoDown Showdown 2023
134 Dyno Loss 5-13 426.16 Sep 9th 2023 Mens East Coast Sectional Championship
93 Charleston Heat Stroke Loss 11-13 1062.52 Sep 9th 2023 Mens East Coast Sectional Championship
167 Pulp Win 13-10 1166.45 Sep 9th 2023 Mens East Coast Sectional Championship
150 Nashville Mudcats Win 13-11 1155.04 Sep 9th 2023 Mens East Coast Sectional Championship
119 Tennessee Folklore Loss 8-15 535.78 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)