#120 El Niño (9-9)

avg: 1091.7  •  sd: 50  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
35 baNC Loss 8-13 1148.18 Jul 8th Club Terminus 2023
88 Black Lung Loss 8-12 861.59 Jul 8th Club Terminus 2023
150 Nashville Mudcats Win 10-8 1188.86 Jul 8th Club Terminus 2023
134 Dyno Win 11-10 1151.16 Jul 9th Club Terminus 2023
118 Raptor Win 10-9 1236.59 Jul 9th Club Terminus 2023
93 Charleston Heat Stroke Loss 10-11 1166.36 Jul 9th Club Terminus 2023
132 Vicious Cycle Loss 9-12 692.35 Aug 5th Swan Boat 2023
213 Stag Win 15-3 1158.46 Aug 5th Swan Boat 2023
118 Raptor Loss 9-10 986.59 Aug 5th Swan Boat 2023
42 UpRoar Loss 8-12 1164.16 Aug 6th Swan Boat 2023
114 Bloom Win 9-8 1274.31 Aug 6th Swan Boat 2023
217 Psychedelic Win 10-6 1029.12 Aug 6th Swan Boat 2023
118 Raptor Win 12-8 1552.74 Sep 9th 2023 Mens Florida Sectional Championship
132 Vicious Cycle Loss 12-13 912.72 Sep 9th 2023 Mens Florida Sectional Championship
217 Psychedelic Win 13-4 1132.96 Sep 9th 2023 Mens Florida Sectional Championship
114 Bloom Loss 9-10 1024.31 Sep 9th 2023 Mens Florida Sectional Championship
118 Raptor Loss 9-11 862.38 Sep 10th 2023 Mens Florida Sectional Championship
217 Psychedelic Win 15-0 1132.96 Sep 10th 2023 Mens Florida 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)