#209 Long Island Riff Raff (9-16)

avg: 589.54  •  sd: 46.23  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
133 BAG Loss 2-13 434.3 Aug 5th Philly Open 2023
115 Bomb Squad Loss 6-13 544.34 Aug 5th Philly Open 2023
177 JAWN Loss 5-13 212.44 Aug 5th Philly Open 2023
200 Rochester Open Club Loss 9-11 432.97 Aug 6th Philly Open 2023
158 Alibi Loss 2-13 287.94 Aug 6th Philly Open 2023
228 Mischief Win 12-7 987.15 Aug 6th Philly Open 2023
189 Dirty Laundry Win 12-11 873.17 Aug 19th Ow My Knee 2023
238 Mohawk Valley Wild Win 12-9 672.72 Aug 19th Ow My Knee 2023
202 Spring Break '93 Loss 11-13 431.29 Aug 19th Ow My Knee 2023
189 Dirty Laundry Loss 12-13 623.17 Aug 20th Ow My Knee 2023
215 EZ Loss 11-12 423.4 Aug 20th Ow My Knee 2023
238 Mohawk Valley Wild Loss 12-13 202.36 Aug 20th Ow My Knee 2023
102 Harvey Cats** Loss 3-13 607.19 Ignored Aug 26th The Incident 2023
70 OAT Loss 6-13 799.46 Aug 26th The Incident 2023
154 Odyssey Loss 8-13 398.12 Aug 26th The Incident 2023
202 Spring Break '93 Win 13-9 1078.7 Aug 26th The Incident 2023
235 Adelphos Win 13-8 870.75 Aug 27th The Incident 2023
189 Dirty Laundry Loss 11-15 367 Aug 27th The Incident 2023
252 Deepfake Win 15-9 565.1 Aug 27th The Incident 2023
246 Army-West Point Win 13-5 771.41 Sep 9th 2023 Mens Metro New York Sectional Championship
230 Bartle Boys Win 12-10 669.04 Sep 9th 2023 Mens Metro New York Sectional Championship
72 Colt** Loss 4-13 789.28 Ignored Sep 9th 2023 Mens Metro New York Sectional Championship
62 Shade** Loss 3-13 849.64 Ignored Sep 9th 2023 Mens Metro New York Sectional Championship
252 Deepfake Win 15-4 649.62 Sep 10th 2023 Mens Metro New York Sectional Championship
202 Spring Break '93 Loss 12-13 535.13 Sep 10th 2023 Mens Metro New York 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)