#228 Flying Dutchmen (2-17)

avg: 221.39  •  sd: 71.87  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
227 Bird Patrol Win 14-13 358.85 Jun 22nd SCINNY 2019
190 A-Block Win 15-14 656.43 Jun 22nd SCINNY 2019
184 Chimney Loss 12-13 431.37 Jun 22nd SCINNY 2019
146 Babe Loss 12-13 692.36 Jun 22nd SCINNY 2019
84 Black Lung** Loss 4-15 525.55 Ignored Jun 23rd SCINNY 2019
205 Flying Pig Loss 3-15 -170.62 Jun 23rd SCINNY 2019
208 Red Imp.ala Loss 10-12 167.42 Jun 23rd SCINNY 2019
133 Kentucky Flying Circus** Loss 2-13 284.93 Ignored Jul 6th Motown Throwdown 2019
164 BlackER Market Y Loss 7-12 190.6 Jul 6th Motown Throwdown 2019
81 Omen** Loss 4-13 538.86 Ignored Jul 6th Motown Throwdown 2019
200 NEO Loss 7-9 176.57 Jul 7th Motown Throwdown 2019
133 Kentucky Flying Circus** Loss 3-13 284.93 Ignored Jul 7th Motown Throwdown 2019
235 Buffalo Open Loss 9-11 -238.88 Jul 7th Motown Throwdown 2019
84 Black Lung** Loss 3-11 525.55 Ignored Sep 7th East Plains Mens Club Sectional Championship 2019
135 Enigma Loss 7-11 408.97 Sep 7th East Plains Mens Club Sectional Championship 2019
193 Midnight Meat Train Loss 5-11 -94.92 Sep 7th East Plains Mens Club Sectional Championship 2019
20 CLE Smokestack** Loss 0-11 1062.79 Ignored Sep 7th East Plains Mens Club Sectional Championship 2019
200 NEO Loss 10-12 217.78 Sep 8th East Plains Mens Club Sectional Championship 2019
133 Kentucky Flying Circus** Loss 4-11 284.93 Ignored Sep 8th East Plains Mens Club Sectional Championship 2019
**Blowout Eligible

FAQ

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
  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
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)