#295 Fox Valley Forge (0-16)

avg: -291.03  •  sd: 119.82  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
93 PanIC** Loss 2-13 584.69 Ignored Aug 3rd Heavyweights 2019
160 EMU** Loss 1-13 294.92 Ignored Aug 3rd Heavyweights 2019
171 Mousetrap** Loss 0-13 199.55 Ignored Aug 3rd Heavyweights 2019
226 Boomtown Pandas** Loss 2-13 -28.39 Ignored Aug 4th Heavyweights 2019
289 Taco Cat Loss 10-13 -361.06 Aug 4th Heavyweights 2019
240 Duloofda Loss 8-13 -24.73 Aug 17th Cooler Classic 31
160 EMU** Loss 1-13 294.92 Ignored Aug 17th Cooler Classic 31
147 Point of No Return** Loss 5-13 332.72 Ignored Aug 17th Cooler Classic 31
213 Mastodon** Loss 2-11 45.52 Ignored Aug 18th Cooler Classic 31
228 Midwestern Mediocrity** Loss 3-11 -74.06 Ignored Aug 18th Cooler Classic 31
71 Northern Comfort** Loss 0-13 682.76 Ignored Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
122 Pandamonium** Loss 2-13 481.72 Ignored Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
240 Duloofda Loss 6-13 -128.57 Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
209 Pushovers-B** Loss 3-13 59.42 Ignored Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
279 Identity Theft Loss 4-13 -390.07 Sep 8th Northwest Plains Mixed Club Sectional Championship 2019
287 Mufanauts Loss 5-13 -527.75 Sep 8th Northwest Plains Mixed 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)