#100 Timber (14-14)

avg: 1041.48  •  sd: 56.98  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
34 Mad Men Loss 6-13 874.41 Jul 13th The Bropen 2019
52 Mallard Loss 6-13 729.58 Jul 13th The Bropen 2019
175 Milwaukee Revival Win 13-5 1237.91 Jul 13th The Bropen 2019
174 Red Bat Win 13-5 1239.73 Jul 13th The Bropen 2019
87 Red Hots - u20 Loss 3-13 514.02 Jul 13th The Bropen 2019
95 HouSE Win 13-12 1195 Jul 14th The Bropen 2019
20 Yogosbo** Loss 2-13 1133.03 Ignored Jul 14th The Bropen 2019
94 Minnesota Superior U20B Loss 9-10 946.38 Jul 14th The Bropen 2019
154 Foxtrot Win 13-7 1319.14 Aug 3rd Heavyweights 2019
82 Black Lung Loss 4-13 526.33 Aug 3rd Heavyweights 2019
231 Black Market III** Win 13-2 735.41 Ignored Aug 3rd Heavyweights 2019
95 HouSE Loss 8-13 573.84 Aug 4th Heavyweights 2019
129 Kentucky Flying Circus Win 13-9 1317 Aug 4th Heavyweights 2019
60 Swans Loss 7-13 713.74 Aug 4th Heavyweights 2019
179 Chimney Win 13-5 1185.69 Aug 17th Cooler Classic 31
41 MKE Loss 6-13 810.84 Aug 17th Cooler Classic 31
95 HouSE Loss 13-15 855.82 Aug 17th Cooler Classic 31
118 CaSTLe Win 13-9 1372.48 Aug 17th Cooler Classic 31
175 Milwaukee Revival Win 9-4 1237.91 Aug 18th Cooler Classic 31
174 Red Bat Win 11-5 1239.73 Aug 18th Cooler Classic 31
99 Black Market II Loss 4-11 452.4 Aug 18th Cooler Classic 31
52 Mallard Loss 10-12 1091.45 Sep 7th Northwest Plains Mens Club Sectional Championship 2019
175 Milwaukee Revival Win 13-5 1237.91 Sep 7th Northwest Plains Mens Club Sectional Championship 2019
95 HouSE Win 12-11 1195 Sep 7th Northwest Plains Mens Club Sectional Championship 2019
41 MKE Loss 5-13 810.84 Sep 8th Northwest Plains Mens Club Sectional Championship 2019
101 Imperial Win 12-9 1385.21 Sep 8th Northwest Plains Mens Club Sectional Championship 2019
20 Yogosbo** Loss 5-13 1133.03 Ignored Sep 8th Northwest Plains Mens Club Sectional Championship 2019
102 THE BODY Win 13-7 1586.67 Sep 8th Northwest 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)