#95 HouSE (13-15)

avg: 1070  •  sd: 47.89  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
28 Nain Rouge Loss 4-13 946.08 Jul 13th The Bropen 2019
174 Red Bat Win 13-6 1239.73 Jul 13th The Bropen 2019
20 Yogosbo** Loss 3-13 1133.03 Ignored Jul 13th The Bropen 2019
94 Minnesota Superior U20B Loss 10-12 833.26 Jul 13th The Bropen 2019
34 Mad Men Loss 7-13 916.87 Jul 14th The Bropen 2019
175 Milwaukee Revival Win 11-8 1003.52 Jul 14th The Bropen 2019
87 Red Hots - u20 Loss 9-10 989.02 Jul 14th The Bropen 2019
100 Timber Loss 12-13 916.48 Jul 14th The Bropen 2019
240 Ditto B** Win 13-5 483.84 Ignored Aug 3rd Heavyweights 2019
129 Kentucky Flying Circus Win 12-8 1339.59 Aug 3rd Heavyweights 2019
102 THE BODY Win 13-11 1257.98 Aug 3rd Heavyweights 2019
48 Cryptic Loss 8-13 860.04 Aug 4th Heavyweights 2019
100 Timber Win 13-8 1537.64 Aug 4th Heavyweights 2019
99 Black Market II Win 13-8 1548.56 Aug 4th Heavyweights 2019
179 Chimney Win 13-6 1185.69 Aug 17th Cooler Classic 31
118 CaSTLe Win 13-11 1182.75 Aug 17th Cooler Classic 31
100 Timber Win 15-13 1255.66 Aug 17th Cooler Classic 31
74 DeMo Win 13-11 1397.82 Aug 17th Cooler Classic 31
60 Swans Loss 5-11 671.27 Aug 18th Cooler Classic 31
56 Scythe Loss 7-9 1008.72 Aug 18th Cooler Classic 31
101 Imperial Loss 6-9 621.28 Aug 18th Cooler Classic 31
52 Mallard Loss 9-12 984.21 Sep 7th Northwest Plains Mens Club Sectional Championship 2019
100 Timber Loss 11-12 916.48 Sep 7th Northwest Plains Mens Club Sectional Championship 2019
20 Yogosbo** Loss 3-13 1133.03 Ignored Sep 7th Northwest Plains Mens Club Sectional Championship 2019
175 Milwaukee Revival Win 12-6 1217.22 Sep 8th Northwest Plains Mens Club Sectional Championship 2019
41 MKE Loss 2-13 810.84 Sep 8th Northwest Plains Mens Club Sectional Championship 2019
102 THE BODY Loss 11-12 904.14 Sep 8th Northwest Plains Mens Club Sectional Championship 2019
101 Imperial Win 13-12 1164.84 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)