#150 Foxtrot (11-16)

avg: 777.94  •  sd: 51.9  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
222 Texas Toast Win 13-3 861.24 Jun 29th Texas 2 Finger Mens and Womens
79 Riverside Loss 9-11 901.96 Jun 29th Texas 2 Finger Mens and Womens
159 DUPlex Win 12-8 1181.72 Jun 29th Texas 2 Finger Mens and Womens
28 Clutch** Loss 4-13 912.24 Ignored Jun 29th Texas 2 Finger Mens and Womens
217 Surrilic Audovice Win 15-10 765.77 Jun 30th Texas 2 Finger Mens and Womens
58 Gaucho Loss 10-15 835.58 Jun 30th Texas 2 Finger Mens and Womens
179 E.V.I.L. Win 15-8 1168.13 Jun 30th Texas 2 Finger Mens and Womens
217 Surrilic Audovice Win 17-11 790.32 Jul 13th Riverside Classic 2019
26 H.I.P** Loss 7-17 983.07 Ignored Jul 13th Riverside Classic 2019
79 Riverside Loss 9-15 635.69 Jul 14th Riverside Classic 2019
64 Gamble Loss 8-15 686.43 Jul 14th Riverside Classic 2019
106 Papa Bear Win 14-13 1144.96 Jul 14th Riverside Classic 2019
201 Alamode Win 15-4 1051.91 Jul 14th Riverside Classic 2019
84 Black Lung Loss 3-13 525.55 Aug 3rd Heavyweights 2019
116 Timber Loss 7-13 411.31 Aug 3rd Heavyweights 2019
231 Black Market III** Win 13-5 706.25 Ignored Aug 3rd Heavyweights 2019
103 Imperial Loss 5-13 434.06 Aug 4th Heavyweights 2019
122 Satellite Loss 8-13 429.87 Aug 4th Heavyweights 2019
208 Red Imp.ala Loss 10-13 77.4 Aug 4th Heavyweights 2019
149 Flash Flood Win 12-11 908.44 Sep 7th Texas Mens Club Sectional Championship 2019
28 Clutch Loss 8-13 1016.08 Sep 7th Texas Mens Club Sectional Championship 2019
64 Gamble Loss 5-13 651.24 Sep 7th Texas Mens Club Sectional Championship 2019
215 Messengers-B Win 11-4 941.18 Sep 7th Texas Mens Club Sectional Championship 2019
106 Papa Bear Win 13-9 1438.53 Sep 8th Texas Mens Club Sectional Championship 2019
79 Riverside Loss 9-13 732.6 Sep 8th Texas Mens Club Sectional Championship 2019
88 Harvey Cats Loss 8-13 602.7 Sep 8th Texas Mens Club Sectional Championship 2019
106 Papa Bear Loss 9-13 601.39 Sep 8th Texas 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)