#154 Foxtrot (11-16)

avg: 761.61  •  sd: 51.9  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
29 Clutch** Loss 4-13 938.44 Ignored Jun 29th Texas 2 Finger Mens and Womens
229 Texas Toast Win 13-3 815.14 Jun 29th Texas 2 Finger Mens and Womens
69 Riverside Loss 9-11 957.05 Jun 29th Texas 2 Finger Mens and Womens
162 DUPlex Win 12-8 1151.34 Jun 29th Texas 2 Finger Mens and Womens
221 Surrilic Audovice Win 15-10 726.29 Jun 30th Texas 2 Finger Mens and Womens
64 Gaucho Loss 10-15 799.26 Jun 30th Texas 2 Finger Mens and Womens
182 E.V.I.L. Win 15-8 1131.26 Jun 30th Texas 2 Finger Mens and Womens
221 Surrilic Audovice Win 17-11 750.85 Jul 13th Riverside Classic 2019
27 H.I.P** Loss 7-17 948.55 Ignored Jul 13th Riverside Classic 2019
69 Riverside Loss 9-15 690.77 Jul 14th Riverside Classic 2019
76 Gamble Loss 8-15 595.71 Jul 14th Riverside Classic 2019
116 Papa Bear Win 14-13 1084.79 Jul 14th Riverside Classic 2019
208 Alamode Win 15-4 1005.69 Jul 14th Riverside Classic 2019
82 Black Lung Loss 3-13 526.33 Aug 3rd Heavyweights 2019
100 Timber Loss 7-13 483.94 Aug 3rd Heavyweights 2019
231 Black Market III** Win 13-5 735.41 Ignored Aug 3rd Heavyweights 2019
101 Imperial Loss 5-13 439.84 Aug 4th Heavyweights 2019
117 Satellite Loss 8-13 461.03 Aug 4th Heavyweights 2019
204 Red Imp.ala Loss 10-13 103.07 Aug 4th Heavyweights 2019
29 Clutch Loss 8-13 1042.28 Sep 7th Texas Mens Club Sectional Championship 2019
218 Messengers-B Win 11-4 898.96 Sep 7th Texas Mens Club Sectional Championship 2019
155 Flash Flood Win 12-11 872.82 Sep 7th Texas Mens Club Sectional Championship 2019
76 Gamble Loss 5-13 560.52 Sep 7th Texas Mens Club Sectional Championship 2019
116 Papa Bear Win 13-9 1378.36 Sep 8th Texas Mens Club Sectional Championship 2019
69 Riverside Loss 9-13 787.69 Sep 8th Texas Mens Club Sectional Championship 2019
91 Harvey Cats Loss 8-13 594.65 Sep 8th Texas Mens Club Sectional Championship 2019
116 Papa Bear Loss 9-13 541.23 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)