#147 Glycerine (13-14)

avg: 779.12  •  sd: 57.33  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
76 Gamble Loss 6-13 560.52 Jun 29th Texas 2 Finger Mens and Womens
221 Surrilic Audovice Loss 10-11 147.69 Jun 29th Texas 2 Finger Mens and Womens
116 Papa Bear Loss 11-13 730.95 Jun 29th Texas 2 Finger Mens and Womens
91 Harvey Cats Loss 8-10 828.14 Jun 29th Texas 2 Finger Mens and Womens
218 Messengers-B Win 13-5 898.96 Jun 30th Texas 2 Finger Mens and Womens
208 Alamode Win 15-7 1005.69 Jun 30th Texas 2 Finger Mens and Womens
229 Texas Toast Win 15-6 815.14 Jun 30th Texas 2 Finger Mens and Womens
69 Riverside Loss 9-15 690.77 Jul 13th Riverside Classic 2019
116 Papa Bear Loss 10-13 631.65 Jul 13th Riverside Classic 2019
215 Quaze Win 15-12 645.35 Jul 13th Riverside Classic 2019
218 Messengers-B Win 14-13 423.96 Jul 14th Riverside Classic 2019
229 Texas Toast Win 15-7 815.14 Jul 14th Riverside Classic 2019
208 Alamode Win 13-9 824.26 Jul 14th Riverside Classic 2019
80 Texas United Loss 8-15 578.64 Jul 14th Riverside Classic 2019
85 Dreadnought Win 13-11 1344.09 Aug 17th Hootie on the Hill 2019
161 Supercell Win 13-7 1269.05 Aug 17th Hootie on the Hill 2019
195 Rawhide Win 13-7 1041.91 Aug 17th Hootie on the Hill 2019
85 Dreadnought Loss 13-14 990.25 Aug 18th Hootie on the Hill 2019
161 Supercell Loss 10-13 383.38 Aug 18th Hootie on the Hill 2019
195 Rawhide Loss 3-4 359.37 Aug 18th Hootie on the Hill 2019
36 Nitro** Loss 4-13 863.41 Ignored Sep 7th Texas Mens Club Sectional Championship 2019
116 Papa Bear Loss 8-13 463.63 Sep 7th Texas Mens Club Sectional Championship 2019
177 Rock Steady Win 13-7 1185.48 Sep 7th Texas Mens Club Sectional Championship 2019
162 DUPlex Win 11-9 959.39 Sep 7th Texas Mens Club Sectional Championship 2019
155 Flash Flood Win 12-8 1188.97 Sep 8th Texas Mens Club Sectional Championship 2019
91 Harvey Cats Loss 5-13 490.81 Sep 8th Texas Mens Club Sectional Championship 2019
116 Papa Bear Loss 8-13 463.63 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)