#69 Riverside (19-9)

avg: 1206.25  •  sd: 48.28  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
29 Clutch Loss 2-13 938.44 Jun 29th Texas 2 Finger Mens and Womens
154 Foxtrot Win 11-9 1010.82 Jun 29th Texas 2 Finger Mens and Womens
162 DUPlex Win 13-8 1206.34 Jun 29th Texas 2 Finger Mens and Womens
229 Texas Toast** Win 13-5 815.14 Ignored Jun 29th Texas 2 Finger Mens and Womens
29 Clutch Loss 8-15 973.63 Jun 30th Texas 2 Finger Mens and Womens
76 Gamble Win 15-11 1541.68 Jun 30th Texas 2 Finger Mens and Womens
27 H.I.P Loss 9-15 1033.07 Jun 30th Texas 2 Finger Mens and Womens
147 Glycerine Win 15-9 1294.61 Jul 13th Riverside Classic 2019
215 Quaze Win 15-8 909.67 Jul 13th Riverside Classic 2019
116 Papa Bear Win 15-9 1475.27 Jul 13th Riverside Classic 2019
154 Foxtrot Win 15-9 1277.09 Jul 14th Riverside Classic 2019
64 Gaucho Loss 13-15 1038.68 Jul 14th Riverside Classic 2019
91 Harvey Cats Win 15-10 1544.41 Jul 14th Riverside Classic 2019
27 H.I.P Loss 11-13 1319.71 Jul 27th PBJ 2019
150 Louisiana Second Line Win 13-10 1096.71 Jul 27th PBJ 2019
219 Texas Heatwave** Win 13-3 873.41 Ignored Jul 27th PBJ 2019
215 Quaze** Win 13-2 944.86 Ignored Jul 27th PBJ 2019
64 Gaucho Win 15-13 1467.04 Jul 28th PBJ 2019
27 H.I.P Loss 9-15 1033.07 Jul 28th PBJ 2019
221 Surrilic Audovice** Win 13-5 872.69 Ignored Jul 28th PBJ 2019
64 Gaucho Win 13-9 1671.43 Sep 7th Texas Mens Club Sectional Championship 2019
162 DUPlex Win 13-6 1310.18 Sep 7th Texas Mens Club Sectional Championship 2019
182 E.V.I.L.** Win 13-4 1166.45 Ignored Sep 7th Texas Mens Club Sectional Championship 2019
36 Nitro Loss 6-13 863.41 Sep 7th Texas Mens Club Sectional Championship 2019
29 Clutch Loss 4-12 938.44 Sep 8th Texas Mens Club Sectional Championship 2019
154 Foxtrot Win 13-9 1180.17 Sep 8th Texas Mens Club Sectional Championship 2019
76 Gamble Loss 11-13 931.68 Sep 8th Texas Mens Club Sectional Championship 2019
91 Harvey Cats Win 13-8 1586.97 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)