#88 The Bandits (17-10)

avg: 1202.88  •  sd: 46.66  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
15 Loco Loss 3-15 1202.34 Jul 13th Philly Invite 2019
86 Eat Lightning Loss 11-12 1096.84 Jul 13th Philly Invite 2019
35 League of Shadows Loss 10-14 1164.69 Jul 13th Philly Invite 2019
117 PS Loss 13-14 974.32 Jul 13th Philly Invite 2019
195 Heavy Flow Win 14-10 1100.37 Jul 14th Philly Invite 2019
142 Philly Twist Win 13-8 1448.45 Jul 14th Philly Invite 2019
151 Buffalo Lake Effect Win 13-5 1523.09 Aug 3rd Philly Open 2019
191 LORD Win 13-9 1132.47 Aug 3rd Philly Open 2019
269 Tropics Ultimate** Win 13-5 893.3 Ignored Aug 3rd Philly Open 2019
208 TBD Win 13-8 1157.87 Aug 3rd Philly Open 2019
96 Birds Win 15-12 1478.88 Aug 4th Philly Open 2019
91 Garbage Plates Win 13-12 1321.12 Aug 4th Philly Open 2019
39 Darkwing Loss 6-12 961.76 Aug 17th Chowdafest 2019
210 Face Off Win 13-8 1154.03 Aug 17th Chowdafest 2019
124 Happy Valley Win 13-10 1395.51 Aug 17th Chowdafest 2019
212 Sorted Beans Win 13-7 1207.13 Aug 17th Chowdafest 2019
86 Eat Lightning Loss 9-11 972.63 Aug 18th Chowdafest 2019
148 Scarecrow Win 13-7 1486.24 Aug 18th Chowdafest 2019
133 Night Shift Win 11-9 1269.27 Aug 18th Chowdafest 2019
81 The Feminists Win 11-10 1377.72 Aug 18th Chowdafest 2019
78 Blowing Heat 3.0 Loss 13-15 1054.93 Sep 7th Founders Mixed Club Sectional Championship 2019
140 Crucible Win 14-9 1457.32 Sep 7th Founders Mixed Club Sectional Championship 2019
94 Soft Boiled Win 13-7 1739.48 Sep 7th Founders Mixed Club Sectional Championship 2019
25 Alloy Loss 6-14 1109.76 Sep 8th Founders Mixed Club Sectional Championship 2019
126 Farm Show Win 13-12 1172.51 Sep 8th Founders Mixed Club Sectional Championship 2019
94 Soft Boiled Loss 8-13 685.79 Sep 8th Founders Mixed Club Sectional Championship 2019
112 Stoke Loss 10-14 714.87 Sep 8th Founders Mixed 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)