#90 Fleet (13-8)

avg: 1197.14  •  sd: 61.68  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
15 Loco** Loss 3-15 1202.34 Ignored Jul 13th Philly Invite 2019
126 Farm Show Loss 9-10 922.51 Jul 13th Philly Invite 2019
195 Heavy Flow Win 15-7 1301.66 Jul 13th Philly Invite 2019
94 Soft Boiled Win 13-9 1600.52 Jul 13th Philly Invite 2019
94 Soft Boiled Win 12-11 1306.95 Jul 14th Philly Invite 2019
112 Stoke Win 12-7 1634.08 Jul 14th Philly Invite 2019
61 Chaotic Good Loss 9-11 1102.66 Aug 10th Chesapeake Open 2019
140 Crucible Loss 10-11 858.45 Aug 10th Chesapeake Open 2019
223 District Cocktails Win 10-5 1161.81 Aug 10th Chesapeake Open 2019
131 Legion Win 10-7 1419.31 Aug 10th Chesapeake Open 2019
72 Ant Madness Loss 10-15 822.7 Aug 11th Chesapeake Open 2019
195 Heavy Flow Win 12-8 1142.82 Aug 11th Chesapeake Open 2019
115 Rat City Win 14-8 1641.71 Aug 11th Chesapeake Open 2019
270 Baltimore BENCH Win 12-7 813.15 Sep 7th Capital Mixed Club Sectional Championship 2019
115 Rat City Win 13-9 1524.24 Sep 7th Capital Mixed Club Sectional Championship 2019
242 RnB Win 13-6 1065.07 Sep 7th Capital Mixed Club Sectional Championship 2019
23 Rally Loss 7-13 1153.8 Sep 7th Capital Mixed Club Sectional Championship 2019
72 Ant Madness Loss 7-11 809.41 Sep 8th Capital Mixed Club Sectional Championship 2019
195 Heavy Flow Win 15-7 1301.66 Sep 8th Capital Mixed Club Sectional Championship 2019
46 Sparkle Ponies Loss 7-13 932.68 Sep 8th Capital Mixed Club Sectional Championship 2019
85 HVAC Win 13-9 1650.41 Sep 8th Capital 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)