#126 Farm Show (7-13)

avg: 1047.51  •  sd: 62.39  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
72 Ant Madness Loss 11-13 1047.46 Jul 13th Philly Invite 2019
46 Sparkle Ponies Loss 7-13 932.68 Jul 13th Philly Invite 2019
177 Unlimited Swipes Win 15-7 1380.86 Jul 13th Philly Invite 2019
90 Fleet Win 10-9 1322.14 Jul 13th Philly Invite 2019
61 Chaotic Good Loss 7-11 884.97 Jul 14th Philly Invite 2019
35 League of Shadows Loss 5-15 963.4 Jul 14th Philly Invite 2019
117 PS Loss 9-11 850.11 Jul 14th Philly Invite 2019
180 Varsity Win 12-8 1213.92 Aug 10th Nuccis Cup 2019
112 Stoke Win 10-9 1238.57 Aug 10th Nuccis Cup 2019
120 Funk Loss 8-9 961.78 Aug 10th Nuccis Cup 2019
180 Varsity Loss 7-12 252.26 Aug 11th Nuccis Cup 2019
112 Stoke Loss 7-12 593.06 Aug 11th Nuccis Cup 2019
25 Alloy Loss 8-15 1144.95 Sep 7th Founders Mixed Club Sectional Championship 2019
15 Loco** Loss 3-13 1202.34 Ignored Sep 7th Founders Mixed Club Sectional Championship 2019
200 Left Turn Lane Win 13-5 1294.93 Sep 7th Founders Mixed Club Sectional Championship 2019
142 Philly Twist Win 13-8 1448.45 Sep 7th Founders Mixed Club Sectional Championship 2019
78 Blowing Heat 3.0 Loss 12-15 968.61 Sep 8th Founders Mixed Club Sectional Championship 2019
94 Soft Boiled Win 12-11 1306.95 Sep 8th Founders Mixed Club Sectional Championship 2019
117 PS Loss 8-10 836.65 Sep 8th Founders Mixed Club Sectional Championship 2019
88 The Bandits Loss 12-13 1077.88 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)