#69 Instant Karma (14-11)

avg: 1306.3  •  sd: 64.36  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
66 Flight Club Win 9-8 1458.31 Jun 22nd Fort Collins Summer Solstice 2019
8 shame.** Loss 4-13 1326.6 Ignored Jun 22nd Fort Collins Summer Solstice 2019
60 Rubix Loss 8-12 923.75 Jun 22nd Fort Collins Summer Solstice 2019
42 Woodwork Loss 7-13 972.28 Jun 22nd Fort Collins Summer Solstice 2019
54 Cutthroat Loss 8-11 1064.2 Jun 23rd Fort Collins Summer Solstice 2019
134 Mixed Signals Win 13-12 1138.23 Jun 23rd Fort Collins Summer Solstice 2019
198 Birds of Paradise** Win 15-1 1298.26 Ignored Aug 3rd 4th Annual Coconino Classic 2019
246 Rogue** Win 15-0 1053.95 Ignored Aug 3rd 4th Annual Coconino Classic 2019
44 Pivot Loss 5-15 900.13 Aug 3rd 4th Annual Coconino Classic 2019
60 Rubix Loss 10-14 966.2 Aug 4th 4th Annual Coconino Classic 2019
143 Superstition Win 5-5 950.28 Aug 4th 4th Annual Coconino Classic 2019
84 Ouzel Loss 10-11 1109.78 Aug 24th Ski Town Classic 2019
102 Family Style Win 10-8 1430.23 Aug 24th Ski Town Classic 2019
66 Flight Club Win 11-5 1933.31 Aug 24th Ski Town Classic 2019
189 The Strangers Win 13-5 1320.83 Aug 24th Ski Town Classic 2019
54 Cutthroat Win 13-6 2029.81 Aug 25th Ski Town Classic 2019
59 Donuts Loss 7-10 994.2 Aug 25th Ski Town Classic 2019
104 Moontower Win 13-7 1716.65 Aug 25th Ski Town Classic 2019
179 Long Beach Legacy Win 15-10 1227.42 Sep 7th So Cal Mixed Club Sectional Championship 2019
176 Spoiler Alert Win 15-6 1381.43 Sep 7th So Cal Mixed Club Sectional Championship 2019
60 Rubix Loss 8-12 923.75 Sep 7th So Cal Mixed Club Sectional Championship 2019
106 California Burrito Win 12-7 1668.73 Sep 8th So Cal Mixed Club Sectional Championship 2019
29 Lotus Loss 8-12 1201.93 Sep 8th So Cal Mixed Club Sectional Championship 2019
60 Rubix Loss 9-11 1115.7 Sep 8th So Cal Mixed Club Sectional Championship 2019
101 Robot Win 13-7 1725.46 Sep 8th So Cal 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)