#134 Mixed Signals (7-13)

avg: 1013.23  •  sd: 64.98  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
54 Cutthroat Loss 8-10 1167.15 Jun 22nd Fort Collins Summer Solstice 2019
14 Love Tractor** Loss 5-13 1226.3 Ignored Jun 22nd Fort Collins Summer Solstice 2019
52 Mesteño Loss 5-12 841.75 Jun 22nd Fort Collins Summer Solstice 2019
24 MOONDOG** Loss 4-13 1110.43 Ignored Jun 22nd Fort Collins Summer Solstice 2019
66 Flight Club Loss 6-13 733.31 Jun 23rd Fort Collins Summer Solstice 2019
69 Instant Karma Loss 12-13 1181.3 Jun 23rd Fort Collins Summer Solstice 2019
108 Argo Win 12-8 1583.08 Aug 24th Ski Town Classic 2019
54 Cutthroat Loss 12-13 1304.81 Aug 24th Ski Town Classic 2019
76 Firefly Loss 7-13 713.09 Aug 24th Ski Town Classic 2019
166 Wasatch Sasquatch Loss 9-11 589.98 Aug 24th Ski Town Classic 2019
239 Fear and Loathing Win 13-8 974.53 Aug 25th Ski Town Classic 2019
246 Rogue Win 13-6 1053.95 Aug 25th Ski Town Classic 2019
189 The Strangers Loss 8-10 458.16 Sep 6th Rocky Mountain Mixed Club Sectional Championship 2019
84 Ouzel Loss 9-10 1109.78 Sep 7th Rocky Mountain Mixed Club Sectional Championship 2019
14 Love Tractor** Loss 4-11 1226.3 Ignored Sep 7th Rocky Mountain Mixed Club Sectional Championship 2019
241 EDM Win 10-6 966.7 Sep 7th Rocky Mountain Mixed Club Sectional Championship 2019
220 All Jeeps, All Night. Win 11-5 1206.44 Sep 8th Rocky Mountain Mixed Club Sectional Championship 2019
128 Springs Mixed Ulty Team Win 10-9 1165.35 Sep 8th Rocky Mountain Mixed Club Sectional Championship 2019
79 Vendetta Loss 5-11 657.35 Sep 8th Rocky Mountain Mixed Club Sectional Championship 2019
158 Sweet Action Win 10-4 1503.34 Sep 8th Rocky Mountain 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)