#80 Flagstaff Ultimate (10-10)

avg: 1177.04  •  sd: 70.74  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
71 Sego Win 10-7 1626.4 Jun 24th Colorado Summer Solstice 2023
1 shame.** Loss 4-15 1667.54 Ignored Jun 24th Colorado Summer Solstice 2023
127 Sin Nombre Win 9-5 1481.85 Jun 24th Colorado Summer Solstice 2023
95 Space Ghosts Win 13-12 1203.53 Jun 24th Colorado Summer Solstice 2023
32 Kansas City United Loss 7-12 1122.92 Jun 25th Colorado Summer Solstice 2023
43 California Burrito Loss 6-12 914.44 Jun 25th Colorado Summer Solstice 2023
28 Flight Club Loss 6-15 1078.42 Jun 25th Colorado Summer Solstice 2023
69 Robot Loss 6-10 758.12 Aug 12th Flower Power 2023
198 Air Throwmads** Win 13-4 1156.25 Ignored Aug 12th Flower Power 2023
151 Spoiler Alert Win 12-3 1424.59 Aug 12th Flower Power 2023
88 Mango Win 13-4 1725.86 Aug 12th Flower Power 2023
113 Shipwreck Win 13-10 1349.17 Aug 13th Flower Power 2023
134 Firefly Win 15-4 1497.39 Aug 13th Flower Power 2023
35 LIT Ultimate Loss 9-12 1217.71 Aug 13th Flower Power 2023
69 Robot Loss 11-12 1129.28 Sep 9th 2023 Mixed So Cal Sectional Championship
244 Erosion** Win 13-4 674.79 Ignored Sep 9th 2023 Mixed So Cal Sectional Championship
145 Family Style Win 11-6 1386.44 Sep 9th 2023 Mixed So Cal Sectional Championship
43 California Burrito Loss 7-10 1104.09 Sep 9th 2023 Mixed So Cal Sectional Championship
113 Shipwreck Loss 10-14 622.33 Sep 10th 2023 Mixed So Cal Sectional Championship
151 Spoiler Alert Loss 8-9 699.59 Sep 10th 2023 Mixed So Cal Sectional Championship
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)