#74 Hazard (11-12)

avg: 1383.45  •  sd: 63.09  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
87 Ghost Train Win 13-5 1909.41 Jul 15th TCT Select Flight West 2023
76 Haymaker Win 8-7 1502.16 Jul 15th TCT Select Flight West 2023
70 OAT Loss 9-13 980.9 Jul 15th TCT Select Flight West 2023
11 Furious George Loss 7-15 1457.44 Jul 16th TCT Select Flight West 2023
69 Clutch Win 14-9 1884.26 Jul 16th TCT Select Flight West 2023
58 Skipjack Loss 7-10 1101.04 Jul 16th TCT Select Flight West 2023
68 Brawl Win 13-10 1746.69 Aug 19th Ski Town Classic 2023
145 Green River Swordfish Win 10-6 1460.42 Aug 19th Ski Town Classic 2023
49 Shrimp Loss 7-12 1034.72 Aug 19th Ski Town Classic 2023
65 Sawtooth Loss 9-10 1318.15 Aug 20th Ski Town Classic 2023
53 Sundance Kids Loss 12-13 1399.03 Aug 20th Ski Town Classic 2023
18 Dark Star-D Loss 7-13 1325.76 Aug 20th Ski Town Classic 2023
240 Bonsoon** Win 13-4 850.91 Ignored Sep 9th 2023 Mens So Cal Sectional Championship
220 Las Vegas Nuke** Win 13-5 1125.05 Ignored Sep 9th 2023 Mens So Cal Sectional Championship
66 OC Crows Loss 11-12 1311.89 Sep 9th 2023 Mens So Cal Sectional Championship
78 Drought Loss 9-15 858.63 Sep 10th 2023 Mens So Cal Sectional Championship
66 OC Crows Loss 7-11 969.99 Sep 10th 2023 Mens So Cal Sectional Championship
3 Revolver** Loss 6-15 1645.3 Ignored Sep 23rd 2023 Southwest Mens Regional Championship
171 Sonoran Dog Win 15-7 1428.2 Sep 23rd 2023 Southwest Mens Regional Championship
140 Mavericks Win 15-5 1573.6 Sep 23rd 2023 Southwest Mens Regional Championship
78 Drought Win 12-10 1612.23 Sep 24th 2023 Southwest Mens Regional Championship
22 SoCal Condors Loss 5-15 1252.4 Sep 24th 2023 Southwest Mens Regional Championship
66 OC Crows Win 15-13 1651.06 Sep 24th 2023 Southwest Mens Regional 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)