#66 HVAC (17-5)

avg: 1244.45  •  sd: 64.94  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
46 Revival Loss 8-12 994.9 Jun 24th Seven Cities Show Down
177 District Cocktails Win 12-6 1228.93 Jun 24th Seven Cities Show Down
234 Voltage** Win 13-1 841.9 Ignored Jun 24th Seven Cities Show Down
124 Magnanimouse Win 13-8 1457.74 Jun 24th Seven Cities Show Down
177 District Cocktails Win 15-11 1030.78 Jun 25th Seven Cities Show Down
104 Legion Loss 10-11 909.18 Jun 25th Seven Cities Show Down
124 Magnanimouse Win 12-5 1561.58 Jun 25th Seven Cities Show Down
114 One More Year Win 12-8 1439.48 Jul 15th MILK round robin
97 Farm Show Win 13-7 1612.62 Jul 15th MILK round robin
242 Ultra Instinct** Win 13-5 710.9 Ignored Jul 15th MILK round robin
213 Milk Win 8-5 880.96 Jul 15th MILK round robin
78 Deadweight Loss 10-12 923.52 Aug 19th Philly Invite 2023
175 Philly Twist Win 10-7 1045.21 Aug 19th Philly Invite 2023
106 Ant Madness Win 13-9 1446.47 Aug 19th Philly Invite 2023
38 Pittsburgh Port Authority Loss 10-15 1047.5 Aug 20th Philly Invite 2023
59 Greater Baltimore Anthem Win 14-13 1434.03 Aug 20th Philly Invite 2023
65 League of Shadows Win 15-13 1462.87 Aug 20th Philly Invite 2023
201 Spice** Win 13-5 1123.93 Ignored Sep 9th 2023 Mixed Capital Sectional Championship
114 One More Year Win 11-8 1363.93 Sep 9th 2023 Mixed Capital Sectional Championship
250 Vanguard and Friends** Win 13-4 478.94 Ignored Sep 9th 2023 Mixed Capital Sectional Championship
14 Rally Loss 4-15 1233.74 Sep 10th 2023 Mixed Capital Sectional Championship
91 Brackish Win 11-10 1211.1 Sep 10th 2023 Mixed Capital 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)