#232 Voltage (3-14)

avg: 248.87  •  sd: 71.67  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
46 Revival** Loss 2-13 853.7 Ignored Jun 24th Seven Cities Show Down
180 District Cocktails Loss 3-13 65.86 Jun 24th Seven Cities Show Down
67 HVAC** Loss 1-13 662.34 Ignored Jun 24th Seven Cities Show Down
122 Magnanimouse** Loss 2-13 381.28 Ignored Jun 24th Seven Cities Show Down
163 Espionage Loss 3-14 179.5 Jun 25th Seven Cities Show Down
197 Swampbenders Loss 4-15 -41.81 Jun 25th Seven Cities Show Down
163 Espionage Loss 5-10 205.61 Aug 5th Philly Open 2023
207 Buffalo Brain Freeze Loss 6-7 351.39 Aug 5th Philly Open 2023
243 NYWT Win 13-7 672.14 Aug 5th Philly Open 2023
58 Garbage Plates** Loss 2-13 717.32 Ignored Aug 5th Philly Open 2023
220 Compost Plates Win 7-6 512.94 Aug 6th Philly Open 2023
241 Ultra Instinct Win 9-7 401.48 Aug 6th Philly Open 2023
106 Ant Madness** Loss 2-15 441.14 Ignored Sep 9th 2023 Mixed Capital Sectional Championship
57 Greater Baltimore Anthem** Loss 1-15 718.14 Ignored Sep 9th 2023 Mixed Capital Sectional Championship
163 Espionage Loss 6-14 179.5 Sep 10th 2023 Mixed Capital Sectional Championship
197 Swampbenders Loss 8-13 62.03 Sep 10th 2023 Mixed Capital Sectional Championship
197 Swampbenders Loss 7-10 168.52 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)