#97 Farm Show (12-7)

avg: 1055.09  •  sd: 67.93  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
66 HVAC Loss 7-13 686.92 Jul 15th MILK round robin
213 Milk Win 10-8 690.02 Jul 15th MILK round robin
114 One More Year Win 10-7 1387.99 Aug 5th Philly Open 2023
62 Funk Loss 9-10 1136.89 Aug 5th Philly Open 2023
217 Compost Plates** Win 13-3 1002.26 Ignored Aug 5th Philly Open 2023
146 Heavy Flow Win 13-5 1423.99 Aug 5th Philly Open 2023
141 PS Win 13-7 1402.1 Aug 6th Philly Open 2023
71 Grand Army Loss 5-10 630.41 Aug 6th Philly Open 2023
147 FLI Win 13-8 1314.45 Aug 26th The Incident 2023
183 Starfire Win 13-6 1202.97 Aug 27th The Incident 2023
183 Starfire Win 13-6 1202.97 Aug 27th The Incident 2023
149 ColorBomb Loss 9-11 556.1 Aug 27th The Incident 2023
155 NY Swipes Win 13-7 1347.95 Aug 27th The Incident 2023
243 NYWT** Win 13-4 703.75 Ignored Aug 27th The Incident 2023
38 Pittsburgh Port Authority Loss 7-13 943.58 Sep 9th 2023 Mixed Founders Sectional Championship
141 PS Win 13-8 1340.73 Sep 9th 2023 Mixed Founders Sectional Championship
242 Ultra Instinct Win 13-6 710.9 Sep 9th 2023 Mixed Founders Sectional Championship
24 Loco** Loss 4-13 1070.85 Ignored Sep 10th 2023 Mixed Founders Sectional Championship
50 Jughandle Loss 6-12 814.14 Sep 10th 2023 Mixed Founders 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)