#142 PS (11-13)

avg: 856.51  •  sd: 54.53  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
120 Mashed Win 13-12 1113.8 Jun 24th LVU’s Disc Days of Summer 2023
57 Greater Baltimore Anthem Loss 8-13 821.98 Jun 24th LVU’s Disc Days of Summer 2023
189 Starfire Win 13-3 1208.1 Jun 24th LVU’s Disc Days of Summer 2023
154 ColorBomb Win 13-7 1376.23 Jun 24th LVU’s Disc Days of Summer 2023
83 Buffalo Lake Effect Loss 7-9 881.3 Jun 25th LVU’s Disc Days of Summer 2023
149 FLI Win 9-7 1109.16 Jun 25th LVU’s Disc Days of Summer 2023
163 Espionage Loss 9-12 434.14 Aug 5th Philly Open 2023
216 Brooklyn Hive Win 11-8 783.61 Aug 5th Philly Open 2023
58 Garbage Plates Loss 9-12 971.96 Aug 5th Philly Open 2023
157 NY Swipes Win 11-10 937.66 Aug 5th Philly Open 2023
116 One More Year Loss 9-10 892.86 Aug 6th Philly Open 2023
98 Farm Show Loss 7-13 516.3 Aug 6th Philly Open 2023
57 Greater Baltimore Anthem Loss 8-15 753.33 Aug 19th Philly Invite 2023
70 League of Shadows Loss 10-12 1008.88 Aug 19th Philly Invite 2023
157 NY Swipes Loss 10-13 484.52 Aug 19th Philly Invite 2023
163 Espionage Win 13-8 1275.66 Aug 20th Philly Invite 2023
106 Ant Madness Loss 12-15 740.65 Aug 20th Philly Invite 2023
148 Heavy Flow Loss 11-15 453.99 Aug 20th Philly Invite 2023
98 Farm Show Loss 8-13 577.67 Sep 9th 2023 Mixed Founders Sectional Championship
241 Ultra Instinct** Win 13-3 722.15 Ignored Sep 9th 2023 Mixed Founders Sectional Championship
213 Milk Win 13-3 1041.23 Sep 9th 2023 Mixed Founders Sectional Championship
178 Philly Twist Win 11-7 1138.96 Sep 10th 2023 Mixed Founders Sectional Championship
178 Philly Twist Win 11-8 1037.67 Sep 10th 2023 Mixed Founders Sectional Championship
154 ColorBomb Loss 7-9 539.36 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)