#119 Mashed (11-9)

avg: 983.99  •  sd: 59.05  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
96 Bench Win 10-9 1192.59 Jun 11th Rochester Round Robin
207 Buffalo Brain Freeze Win 10-9 604.62 Jun 11th Rochester Round Robin
217 Compost Plates Win 13-4 1002.26 Jun 11th Rochester Round Robin
48 Townies Loss 3-13 802.86 Jun 11th Rochester Round Robin
141 PS Loss 12-13 719.57 Jun 24th LVU’s Disc Days of Summer 2023
183 Starfire Win 13-6 1202.97 Jun 24th LVU’s Disc Days of Summer 2023
84 Buffalo Lake Effect Loss 7-10 740.55 Jun 24th LVU’s Disc Days of Summer 2023
149 ColorBomb Win 13-6 1405.31 Jun 24th LVU’s Disc Days of Summer 2023
59 Greater Baltimore Anthem Loss 9-10 1184.03 Jun 25th LVU’s Disc Days of Summer 2023
146 Heavy Flow Win 12-8 1265.15 Jun 25th LVU’s Disc Days of Summer 2023
177 District Cocktails Win 11-9 898.83 Aug 5th Philly Open 2023
175 Philly Twist Win 10-9 780.55 Aug 5th Philly Open 2023
111 Lampshade Win 11-10 1130.42 Aug 5th Philly Open 2023
95 Scarecrow Win 13-6 1668.5 Aug 6th Philly Open 2023
62 Funk Loss 5-13 661.89 Aug 6th Philly Open 2023
24 Loco** Loss 4-13 1070.85 Ignored Aug 6th Philly Open 2023
96 Bench Loss 10-12 829.47 Sep 9th 2023 Mixed Upstate New York Sectional Championship
84 Buffalo Lake Effect Loss 7-9 850.88 Sep 9th 2023 Mixed Upstate New York Sectional Championship
217 Compost Plates Win 13-4 1002.26 Sep 9th 2023 Mixed Upstate New York Sectional Championship
40 UNION Loss 3-13 891.86 Sep 9th 2023 Mixed Upstate New York 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)