#207 Buffalo Brain Freeze (5-21)

avg: 479.62  •  sd: 55.1  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
96 Bench Loss 8-12 626.44 Jun 11th Rochester Round Robin
217 Compost Plates Loss 8-9 277.26 Jun 11th Rochester Round Robin
84 Buffalo Lake Effect** Loss 3-13 530.22 Ignored Jun 11th Rochester Round Robin
119 Mashed Loss 9-10 858.99 Jun 11th Rochester Round Robin
40 UNION** Loss 3-11 891.86 Ignored Jun 11th Rochester Round Robin
146 Heavy Flow Loss 7-13 266.46 Jun 24th LVU’s Disc Days of Summer 2023
184 Crucible Loss 4-11 0.41 Jun 24th LVU’s Disc Days of Summer 2023
68 Heat Wave** Loss 4-12 636.17 Ignored Jun 24th LVU’s Disc Days of Summer 2023
55 Garbage Plates Loss 8-13 846.11 Jun 24th LVU’s Disc Days of Summer 2023
183 Starfire Loss 9-10 477.97 Jun 25th LVU’s Disc Days of Summer 2023
147 FLI Loss 7-10 428.63 Jun 25th LVU’s Disc Days of Summer 2023
147 FLI Loss 6-12 238.98 Jul 8th AntlerLock
44 The Buoy Association Loss 8-14 937.98 Jul 8th AntlerLock
168 Default Loss 9-12 395.99 Jul 8th AntlerLock
190 Rainbow Win 7-4 1061.41 Jul 9th AntlerLock
120 WHUF [B] Loss 7-14 389 Jul 9th AntlerLock
245 Vintage Ultimate Club Win 15-7 672.48 Jul 9th AntlerLock
201 Spice Loss 9-12 178.56 Aug 5th Philly Open 2023
216 Brooklyn Hive Loss 8-11 39.46 Aug 5th Philly Open 2023
55 Garbage Plates** Loss 3-12 742.27 Ignored Aug 5th Philly Open 2023
234 Voltage Win 7-6 366.9 Aug 5th Philly Open 2023
242 Ultra Instinct Win 11-7 577.79 Aug 6th Philly Open 2023
243 NYWT Win 11-8 469.36 Aug 6th Philly Open 2023
55 Garbage Plates** Loss 4-13 742.27 Ignored Sep 9th 2023 Mixed Upstate New York Sectional Championship
48 Townies** Loss 4-13 802.86 Ignored Sep 9th 2023 Mixed Upstate New York Sectional Championship
96 Bench Loss 9-13 649.03 Sep 10th 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)