#147 FLI (10-13)

avg: 818.29  •  sd: 51.28  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
55 Garbage Plates Loss 8-10 1079.6 Jun 24th LVU’s Disc Days of Summer 2023
146 Heavy Flow Win 8-6 1124.48 Jun 24th LVU’s Disc Days of Summer 2023
184 Crucible Win 11-10 725.41 Jun 24th LVU’s Disc Days of Summer 2023
68 Heat Wave Loss 7-8 1111.17 Jun 24th LVU’s Disc Days of Summer 2023
141 PS Loss 7-9 565.23 Jun 25th LVU’s Disc Days of Summer 2023
207 Buffalo Brain Freeze Win 10-7 869.28 Jun 25th LVU’s Disc Days of Summer 2023
95 Scarecrow Loss 7-12 547.99 Jul 8th AntlerLock
207 Buffalo Brain Freeze Win 12-6 1058.93 Jul 8th AntlerLock
168 Default Win 11-8 1106.97 Jul 8th AntlerLock
44 The Buoy Association** Loss 4-10 874.01 Ignored Jul 8th AntlerLock
163 Sunken Circus Loss 8-10 509.07 Jul 9th AntlerLock
130 Zero Strategy Loss 5-6 766.48 Jul 9th AntlerLock
97 Farm Show Loss 8-13 558.93 Aug 26th The Incident 2023
227 The Incidentals Win 13-6 913.98 Aug 26th The Incident 2023
155 NY Swipes Win 10-9 915.42 Aug 26th The Incident 2023
178 Eat Lightning Loss 9-10 524.39 Aug 27th The Incident 2023
183 Starfire Win 15-5 1202.97 Aug 27th The Incident 2023
155 NY Swipes Loss 9-11 541.21 Aug 27th The Incident 2023
183 Starfire Win 12-6 1182.28 Sep 9th 2023 Mixed Metro New York Sectional Championship
216 Brooklyn Hive Win 13-7 962.61 Sep 9th 2023 Mixed Metro New York Sectional Championship
62 Funk Loss 9-13 843.32 Sep 9th 2023 Mixed Metro New York Sectional Championship
68 Heat Wave Loss 8-13 740.01 Sep 9th 2023 Mixed Metro New York Sectional Championship
162 Room Temperature Loss 10-14 376.17 Sep 10th 2023 Mixed Metro 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)