#154 Odyssey (10-17)

avg: 894.28  •  sd: 67.27  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
158 Alibi Loss 8-13 391.78 Jul 8th AntlerLock
230 Bartle Boys Win 13-10 759.06 Jul 8th AntlerLock
189 Dirty Laundry Win 10-9 873.17 Jul 8th AntlerLock
79 Red Tide Loss 4-15 771.93 Jul 8th AntlerLock
189 Dirty Laundry Loss 3-14 148.17 Jul 9th AntlerLock
226 Buffalo Frostbite Win 14-5 1086.54 Jul 9th AntlerLock
109 Ascension Loss 7-11 701.88 Jul 15th Boston Invite 2023
133 BAG Loss 2-13 434.3 Jul 15th Boston Invite 2023
169 MBTA Loss 7-9 551.28 Jul 15th Boston Invite 2023
94 Magma Bears Loss 4-12 691.23 Jul 15th Boston Invite 2023
109 Ascension Loss 10-14 770.08 Aug 5th Vacationland
71 Big Wrench Loss 4-15 795.01 Aug 5th Vacationland
62 Shade Loss 4-9 849.64 Aug 5th Vacationland
169 MBTA Loss 11-13 601.77 Aug 6th Vacationland
231 Madhouse Win 15-9 938.7 Aug 6th Vacationland
102 Harvey Cats Loss 9-13 788.63 Aug 26th The Incident 2023
70 OAT Loss 9-12 1054.1 Aug 26th The Incident 2023
202 Spring Break '93 Win 13-2 1260.13 Aug 26th The Incident 2023
209 Long Island Riff Raff Win 13-8 1085.7 Aug 26th The Incident 2023
235 Adelphos Win 13-5 974.59 Aug 27th The Incident 2023
189 Dirty Laundry Loss 11-12 623.17 Aug 27th The Incident 2023
7 DiG** Loss 5-15 1567.51 Ignored Sep 9th 2023 Mens East New England Sectional Championship
43 Mystery Box Loss 7-14 1014.65 Sep 9th 2023 Mens East New England Sectional Championship
169 MBTA Win 15-8 1395.42 Sep 9th 2023 Mens East New England Sectional Championship
133 BAG Win 13-11 1263.14 Sep 10th 2023 Mens East New England Sectional Championship
43 Mystery Box** Loss 6-15 997.54 Ignored Sep 10th 2023 Mens East New England Sectional Championship
79 Red Tide Win 15-14 1496.93 Sep 10th 2023 Mens East New England 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)