#64 Obscure (8-6)

avg: 1250.38  •  sd: 44.75  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
111 Lampshade Win 13-12 1130.42 Jul 15th Boston Invite 2023
48 Townies Loss 8-13 906.7 Jul 15th Boston Invite 2023
183 Starfire** Win 13-5 1202.97 Ignored Jul 15th Boston Invite 2023
158 Lobrid Win 15-5 1385.95 Jul 15th Boston Invite 2023
95 Scarecrow Win 15-13 1282.68 Sep 9th 2023 Mixed East New England Sectional Championship
158 Lobrid Win 13-9 1204.52 Sep 9th 2023 Mixed East New England Sectional Championship
45 Wild Card Loss 7-13 900 Sep 9th 2023 Mixed East New England Sectional Championship
44 The Buoy Association Loss 10-11 1349.01 Sep 9th 2023 Mixed East New England Sectional Championship
47 Darkwing Loss 11-15 1038.33 Sep 10th 2023 Mixed East New England Sectional Championship
111 Lampshade Win 15-11 1386.58 Sep 10th 2023 Mixed East New England Sectional Championship
65 League of Shadows Win 13-11 1477.53 Sep 10th 2023 Mixed East New England Sectional Championship
47 Darkwing Loss 12-13 1294.5 Sep 23rd 2023 Northeast Mixed Regional Championship
7 XIST Loss 6-13 1320.86 Sep 23rd 2023 Northeast Mixed Regional Championship
84 Buffalo Lake Effect Win 15-12 1430.71 Sep 24th 2023 Northeast Mixed Regional 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)