#71 Big Wrench (13-12)

avg: 1395.01  •  sd: 49.96  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
- Retired Win 13-10 1395 Jun 18th Sprout Round Robin
24 Blueprint Loss 10-13 1436.37 Jun 18th Sprout Round Robin
26 Sprout Loss 11-13 1516.92 Jun 18th Sprout Round Robin
111 Regiment Win 13-7 1718.25 Jul 15th Boston Invite 2023
32 Scoop Loss 8-9 1550.57 Jul 15th Boston Invite 2023
60 Switchback Win 11-8 1841.38 Jul 15th Boston Invite 2023
16 General Strike Loss 7-12 1416.09 Jul 15th Boston Invite 2023
109 Ascension Win 15-9 1684.26 Aug 5th Vacationland
154 Odyssey Win 15-4 1494.28 Aug 5th Vacationland
79 Red Tide Win 14-11 1685.26 Aug 5th Vacationland
137 Expendables Win 15-13 1212.58 Aug 6th Vacationland
51 TireBizFriz Loss 10-12 1314.38 Aug 6th Vacationland
62 Shade Win 13-11 1678.48 Aug 6th Vacationland
133 BAG Win 12-6 1613.61 Sep 9th 2023 Mens East New England Sectional Championship
- WHUF [B] Win 14-11 1527.21 Sep 9th 2023 Mens East New England Sectional Championship
79 Red Tide Loss 9-13 953.36 Sep 9th 2023 Mens East New England Sectional Championship
44 Red Circus Loss 9-15 1070.36 Sep 9th 2023 Mens East New England Sectional Championship
79 Red Tide Win 12-7 1892.44 Sep 10th 2023 Mens East New England Sectional Championship
44 Red Circus Loss 10-13 1257.7 Sep 10th 2023 Mens East New England Sectional Championship
158 Alibi Win 15-8 1452.75 Sep 23rd 2023 Northeast Mens Regional Championship
51 TireBizFriz Loss 8-13 1056.34 Sep 23rd 2023 Northeast Mens Regional Championship
94 Magma Bears Loss 11-12 1166.23 Sep 23rd 2023 Northeast Mens Regional Championship
51 TireBizFriz Loss 7-15 952.5 Sep 23rd 2023 Northeast Mens Regional Championship
158 Alibi Win 15-5 1487.94 Sep 24th 2023 Northeast Mens Regional Championship
62 Shade Loss 9-11 1200.43 Sep 24th 2023 Northeast Mens 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)