#197 Swampbenders (7-16)

avg: 558.19  •  sd: 44.04  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
163 Espionage Loss 5-11 179.5 Jun 24th Seven Cities Show Down
202 Spice Win 9-7 815.04 Jun 24th Seven Cities Show Down
106 Ant Madness Loss 5-11 441.14 Jun 24th Seven Cities Show Down
105 Legion Loss 5-11 443.98 Jun 24th Seven Cities Show Down
93 Brackish Loss 4-11 497.19 Jun 24th Seven Cities Show Down
163 Espionage Loss 11-14 466.17 Jun 25th Seven Cities Show Down
232 Voltage Win 15-4 848.87 Jun 25th Seven Cities Show Down
206 Piedmont United Win 10-9 613.76 Jul 22nd Filling the Void 2023
105 Legion Loss 6-12 464.67 Jul 22nd Filling the Void 2023
66 Malice in Wonderland** Loss 3-13 668.7 Ignored Jul 22nd Filling the Void 2023
130 904 Shipwreck Loss 6-14 308.32 Jul 23rd Filling the Void 2023
85 Too Much Fun Loss 6-12 571.21 Jul 23rd Filling the Void 2023
97 Scarecrow Loss 6-13 474.23 Aug 5th Philly Open 2023
65 Grand Army** Loss 5-13 674.14 Ignored Aug 5th Philly Open 2023
186 Crucible Win 9-6 1034.48 Aug 5th Philly Open 2023
139 Goosebumps Loss 9-11 621.24 Aug 5th Philly Open 2023
177 Eat Lightning Loss 7-10 282.83 Aug 6th Philly Open 2023
186 Crucible Win 12-10 854.04 Aug 6th Philly Open 2023
106 Ant Madness Loss 8-12 599.98 Sep 9th 2023 Mixed Capital Sectional Championship
57 Greater Baltimore Anthem** Loss 6-15 718.14 Ignored Sep 9th 2023 Mixed Capital Sectional Championship
214 Deep Cut Loss 11-13 206.93 Sep 10th 2023 Mixed Capital Sectional Championship
232 Voltage Win 13-8 745.03 Sep 10th 2023 Mixed Capital Sectional Championship
232 Voltage Win 10-7 638.54 Sep 10th 2023 Mixed Capital 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)