#137 Catalyst (8-9)

avg: 854.77  •  sd: 65.87  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
187 Oasis Ultimate Win 15-9 1093.82 Jul 8th Summer Glazed Daze 2023
219 Flood Zone Win 15-8 941.72 Jul 8th Summer Glazed Daze 2023
98 FlyTrap Loss 10-11 928.4 Jul 8th Summer Glazed Daze 2023
148 Verdant Win 14-13 935.39 Jul 9th Summer Glazed Daze 2023
237 Rampage Win 13-6 803.33 Jul 22nd Filling the Void 2023
248 Pickles** Win 13-3 626.54 Ignored Jul 22nd Filling the Void 2023
106 Ant Madness Loss 10-11 902.9 Jul 22nd Filling the Void 2023
91 Brackish Win 13-6 1686.1 Jul 22nd Filling the Void 2023
133 904 Shipwreck Loss 9-12 528.26 Jul 23rd Filling the Void 2023
61 Malice in Wonderland Loss 6-15 694.25 Jul 23rd Filling the Void 2023
104 Legion Loss 7-8 909.18 Jul 23rd Filling the Void 2023
237 Rampage Win 11-6 750.03 Sep 9th 2023 Mixed North Carolina Sectional Championship
248 Pickles** Win 13-4 626.54 Ignored Sep 9th 2023 Mixed North Carolina Sectional Championship
108 Bear Jordan Loss 8-13 530.93 Sep 9th 2023 Mixed North Carolina Sectional Championship
61 Malice in Wonderland Loss 11-13 1065.41 Sep 9th 2023 Mixed North Carolina Sectional Championship
69 Too Much Fun Loss 8-12 776.12 Sep 10th 2023 Mixed North Carolina Sectional Championship
124 Magnanimouse Loss 11-15 580.42 Sep 10th 2023 Mixed North Carolina 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)