#130 904 Shipwreck (7-7)

avg: 908.32  •  sd: 79.67  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
202 Spice Win 10-9 660.71 Jul 8th Summer Glazed Daze 2023
85 Too Much Fun Loss 8-11 784.91 Jul 8th Summer Glazed Daze 2023
96 Bear Jordan Loss 8-12 634.85 Jul 8th Summer Glazed Daze 2023
152 Verdant Loss 9-10 699.5 Jul 8th Summer Glazed Daze 2023
236 Rampage** Win 13-2 825.56 Ignored Jul 22nd Filling the Void 2023
248 Pickles** Win 13-2 650.83 Ignored Jul 22nd Filling the Void 2023
93 Brackish Loss 12-13 972.19 Jul 22nd Filling the Void 2023
106 Ant Madness Loss 12-13 916.14 Jul 22nd Filling the Void 2023
141 Catalyst Win 12-9 1211.74 Jul 23rd Filling the Void 2023
197 Swampbenders Win 14-6 1158.19 Jul 23rd Filling the Void 2023
93 Brackish Win 11-4 1697.19 Jul 23rd Filling the Void 2023
- Rocket Win 14-6 1075.06 Sep 9th 2023 Mixed Florida Sectional Championship
175 Oasis Ultimate Loss 11-12 569.07 Sep 9th 2023 Mixed Florida Sectional Championship
81 B-Unit Loss 8-13 680.22 Sep 9th 2023 Mixed Florida Sectional Championship
**Blowout Eligible

FAQ

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
  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
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)