#129 Foxtrot (11-15)

avg: 1042.89  •  sd: 52.05  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
146 Ronin Loss 11-13 722.66 Jun 24th Huntsville Huckfest
124 Battleship Loss 8-10 798.26 Jun 24th Huntsville Huckfest
207 Villains Win 11-7 1066.83 Jun 24th Huntsville Huckfest
150 Nashville Mudcats Loss 10-11 801.2 Jun 24th Huntsville Huckfest
116 Atlanta Arson Loss 9-11 894.68 Jun 25th Huntsville Huckfest
118 Raptor Loss 7-11 644.7 Jun 25th Huntsville Huckfest
172 Memphis Pharaohs Loss 8-9 700.27 Jun 25th Huntsville Huckfest
68 Brawl Loss 6-11 871.86 Jul 22nd Riverside Classic 2023
165 Firefly TX Win 11-5 1458.17 Jul 22nd Riverside Classic 2023
125 Cowtown Cannons Win 12-8 1497.77 Jul 22nd Riverside Classic 2023
197 Texas United Win 12-5 1297.04 Jul 22nd Riverside Classic 2023
105 Dreadnought Loss 12-14 966.88 Jul 23rd Riverside Classic 2023
68 Brawl Win 9-8 1543.55 Jul 23rd Riverside Classic 2023
122 Lil Heroes Win 15-13 1302.6 Jul 23rd Riverside Classic 2023
168 San Antonio Warhawks Win 13-3 1431.23 Aug 12th PBJ 2023
97 Texas Duffy Loss 9-11 1032.94 Aug 12th PBJ 2023
165 Firefly TX Win 10-7 1247.84 Aug 12th PBJ 2023
168 San Antonio Warhawks Win 8-7 956.23 Aug 13th PBJ 2023
165 Firefly TX Loss 11-12 733.17 Aug 13th PBJ 2023
122 Lil Heroes Loss 11-13 859.58 Aug 13th PBJ 2023
68 Brawl Loss 7-13 861.02 Sep 9th 2023 Mens Texas Sectional Championship
203 Shrimp Discs Win 13-6 1252.03 Sep 9th 2023 Mens Texas Sectional Championship
153 Sprawl Loss 7-8 773.87 Sep 9th 2023 Mens Texas Sectional Championship
50 H.I.P Loss 11-13 1324.67 Sep 9th 2023 Mens Texas Sectional Championship
222 RGV Tlacuaches Win 15-3 1106.77 Sep 10th 2023 Mens Texas Sectional Championship
165 Firefly TX Loss 11-12 733.17 Sep 10th 2023 Mens Texas 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)