#151 Predator (11-9)

avg: 766.7  •  sd: 70.94  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
106 H.O.G. Ultimate Loss 7-11 540.23 Jul 6th Huntsville Huckfest 2019
35 Tanasi** Loss 2-11 873.63 Ignored Jul 6th Huntsville Huckfest 2019
186 Battleship Win 11-4 1152.69 Jul 6th Huntsville Huckfest 2019
198 Villains Win 11-5 1073.7 Jul 6th Huntsville Huckfest 2019
66 Ironmen Loss 2-11 628.16 Jul 7th Huntsville Huckfest 2019
187 Rampage Win 11-10 658.03 Jul 7th Huntsville Huckfest 2019
192 Trent's Team Win 11-9 768.06 Jul 7th Huntsville Huckfest 2019
122 Cockfight Loss 8-9 798.45 Jul 20th 2019 Club Terminus
140 Space Coast Ultimate Loss 10-11 708.66 Jul 20th 2019 Club Terminus
202 War Machine Win 12-6 1015.48 Jul 20th 2019 Club Terminus
81 Bullet Loss 2-13 526.43 Jul 20th 2019 Club Terminus
106 H.O.G. Ultimate Win 11-9 1256.33 Jul 21st 2019 Club Terminus
140 Space Coast Ultimate Win 10-8 1096.32 Jul 21st 2019 Club Terminus
126 Rougaroux Win 10-7 1294.69 Jul 21st 2019 Club Terminus
124 Swamp Horse Loss 8-11 549.77 Aug 17th Mudbowl 2019
168 Barefoot Loss 12-13 548.23 Aug 17th Mudbowl 2019
192 Trent's Team Win 11-4 1118.85 Aug 17th Mudbowl 2019
212 Gentlemen's Club Win 12-9 729.86 Aug 18th Mudbowl 2019
186 Battleship Loss 4-13 -47.31 Aug 18th Mudbowl 2019
202 War Machine Win 11-10 561.17 Aug 18th Mudbowl 2019
**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)