#9 SoCal Condors (17-2)

avg: 1970.39  •  sd: 85.19  •  top 16/20: 97.6%

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# Opponent Result Game Rating Status Date Event
11 Johnny Bravo Win 14-13 2023.7 Jul 13th TCT Pro Elite Challenge 2019
3 PoNY Loss 11-13 1939.17 Jul 13th TCT Pro Elite Challenge 2019
18 Patrol Win 13-7 2295.85 Jul 13th TCT Pro Elite Challenge 2019
16 Chain Lightning Win 13-9 2255.54 Jul 14th TCT Pro Elite Challenge 2019
14 Doublewide Loss 10-13 1544.15 Jul 14th TCT Pro Elite Challenge 2019
32 Prairie Fire Win 13-8 2010.27 Jul 14th TCT Pro Elite Challenge 2019
16 Chain Lightning Win 16-14 2045.26 Aug 17th TCT Elite Select Challenge 2019
32 Prairie Fire Win 15-6 2114.11 Aug 17th TCT Elite Select Challenge 2019
57 Red Circus** Win 15-5 1882.69 Ignored Aug 17th TCT Elite Select Challenge 2019
11 Johnny Bravo Win 11-10 2023.7 Aug 18th TCT Elite Select Challenge 2019
10 DiG Win 10-8 2229.71 Aug 18th TCT Elite Select Challenge 2019
15 Rhino Slam! Win 10-7 2243.21 Aug 18th TCT Elite Select Challenge 2019
194 Goaltimate All Stars** Win 13-0 1103.16 Ignored Sep 7th So Cal Mens Club Sectional Championship 2019
119 DOGGPOUND Win 13-6 1549.84 Sep 7th So Cal Mens Club Sectional Championship 2019
55 Streetgang Win 13-9 1708.17 Sep 7th So Cal Mens Club Sectional Championship 2019
228 desert penguins** Win 13-0 826.12 Ignored Sep 7th So Cal Mens Club Sectional Championship 2019
61 Sundowners Win 13-7 1825.6 Sep 8th So Cal Mens Club Sectional Championship 2019
165 OC Crows** Win 13-2 1295.41 Ignored Sep 8th So Cal Mens Club Sectional Championship 2019
61 Sundowners** Win 15-5 1868.07 Ignored Sep 8th So Cal Mens Club Sectional Championship 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)