#31 Metro North (10-15)

avg: 1556.32  •  sd: 53.45  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
12 Mischief Loss 11-12 1659.35 Jul 7th TCT Pro Elite Challenge 2018
13 Birdfruit Loss 9-13 1360.72 Jul 7th TCT Pro Elite Challenge 2018
10 shame. Loss 6-13 1244.73 Jul 7th TCT Pro Elite Challenge 2018
26 Alloy Win 12-10 1827.48 Jul 8th TCT Pro Elite Challenge 2018
21 Public Enemy Win 10-9 1800.65 Jul 8th TCT Pro Elite Challenge 2018
20 No Touching! Loss 8-11 1315.77 Jul 8th TCT Pro Elite Challenge 2018
73 Chaotic Good Win 13-5 1865.65 Aug 11th Chesapeake Open 2018
104 Shakedown Win 13-7 1658.1 Aug 11th Chesapeake Open 2018
30 Jughandle Win 10-7 1947.02 Aug 11th Chesapeake Open 2018
18 Loco Loss 9-12 1389.03 Aug 11th Chesapeake Open 2018
24 Rally Loss 8-12 1169.96 Aug 12th Chesapeake Open 2018
30 Jughandle Loss 8-11 1191.74 Aug 12th Chesapeake Open 2018
22 XIST Loss 12-13 1493.05 Sep 1st TCT Pro Championships 2018
3 Drag'n Thrust Loss 11-15 1637.06 Sep 1st TCT Pro Championships 2018
4 BFG Loss 10-15 1526.29 Sep 1st TCT Pro Championships 2018
20 No Touching! Loss 12-15 1380.89 Sep 1st TCT Pro Championships 2018
22 XIST Win 14-12 1839 Sep 2nd TCT Pro Championships 2018
11 Slow White Loss 11-13 1598.46 Sep 2nd TCT Pro Championships 2018
22 XIST Loss 11-13 1389.21 Sep 22nd Northeast Mixed Regional Championship 2018
92 Garbage Plates Win 11-10 1288.36 Sep 22nd Northeast Mixed Regional Championship 2018
58 Happy Valley Win 15-11 1692.58 Sep 22nd Northeast Mixed Regional Championship 2018
102 Titan NE Win 15-4 1706.96 Sep 22nd Northeast Mixed Regional Championship 2018
9 Wild Card Win 13-12 1998.65 Sep 23rd Northeast Mixed Regional Championship 2018
6 Snake Country Loss 11-15 1561.81 Sep 23rd Northeast Mixed Regional Championship 2018
11 Slow White Loss 9-15 1311.82 Sep 23rd Northeast Mixed Regional Championship 2018
**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)