#44 Crackle (14-11)

avg: 966.74  •  sd: 56.56  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
66 Iowa Wild Rose Win 13-7 1034.8 Jun 30th Spirit of the Plains 2018
66 Iowa Wild Rose Win 11-4 1077.26 Jun 30th Spirit of the Plains 2018
26 Elevate Loss 6-13 801.11 Jul 28th TCT Select Flight Invite 2018
43 Green Means Go Win 13-6 1596.6 Jul 28th TCT Select Flight Invite 2018
57 Helix Win 13-8 1168.57 Jul 28th TCT Select Flight Invite 2018
36 Seattle Soul Loss 6-8 801.71 Jul 28th TCT Select Flight Invite 2018
32 FAB Loss 6-11 644 Jul 29th TCT Select Flight Invite 2018
25 Colorado Small Batch Loss 7-13 889.57 Jul 29th TCT Select Flight Invite 2018
31 Indy Rogue Loss 6-13 603.99 Jul 29th TCT Select Flight Invite 2018
55 Sureshot Win 13-7 1252.17 Aug 18th Cooler Classic 30
74 MystiKuE Win 13-7 788.64 Aug 18th Cooler Classic 30
66 Iowa Wild Rose Win 13-2 1077.26 Aug 18th Cooler Classic 30
34 Dish Loss 12-13 1035.8 Aug 18th Cooler Classic 30
50 Cold Cuts Win 15-11 1199.43 Aug 19th Cooler Classic 30
70 Lady Forward Win 15-5 977.96 Aug 19th Cooler Classic 30
34 Dish Loss 11-12 1035.8 Aug 19th Cooler Classic 30
50 Cold Cuts Loss 11-12 693.27 Sep 8th Northwest Plains Womens Sectional Championship 2018
70 Lady Forward Win 10-6 874.12 Sep 8th Northwest Plains Womens Sectional Championship 2018
74 MystiKuE** Win 13-3 831.1 Ignored Sep 8th Northwest Plains Womens Sectional Championship 2018
16 Heist** Loss 4-15 1122.08 Ignored Sep 22nd North Central Womens Regional Championship 2018
50 Cold Cuts Win 13-11 1047.11 Sep 22nd North Central Womens Regional Championship 2018
66 Iowa Wild Rose Win 10-6 973.42 Sep 22nd North Central Womens Regional Championship 2018
24 Wicked Loss 3-15 892.17 Sep 23rd North Central Womens Regional Championship 2018
19 Pop** Loss 6-15 1079.32 Ignored Sep 23rd North Central Womens Regional Championship 2018
66 Iowa Wild Rose Win 10-7 866.93 Sep 23rd North Central Womens 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)