#55 Sureshot (16-13)

avg: 694.64  •  sd: 38.73  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
57 Helix Win 11-9 921.62 Jun 16th SCINNY 2018
58 Stellar Win 11-9 912.49 Jun 16th SCINNY 2018
75 Autonomous Win 13-1 735.98 Jun 16th SCINNY 2018
31 Indy Rogue Loss 3-13 603.99 Jun 16th SCINNY 2018
60 Eliza Furnace Win 12-8 1047.73 Jun 24th SCINNY 2018
49 Sparks Loss 8-13 328.43 Jun 24th SCINNY 2018
34 Dish Loss 6-13 560.8 Jun 24th SCINNY 2018
73 Honey Pot Win 15-9 764.91 Jul 7th Huckfest 2018
59 Queen Cake Win 12-11 739.29 Jul 7th Huckfest 2018
40 Steel Loss 5-15 441 Jul 7th Huckfest 2018
59 Queen Cake Win 11-8 979.9 Jul 8th Huckfest 2018
40 Steel Loss 7-15 441 Jul 8th Huckfest 2018
50 Cold Cuts Loss 12-13 693.27 Aug 18th Cooler Classic 30
74 MystiKuE Win 13-5 831.1 Aug 18th Cooler Classic 30
66 Iowa Wild Rose Win 13-10 805.41 Aug 18th Cooler Classic 30
44 Crackle Loss 7-13 409.21 Aug 18th Cooler Classic 30
34 Dish Loss 5-13 560.8 Aug 19th Cooler Classic 30
70 Lady Forward Win 15-10 831.56 Aug 19th Cooler Classic 30
50 Cold Cuts Loss 11-14 504.93 Aug 19th Cooler Classic 30
75 Autonomous Win 11-3 735.98 Aug 25th Indy Invite Club 2018
74 MystiKuE Win 7-3 831.1 Aug 25th Indy Invite Club 2018
49 Sparks Win 13-12 949.59 Sep 15th East Plains Womens Sectional Championship 2018
61 Notorious C.L.E. Win 12-9 941.81 Sep 15th East Plains Womens Sectional Championship 2018
10 Nemesis** Loss 4-13 1224.48 Ignored Sep 22nd Great Lakes Womens Regional Championship 2018
31 Indy Rogue Loss 8-13 707.83 Sep 22nd Great Lakes Womens Regional Championship 2018
61 Notorious C.L.E. Win 10-9 721.45 Sep 22nd Great Lakes Womens Regional Championship 2018
75 Autonomous Win 15-6 735.98 Sep 22nd Great Lakes Womens Regional Championship 2018
34 Dish Loss 11-15 779.63 Sep 23rd Great Lakes Womens Regional Championship 2018
61 Notorious C.L.E. Loss 8-14 60.41 Sep 23rd Great Lakes 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)