#17 Sprout (16-4)

avg: 1767.5  •  sd: 120.74  •  top 16/20: 41.7%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
141 Regiment** Win 15-6 1439.81 Ignored Jun 22nd Boston Invite 2019
95 Red Tide Win 15-7 1677.07 Jun 22nd Boston Invite 2019
44 Shade Win 14-10 1807.89 Jun 22nd Boston Invite 2019
51 Lantern Win 15-1 1958.82 Jun 23rd Boston Invite 2019
53 Colt Win 15-7 1940.96 Jun 23rd Boston Invite 2019
8 DiG Loss 12-14 1730.78 Jun 23rd Boston Invite 2019
94 Log Jam** Win 15-3 1677.67 Ignored Jul 6th AntlerLock 2019
62 Big Wrench Win 13-11 1505.48 Jul 6th AntlerLock 2019
95 Red Tide Win 15-7 1677.07 Jul 6th AntlerLock 2019
104 Burly** Win 15-6 1625.93 Ignored Jul 7th AntlerLock 2019
62 Big Wrench Win 15-5 1876.64 Jul 7th AntlerLock 2019
241 defunCT** Win 15-0 438.58 Ignored Jul 7th AntlerLock 2019
10 GOAT Loss 12-13 1756 Sep 21st Northeast Club Mens Regional Championship 2019
35 Blueprint Win 13-7 2034.72 Sep 21st Northeast Club Mens Regional Championship 2019
112 Somerville BAG Win 13-6 1593.38 Sep 21st Northeast Club Mens Regional Championship 2019
54 Red Circus Win 13-8 1821.9 Sep 21st Northeast Club Mens Regional Championship 2019
10 GOAT Loss 10-14 1482.3 Sep 22nd Northeast Club Mens Regional Championship 2019
66 Deathsquad Win 15-11 1623.48 Sep 22nd Northeast Club Mens Regional Championship 2019
4 PoNY Loss 14-16 1900.13 Sep 22nd Northeast Club Mens Regional Championship 2019
54 Red Circus Win 15-6 1925.74 Sep 22nd Northeast Club Mens Regional 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)