#26 Sprout (15-9)

avg: 1745.77  •  sd: 73.65  •  top 16/20: 0.2%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
71 Big Wrench Win 13-11 1623.85 Jun 18th Sprout Round Robin
24 Blueprint Loss 8-13 1268.36 Jun 18th Sprout Round Robin
- Tire Win 13-5 1992.63 Jun 18th Sprout Round Robin
24 Blueprint Win 12-10 2002.64 Jul 15th Boston Invite 2023
79 Red Tide Win 12-9 1717.29 Jul 15th Boston Invite 2023
92 Club M - Manic Win 13-6 1891.42 Jul 15th Boston Invite 2023
82 Lantern Win 13-4 1949.71 Jul 15th Boston Invite 2023
39 Pittsburgh Temper Win 15-12 1925.2 Aug 19th TCT Elite Select Challenge 2023
13 Vault Loss 11-12 1879.36 Aug 19th TCT Elite Select Challenge 2023
27 Omen Loss 11-15 1358.62 Aug 19th TCT Elite Select Challenge 2023
50 H.I.P Win 15-12 1854 Aug 20th TCT Elite Select Challenge 2023
39 Pittsburgh Temper Loss 7-12 1104.2 Aug 20th TCT Elite Select Challenge 2023
25 Mad Men Loss 10-14 1358.57 Aug 20th TCT Elite Select Challenge 2023
- You Need to Calm Down** Win 13-2 1168.77 Ignored Sep 9th 2023 Mens West New England Sectional Championship
- ClubM - MESA** Win 13-4 600 Ignored Sep 9th 2023 Mens West New England Sectional Championship
109 Ascension Win 13-6 1768.78 Sep 10th 2023 Mens West New England Sectional Championship
51 TireBizFriz Loss 12-13 1427.5 Sep 10th 2023 Mens West New England Sectional Championship
24 Blueprint Win 12-10 2002.64 Sep 23rd 2023 Northeast Mens Regional Championship
15 GOAT Loss 10-13 1644.13 Sep 23rd 2023 Northeast Mens Regional Championship
21 Phoenix Loss 13-15 1645.07 Sep 23rd 2023 Northeast Mens Regional Championship
94 Magma Bears Win 15-8 1856.04 Sep 23rd 2023 Northeast Mens Regional Championship
32 Scoop Win 15-9 2191.05 Sep 24th 2023 Northeast Mens Regional Championship
24 Blueprint Loss 11-14 1451.18 Sep 24th 2023 Northeast Mens Regional Championship
15 GOAT Win 14-11 2285.61 Sep 24th 2023 Northeast Mens Regional Championship
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)