#63 Pine Baroness (7-7)

avg: 696.66  •  sd: 77.67  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
15 Iris** Loss 5-13 1147.14 Ignored Jul 15th Boston Invite 2023
- Vintage Loss 5-10 587.25 Jul 15th Boston Invite 2023
- Rip Tide Win 7-6 696.65 Jul 15th Boston Invite 2023
- Tempest Win 10-7 911.3 Jul 15th Boston Invite 2023
48 Venus Win 3-2 1071.23 Jul 16th Boston Invite 2023
47 Vice Loss 7-11 481.36 Aug 5th Philly Open 2023
42 Wave Loss 6-13 437.44 Aug 5th Philly Open 2023
37 Agency Loss 8-11 783.47 Aug 5th Philly Open 2023
94 Dissent** Win 13-2 626.69 Ignored Aug 5th Philly Open 2023
86 Versa Win 11-4 763.15 Aug 6th Philly Open 2023
73 Incline Loss 8-10 207.62 Aug 6th Philly Open 2023
23 Flight Loss 7-15 939.4 Sep 9th 2023 Womens Founders Sectional Championship
- Splurge Win 15-5 870 Sep 9th 2023 Womens Founders Sectional Championship
- Phang** Win 15-4 443.35 Ignored Sep 9th 2023 Womens Founders Sectional 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)