#44 Pennsylvania (6-8)

avg: 1484.31  •  sd: 77.07  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
69 Case Western Reserve Win 15-4 1850.46 Feb 25th Commonwealth Cup Weekend2 2023
129 Maryland** Win 15-2 1376.19 Ignored Feb 25th Commonwealth Cup Weekend2 2023
99 MIT Win 15-3 1583.32 Feb 25th Commonwealth Cup Weekend2 2023
32 SUNY-Binghamton Win 10-6 2147.75 Feb 26th Commonwealth Cup Weekend2 2023
40 Georgia Win 9-8 1655.7 Feb 26th Commonwealth Cup Weekend2 2023
19 Yale Loss 6-13 1186.06 Feb 26th Commonwealth Cup Weekend2 2023
14 Virginia Loss 8-11 1565.06 Feb 26th Commonwealth Cup Weekend2 2023
31 California Loss 7-13 1100.43 Mar 18th Womens Centex1
18 Colorado State Loss 10-13 1483.36 Mar 18th Womens Centex1
33 Ohio State Loss 7-11 1167.01 Mar 18th Womens Centex1
47 Florida Loss 10-13 1139.75 Mar 19th Womens Centex1
75 Boston University Win 8-5 1675.18 Mar 19th Womens Centex1
10 Northeastern Loss 8-13 1638.17 Mar 19th Womens Centex1
45 Washington University Loss 10-11 1354.26 Mar 19th Womens Centex1
**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)