#41 William & Mary (12-4)

avg: 1718.88  •  sd: 53.4  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
162 American Win 11-8 1470.02 Jan 28th Mid Atlantic Warmup
168 Johns Hopkins Win 13-6 1686.58 Jan 28th Mid Atlantic Warmup
167 Virginia Commonwealth Win 12-7 1610.62 Jan 28th Mid Atlantic Warmup
56 James Madison Win 10-9 1724.64 Jan 29th Mid Atlantic Warmup
83 RIT Win 14-13 1575.36 Jan 29th Mid Atlantic Warmup
107 Tennessee Win 14-10 1740.42 Feb 11th Queen City Tune Up1
49 Notre Dame Win 15-9 2158.74 Feb 11th Queen City Tune Up1
30 Ohio State Loss 11-14 1522.63 Feb 11th Queen City Tune Up1
51 Virginia Win 12-11 1760.46 Feb 11th Queen City Tune Up1
50 Case Western Reserve Win 9-8 1765.01 Feb 12th Queen City Tune Up1
85 Alabama Win 13-6 2046.99 Feb 25th Easterns Qualifier 2023
59 Cincinnati Win 12-10 1816.83 Feb 25th Easterns Qualifier 2023
45 Georgetown Loss 12-13 1571.69 Feb 25th Easterns Qualifier 2023
24 North Carolina-Charlotte Loss 8-13 1398.32 Feb 25th Easterns Qualifier 2023
33 Duke Win 13-10 2118.8 Feb 26th Easterns Qualifier 2023
27 South Carolina Loss 11-15 1467.01 Feb 26th Easterns Qualifier 2023
**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)