#101 SUNY-Binghamton (5-9)

avg: 1024.93  •  sd: 83.77  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
157 Virginia Commonwealth Win 12-8 1112.02 Jan 27th Mid Atlantic Warm Up
94 Connecticut Win 11-9 1321.45 Jan 27th Mid Atlantic Warm Up
80 Case Western Reserve Win 10-6 1685.23 Jan 27th Mid Atlantic Warm Up
85 Dartmouth Loss 7-9 851.82 Jan 27th Mid Atlantic Warm Up
129 Boston University Loss 8-11 542.14 Jan 28th Mid Atlantic Warm Up
83 Carnegie Mellon Loss 9-13 725.77 Jan 28th Mid Atlantic Warm Up
34 South Carolina Loss 9-13 1142.19 Feb 24th Easterns Qualifier 2024
137 Kennesaw State Win 12-6 1417.93 Feb 24th Easterns Qualifier 2024
77 William & Mary Loss 6-13 605.07 Feb 24th Easterns Qualifier 2024
63 Temple Loss 11-12 1150.4 Feb 24th Easterns Qualifier 2024
29 Ohio State Loss 5-12 995.06 Feb 25th Easterns Qualifier 2024
71 Maryland Loss 12-15 935.36 Feb 25th Easterns Qualifier 2024
148 Rutgers Win 8-5 1184.2 Feb 25th Easterns Qualifier 2024
137 Kennesaw State Loss 6-7 713.61 Feb 25th Easterns Qualifier 2024
**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)