#102 Syracuse (12-12)

avg: 1260.39  •  sd: 74.52  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
120 Connecticut Loss 10-11 1054.02 Feb 8th NJ Warmup 2025
236 NYU Loss 9-11 400.33 Feb 8th NJ Warmup 2025
179 Pennsylvania Win 12-11 1036.9 Feb 8th NJ Warmup 2025
192 Princeton Loss 10-12 616.28 Feb 8th NJ Warmup 2025
44 Emory Loss 8-12 1167.04 Feb 22nd Easterns Qualifier 2025
88 Georgetown Loss 4-11 708.67 Feb 22nd Easterns Qualifier 2025
37 North Carolina-Wilmington Loss 8-9 1510.07 Feb 22nd Easterns Qualifier 2025
87 Temple Win 10-9 1435.92 Feb 22nd Easterns Qualifier 2025
96 Appalachian State Loss 12-13 1149.42 Feb 23rd Easterns Qualifier 2025
183 Kennesaw State Win 14-6 1490.74 Feb 23rd Easterns Qualifier 2025
128 SUNY-Binghamton Win 13-12 1253.07 Feb 23rd Easterns Qualifier 2025
153 Carleton University Win 13-1 1645.56 Mar 22nd Salt City Classic
24 Ottawa Loss 5-13 1233.85 Mar 22nd Salt City Classic
151 Rhode Island Win 12-7 1571.7 Mar 22nd Salt City Classic
83 SUNY-Buffalo Loss 9-11 1071.72 Mar 22nd Salt City Classic
151 Rhode Island Loss 8-9 926.19 Mar 23rd Salt City Classic
128 SUNY-Binghamton Win 13-8 1624.23 Mar 23rd Salt City Classic
120 Connecticut Win 12-8 1620.18 Mar 29th East Coast Invite 2025
132 Rutgers Win 15-5 1716.55 Mar 29th East Coast Invite 2025
177 Towson Win 14-9 1399.43 Mar 29th East Coast Invite 2025
116 West Chester Win 15-10 1645.77 Mar 29th East Coast Invite 2025
56 Cornell Loss 5-10 950.04 Mar 30th East Coast Invite 2025
83 SUNY-Buffalo Loss 6-12 741.62 Mar 30th East Coast Invite 2025
87 Temple Win 12-10 1549.04 Mar 30th East Coast Invite 2025
**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)