#105 Liberty (13-5)

avg: 1232.91  •  sd: 78.96  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
199 North Carolina State-B Win 10-6 1313.23 Feb 15th 2025 Commonwealth Cup Weekend 1
230 West Virginia Win 10-5 1259.28 Feb 15th 2025 Commonwealth Cup Weekend 1
344 South Carolina-B** Win 11-0 729.6 Ignored Feb 15th 2025 Commonwealth Cup Weekend 1
11 Davenport** Loss 4-11 1380.95 Ignored Feb 16th 2025 Commonwealth Cup Weekend 1
99 Oberlin Loss 6-7 1141.1 Feb 16th 2025 Commonwealth Cup Weekend 1
56 Cornell Loss 2-13 923.94 Mar 1st Oak Creek Challenge 2025
226 SUNY-Albany Win 10-7 1086.74 Mar 1st Oak Creek Challenge 2025
116 West Chester Loss 2-7 592.17 Mar 1st Oak Creek Challenge 2025
336 SUNY-Cortland Win 11-5 791.65 Mar 2nd Oak Creek Challenge 2025
83 SUNY-Buffalo Win 8-7 1445.93 Mar 2nd Oak Creek Challenge 2025
226 SUNY-Albany Win 11-4 1297.07 Mar 2nd Oak Creek Challenge 2025
97 Duke Win 14-7 1856.31 Mar 22nd Atlantic Coast Open 2025
159 George Mason Win 10-8 1260.43 Mar 22nd Atlantic Coast Open 2025
170 Massachusetts -B Win 11-10 1084.86 Mar 22nd Atlantic Coast Open 2025
276 Virginia Tech-B Win 12-6 1056.9 Mar 22nd Atlantic Coast Open 2025
96 Appalachian State Loss 12-15 973.93 Mar 23rd Atlantic Coast Open 2025
113 Lehigh Win 12-10 1442.36 Mar 23rd Atlantic Coast Open 2025
81 North Carolina-Charlotte Win 11-6 1868.95 Mar 23rd Atlantic Coast Open 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)