#106 Liberty (9-8)

avg: 1342.91  •  sd: 85.61  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
200 North Carolina-B Win 13-6 1539.77 Feb 18th Commonwealth Cup Weekend1 2023
126 Franciscan Win 12-8 1708.75 Feb 18th Commonwealth Cup Weekend1 2023
68 Wisconsin-Milwaukee Loss 6-13 949.93 Feb 18th Commonwealth Cup Weekend1 2023
140 Cedarville Win 13-7 1745.72 Feb 19th Commonwealth Cup Weekend1 2023
127 Elon Loss 8-13 766.96 Feb 19th Commonwealth Cup Weekend1 2023
133 Davidson Win 12-6 1817.47 Feb 19th Commonwealth Cup Weekend1 2023
204 Maine Win 10-9 1056.22 Mar 11th Oak Creek Invite 2023
69 Maryland Win 11-8 1905.57 Mar 11th Oak Creek Invite 2023
76 Princeton Loss 7-11 1016.37 Mar 11th Oak Creek Invite 2023
187 SUNY-Geneseo Win 8-4 1560.78 Mar 11th Oak Creek Invite 2023
83 RIT Loss 8-11 1084.75 Mar 12th Oak Creek Invite 2023
71 Cornell Win 11-10 1628.6 Apr 1st Atlantic Coast Open 2023
45 Georgetown Loss 4-14 1096.69 Apr 1st Atlantic Coast Open 2023
172 East Carolina Win 15-4 1663.43 Apr 1st Atlantic Coast Open 2023
70 Lehigh Loss 14-15 1401.73 Apr 2nd Atlantic Coast Open 2023
84 Richmond Loss 10-15 996.32 Apr 2nd Atlantic Coast Open 2023
63 Rutgers Loss 9-15 1053.3 Apr 2nd Atlantic Coast Open 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)