#68 Wisconsin-Milwaukee (13-6)

avg: 1549.93  •  sd: 64.31  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
106 Liberty Win 13-6 1942.91 Feb 18th Commonwealth Cup Weekend1 2023
126 Franciscan Win 13-12 1392.6 Feb 18th Commonwealth Cup Weekend1 2023
200 North Carolina-B Win 13-8 1435.92 Feb 18th Commonwealth Cup Weekend1 2023
194 Christopher Newport Win 13-8 1454.23 Feb 19th Commonwealth Cup Weekend1 2023
127 Elon Win 9-7 1542.45 Feb 19th Commonwealth Cup Weekend1 2023
133 Davidson Win 10-6 1734.32 Feb 19th Commonwealth Cup Weekend1 2023
142 Carleton College-CHOP Win 13-7 1741.03 Mar 4th Midwest Throwdown 2023
313 Illinois-B** Win 13-3 954.3 Ignored Mar 4th Midwest Throwdown 2023
22 Washington University Loss 8-11 1539.71 Mar 4th Midwest Throwdown 2023
92 Missouri S&T Loss 8-9 1304.82 Mar 5th Midwest Throwdown 2023
94 Saint Louis Win 11-10 1549.8 Mar 5th Midwest Throwdown 2023
64 St. Olaf Loss 9-10 1443 Mar 5th Midwest Throwdown 2023
90 Chicago Win 7-6 1558.78 Apr 1st Huck Finn1
116 John Brown Win 7-2 1905.98 Apr 1st Huck Finn1
104 Florida State Loss 5-7 1016.87 Apr 1st Huck Finn1
75 Grinnell Win 7-4 1982.93 Apr 1st Huck Finn1
85 Alabama Loss 10-11 1321.99 Apr 2nd Huck Finn1
98 Kentucky Win 13-9 1835.37 Apr 2nd Huck Finn1
94 Saint Louis Loss 8-9 1299.8 Apr 2nd Huck Finn1
**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)