#60 Michigan State (12-5)

avg: 1486.35  •  sd: 72.76  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
122 Boston University Win 12-5 1767.78 Jan 25th Mid Atlantic Warm Up 2025
272 Virginia Commonwealth Win 13-7 1068.86 Jan 25th Mid Atlantic Warm Up 2025
138 RIT Win 13-3 1692.92 Jan 25th Mid Atlantic Warm Up 2025
78 Richmond Win 13-5 1948.03 Jan 25th Mid Atlantic Warm Up 2025
64 James Madison Loss 9-11 1208.17 Jan 26th Mid Atlantic Warm Up 2025
115 Vermont-B Win 14-10 1593.42 Jan 26th Mid Atlantic Warm Up 2025
61 Alabama-Huntsville Loss 10-13 1136.2 Feb 15th Queen City Tune Up 2025
65 Tennessee Loss 9-12 1108.17 Feb 15th Queen City Tune Up 2025
15 Washington University Loss 6-13 1351.63 Feb 15th Queen City Tune Up 2025
52 William & Mary Loss 8-9 1426.49 Feb 16th Queen City Tune Up 2025
81 North Carolina-Charlotte Win 8-6 1622.75 Feb 16th Queen City Tune Up 2025
249 Cedarville Win 14-9 1086.67 Mar 15th Grand Rapids Invite 2025
123 Wisconsin-Milwaukee Win 11-6 1693.69 Mar 15th Grand Rapids Invite 2025
164 Ohio Win 12-9 1322.23 Mar 15th Grand Rapids Invite 2025
11 Davenport Win 12-11 2105.95 Mar 16th Grand Rapids Invite 2025
131 Pittsburgh-B Win 13-9 1539.87 Mar 16th Grand Rapids Invite 2025
63 Notre Dame Win 12-11 1584.46 Mar 16th Grand Rapids 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)