#147 Maryland-Baltimore County (10-11)

avg: 1315.87  •  sd: 55.71  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
226 American Win 11-7 1500.01 Feb 24th Monument Melee
289 Drexel Win 13-5 1369.67 Feb 24th Monument Melee
204 Virginia Commonwealth Loss 7-11 641.09 Feb 24th Monument Melee
226 American Win 10-8 1295.79 Feb 25th Monument Melee
217 George Washington Win 9-8 1183.5 Feb 25th Monument Melee
170 Villanova Loss 6-10 755.8 Feb 25th Monument Melee
77 Carnegie Mellon Loss 8-11 1241.86 Mar 2nd Oak Creek Challenge 2024
162 Rutgers Win 10-9 1407.55 Mar 2nd Oak Creek Challenge 2024
150 West Chester Win 11-9 1563.73 Mar 2nd Oak Creek Challenge 2024
77 Carnegie Mellon Loss 9-13 1188.9 Mar 3rd Oak Creek Challenge 2024
126 Towson Loss 10-13 1060.95 Mar 3rd Oak Creek Challenge 2024
166 RIT Win 11-10 1392.82 Mar 3rd Oak Creek Challenge 2024
226 American Win 10-7 1422.79 Apr 20th Colonial D I Mens Conferences 2024
148 Johns Hopkins Win 8-7 1440.12 Apr 20th Colonial D I Mens Conferences 2024
64 Maryland Loss 11-12 1552.89 Apr 20th Colonial D I Mens Conferences 2024
87 Georgetown Loss 6-15 954.4 Apr 21st Colonial D I Mens Conferences 2024
126 Towson Win 13-12 1514.09 Apr 21st Colonial D I Mens Conferences 2024
50 Duke Loss 14-15 1647.52 May 4th Atlantic Coast D I College Mens Regionals 2024
27 North Carolina-Wilmington Loss 8-15 1430.47 May 4th Atlantic Coast D I College Mens Regionals 2024
64 Maryland Loss 8-12 1236.73 May 4th Atlantic Coast D I College Mens Regionals 2024
87 Georgetown Loss 11-13 1325.56 May 5th Atlantic Coast D I College Mens Regionals 2024
**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)