#86 Maryland (12-6)

avg: 1592.3  •  sd: 66.86  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
255 Christopher Newport** Win 13-1 937.52 Ignored Feb 10th Black Pearl Invitational 2018
173 East Carolina Win 9-4 1638.17 Feb 10th Black Pearl Invitational 2018
222 Drexel** Win 13-1 1303.13 Ignored Feb 10th Black Pearl Invitational 2018
139 Michigan State Win 11-9 1503.47 Feb 10th Black Pearl Invitational 2018
90 Georgia College Win 8-7 1687.37 Feb 11th Black Pearl Invitational 2018
188 Mary Washington** Win 9-3 1542.86 Ignored Feb 11th Black Pearl Invitational 2018
250 Davidson** Win 15-1 1020.47 Ignored Feb 24th Commonwealth Cup 2018
123 MIT Win 15-5 1959.23 Feb 24th Commonwealth Cup 2018
49 Duke Loss 12-14 1730.52 Feb 24th Commonwealth Cup 2018
80 James Madison Loss 8-9 1522.06 Feb 25th Commonwealth Cup 2018
139 Michigan State Win 12-7 1774.78 Feb 25th Commonwealth Cup 2018
74 Massachusetts Loss 5-10 1137.14 Feb 25th Commonwealth Cup 2018
31 Penn State Loss 6-13 1486.19 Mar 17th Bonanza 2018
88 Georgetown Loss 7-9 1299.29 Mar 17th Bonanza 2018
215 Virginia-B** Win 12-4 1376.36 Ignored Mar 17th Bonanza 2018
173 East Carolina Win 12-3 1638.17 Mar 17th Bonanza 2018
80 James Madison Loss 12-13 1522.06 Mar 18th Bonanza 2018
150 Virginia Commonwealth Win 13-4 1786.24 Mar 18th Bonanza 2018
**Blowout Eligible

FAQ

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
  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
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)