#70 Maryland (10-7)

avg: 1328.26  •  sd: 89.59  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
52 Columbia Loss 9-11 1254.07 Feb 23rd Commonwealth Cup 2019
99 MIT Win 11-8 1493.08 Feb 23rd Commonwealth Cup 2019
27 Delaware Loss 3-10 1214.9 Feb 23rd Commonwealth Cup 2019
271 Virginia-B** Win 13-0 416.54 Ignored Feb 23rd Commonwealth Cup 2019
61 James Madison Win 9-8 1560.16 Feb 24th Commonwealth Cup 2019
241 Cornell-B** Win 15-1 828.44 Ignored Mar 9th Delaware The Main Event 2019
65 Massachusetts Loss 11-12 1271.29 Mar 9th Delaware The Main Event 2019
131 Rutgers Win 15-5 1590.5 Mar 9th Delaware The Main Event 2019
65 Massachusetts Loss 10-12 1158.16 Mar 10th Delaware The Main Event 2019
27 Delaware Loss 5-12 1214.9 Mar 10th Delaware The Main Event 2019
121 Towson Win 13-9 1443.52 Mar 10th Delaware The Main Event 2019
131 Rutgers Loss 9-10 865.5 Mar 10th Delaware The Main Event 2019
207 Wisconsin-Eau Claire Win 12-6 1078.15 Mar 23rd College Southerns XVIII
- Charleston** Win 13-0 538.98 Ignored Mar 23rd College Southerns XVIII
87 Auburn Win 11-9 1484.47 Mar 24th College Southerns XVIII
20 North Carolina-Wilmington** Loss 2-15 1360.18 Ignored Mar 24th College Southerns XVIII
122 Georgia College Win 15-7 1623.21 Mar 24th College Southerns XVIII
**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)