#52 Columbia (14-6)

avg: 1503.27  •  sd: 74.58  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
182 George Mason** Win 13-3 1228.31 Ignored Feb 23rd Commonwealth Cup 2019
117 Catholic Win 13-2 1643.8 Feb 23rd Commonwealth Cup 2019
70 Maryland Win 11-9 1577.47 Feb 23rd Commonwealth Cup 2019
11 Pittsburgh Loss 8-13 1587.11 Feb 24th Commonwealth Cup 2019
45 Virginia Loss 9-13 1127.13 Feb 24th Commonwealth Cup 2019
67 Yale Loss 12-13 1258.49 Mar 9th Delaware The Main Event 2019
227 Delaware-B** Win 13-1 956.49 Ignored Mar 9th Delaware The Main Event 2019
161 Drexel Win 13-9 1229.55 Mar 9th Delaware The Main Event 2019
121 Towson Win 13-0 1624.96 Mar 9th Delaware The Main Event 2019
67 Yale Win 12-10 1621.61 Mar 10th Delaware The Main Event 2019
57 Cornell Loss 11-12 1335.62 Mar 10th Delaware The Main Event 2019
131 Rutgers Win 13-5 1590.5 Mar 10th Delaware The Main Event 2019
65 Massachusetts Win 11-7 1863.18 Mar 10th Delaware The Main Event 2019
231 Pennsylvania-B** Win 15-0 917.18 Ignored Mar 30th West Chester Ram Jam 2019
76 Rensselaer Polytech Win 11-4 1885.87 Mar 30th West Chester Ram Jam 2019
257 Millersville** Win 13-0 699.08 Ignored Mar 30th West Chester Ram Jam 2019
31 West Chester Loss 7-13 1156.49 Mar 30th West Chester Ram Jam 2019
67 Yale Win 8-6 1683.98 Mar 31st West Chester Ram Jam 2019
41 Harvard Loss 7-9 1288.32 Mar 31st West Chester Ram Jam 2019
56 Pennsylvania Win 9-8 1612.36 Mar 31st West Chester Ram Jam 2019
**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)