#127 Boston College (10-10)

avg: 1274.72  •  sd: 63.43  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
18 Michigan Loss 9-13 1490.2 Feb 8th Florida Warm Up 2019
106 Illinois State Loss 12-13 1202.34 Feb 8th Florida Warm Up 2019
73 Temple Loss 7-12 960.36 Feb 8th Florida Warm Up 2019
69 Emory Loss 8-10 1245.79 Feb 9th Florida Warm Up 2019
55 Florida State Loss 7-13 1054.14 Feb 9th Florida Warm Up 2019
54 Virginia Tech Loss 7-13 1061.91 Feb 9th Florida Warm Up 2019
150 Cornell Loss 11-12 1053.08 Feb 9th Florida Warm Up 2019
136 South Florida Win 14-6 1837.03 Feb 10th Florida Warm Up 2019
68 Cincinnati Loss 3-10 915.37 Feb 10th Florida Warm Up 2019
- Providence College Win 13-6 1183.62 Mar 23rd 2019 Bryant Round Robin
288 Massachusetts-Lowell Win 12-4 1312.56 Mar 23rd 2019 Bryant Round Robin
60 Bryant University Loss 6-10 1058.21 Mar 23rd 2019 Bryant Round Robin
176 Bentley Win 11-6 1611.97 Mar 23rd 2019 Bryant Round Robin
317 Worcester Polytech** Win 13-1 1196.85 Ignored Mar 30th Tea Cup 2019
214 Hartford Win 11-4 1538.67 Mar 30th Tea Cup 2019
213 Columbia Win 13-2 1548.26 Mar 30th Tea Cup 2019
122 Yale Loss 6-10 783.36 Mar 30th Tea Cup 2019
220 Northeastern-B Win 12-5 1521.97 Mar 31st Tea Cup 2019
122 Yale Win 11-8 1645.13 Mar 31st Tea Cup 2019
262 Tufts-B Win 10-9 944.8 Mar 31st Tea Cup 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)