#162 Rutgers (12-26)

avg: 1282.55  •  sd: 47.33  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
191 NYU Win 9-7 1436.14 Feb 5th New Jersey Warmup
92 Pennsylvania Win 12-7 2059.88 Feb 10th New Jersey Warmup
93 Princeton Loss 9-11 1288.83 Feb 10th New Jersey Warmup
120 Syracuse Loss 10-13 1075.12 Feb 10th New Jersey Warmup
163 Columbia Loss 11-14 962.09 Feb 11th New Jersey Warmup
191 NYU Win 12-10 1394.93 Feb 11th New Jersey Warmup
97 Lehigh Loss 11-14 1213 Feb 11th New Jersey Warmup
48 Auburn Loss 7-9 1502.95 Feb 24th Easterns Qualifier 2024
74 Cincinnati Loss 7-13 1056.47 Feb 24th Easterns Qualifier 2024
54 Emory Loss 6-11 1208.63 Feb 24th Easterns Qualifier 2024
70 James Madison Loss 6-9 1214.62 Feb 24th Easterns Qualifier 2024
27 North Carolina-Wilmington** Loss 5-13 1395.28 Ignored Feb 25th Easterns Qualifier 2024
97 Lehigh Loss 7-15 926.34 Feb 25th Easterns Qualifier 2024
103 SUNY-Binghamton Loss 5-8 1038.04 Feb 25th Easterns Qualifier 2024
77 Carnegie Mellon Loss 8-11 1241.86 Mar 2nd Oak Creek Challenge 2024
147 Maryland-Baltimore County Loss 9-10 1190.87 Mar 2nd Oak Creek Challenge 2024
150 West Chester Win 8-7 1439.53 Mar 2nd Oak Creek Challenge 2024
72 Appalachian State Loss 10-11 1503.65 Mar 3rd Oak Creek Challenge 2024
77 Carnegie Mellon Loss 7-9 1328.13 Mar 3rd Oak Creek Challenge 2024
166 RIT Loss 6-13 667.82 Mar 3rd Oak Creek Challenge 2024
79 Case Western Reserve Loss 6-13 995.69 Mar 30th East Coast Invite 2024
75 Dartmouth Loss 8-9 1487.49 Mar 30th East Coast Invite 2024
202 George Mason Win 8-6 1416.82 Mar 30th East Coast Invite 2024
93 Princeton Loss 9-10 1413.03 Mar 30th East Coast Invite 2024
152 Harvard Win 11-9 1560.45 Mar 31st East Coast Invite 2024
92 Pennsylvania Loss 6-11 992.67 Mar 31st East Coast Invite 2024
163 Columbia Win 13-8 1771.58 Apr 13th Metro NY D I Mens Conferences 2024
374 New Jersey Tech** Win 13-1 923.7 Ignored Apr 13th Metro NY D I Mens Conferences 2024
272 Rowan Win 13-3 1456.78 Apr 13th Metro NY D I Mens Conferences 2024
163 Columbia Win 13-6 1875.42 Apr 14th Metro NY D I Mens Conferences 2024
191 NYU Loss 8-10 894.14 Apr 14th Metro NY D I Mens Conferences 2024
191 NYU Loss 14-15 1031.8 Apr 14th Metro NY D I Mens Conferences 2024
102 Connecticut Win 12-11 1620.12 Apr 27th Metro East D I College Mens Regionals 2024
85 Cornell Loss 7-12 1054.5 Apr 27th Metro East D I College Mens Regionals 2024
283 Hofstra Win 15-5 1409.27 Apr 27th Metro East D I College Mens Regionals 2024
103 SUNY-Binghamton Loss 4-15 891.64 Apr 27th Metro East D I College Mens Regionals 2024
30 Ottawa Loss 8-15 1375.87 Apr 28th Metro East D I College Mens Regionals 2024
103 SUNY-Binghamton Loss 9-13 1073.08 Apr 28th Metro East 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)