#51 Ohio State (16-10)

avg: 1537.69  •  sd: 60.07  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
234 Haverford Win 13-7 1365.03 Feb 3rd Mid Atlantic Warmup 2018
177 Virginia Commonwealth Win 13-4 1622.23 Feb 3rd Mid Atlantic Warmup 2018
161 Boston University Win 13-2 1687.79 Feb 3rd Mid Atlantic Warmup 2018
102 Richmond Loss 11-13 1098.04 Feb 3rd Mid Atlantic Warmup 2018
48 Dartmouth Loss 11-14 1252.09 Feb 4th Mid Atlantic Warmup 2018
115 Villanova Win 14-11 1590.01 Feb 4th Mid Atlantic Warmup 2018
102 Richmond Win 10-9 1451.88 Feb 4th Mid Atlantic Warmup 2018
33 Maryland Loss 11-12 1559.28 Feb 17th Easterns Qualifier 2018
46 South Carolina Loss 10-11 1454.36 Feb 17th Easterns Qualifier 2018
62 Vermont Win 13-9 1884.4 Feb 17th Easterns Qualifier 2018
84 Virginia Win 13-11 1630.98 Feb 17th Easterns Qualifier 2018
75 Tennessee-Chattanooga Loss 8-13 919.51 Feb 17th Easterns Qualifier 2018
40 Iowa Loss 12-13 1499.81 Feb 18th Easterns Qualifier 2018
98 Clemson Win 13-11 1566.88 Feb 18th Easterns Qualifier 2018
78 Georgetown Win 11-9 1664.28 Feb 18th Easterns Qualifier 2018
45 Illinois State Loss 8-15 1021.35 Mar 3rd Midwest Throwdown 2018
164 St John's Win 15-6 1673.4 Mar 3rd Midwest Throwdown 2018
69 Carleton College-GoP Win 15-13 1663.64 Mar 3rd Midwest Throwdown 2018
47 Iowa State Win 11-9 1817.45 Mar 4th Midwest Throwdown 2018
170 Kansas State Win 15-5 1659.64 Mar 4th Midwest Throwdown 2018
49 Marquette Win 15-7 2148.36 Mar 4th Midwest Throwdown 2018
74 Washington University Win 15-3 2018.49 Mar 4th Midwest Throwdown 2018
44 Illinois Win 12-8 2030.18 Mar 31st Huck Finn 2018
45 Illinois State Loss 10-15 1132.55 Mar 31st Huck Finn 2018
29 Texas Loss 8-13 1214.94 Mar 31st Huck Finn 2018
39 Northwestern Loss 11-14 1315.36 Mar 31st Huck Finn 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)