#81 Ohio (12-5)

avg: 1268.3  •  sd: 99.83  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
93 Kennesaw State Win 13-8 1684.2 Feb 23rd Commonwealth Cup 2019
262 Michigan-B** Win 13-1 634.6 Ignored Feb 23rd Commonwealth Cup 2019
51 Florida State Loss 8-13 1012.19 Feb 23rd Commonwealth Cup 2019
99 MIT Loss 9-10 1002.48 Feb 24th Commonwealth Cup 2019
182 George Mason** Win 13-4 1228.31 Ignored Feb 24th Commonwealth Cup 2019
212 SUNY-Fredonia** Win 13-4 1078.81 Ignored Mar 9th Mash Up 2019
154 Smith Win 10-5 1430.94 Mar 9th Mash Up 2019
17 Vermont** Loss 0-13 1413.2 Ignored Mar 9th Mash Up 2019
63 New Hampshire Loss 4-10 814.87 Mar 10th Mash Up 2019
284 Miami (Ohio)** Win 13-0 7.25 Ignored Mar 10th Mash Up 2019
201 Indiana Win 13-7 1096.17 Mar 23rd CWRUL Memorial 2019
178 Wheaton College IL** Win 13-2 1255.76 Ignored Mar 23rd CWRUL Memorial 2019
169 Rochester Win 9-3 1354.37 Mar 23rd CWRUL Memorial 2019
104 Boston College Win 12-5 1694.98 Mar 23rd CWRUL Memorial 2019
94 Carnegie Mellon Loss 10-11 1059.72 Mar 24th CWRUL Memorial 2019
75 Purdue Win 10-9 1413.08 Mar 24th CWRUL Memorial 2019
111 Michigan State Win 9-7 1337.58 Mar 24th CWRUL Memorial 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)