#59 Ohio (12-7)

avg: 1176.86  •  sd: 107.55  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
7 Carleton College** Loss 0-12 1552.01 Ignored Feb 11th Queen City Tune Up1
38 Chicago Loss 9-10 1329.66 Feb 11th Queen City Tune Up1
55 Appalachian State Win 8-4 1796.66 Feb 11th Queen City Tune Up1
14 Virginia Loss 6-10 1312.48 Feb 11th Queen City Tune Up1
66 Case Western Reserve Win 9-6 1540.76 Feb 12th Queen City Tune Up1
40 Georgia Loss 4-9 813.2 Feb 12th Queen City Tune Up1
138 Cincinnati Win 9-3 1194.1 Mar 4th Huckleberry Flick Tournament
171 Dayton** Win 9-3 860.12 Ignored Mar 4th Huckleberry Flick Tournament
215 SUNY-Buffalo** Win 12-0 143.7 Ignored Mar 4th Huckleberry Flick Tournament
202 Miami (Ohio)** Win 12-3 507.76 Ignored Mar 4th Huckleberry Flick Tournament
138 Cincinnati Win 8-4 1158.91 Mar 5th Huckleberry Flick Tournament
171 Dayton** Win 6-2 860.12 Ignored Mar 5th Huckleberry Flick Tournament
28 South Carolina Loss 5-10 967.46 Mar 25th Rodeo 2023
182 Georgetown-B** Win 11-3 771.54 Ignored Mar 25th Rodeo 2023
213 Elon** Win 13-0 287.65 Ignored Mar 25th Rodeo 2023
67 Massachusetts Win 12-7 1640.16 Mar 25th Rodeo 2023
25 Duke Loss 4-12 968.74 Mar 26th Rodeo 2023
130 Liberty Win 10-6 1126.36 Mar 26th Rodeo 2023
64 Williams Loss 6-12 569.19 Mar 26th Rodeo 2023
**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)