#123 Oberlin (11-11)

avg: 1396.72  •  sd: 59.57  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
88 Berry Loss 7-13 994.15 Mar 2nd FCS D III Tune Up 2024
84 Elon Loss 12-13 1451.44 Mar 2nd FCS D III Tune Up 2024
153 Missouri S&T Win 13-7 1862.68 Mar 2nd FCS D III Tune Up 2024
65 Richmond Loss 11-12 1549.99 Mar 2nd FCS D III Tune Up 2024
114 Davidson Loss 11-12 1312.27 Mar 3rd FCS D III Tune Up 2024
179 North Carolina-Asheville Win 13-8 1695.68 Mar 3rd FCS D III Tune Up 2024
172 Union (Tennessee) Win 13-8 1729.84 Mar 3rd FCS D III Tune Up 2024
316 Calvin University** Win 13-4 1260.41 Ignored Mar 16th Grand Rapids College Invite
135 Grand Valley Loss 9-12 1025.79 Mar 16th Grand Rapids College Invite
270 Wisconsin-Platteville Win 12-4 1460.27 Mar 16th Grand Rapids College Invite
37 Michigan Loss 9-11 1636.54 Mar 17th Grand Rapids College Invite
280 Western Michigan Win 12-5 1428.64 Mar 17th Grand Rapids College Invite
145 Southern Illinois-Edwardsville Loss 9-10 1206.75 Mar 17th Grand Rapids College Invite
86 Cedarville Loss 8-11 1189.91 Apr 13th Ohio D III Mens Conferences 2024
68 Franciscan Loss 7-12 1139.97 Apr 13th Ohio D III Mens Conferences 2024
168 Kenyon Loss 8-12 811.2 Apr 13th Ohio D III Mens Conferences 2024
173 Xavier Loss 11-12 1108.43 Apr 13th Ohio D III Mens Conferences 2024
86 Cedarville Win 10-9 1680.52 Apr 27th Ohio Valley D III College Mens Regionals 2024
318 Swarthmore** Win 8-1 1255.47 Ignored Apr 27th Ohio Valley D III College Mens Regionals 2024
171 Scranton Win 12-11 1363.19 Apr 27th Ohio Valley D III College Mens Regionals 2024
173 Xavier Win 13-5 1833.43 Apr 27th Ohio Valley D III College Mens Regionals 2024
198 Messiah Win 13-9 1547.56 Apr 28th Ohio Valley D III 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)