#282 Toledo (9-12)

avg: 818.55  •  sd: 98.38  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
110 Davenport** Loss 4-13 867.57 Ignored Mar 16th Grand Rapids College Invite
340 DePaul Loss 11-12 430.29 Mar 16th Grand Rapids College Invite
145 Southern Illinois-Edwardsville Loss 9-11 1082.54 Mar 16th Grand Rapids College Invite
316 Calvin University Win 13-8 1156.57 Mar 17th Grand Rapids College Invite
362 Concordia-Wisconsin Win 13-4 1038.12 Mar 17th Grand Rapids College Invite
257 Wisconsin-B Win 9-6 1336.41 Mar 17th Grand Rapids College Invite
270 Wisconsin-Platteville Win 9-4 1460.27 Mar 17th Grand Rapids College Invite
222 Ball State Loss 4-10 443.66 Mar 30th Illinois Invite 2024
369 Illinois-B Win 8-4 925.12 Mar 30th Illinois Invite 2024
294 Knox Loss 2-11 137.81 Mar 30th Illinois Invite 2024
323 Purdue-B Win 8-6 931.13 Mar 30th Illinois Invite 2024
264 Wheaton (Illinois) Loss 1-7 291.59 Mar 30th Illinois Invite 2024
369 Illinois-B Loss 7-15 -239.68 Mar 31st Illinois Invite 2024
294 Knox Loss 10-11 612.81 Mar 31st Illinois Invite 2024
74 Cincinnati** Loss 1-13 1014 Ignored Apr 20th Ohio D I Mens Conferences 2024
194 Ohio Loss 6-9 724.06 Apr 20th Ohio D I Mens Conferences 2024
35 Ohio State** Loss 1-13 1303.25 Ignored Apr 20th Ohio D I Mens Conferences 2024
347 Wright State Win 10-5 1101.26 Apr 20th Ohio D I Mens Conferences 2024
268 Akron Win 15-14 996.21 Apr 21st Ohio D I Mens Conferences 2024
182 Dayton Win 11-7 1657.29 Apr 21st Ohio D I Mens Conferences 2024
292 Kent State Loss 12-13 622.63 Apr 21st Ohio D I Mens Conferences 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)