#327 Indiana-B (6-6)

avg: 575.63  •  sd: 81.61  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
308 Alabama-B Win 10-8 902.49 Mar 2nd First Annual Jaxx Jamboree
109 Truman State Loss 6-13 723.3 Mar 2nd First Annual Jaxx Jamboree
404 Alabama-Huntsville-B Win 10-8 452.78 Mar 2nd First Annual Jaxx Jamboree
274 Union (Tennessee) Loss 6-10 275.46 Mar 2nd First Annual Jaxx Jamboree
263 Georgia Tech-B Loss 6-12 234.63 Mar 3rd First Annual Jaxx Jamboree
404 Alabama-Huntsville-B Win 12-6 769.42 Mar 3rd First Annual Jaxx Jamboree
309 Illinois State-B Win 12-5 1233.22 Mar 30th Illinois Invite 8
316 Purdue-B Loss 6-8 299.31 Mar 30th Illinois Invite 8
236 Wisconsin-Platteville Loss 2-12 302 Mar 31st Illinois Invite 8
385 Michigan State-B Win 8-6 591.9 Mar 31st Illinois Invite 8
314 Wisconsin-C Win 8-7 734.54 Mar 31st Illinois Invite 8
275 Illinois-B Loss 4-7 274.77 Mar 31st Illinois Invite 8
**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)