#309 Illinois State-B (10-10)

avg: 633.22  •  sd: 81.36  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
308 Alabama-B Win 9-7 919.16 Jan 26th T Town Throwdown
404 Alabama-Huntsville-B Win 13-3 790.11 Jan 26th T Town Throwdown
370 Kentucky-B Win 9-5 899.99 Jan 26th T Town Throwdown
322 Mississippi Loss 12-13 462.21 Jan 27th T Town Throwdown
103 Georgia State** Loss 3-15 748.38 Ignored Jan 27th T Town Throwdown
346 Marquette-B Win 9-6 918.74 Mar 22nd Meltdown 2019
329 Northern Illinois Loss 6-7 436.93 Mar 22nd Meltdown 2019
112 Wisconsin-Whitewater Loss 6-10 810.05 Mar 22nd Meltdown 2019
198 Valparaiso Loss 7-13 440.53 Mar 22nd Meltdown 2019
360 Illinois-Chicago Win 11-6 977.89 Mar 24th Meltdown 2019
421 Carthage College Win 13-3 676.33 Mar 24th Meltdown 2019
237 Loyola-Chicago Win 10-8 1162.52 Mar 24th Meltdown 2019
329 Northern Illinois Win 10-4 1161.93 Mar 24th Meltdown 2019
327 Indiana-B Loss 5-12 -24.37 Mar 30th Illinois Invite 8
316 Purdue-B Loss 3-9 -0.2 Mar 30th Illinois Invite 8
385 Michigan State-B Loss 9-10 166.4 Mar 30th Illinois Invite 8
236 Wisconsin-Platteville Loss 5-9 372.94 Mar 31st Illinois Invite 8
275 Illinois-B Loss 6-7 645.93 Mar 31st Illinois Invite 8
314 Wisconsin-C Win 8-3 1209.54 Mar 31st Illinois Invite 8
408 Wisconsin-Milwaukee-B Win 5-4 305.46 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)