#384 Grinnell (3-9)

avg: 207.76  •  sd: 73.89  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
139 Luther** Loss 4-15 568.04 Ignored Mar 3rd Midwest Throwdown 2018
142 North Park** Loss 1-15 563.76 Ignored Mar 3rd Midwest Throwdown 2018
413 Wisconsin-Milwaukee-B Win 15-4 499.67 Mar 3rd Midwest Throwdown 2018
261 Drake Loss 6-15 147.36 Mar 4th Midwest Throwdown 2018
342 Washington University-B Loss 8-15 -168.45 Mar 4th Midwest Throwdown 2018
352 Belmont Loss 9-11 109.33 Mar 17th D III Midwestern Invite 2018
257 Knox Loss 6-11 208.93 Mar 17th D III Midwestern Invite 2018
153 Xavier** Loss 2-13 515.49 Ignored Mar 17th D III Midwestern Invite 2018
135 Brandeis** Loss 2-13 574.86 Ignored Mar 17th D III Midwestern Invite 2018
304 Olivet Nazarene Loss 10-15 114.81 Mar 18th D III Midwestern Invite 2018
423 Coe Win 15-8 351.36 Mar 18th D III Midwestern Invite 2018
377 Wisconsin-Platteville Win 11-10 383.33 Mar 18th D III Midwestern Invite 2018
**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)