#194 Kansas State (9-5)

avg: 1007.61  •  sd: 83.43  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
92 John Brown Loss 8-13 881.52 Feb 2nd Big D in Little d Open 2019
179 Nebraska Win 13-11 1287.68 Feb 2nd Big D in Little d Open 2019
394 North Texas-B Win 13-6 860.18 Feb 2nd Big D in Little d Open 2019
67 Oklahoma State Loss 2-13 933.96 Feb 2nd Big D in Little d Open 2019
175 North Texas Win 12-9 1412.46 Feb 3rd Big D in Little d Open 2019
23 Texas Tech** Loss 6-15 1231.13 Ignored Feb 3rd Big D in Little d Open 2019
67 Oklahoma State Loss 1-11 933.96 Feb 3rd Big D in Little d Open 2019
156 Minnesota-B Win 12-11 1261.27 Mar 30th Old Capitol Open 2019
433 Chicago-B** Win 13-1 421.23 Ignored Mar 30th Old Capitol Open 2019
424 Coe Win 13-6 635.35 Mar 30th Old Capitol Open 2019
419 Northwestern-St. Paul Win 12-7 597.99 Mar 30th Old Capitol Open 2019
53 Indiana Loss 12-14 1405.67 Mar 31st Old Capitol Open 2019
352 Nebraska-Omaha Win 12-10 713.95 Mar 31st Old Capitol Open 2019
156 Minnesota-B Win 14-13 1261.27 Mar 31st Old Capitol Open 2019
**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)