#37 Northwestern (9-12)

avg: 2028.18  •  sd: 61.37  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
5 Oregon Loss 7-15 2010.52 Feb 17th Presidents Day Invitational Tournament 2018
2 California-San Diego** Loss 4-14 2132.82 Ignored Feb 17th Presidents Day Invitational Tournament 2018
33 UCLA Loss 8-11 1697.08 Feb 17th Presidents Day Invitational Tournament 2018
105 Chico State Win 14-3 2079.34 Feb 18th Presidents Day Invitational Tournament 2018
16 Western Washington Loss 8-9 2219.39 Feb 18th Presidents Day Invitational Tournament 2018
22 Minnesota Loss 7-12 1708.32 Feb 18th Presidents Day Invitational Tournament 2018
20 Washington Loss 7-9 1960.9 Feb 19th Presidents Day Invitational Tournament 2018
44 Colorado State Win 9-7 2260.93 Mar 3rd Midwest Throwdown 2018
55 Iowa State Loss 6-12 1267.15 Mar 3rd Midwest Throwdown 2018
96 St Olaf Win 15-6 2126.06 Mar 3rd Midwest Throwdown 2018
42 Wisconsin Loss 8-11 1638.09 Mar 4th Midwest Throwdown 2018
108 Wisconsin-Eau Claire Win 15-0 2047.12 Mar 4th Midwest Throwdown 2018
89 Iowa Win 11-6 2117.17 Mar 4th Midwest Throwdown 2018
57 Kansas Win 14-3 2436.54 Mar 4th Midwest Throwdown 2018
28 Washington University Loss 10-11 1988.89 Mar 24th Womens Centex 2018
13 Ohio State Loss 7-13 1847.39 Mar 24th Womens Centex 2018
55 Iowa State Win 13-10 2174.6 Mar 24th Womens Centex 2018
33 UCLA Win 11-10 2187.69 Mar 24th Womens Centex 2018
28 Washington University Win 14-9 2587.76 Mar 24th Womens Centex 2018
9 Colorado Loss 7-15 1899.69 Mar 25th Womens Centex 2018
11 Texas Loss 10-13 2143.6 Mar 25th Womens Centex 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)