#82 Northwestern (6-10)

avg: 1332.46  •  sd: 105.7  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
9 California-Santa Barbara** Loss 4-15 1821.8 Ignored Jan 27th Santa Barbara Invite 2024
32 UCLA Loss 7-15 1251.87 Jan 27th Santa Barbara Invite 2024
5 Oregon** Loss 2-15 2005.7 Ignored Jan 27th Santa Barbara Invite 2024
23 Cal Poly-SLO** Loss 5-13 1371.29 Ignored Jan 28th Santa Barbara Invite 2024
15 California-San Diego** Loss 5-15 1562.55 Ignored Jan 28th Santa Barbara Invite 2024
28 St Olaf Win 6-5 2046.34 Mar 2nd Midwest Throwdown 2024
64 Missouri Win 9-7 1763.7 Mar 2nd Midwest Throwdown 2024
202 Wisconsin-B** Win 8-2 799.06 Ignored Mar 2nd Midwest Throwdown 2024
84 Iowa State Win 10-5 1897.7 Mar 3rd Midwest Throwdown 2024
51 Macalester Loss 5-6 1483.92 Mar 3rd Midwest Throwdown 2024
109 Truman State Loss 6-7 999.52 Mar 3rd Midwest Throwdown 2024
100 Davenport Win 9-6 1612.53 Mar 30th Old Capitol Open 2024
51 Macalester Loss 3-8 1008.92 Mar 30th Old Capitol Open 2024
140 Wisconsin-Milwaukee Win 7-6 1010.46 Mar 30th Old Capitol Open 2024
79 Kansas Loss 0-9 755.6 Mar 31st Old Capitol Open 2024
42 Purdue Loss 1-12 1100.79 Mar 31st Old Capitol Open 2024
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)