#139 Puget Sound (12-10)

avg: 1305.31  •  sd: 49.96  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
89 Colorado College Loss 10-13 1168.74 Feb 8th DIII Grand Prix 2025
118 Colorado Mines Win 13-10 1700.8 Feb 8th DIII Grand Prix 2025
199 Occidental Win 13-8 1571.21 Feb 8th DIII Grand Prix 2025
107 Claremont Loss 9-13 1026.25 Feb 9th DIII Grand Prix 2025
291 Reed Win 13-7 1288.81 Feb 9th DIII Grand Prix 2025
43 Whitman Loss 9-13 1365.04 Feb 9th DIII Grand Prix 2025
231 Air Force Win 13-4 1542.02 Mar 1st D III River City Showdown 2025
142 Davidson Win 10-7 1681.11 Mar 1st D III River City Showdown 2025
170 Messiah Win 13-9 1613.63 Mar 1st D III River City Showdown 2025
78 Richmond Loss 7-11 1115.57 Mar 1st D III River City Showdown 2025
60 Carleton College-CHOP Loss 8-13 1165.72 Mar 2nd D III River City Showdown 2025
33 Elon Loss 3-13 1242.66 Mar 2nd D III River City Showdown 2025
145 Oberlin Loss 11-13 1055.96 Mar 2nd D III River City Showdown 2025
157 Washington-B Win 15-11 1621.37 Mar 29th Northwest Challenge D3
307 Whitworth Win 12-11 781.96 Mar 29th Northwest Challenge D3
250 Portland Win 15-8 1448.54 Mar 30th Northwest Challenge D3
83 Simon Fraser Loss 11-15 1161.17 Mar 30th Northwest Challenge D3
315 Pacific Lutheran Win 11-5 1219.3 Apr 19th Northwest D III Mens Conferences 2025
43 Whitman Loss 7-14 1200.72 Apr 19th Northwest D III Mens Conferences 2025
291 Reed Win 12-8 1172.43 Apr 19th Northwest D III Mens Conferences 2025
40 Lewis & Clark Loss 11-15 1426.43 Apr 20th Northwest D III Mens Conferences 2025
250 Portland Win 15-10 1337.34 Apr 20th Northwest D III Mens Conferences 2025
**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)