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Dark of Night

# SchoolTeam A B TOT
1 Tufts University Tufts University Jumbo 5 12 17
2 Tufts University Tufts University Jumbos 16 13 29
3 Northeastern University Northeastern University Huskies 1 17 14 31
4 Tufts University Tufts University Jumbalaya 17 18 35
5 Brown University Brown University Bears 31 5 36
6 Brandeis University Brandeis University Judges 11 29 40
7 University of New Hampshire University of New Hampshire Wildcats 19 22 41
8 University of Connecticut University of Connecticut Huskies 25 24 49
9 Massachusetts Institute of Technology Massachusetts Institute of Technology Engineers 30 19 49
10 Northeastern University Northeastern University Huskies 2 21 32 53
11 Massachusetts Institute of Technology Massachusetts Institute of Technology Angry Beavers 25 28 53
12 Johnson and Wales University Johnson and Wales University Wildcats 31 22 53
13 University of New Hampshire University of New Hampshire Wildkittens 26 35 61
SchoolTeam R1 R2 R3 TOT Sailors
Tufts University Tufts University Jumbo 2 2 1 5 William Hutchings '13 [1-3]
Margaret Bacon '14 [1-2]
William Haeger '14 [3]
Brandeis University Brandeis University Judges 6 3 2 11 Jacob Hardy '13
Todd Kerkland '13
Tufts University Tufts University Jumbos 1 1 DSQ 16 David Liebenberg '14
Charles Proctor '14
Tufts University Tufts University Jumbalaya 3 5 9 17 Amanda Sommi '16
Mackenzie Loy '13
Northeastern University Northeastern University Huskies 1 4 6 7 17 Evan Gregory '16
Estelle Beguin '14
University of New Hampshire University of New Hampshire Wildcats 10 4 5 19 Will Humphrey '14
Northeastern University Northeastern University Huskies 2 8 9 4 21
University of Connecticut University of Connecticut Huskies 5 10 10 25 James Fales '13
Andrew Silhavy '14
Massachusetts Institute of Technology Massachusetts Institute of Technology Angry Beavers 9 13 3 25 Lisa Archibald '16
Kayla Ngan '15
University of New Hampshire University of New Hampshire Wildkittens 7 7 12 26 Paige Fagan '14
Ted Gettinger '15
Massachusetts Institute of Technology Massachusetts Institute of Technology Engineers 11 11 8 30 Sarah Mountjoy '14
Zachary Drach '15
Johnson and Wales University Johnson and Wales University Wildcats 12 8 11 31 Winsor Williams '13
Heather Ireland '15
Brown University Brown University Bears 13 12 6 31 Timothy Harding '15
Courtney Bergh '16
SchoolTeam R1 R2 R3 TOT Sailors
Brown University Brown University Bears 1 2 2 5 Nathan Allman '16
Albert Brown '16
Tufts University Tufts University Jumbo 3 4 5 12 Rolfe Glover '16
Kate Wasynczuk '16
Tufts University Tufts University Jumbos 9 3 1 13 William Haeger '14
Paula Grasberger '14
Northeastern University Northeastern University Huskies 1 2 8 4 14 Jesse Thomas '17
Linnea Goldstein '16
Tufts University Tufts University Jumbalaya 8 1 9 18 Pierre Dupont '16
Emily Peck '16
Massachusetts Institute of Technology Massachusetts Institute of Technology Engineers 7 9 3 19 Matthew Vernacchia '15
Brian Belding '15
University of New Hampshire University of New Hampshire Wildcats 4 10 8 22 Zachary Karakouzian '16
David Mazotas '16
Johnson and Wales University Johnson and Wales University Wildcats 10 5 7 22 Conall Finn '16
Erin Meltzer '14
University of Connecticut University of Connecticut Huskies 5 6 13 24 William Kresic '13
Lyndsay Stockwell '14
Massachusetts Institute of Technology Massachusetts Institute of Technology Angry Beavers 6 11 11 28 Jamila Smith-Dell '16
Victoria Stivanello '16
Brandeis University Brandeis University Judges 11 12 6 29 Sarah Hyman '15
Northeastern University Northeastern University Huskies 2 13 7 12 32
University of New Hampshire University of New Hampshire Wildkittens 12 13 10 35 Paige Fagan '14
Ted Gettinger '15
Boat Speed Analyzer
SlowExpected boat effectFast
−0.090+0.09
Places per race a team should expect to gain or lose in this boat against what its sailors' ratings predict, from a model of this fleet fitted on every regatta sailed here since Fall 2012 (1 regattas). Shown at the 40% that holds up on regattas the model never saw; hover a sail for its value and uncertainty. Grey = boat not in the fit. How this is estimated.

Division A

Team1A2A3A
Brandeis UniversityBrandeis University Judges131313
Brown UniversityBrown University Bears444
University of ConnecticutUniversity of Connecticut Huskies101010
Johnson and Wales UniversityJohnson and Wales University Wildcats222
Massachusetts Institute of TechnologyMassachusetts Institute of Technology Angry Beavers333
Massachusetts Institute of TechnologyMassachusetts Institute of Technology Engineers212121
University of New HampshireUniversity of New Hampshire Wildcats222222
University of New HampshireUniversity of New Hampshire Wildkittens888
Northeastern UniversityNortheastern University Huskies 1202020
Northeastern UniversityNortheastern University Huskies 2272727
Tufts UniversityTufts University Jumbalaya111
Tufts UniversityTufts University Jumbo777
Tufts UniversityTufts University Jumbos161616

Division B

Team1B2B3B
Brandeis UniversityBrandeis University Judges131313
Brown UniversityBrown University Bears444
University of ConnecticutUniversity of Connecticut Huskies101010
Johnson and Wales UniversityJohnson and Wales University Wildcats222
Massachusetts Institute of TechnologyMassachusetts Institute of Technology Angry Beavers333
Massachusetts Institute of TechnologyMassachusetts Institute of Technology Engineers212121
University of New HampshireUniversity of New Hampshire Wildcats222222
University of New HampshireUniversity of New Hampshire Wildkittens888
Northeastern UniversityNortheastern University Huskies 1202020
Northeastern UniversityNortheastern University Huskies 2272727
Tufts UniversityTufts University Jumbalaya111
Tufts UniversityTufts University Jumbo777
Tufts UniversityTufts University Jumbos161616

Conditions — 11/08/2012 (8am–6pm)

🌦️Light drizzle
Humidity 86%  ·  Pressure 1003.9 hPa

Temperature

37°F
↑ 38°F   ↓ 36°F
Feels like 24°F

Wind

● from   ▲ toward
20.1 kn
avg  ·  max 21.1 kn
Gusts to 39.5 kn
From N (359°)

Sky & Precipitation

Cloud cover100% Sunshine0.0 hrs Humidity86% Pressure1003.9 hPa Rain0.04 in

Orderliness — underdogs or favourites?

Breeze: N 20 kn (weather reanalysis in the scorer’s units)
In this breeze at Tufts: a strongly underdogs’ day (−0.11)
Expect upsets: lower-rated teams have a better chance of beating the seeds, and the fleet bunches up.
Fleet adjustment +0.04 (a softer or greener fleet makes the ratings stick) · combined forecast −0.08
Actual: a strongly underdogs’ day (−0.86 ± 0.16)

Orderliness is how tightly the finishing order followed the pre-regatta ratings, relative to a typical event (0). Positive is the favourites’ day: the ratings carried more weight than usual and the top seeds finished where expected. Negative is the underdogs’ day: the fleet compressed and the favourites came back to the pack. A value of ±0.11 means a rating gap counts about 10% less than on a typical day.

The breeze reading is the chart’s value at this regatta’s wind direction and speed (the star): this venue’s pattern of which directions bring order and which bring upsets, with breeze generally orderly and light air surprising. The fleet adjustment comes from the entry list: the stronger and more experienced the fleet, the more surprising the racing. How this is estimated · compare venues.

Orderliness beyond the fleet at Tufts by wind direction (angle) and speed (rings), fitted surface; dots are labelled regatta-days, ★ this regatta (60 labelled days at Tufts).

From the notes

Short write-ups of what the ratings and results show, with the numbers and how they were computed.

All notes →