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Bobby Berliner Midweek Firefly

# SchoolTeam A TOT
1 Northeastern University Northeastern University Huskies 1 12 12
2 Tufts University Tufts University Jumbos 4 12 12
3 Tufts University Tufts University Jumbos 1 20 20
4 Tufts University Tufts University Jumbos 2 21 21
5 Massachusetts Institute of Technology Massachusetts Institute of Technology Engineers 5 22 22
6 Tufts University Tufts University Jumbos 5 22 22
7 Boston University Boston University Terriers 1 27 27
8 Tufts University Tufts University Jumbos 3 29 29
9 Massachusetts Institute of Technology Massachusetts Institute of Technology Engineers 1 36 36
10 Massachusetts Institute of Technology Massachusetts Institute of Technology Engineers 2 39 39
11 Northeastern University Northeastern University Huskies 2 40 40
12 Boston University Boston University Terriers 2 40 40
13 Massachusetts Institute of Technology Massachusetts Institute of Technology Engineers 4 48 48
14 Massachusetts Institute of Technology Massachusetts Institute of Technology Engineers 3 52 52
SchoolTeam R1 R2 R3 R4 TOT Sailors
Northeastern University Northeastern University Huskies 1 3 1 1 7 12 Jackson Hamilton '19
Jacqueline Berlin '19
Tufts University Tufts University Jumbos 4 5 2 3 2 12 Jack Bitney '19
Lara Dienemann '18
Tufts University Tufts University Jumbos 1 2 5 2 11 20 Cameron Holley '19
Ian Morgan '19
Tufts University Tufts University Jumbos 2 10 4 4 3 21 Talia Toland '22
Lucy Robison '18
Massachusetts Institute of Technology Massachusetts Institute of Technology Engineers 5 1 7 10 4 22 Ryan Hennessey '21
Brooke Mcgoldrick '20
Tufts University Tufts University Jumbos 5 6 6 5 5 22 Chris Keller '19
Michelle Chisdak '18
Boston University Boston University Terriers 1 7 3 9 8 27 Raymond Groble Iv '21
Katherine Bertolini '21
Tufts University Tufts University Jumbos 3 9 8 6 6 29 Jackson Mccoy '19
Sabina Van Mell '19
Massachusetts Institute of Technology Massachusetts Institute of Technology Engineers 1 14 14 7 1 36 Connor Chung '20
Fiona Mckellar '20
Massachusetts Institute of Technology Massachusetts Institute of Technology Engineers 2 4 9 13 13 39 Emily Haig '21
Noa Yoder '19
Northeastern University Northeastern University Huskies 2 8 10 12 10 40 Zachary Bresnick '21
Katherine Alfond '19
Boston University Boston University Terriers 2 11 12 8 9 40 Skye Shepherd '20
Olivia Cronin-Golomb '20
Massachusetts Institute of Technology Massachusetts Institute of Technology Engineers 4 12 11 11 14 48 Julia Wyatt '21
Isabelle Yen '21
Massachusetts Institute of Technology Massachusetts Institute of Technology Engineers 3 13 13 14 12 52 Preston Tower '21
Alice Lin '20
Boat Speed Analyzer
SlowExpected boat effectFast
−0.140+0.14
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 Spring 2013 (15 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

Team1A2A3A4A
Boston UniversityBoston University Terriers 14444
Boston UniversityBoston University Terriers 26666
Massachusetts Institute of TechnologyMassachusetts Institute of Technology Engineers 110101010
Massachusetts Institute of TechnologyMassachusetts Institute of Technology Engineers 213131313
Massachusetts Institute of TechnologyMassachusetts Institute of Technology Engineers 311111111
Massachusetts Institute of TechnologyMassachusetts Institute of Technology Engineers 416161616
Massachusetts Institute of TechnologyMassachusetts Institute of Technology Engineers 520202020
Northeastern UniversityNortheastern University Huskies 117171717
Northeastern UniversityNortheastern University Huskies 23333
Tufts UniversityTufts University Jumbos 15555
Tufts UniversityTufts University Jumbos 27777
Tufts UniversityTufts University Jumbos 318181818
Tufts UniversityTufts University Jumbos 419191919
Tufts UniversityTufts University Jumbos 521212121

Conditions — 10/19/2017 (8am–6pm)

☀️Clear sky
Humidity 56%  ·  Pressure 1019.8 hPa

Temperature

66°F
↑ 72°F   ↓ 52°F
Feels like 61°F

Wind

● from   ▲ toward
10.2 kn
avg  ·  max 12.2 kn
Gusts to 22.4 kn
From SSW (211°)

Sky & Precipitation

Cloud cover11% Sunshine10.7 hrs Humidity56% Pressure1019.8 hPa

Orderliness — underdogs or favourites?

Breeze: SW 12 kn (scorer’s report)
In this breeze at MIT: an underdogs’ day (−0.04)
Expect upsets: lower-rated teams have a better chance of beating the seeds, and the fleet bunches up.
Fleet adjustment −0.11 (a strong, experienced fleet makes upsets likelier) · combined forecast −0.15
Actual: a strongly underdogs’ day (−0.63 ± 0.25)

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 ±0.04 means a rating gap counts about 4% 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 MIT by wind direction (angle) and speed (rings), fitted surface; dots are labelled regatta-days, ★ this regatta (112 labelled days at MIT).

From the notes

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

All notes →