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# SchoolTeam A TOT
1 Crimson Crimson Crimson 1 1
2 Boston College Boston College Eagles 2 2
3 U. S. Coast Guard Academy U. S. Coast Guard Academy Bears 3 3
4 Bulldogs Bulldogs Bulldogs 4 4
5 Big Green Big Green Big Green 5 5
6 Tufts University Tufts University Jumbos 6 6
7 Hawks Hawks Hawks 7 7
8 Engineers Engineers Engineers 8 8
9 Rams Rams Rams 9 9
10 Bears Bears Bears 10 10
11 Bowdoin College Bowdoin College Polar Bears 11 11
12 Terriers Terriers Terriers 12 12
13 Huskies Huskies Huskies 13 13
14 Catamounts Catamounts Catamounts 14 14
15 Buccaneers Buccaneers Buccaneers 15 15
16 Camels Camels Camels 16 16
SchoolTeam R1 TOT Sailors
Crimson Crimson Crimson 1 1
Boston College Boston College Eagles 2 2 Aidan Cunningham '26
Caroline Sibilly '26
U. S. Coast Guard Academy U. S. Coast Guard Academy Bears 3 3 Aiana Cayao '26
Harlan Brady '24
Bulldogs Bulldogs Bulldogs 4 4
Big Green Big Green Big Green 5 5
Tufts University Tufts University Jumbos 6 6 Adam Larzelere '25
Adelaide Straub '24
Hawks Hawks Hawks 7 7
Engineers Engineers Engineers 8 8
Rams Rams Rams 9 9
Bears Bears Bears 10 10
Bowdoin College Bowdoin College Polar Bears 11 11 Caleb Adams-Hull '23
Alex Bloom '26
Terriers Terriers Terriers 12 12
Huskies Huskies Huskies 13 13
Catamounts Catamounts Catamounts 14 14
Buccaneers Buccaneers Buccaneers 15 15
Camels Camels Camels 16 16
Boat Speed Analyzer
SlowExpected boat effectFast
−0.100+0.10
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 2022 (14 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

Team1A
Boston CollegeBoston College Eagles1
TerriersTerriers Terriers2
Bowdoin CollegeBowdoin College Polar Bears3
BearsBears Bears4
U. S. Coast Guard AcademyU. S. Coast Guard Academy Bears13
CamelsCamels Camels5
Big GreenBig Green Big Green6
CrimsonCrimson Crimson7
BuccaneersBuccaneers Buccaneers9
EngineersEngineers Engineers8
HuskiesHuskies Huskies10
RamsRams Rams14
HawksHawks Hawks11
Tufts UniversityTufts University Jumbos12
CatamountsCatamounts Catamounts15
BulldogsBulldogs Bulldogs16

Conditions — 09/16/2023 (8am–6pm)

☁️Overcast
Humidity 69%  ·  Pressure 1004.2 hPa

Temperature

64°F
↑ 70°F   ↓ 57°F
Feels like 57°F

Wind

● from   ▲ toward
15.6 kn
avg  ·  max 17.7 kn
Gusts to 30.9 kn
From WNW (298°)

Sky & Precipitation

Cloud cover98% Sunshine2.5 hrs Humidity69% Pressure1004.2 hPa Rain0.19 in

What this breeze does at MIT — from fleet racing

Breeze: NW about 16 kn (weather reanalysis in the scorer’s units)
In fleet races at MIT in this breeze: a typical day (+0.01)
Nothing in this breeze favours either side in fleet racing here: results follow the ratings about as usual.

Orderliness is how tightly a fleet race’s finishing order follows the pre-regatta ratings, relative to a typical event (0): positive is the favourites’ day, negative the underdogs’. A value of ±0.01 means a rating gap counts about 1% more than on a typical day. This event is not a fleet race the rating model scores, so there is no actual value for it: this is what this venue’s fleet racing history says about the breeze on the day, read off the chart at the star. 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 fleet-race 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 →