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Princeton Fall Open

# SchoolTeam A B TOT
1 Princeton University Princeton University Tigers 9 17 26
2 Rutgers University Rutgers University Scarlet Knights 29 21 50
3 University of Delaware University of Delaware Blue Hens 24 29 53
4 Orange Orange Orange 43 13 56
5 University of Maryland University of Maryland Terps 25 46 71
6 Drexel University Drexel University Dragons 31 43 74
7 U. S. Military Academy U. S. Military Academy Black Knights 48 27 75
8 Monmouth University Monmouth University Hawks 44 56 100
SchoolTeam R1 R2 R3 R4 R5 R6 R7 TOT Sailors
Princeton University Princeton University Tigers 1 1 1 2 1 1 2 9 Advik Eswaran '27
Kaitlyn Greppin '26
University of Delaware University of Delaware Blue Hens 2 4 3 4 3 3 5 24 Brendan Van Riper '27
University of Maryland University of Maryland Terps 4 2 4 1 4 4 6 25 Noah Simcox '28
Visesh Uppoor '26
Rutgers University Rutgers University Scarlet Knights DNS 3 6 3 2 5 1 29 Andrew Martin '27
Rashadul Quazi '26
Drexel University Drexel University Dragons 3 6 2 8 6 2 4 31 Alexander Pfeffer '28
Bhavika Choudhary '28
Orange Orange Orange 7 8 5 5 5 6 7 43
Monmouth University Monmouth University Hawks 6 5 8 7 7 8 3 44 Julia Marich '28
Joseph Arrigo '25
U. S. Military Academy U. S. Military Academy Black Knights 5 7 7 6 8 7 8 48 Nathan Gaddis '29 [1-7]
Madelyn Zimmerman '28 [1-2]
Thomas Brearley '27 [3-7]
SchoolTeam R1 R2 R3 R4 R5 R6 R7 TOT Sailors
Orange Orange Orange 1 1 3 3 2 2 1 13
Princeton University Princeton University Tigers 2 3 6 2 1 1 2 17 Johnny Leadingham '26 [1-2]
Cole Crosby '26 [3-7]
Tacy Guest '26 [1-7]
Rutgers University Rutgers University Scarlet Knights 3 4 4 1 3 3 3 21 Theodore Li '29 [1-7]
Albert Ott '29 [1-2, 5-7]
Wesley Thorson Renomeron '29 [3-4]
U. S. Military Academy U. S. Military Academy Black Knights 6 2 1 4 5 5 4 27 Morgan Zylinski '29
Matthew Grube '29
University of Delaware University of Delaware Blue Hens 4 5 2 5 4 4 5 29 Tyler Needham '27
Brian Polak '27
Drexel University Drexel University Dragons 7 6 5 6 6 7 6 43 Jonathan Walerys '27 [1-2, 5-7]
Carter Weiss '29 [3-4]
Enzo Garcia '28 [1-2, 5-7]
Charlotte Shaw '26 [3-4]
University of Maryland University of Maryland Terps 5 7 7 7 7 6 7 46 Nathan Story '29
Ken Tashiro '28
Monmouth University Monmouth University Hawks 8 8 8 8 8 8 8 56 Carolynn Wildrick '28
John Bailey '28
Boat Speed Analyzer
SlowExpected boat effectFast
−0.050+0.05
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 2013 (10 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

Team1A2A3A4A5A6A7A
U. S. Military AcademyU. S. Military Academy Black Knights771212222
University of DelawareUniversity of Delaware Blue Hens111111444
Drexel UniversityDrexel University Dragons1144666
University of MarylandUniversity of Maryland Terps121222555
Monmouth UniversityMonmouth University Hawks2255777
Princeton UniversityPrinceton University Tigers4466111111
Rutgers UniversityRutgers University Scarlet Knights5577121212
OrangeOrange Orange661111111

Division B

Team1B2B3B4B5B6B7B
U. S. Military AcademyU. S. Military Academy Black Knights111111444
University of DelawareUniversity of Delaware Blue Hens121222555
Drexel UniversityDrexel University Dragons2255777
University of MarylandUniversity of Maryland Terps1144666
Monmouth UniversityMonmouth University Hawks4466111111
Princeton UniversityPrinceton University Tigers5577121212
Rutgers UniversityRutgers University Scarlet Knights661111111
OrangeOrange Orange771212222

Conditions — 10/04/2025 (8am–6pm)

☀️Clear sky
Humidity 57%  ·  Pressure 1023.0 hPa

Temperature

72°F
↑ 79°F   ↓ 54°F
Feels like 72°F

Wind

● from   ▲ toward
3.4 kn
avg  ·  max 4.7 kn
Gusts to 10.9 kn
From WSW (251°)

Sky & Precipitation

Cloud cover28% Sunshine10.9 hrs Humidity57% Pressure1023.0 hPa

Orderliness — underdogs or favourites?

Breeze: SW 6 kn (weather reanalysis in the scorer’s units)
In this breeze at Princeton: an underdogs’ day (−0.08)
Expect upsets: lower-rated teams have a better chance of beating the seeds, and the fleet bunches up.
Fleet adjustment +0.18 (a softer or greener fleet makes the ratings stick) · combined forecast +0.10
Actual: about typical, within noise (+0.35 ± 0.19)

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 ±0.08 means a rating gap counts about 7% 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 Princeton by wind direction (angle) and speed (rings), fitted surface; dots are labelled regatta-days, ★ this regatta (only 5 labelled days at Princeton, so the surface is mostly the all-venue pattern).

From the notes

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

All notes →