SEISA Women's Fall Championship

Analysis
# SchoolTeam TOT
1 Tulane University Tulane University Green Wave 23
2 Texas A&M University Texas A&M University Aggies 39
3 University of Texas University of Texas Longhorns 64
SchoolTeam R1 R2 R3 R4 R5 R6 TOT Sailors
Tulane University Tulane University Green Wave A 2 2 1 1 1 1 8 Oakley Cunningham '27 [1]
Audrey Permenter '27 [2-6]
Sophia Adams '27 [1]
Caitlin Briggs '27 [2-6]
Tulane University Tulane University Green Wave B 1 3 2 3 3 3 15 Ava Anderson '27 [1]
Mira Herlihy '27 [2-6]
Catherine Anderson '26 [1]
Texas A&M University Texas A&M University Aggies B 3 1 3 2 4 2 15 Kate Hennig '26 [1-5]
Sydney Krahulik '27 [6]
Sydney Krahulik '27 [1-5]
Kate Hennig '26 [6]
Texas A&M University Texas A&M University Aggies A 5 5 4 4 2 4 24 Hanna Progelhof '25 [1-6]
Jamie Morin '27 [1-4]
Emily Davison '24 [5-6]
University of Texas University of Texas Longhorns A 4 4 6 5 5 5 29 Sophia Herrada '24
Reema Nannapaneni '27
University of Texas University of Texas Longhorns B 6 6 5 6 6 6 35 Madi Ang '24
Delilah D'Souza '24
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 2023 (2 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

Team1A2A3A4A5A6A
University of TexasUniversity of Texas Longhorns333344
Texas A&M UniversityTexas A&M University Aggies111122
Tulane UniversityTulane University Green Wave222211

Division B

Team1B2B3B4B5B6B
University of TexasUniversity of Texas Longhorns666655
Texas A&M UniversityTexas A&M University Aggies444433
Tulane UniversityTulane University Green Wave555566
School / Team SkipperCrew
Texas A&M University Texas A&M University Hanna Progelhof '25 [1-6] Jamie Morin '27 [1-4]
Emily Davison '24 [5-6]
Aggies Kate Hennig '26 [1-5]
Sydney Krahulik '27 [6]
Sydney Krahulik '27 [1-5]
Kate Hennig '26 [6]
Tulane University Tulane University Oakley Cunningham '27 [1]
Audrey Permenter '27 [2-6]
Sophia Adams '27 [1]
Caitlin Briggs '27 [2-6]
Green Wave Ava Anderson '27 [1]
Mira Herlihy '27 [2-6]
Catherine Anderson '26 [1]
University of Texas University of Texas Sophia Herrada '24 Reema Nannapaneni '27
Longhorns Madi Ang '24 Delilah D'Souza '24

Conditions — 10/29/2023 (8am–6pm)

☁️Overcast
Humidity 83%  ·  Pressure 1016.5 hPa

Temperature

64°F
↑ 74°F   ↓ 55°F
Feels like 63°F

Wind

● from   ▲ toward
9.7 kn
avg  ·  max 14.4 kn
Gusts to 24.3 kn
From N (10°)

Sky & Precipitation

Cloud cover93% Sunshine3.2 hrs Humidity83% Pressure1016.5 hPa Rain0.32 in

What this breeze does at Texas — from fleet racing

Breeze: N about 12 kn (weather reanalysis in the scorer’s units)
In fleet races at Texas in this breeze: a favourites’ day (+0.09)
Favourites’ conditions: in fleet racing here the results follow the ratings more closely than usual, and the top seeds hold their places.

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 ±0.09 means a rating gap counts about 8% 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 Texas by wind direction (angle) and speed (rings), fitted surface; dots are labelled regatta-days, ★ this regatta (19 labelled fleet-race days at Texas).

From the notes

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

All notes →