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SAISA North Points #4

# SchoolTeam A B TOT
1 Georgia Institute of Technology Georgia Institute of Technology Yellow Jackets 1 7 11 18
2 Clemson University Clemson University Tigers 10 9 19
3 University of Tennessee University of Tennessee Volunteers 1 11 10 21
4 North Carolina State University North Carolina State University Wolfpack 11 11 22
5 Duke University Duke University Blue Devils 12 10 22
6 Georgia Institute of Technology Georgia Institute of Technology Yellow Jackets 2 13 20 33
7 University of Tennessee University of Tennessee Volunteers 2 25 22 47
8 Auburn University Auburn University Tigers 20 28 48
9 University of Georgia University of Georgia Bulldogs 28 22 50
10 University of South Carolina University of South Carolina Coed 28 22 50
SchoolTeam R1 R2 R3 TOT Sailors
Clemson University Clemson University Tigers 4 4 1 9 Edwin Strong '15
Evelyn Moseley '15
Duke University Duke University Blue Devils 1 3 6 10 John Sipp '18
David Eacho '18
University of Tennessee University of Tennessee Volunteers 1 7 1 2 10 John Lindahl '15
Breanna Rhyne '16
Georgia Institute of Technology Georgia Institute of Technology Yellow Jackets 1 2 6 3 11 Joshua Kim '17
Ethan Westcoat '18
North Carolina State University North Carolina State University Wolfpack 5 2 4 11 Elijah Jones '18
Jillian Tucker '15
Georgia Institute of Technology Georgia Institute of Technology Yellow Jackets 2 8 7 5 20 Andres Menendez '17 [1-2]
Scott Claudon '16 [3]
Scott Claudon '16 [1-2]
Kenji Tanaka '18 [3]
University of Georgia University of Georgia Bulldogs 3 10 9 22 Erica Trotter '17
Rhiannon Euhus '18
University of South Carolina University of South Carolina Coed 6 8 8 22 Jack Gonzales '18
Anna Natterstad '17
University of Tennessee University of Tennessee Volunteers 2 10 5 7 22 Matthew Art '18
Christopher Haseler '18
Auburn University Auburn University Tigers 9 9 10 28 Shawn Majzlik '18 [1-2]
Rachael Payton '15 [3]
Taylor Lemaitre '17 [1-2]
Samantha Vaughn '15 [3]
Boat Speed Analyzer
SlowExpected boat effectFast
−0.190+0.19
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 (8 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
Auburn UniversityAuburn University Tigers10109
Clemson UniversityClemson University Tigers9910
Duke UniversityDuke University Blue Devils887
University of GeorgiaUniversity of Georgia Bulldogs443
Georgia Institute of TechnologyGeorgia Institute of Technology Yellow Jackets 1778
Georgia Institute of TechnologyGeorgia Institute of Technology Yellow Jackets 2665
North Carolina State UniversityNorth Carolina State University Wolfpack556
University of South CarolinaUniversity of South Carolina Coed334
University of TennesseeUniversity of Tennessee Volunteers 1221
University of TennesseeUniversity of Tennessee Volunteers 2112

Division B

Team1B2B3B
Auburn UniversityAuburn University Tigers10109
Clemson UniversityClemson University Tigers9910
Duke UniversityDuke University Blue Devils887
University of GeorgiaUniversity of Georgia Bulldogs443
Georgia Institute of TechnologyGeorgia Institute of Technology Yellow Jackets 1778
Georgia Institute of TechnologyGeorgia Institute of Technology Yellow Jackets 2665
North Carolina State UniversityNorth Carolina State University Wolfpack556
University of South CarolinaUniversity of South Carolina Coed334
University of TennesseeUniversity of Tennessee Volunteers 1221
University of TennesseeUniversity of Tennessee Volunteers 2112

Conditions — 03/28/2015 (8am–6pm)

☀️Clear sky
Humidity 41%  ·  Pressure 1023.5 hPa

Temperature

38°F
↑ 44°F   ↓ 29°F
Feels like 31°F

Wind

● from   ▲ toward
5.1 kn
avg  ·  max 6.0 kn
Gusts to 16.9 kn
From NNW (344°)

Sky & Precipitation

Cloud cover27% Sunshine10.1 hrs Humidity41% Pressure1023.5 hPa

Orderliness — underdogs or favourites?

Breeze: N 8 kn (weather reanalysis in the scorer’s units)
In this breeze at Tennessee: a typical day (−0.02)
Nothing in the breeze favours either side; expect results to follow the ratings about as usual.
Fleet adjustment +0.12 (a softer or greener fleet makes the ratings stick) · combined forecast +0.10
Actual: about typical, within noise (−0.25 ± 0.20)

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 ±0.02 means a rating gap counts about 1% 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 Tennessee by wind direction (angle) and speed (rings), fitted surface; dots are labelled regatta-days, ★ this regatta (only 3 labelled days at Tennessee, 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 →