Navigate

MCSA Women's Championship

# SchoolTeam A B TOT
1 University of Wisconsin University of Wisconsin Badgers 13 15 28
2 University of Michigan University of Michigan Wolverines 22 20 42
3 University of Notre Dame University of Notre Dame Fighting Irish 44 29 73
4 University of Minnesota University of Minnesota Gophers 48 48 96
5 Northwestern University Northwestern University Wildcats 59 39 98
6 Spartans Spartans Spartans 54 MRP 89 MRP 143 MRP
7 University of Toledo University of Toledo Rockets 93 MRP 93 MRP 186 MRP
8 John Carroll University John Carroll University John Carroll 107 MRP 101 MRP 208 MRP
9 Broncos Broncos Broncos 104 MRP 110 MRP 214 MRP
SchoolTeam R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 TOT Sailors
University of Wisconsin University of Wisconsin Badgers 2 1 1 1 1 2 1 2 1 1 13 Andrea Sullivan '18
Maggie Houtz '19
University of Michigan University of Michigan Wolverines 1 2 2 2 2 1 2 1 3 6 22 Lane Tobin '18
Amy Baer '19
University of Notre Dame University of Notre Dame Fighting Irish 5 3 3 4 3 5 7 5 6 3 44 Chloe Frentzel '21 [1-10]
Molly Lafave '19 [1-2, 5-6, 9-10]
Grace Hillman '20 [3-4, 7-8]
University of Minnesota University of Minnesota Gophers 4 6 5 5 5 6 4 6 2 5 48 Cailin Oakes '18 [1-10]
Madeline Jones '20 [1-4]
Holly Mckee '20 [5-10]
Spartans Spartans Spartans 3 4 4 3 4 3 3 3 5 2 54 MRP
Northwestern University Northwestern University Wildcats 8 8 6 6 DNF 4 5 4 4 4 59 Susan Riley '17
Mariel Tang '20
University of Toledo University of Toledo Rockets 6 5 8 7 DNF DNS 6 7 7 7 93 MRP Kristen Ruta '19
Carrington Gelardi '18
Broncos Broncos Broncos 7 7 7 8 DNF DNS DNS 8 8 9 104 MRP
John Carroll University John Carroll University John Carroll 9 9 9 9 DNF 7 8 9 9 8 107 MRP Molly Mccarthy '19
Gianna Caroniti '19
SchoolTeam R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 TOT Sailors
University of Wisconsin University of Wisconsin Badgers 3 1 3 1 1 1 2 1 1 1 15 Carolyn Keck '19 [1-10]
Emma Zalog '20 [1-2]
Rebekah Janssen '21 [3-10]
University of Michigan University of Michigan Wolverines 2 3 1 2 2 3 1 2 2 2 20 Sarah Youtt '21
Sarah Silvestri '19
University of Notre Dame University of Notre Dame Fighting Irish 4 2 2 3 3 2 3 4 3 3 29 Leah Peluchiwski '20
Kata Lamb '20
Northwestern University Northwestern University Wildcats 1 5 5 4 4 4 5 3 4 4 39 Audrey Debruine '19
Olivia Martins '20
University of Minnesota University of Minnesota Gophers 5 4 4 5 5 5 4 5 6 5 48 Bailey Adkins '19
Cassandra Trask '20
Spartans Spartans Spartans 9 6 6 7 7 6 7 6 5 DNF 89 MRP
University of Toledo University of Toledo Rockets 6 7 8 6 6 7 8 8 7 DNF 93 MRP Rebeccca Sadoski '18 [1-10]
Kaitlin Conner '20 [1-4]
Caitlin Mutti '20 [5-10]
John Carroll University John Carroll University John Carroll 8 DNF DNS DNS 8 8 6 7 8 6 101 MRP Hannah Roberts '21
Samantha Nagy '21
Broncos Broncos Broncos 7 DNS 7 8 DNF DNS 9 9 DNF DNF 110 MRP
Boat Speed Analyzer
SlowExpected boat effectFast
−0.080+0.08
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 2015 (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

Team1A2A3A4A5A6A7A8A9A10A
John Carroll UniversityJohn Carroll University John Carroll101033557799
University of MichiganUniversity of Michigan Wolverines446688101033
SpartansSpartans Spartans224466881010
University of MinnesotaUniversity of Minnesota Gophers5577992244
Northwestern UniversityNorthwestern University Wildcats3355779922
University of Notre DameUniversity of Notre Dame Fighting Irish668810103355
University of ToledoUniversity of Toledo Rockets7799224466
BroncosBroncos Broncos9922446688
University of WisconsinUniversity of Wisconsin Badgers881010335577

Division B

Team1B2B3B4B5B6B7B8B9B10B
John Carroll UniversityJohn Carroll University John Carroll224466881010
University of MichiganUniversity of Michigan Wolverines5577992244
SpartansSpartans Spartans3355779922
University of MinnesotaUniversity of Minnesota Gophers668810103355
Northwestern UniversityNorthwestern University Wildcats446688101033
University of Notre DameUniversity of Notre Dame Fighting Irish7799224466
University of ToledoUniversity of Toledo Rockets881010335577
BroncosBroncos Broncos101033557799
University of WisconsinUniversity of Wisconsin Badgers9922446688

Conditions — 04/14/2018 (8am–6pm)

☁️Overcast
Humidity 93%  ·  Pressure 1014.8 hPa

Temperature

37°F
↑ 39°F   ↓ 33°F
Feels like 27°F

Wind

● from   ▲ toward
13.2 kn
avg  ·  max 14.8 kn
Gusts to 29.5 kn
From NE (54°)

Sky & Precipitation

Cloud cover100% Sunshine0.0 hrs Humidity93% Pressure1014.8 hPa Rain0.58 in

Orderliness — underdogs or favourites?

Breeze: NE 14 kn · E 14 kn (weather reanalysis in the scorer’s units)
In this breeze at Michigan: a strongly favourites’ day (+0.14)
Back the top seeds: results should follow the ratings, and the gaps between favourites hold.
Fleet adjustment +0.10 (a softer or greener fleet makes the ratings stick) · combined forecast +0.24
Actual: a strongly favourites’ day (+0.59 ± 0.16)

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 ±0.14 means a rating gap counts about 12% more 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 Michigan by wind direction (angle) and speed (rings), fitted surface; dots are labelled regatta-days, ★ this regatta (only 12 labelled days at Michigan, 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 →