| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
College of Charleston | Cougars | 7–1 |
| 2 |  |
Rollins College | Tars | 5–3 |
| 3 |  |
University of South Florida | Bulls | 5–3 |
| 4 |  |
Jacksonville University | Fins | 3–5 |
| 5 |  |
North Carolina State University | Wolfpack | 1–4 |
| 6 |  |
Clemson University | Tigers | 0–5 |
Each side is the sum of its three boats (the skipper's fleet rating times 0.72 plus a team race offset learned from their past matches, plus the crew's offset and a small experience term) plus the school's team race strength and a home-water edge for the host. The win probability is a logistic function of the difference. The forecast was made before the event: the model was refitted on every match sailed before the first day, with fleet ratings as of the week before.
Fitted on the 28,110 team race matches sailed before 2026-02-15, using the line-ups that actually raced. It called 17 of 21 matches (81%) with a log-loss of 0.366 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness −0.07 ± 0.38: a typical event, more orderly than 36% of college team race events (temperature of the forecast log-odds that best fits the results, relative to the league average; nothing about the field, venue or wind predicts it, see the Weather tab). vs forecast is a team's wins minus the wins the model expected from the matches it sailed: positive means it beat its rating.
For each side, the performance strength is the value that would have made its record least surprising: the strength at which the model's expected wins over exactly these opponents equal the actual wins, with every opponent fixed at its pre-event strength. For a skipper, the same shift is applied only to their boat in the matches they sailed, with team-mates and opponents fixed; team-mates who sailed every match together therefore get the same number. Surprise is in bits: -log2 of the probability of the record at the pre-event strength minus the same at the performance strength. P(this good or better) treats matches as independent coin flips at the model's pre-event probabilities, so it ignores form within the day; read it as a rough guide.
Pre-event strength against the strength that would have made each record least surprising, everything else fixed. Δ is in the model's logit units, the same scale as the boat values above (a side is three boats plus the school term); green is a clear over-performance, red a clear under-performance. Skippers need three or more matches.
| Place | School | Strength | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| 4 | Jacksonville University | 4.58 | 5.71 | 3–5 | 2.0 | +1.13 | 0.9 | 24% |
| 2 | Rollins College | 6.42 | 6.88 | 5–3 | 4.5 | +0.46 | 0.2 | 51% |
| 3 | University of South Florida | 7.03 | 6.57 | 5–3 | 5.5 | −0.46 | 0.2 | 84% |
| 5 | North Carolina State University | 4.01 | 3.56 | 1–4 | 1.2 | −0.46 | 0.1 | 86% |
| 1 | College of Charleston | 8.44 | 7.95 | 7–1 | 7.3 | −0.49 | 0.1 | 87% |
| 6 | Clemson University | 2.98 | -0.02 | 0–5 | 0.5 | ≤−3.00 | 0.7 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Cougars | Tars | Bulls | Fins | Wolfpack | Tigers | |
|---|---|---|---|---|---|---|---|---|
| College of Charleston Cougars | 7–1 | ✕ | W | W | W | W | W |
| Rollins College Tars | 5–3 | L | ✕ | W | W | W | W |
| University of South Florida Bulls | 5–3 | L | L | ✕ | W | W | W |
| Jacksonville University Fins | 3–5 | L | L | L | ✕ | W | W |
| North Carolina State University Wolfpack | 1–4 | L | L | L | L | ✕ | W |
| Clemson University Tigers | 0–5 | L | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Tars | 1-2-6 | def. | |
Bulls | 3-4-5 |
| 2 | |
Cougars | 1-2-5 | def. | |
Wolfpack | 3-4-6 |
| 3 | |
Fins | 1-2-6 | def. | |
Tigers | 3-4-5 |
| 4 | |
Cougars | 1-2-5 | def. | |
Tars | 3-4-6 |
| 5 | |
Bulls | 1-2-3 | def. | |
Tigers | 4-5-6 |
| 6 | |
Fins | 1-2-6 | def. | |
Wolfpack | 3-4-5 |
| 7 | |
Tars | 1-2-4 | def. | |
Tigers | 3-5-6 |
| 8 | |
Cougars | 1-2-4 | def. | |
Fins | 3-5-6 |
| 9 | |
Bulls | 1-2-3 | def. | |
Wolfpack | 4-5-6 |
| 10 | |
Cougars | 1-2-3 | def. | |
Tigers | 4-5-6 |
| 11 | |
Bulls | 1-4-5 | def. | |
Fins | 2-3-6 |
| 12 | |
Tars | 1-2-3 | def. | |
Wolfpack | 4-5-6 |
| 13 | |
Bulls | 1-2-4 | def. | |
Cougars | 3-5-6 |
| 14 | |
Wolfpack | 1-2-3 | def. | |
Tigers | 4-5-6 |
| 15 | |
Fins | 1-4-5 | def. | |
Tars | 2-3-6 |
| 16 | |
Cougars | 1-2-3 | def. | |
Fins | 4-5-6 |
| 17 | |
Tars | 1-2-6 | def. | |
Bulls | 3-4-5 |
| 18 | |
Cougars | 1-2-3 | def. | |
Tars | 4-5-6 |
| 19 | |
Bulls | 1-2-4 | def. | |
Fins | 3-5-6 |
| 20 | |
Tars | 1-2-4 | def. | |
Fins | 3-5-6 |
| 21 | |
Cougars | 1-2-6 | def. | |
Bulls | 3-4-5 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
College of Charleston | Cougars | Ashley Alfortish '27 Bella Shakespeare '27 Georgia Shuster '29 |
Lucy Zinn '28 Lucy Elvart '28 Gaelen Adam '29 |
|
Rollins College | Tars | Adelaide Matzky '29 Annie Samis '29 Shay Bridge '28 |
Mollie Wood '29 Jane Mckenzie '27 Maggie Burnham '26 |
|
University of South Florida | Bulls | Ghislaine Van Empel '27 Grace Jones '28 Kailey Warrior '27 |
Catherine Brennan '26 Melissa Janes '26 Madisen Hamai '26 |
|
Jacksonville University | Fins | Fiona Froelich '28 Kaitlyn Anderson '29 Kaitlyn Liebel '26 |
Cheyenne Dooley '28 Annie Mckenzie '29 Amelia Sulciner '28 |
|
North Carolina State University | Wolfpack | Evelyn Hannah '28 Lyla Solway '28 Olivia Burdette '29 |
Olivia Soucy '28 Sarina Schmoyer '27 Reese Levinson '29 |
|
Clemson University | Tigers | Ashton Loring '26 Madeleine Harris '29 Myah Frashier '28 |
Vanessa Marahrens '26 Madison Cannon '29 Taylor Bulwinkle '28 |
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% less 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.
Short write-ups of what the ratings and results show, with the numbers and how they were computed.
