| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 | University of South Florida | Bulls | 15–0 | |
| 2 | University of Miami | Hurricanes | 9–6 | |
| 3 | Jacksonville University | Dolphins | 9–6 | |
| 4 | Rollins College | Tars | 7–8 | |
| 5 | Jacksonville University | Fins | 3–12 | |
| 6 | Clemson University | Tigers | 2–13 |
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 25,056 team race matches sailed before 2025-02-15, using the line-ups that actually raced. It called 38 of 45 matches (84%) with a log-loss of 0.433 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.44 ± 0.30: an orderly event, more orderly than 89% 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) |
|---|---|---|---|---|---|---|---|---|
| 1 | University of South Florida Bulls | 7.06 | 10.06 | 15–0 | 12.7 | ≥+3.00 | 3.4 | 8% |
| 2 | University of Miami Hurricanes | 5.39 | 5.97 | 9–6 | 7.3 | +0.58 | 0.7 | 24% |
| 4 | Rollins College Tars | 4.91 | 5.44 | 7–8 | 5.4 | +0.53 | 0.6 | 25% |
| 5 | Jacksonville University Fins | 4.51 | 4.09 | 3–12 | 4.0 | −0.42 | 0.3 | 82% |
| 3 | Jacksonville University Dolphins | 6.31 | 5.76 | 9–6 | 10.5 | −0.55 | 0.6 | 90% |
| 6 | Clemson University Tigers | 4.81 | 3.49 | 2–13 | 5.0 | −1.32 | 2.6 | 99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Zachariah Schemel | University of South Florida | 2.58 | 5.58 | 15–0 | 12.7 | ≥+3.00 | 3.4 | 8% |
| Efe Guder | University of South Florida | 2.03 | 5.03 | 15–0 | 12.7 | ≥+3.00 | 3.4 | 8% |
| Danny Riano | University of Miami | 2.06 | 2.65 | 9–6 | 7.3 | +0.58 | 0.7 | 24% |
| Ka Hamner | Rollins College | 1.18 | 1.71 | 7–8 | 5.4 | +0.53 | 0.6 | 25% |
| Jack Adderley | Rollins College | 1.08 | 1.61 | 7–8 | 5.4 | +0.53 | 0.6 | 25% |
| Ella Lansford | Jacksonville University | 1.08 | 0.66 | 3–12 | 4.0 | −0.42 | 0.3 | 82% |
| Stefanos Pappas | Jacksonville University | 1.77 | 1.22 | 9–6 | 10.5 | −0.55 | 0.6 | 90% |
| Joshua Knowles | Jacksonville University | 1.62 | 1.07 | 9–6 | 10.5 | −0.55 | 0.6 | 90% |
| Nilah Miller | Clemson University | 1.68 | 0.36 | 2–13 | 5.0 | −1.32 | 2.6 | 99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Bulls | Hurricanes | Dolphins | Tars | Fins | Tigers | |
|---|---|---|---|---|---|---|---|---|
| University of South Florida Bulls | 5–0 | ✕ | W | W | W | W | W | |
| University of Miami Hurricanes | 4–1 | L | ✕ | W | W | W | W | |
| Jacksonville University Dolphins | 4–6 | L | L | ✕ | L | ✕ | W | |
| Rollins College Tars | 2–3 | L | L | W | ✕ | W | W | |
| Jacksonville University Fins | 4–6 | L | L | ✕ | L | ✕ | W | |
| Clemson University Tigers | 0–5 | L | L | L | L | L | ✕ |
| Team | Rec. | Bulls | Hurricanes | Dolphins | Tars | Fins | Tigers | |
|---|---|---|---|---|---|---|---|---|
| University of South Florida Bulls | 5–0 | ✕ | W | W | W | W | W | |
| University of Miami Hurricanes | 2–3 | L | ✕ | L | W | L | L | |
| Jacksonville University Dolphins | 5–5 | L | W | ✕ | L | ✕ | W | |
| Rollins College Tars | 2–3 | L | L | W | ✕ | W | W | |
| Jacksonville University Fins | 5–5 | L | W | ✕ | L | ✕ | W | |
| Clemson University Tigers | 1–4 | L | W | L | L | L | ✕ |
| Team | Rec. | Bulls | Hurricanes | Dolphins | Tars | Fins | Tigers | |
|---|---|---|---|---|---|---|---|---|
| University of South Florida Bulls | 5–0 | ✕ | W | W | W | W | W | |
| University of Miami Hurricanes | 3–2 | L | ✕ | W | L | W | W | |
| Jacksonville University Dolphins | 3–7 | L | L | ✕ | L | ✕ | L | |
| Rollins College Tars | 3–2 | L | W | W | ✕ | W | W | |
| Jacksonville University Fins | 3–7 | L | L | ✕ | L | ✕ | L | |
| Clemson University Tigers | 1–4 | L | L | W | L | W | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | Tars | 1-2-4 | def. | Tigers | 3-5-6 | ||
| 2 | Dolphins | 1-2-6 | def. | Fins | 3-4-5 | ||
| 3 | Bulls | 1-2-4 | def. | Hurricanes | 3-5-6 | ||
| 4 | Dolphins | 1-2-4 | def. | Tigers | 3-5-6 | ||
| 5 | Bulls | 1-3-5 | def. | Tars | 2-4-6 | ||
| 6 | Hurricanes | 1-2-5 | def. | Fins | 3-4-6 | ||
| 7 | Bulls | 1-2-5 | def. | Dolphins | 3-4-6 | ||
| 8 | Fins | 2-3-4 | def. | Tigers | 1-5-6 | ||
| 9 | Hurricanes | 1-4-5 | def. | Tars | 2-3-6 | ||
| 10 | Bulls | 1-3-5 | def. | Fins | 2-4-6 | ||
| 11 | Dolphins | 1-2-5 | def. | Tars | 3-4-6 | ||
| 12 | Hurricanes | 2-3-5 | def. | Tigers | 1-4-6 | ||
| 13 | Tars | 1-2-5 | def. | Fins | 3-4-6 | ||
| 14 | Bulls | 1-2-5 | def. | Tigers | 3-4-6 | ||
| 15 | Hurricanes | 1-3-4 | def. | Dolphins | 2-5-6 | ||
| 16 | Tars | 2-3-4 | def. | Tigers | 1-5-6 | ||
| 17 | Dolphins | 1-2-5 | def. | Fins | 3-4-6 | ||
| 18 | Bulls | 1-2-5 | def. | Hurricanes | 3-4-6 | ||
| 19 | Dolphins | 1-2-3 | def. | Tigers | 4-5-6 | ||
| 20 | Bulls | 1-2-5 | def. | Tars | 3-4-6 | ||
| 21 | Hurricanes | 1-2-5 | def. | Fins | 3-4-6 | ||
| 22 | Bulls | 1-3-6 | def. | Dolphins | 2-4-5 | ||
| 23 | Fins | 1-3-5 | def. | Tigers | 2-4-6 | ||
| 24 | Hurricanes | 1-2-6 | def. | Tars | 3-4-5 | ||
| 25 | Bulls | 1-2-4 | def. | Fins | 3-5-6 | ||
| 26 | Dolphins | 1-2-5 | def. | Tars | 3-4-6 | ||
| 27 | Tigers | 1-3-6 | def. | Hurricanes | 2-4-5 | ||
| 28 | Tars | 1-3-5 | def. | Fins | 2-4-6 | ||
| 29 | Bulls | 1-2-3 | def. | Tigers | 4-5-6 | ||
| 30 | Dolphins | 1-2-4 | def. | Hurricanes | 3-5-6 | ||
| 31 | Tars | 2-3-4 | def. | Tigers | 1-5-6 | ||
| 32 | Fins | 1-3-6 | def. | Dolphins | 2-4-5 | ||
| 33 | Bulls | 1-2-4 | def. | Hurricanes | 3-5-6 | ||
| 34 | Dolphins | 1-2-5 | def. | Tigers | 3-4-6 | ||
| 35 | Bulls | 1-2-3 | def. | Tars | 4-5-6 | ||
| 36 | Hurricanes | 1-2-6 | def. | Fins | 3-4-5 | ||
| 37 | Bulls | 1-4-5 | def. | Dolphins | 2-3-6 | ||
| 38 | Tigers | 1-2-3 | def. | Fins | 4-5-6 | ||
| 39 | Tars | 2-3-5 | def. | Hurricanes | 1-4-6 | ||
| 40 | Bulls | 1-2-5 | def. | Fins | 3-4-6 | ||
| 41 | Dolphins | 2-3-4 | def. | Tars | 1-5-6 | ||
| 42 | Hurricanes | 1-2-5 | def. | Tigers | 3-4-6 | ||
| 43 | Tars | 1-2-4 | def. | Fins | 3-5-6 | ||
| 44 | Bulls | 1-2-5 | def. | Tigers | 3-4-6 | ||
| 45 | Hurricanes | 1-2-6 | def. | Dolphins | 3-4-5 | ||
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
| University of South Florida | Bulls | Efe Guder '28 Humberto Porrata '25 Zachariah Schemel '25 |
Ruth Bergman '28 Mercedes Newland Cespedes '24 Saleta Powell '25 |
|
| University of Miami | Hurricanes | Danny Riano '27 Harrison Vanderground '28 Nathan Long '28 |
Isaac Van Buren '28 Jospeh Iacono '27 Jadin Gonzalez '28 |
|
| Jacksonville University | Dolphins | Joshua Knowles '26 Patrick Igoe '26 Stefanos Pappas '25 |
Elizabeth Williamson '26 Roman Borger '26 Sarah Goodyear '26 |
|
| Rollins College | Tars | Jack Adderley '28 Ka Hamner '26 Milo Miller '27 |
Maggie Burnham '26 Henry Campbell '25 Alexander Goldsmith '28 Jane Mckenzie '27 |
|
| Jacksonville University | Fins | Ella Lansford '27 Ella Wisely '27 Fiona Froelich '28 |
Rori Bywater '25 Owen Bannasch '26 Kayla Putzke '24 |
|
| Clemson University | Tigers | Luke Adams '28 Nilah Miller '25 Rowan Barnes '26 |
Paige Phillips '25 Ellison Fleming '26 Jonathan Caruso '25 |
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 ±0.03 means a rating gap counts about 3% 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.