| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 | College of Charleston | Cougars | 8–2 | |
| 2 | University of Miami | Hurricanes | 8–2 | |
| 3 | University of South Florida | Bulls | 6–4 | |
| 4 | Eckerd College | Tritons | 4–6 | |
| 5 | Jacksonville University | Fins | 4–6 | |
| 6 | Rollins College | Tars | 0–10 |
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 16,026 team race matches sailed before 2022-02-26, using the line-ups that actually raced. It called 26 of 30 matches (87%) with a log-loss of 0.433 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness −0.42 ± 0.31: an upset-heavy event, more orderly than 13% 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) |
|---|---|---|---|---|---|---|---|---|
| 5 | Jacksonville University | 4.66 | 6.16 | 4–6 | 2.5 | +1.50 | 1.9 | 10% |
| 2 | University of Miami | 7.46 | 8.36 | 8–2 | 7.2 | +0.90 | 0.5 | 40% |
| 3 | University of South Florida | 6.73 | 6.61 | 6–4 | 6.2 | −0.12 | 0.0 | 73% |
| 4 | Eckerd College | 5.79 | 5.25 | 4–6 | 4.5 | −0.54 | 0.2 | 87% |
| 1 | College of Charleston | 9.01 | 7.45 | 8–2 | 9.4 | −1.55 | 1.8 | 99% |
| 6 | Rollins College | 2.42 | -0.58 | 0–10 | 0.3 | ≤−3.00 | 0.4 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Stefanos Pappas | Jacksonville University | 1.62 | 3.12 | 4–6 | 2.5 | +1.50 | 1.9 | 10% |
| Thomas Pappas | Jacksonville University | 1.40 | 2.90 | 4–6 | 2.5 | +1.50 | 1.9 | 10% |
| Richard Mccann | University of Miami | 2.36 | 3.26 | 8–2 | 7.2 | +0.90 | 0.5 | 40% |
| Atlee Kohl | University of Miami | 2.58 | 3.49 | 8–2 | 7.2 | +0.90 | 0.5 | 40% |
| Aidan Dennis | University of Miami | 2.26 | 3.16 | 8–2 | 7.2 | +0.90 | 0.5 | 40% |
| Aden Anderson | Jacksonville University | 1.26 | 1.39 | 2–2 | 2.0 | +0.13 | 0.0 | 86% |
| Andreas Keswater | University of South Florida | 1.90 | 1.78 | 6–4 | 6.2 | −0.12 | 0.0 | 73% |
| Zachariah Schemel | University of South Florida | 2.34 | 2.22 | 6–4 | 6.2 | −0.12 | 0.0 | 73% |
| Axel Stordahl | College of Charleston | 2.87 | 1.01 | 6–2 | 7.5 | −1.86 | 2.3 | 99% |
| Jackson Mcgeough | Rollins College | 0.23 | -2.77 | 0–10 | 0.3 | ≤−3.00 | 0.4 | >99% |
| Jason Goldsmith | Rollins College | 0.25 | -2.75 | 0–10 | 0.3 | ≤−3.00 | 0.4 | >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 | Hurricanes | Bulls | Tritons | Fins | Tars | |
|---|---|---|---|---|---|---|---|---|
| College of Charleston Cougars | 4–1 | ✕ | W | W | W | L | W | |
| University of Miami Hurricanes | 4–1 | L | ✕ | W | W | W | W | |
| University of South Florida Bulls | 2–3 | L | L | ✕ | W | L | W | |
| Eckerd College Tritons | 2–3 | L | L | L | ✕ | W | W | |
| Jacksonville University Fins | 3–2 | W | L | W | L | ✕ | W | |
| Rollins College Tars | 0–5 | L | L | L | L | L | ✕ |
| Team | Rec. | Cougars | Hurricanes | Bulls | Tritons | Fins | Tars | |
|---|---|---|---|---|---|---|---|---|
| College of Charleston Cougars | 4–1 | ✕ | L | W | W | W | W | |
| University of Miami Hurricanes | 4–1 | W | ✕ | L | W | W | W | |
| University of South Florida Bulls | 4–1 | L | W | ✕ | W | W | W | |
| Eckerd College Tritons | 2–3 | L | L | L | ✕ | W | W | |
| Jacksonville University Fins | 1–4 | L | L | L | L | ✕ | W | |
| Rollins College Tars | 0–5 | L | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | Tritons | 1-2-6 DNF | def. | Fins | 3-4-5 | ||
| 2 | Cougars | 1-2-5 | def. | Hurricanes | 3-4-6 | ||
| 3 | Bulls | 1-2-3 | def. | Tars | 4-5-6 | ||
| 4 | Fins | 1-2-6 | def. | Cougars | 3-4-5 | ||
| 5 | Bulls | 1-2-3 | def. | Tritons | 4-5-6 | ||
| 6 | Hurricanes | 1-2-3 | def. | Tars | 4-5-6 | ||
| 7 | Fins | 1-3-5 | def. | Bulls | 2-4-6 | ||
| 8 | Cougars | 1-2-3 | def. | Tars | 4-5-6 | ||
| 9 | Hurricanes | 1-2-3 | def. | Tritons | 4-5-6 | ||
| 10 | Cougars | 2-3-5 | def. | Bulls | 1-4-6 | ||
| 11 | Tritons | 1-2-3 | def. | Tars | 4-5-6 | ||
| 12 | Hurricanes | 1-2-3 | def. | Fins | 4-5-6 | ||
| 13 | Cougars | 1-2-5 | def. | Tritons | 3-4-6 | ||
| 14 | Hurricanes | 1-2-5 | def. | Bulls | 3-4-6 | ||
| 15 | Fins | 1-2-3 | def. | Tars | 4-5-6 DNS,DNS,DNS | ||
| 16 | Tritons | 2-3-4 | def. | Fins | 1-5-6 | ||
| 17 | Hurricanes | 2-3-4 | def. | Cougars | 1-5-6 | ||
| 18 | Bulls | 1-2-3 | def. | Tars | 4-5-6 DNS,DNS,DNS | ||
| 19 | Cougars | 1-2-5 | def. | Fins | 3-4-6 | ||
| 20 | Bulls | 1-2-6 | def. | Tritons | 3-4-5 | ||
| 21 | Hurricanes | 1-2-3 | def. | Tars | 4-5-6 DNS,DNS,DNS | ||
| 22 | Bulls | 2-3-4 | def. | Fins | 1-5-6 | ||
| 23 | Cougars | 1-2-3 | def. | Tars | 4-5-6 DNS,DNS,DNS | ||
| 24 | Hurricanes | 1-2-4 | def. | Tritons | 3-5-6 | ||
| 25 | Cougars | 1-2-5 | def. | Bulls | 3-4-6 | ||
| 26 | Tritons | 1-2-3 | def. | Tars | 4-5-6 DNS,DNS,DNS | ||
| 27 | Hurricanes | 1-2-4 | def. | Fins | 3-5-6 | ||
| 28 | Cougars | 1-2-6 | def. | Tritons | 3-4-5 | ||
| 29 | Bulls | 1-2-5 | def. | Hurricanes | 3-4-6 | ||
| 30 | Fins | 1-2-3 | def. | Tars | 4-5-6 DNS,DNS,DNS | ||
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
| College of Charleston | Cougars | Axel Stordahl '24 Brandon Geller '23 Max Anker '24 Pierce Ornstein '22 |
Noelle Owen '23 Chloe Hudgins '24 Anna Sherry '23 Jack Sutton '22 |
|
| University of Miami | Hurricanes | Aidan Dennis '25 Atlee Kohl '25 Richard Mccann '23 |
Chloe Beach '24 Natalie Elder '25 Grace Harden '22 |
|
| University of South Florida | Bulls | Andreas Keswater '24 Humberto Porrata '25 Zachariah Schemel '25 |
Emmy Digiacomo '24 Jackie Morrison '23 Aine-Maire Porter '25 Hannah Marsicano '24 |
|
| Eckerd College | Tritons | Cameron Robinson '23 Eden Nykamp '25 Griffin Richardson '25 Sean Tallman '22 |
Amelia Johnson '25 Brooks Jordan '24 Elissa Martinez '23 |
|
| Jacksonville University | Fins | Aden Anderson '25 Patrick Barney '25 Stefanos Pappas '25 Thomas Pappas '25 |
Kayla Putzke '24 Elisabeth Bowman '22 Piper Desantis '23 Mia Porter '22 |
|
| Rollins College | Tars | Carly Orhan '23 Jackson Mcgeough '25 Jason Goldsmith '23 |
Angelina Khourisader '23 Imogene Dunn '25 Clayton Weum '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 ±0.01 means a rating gap counts about 1% 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.
Short write-ups of what the ratings and results show, with the numbers and how they were computed.