| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Tufts University | Jumbos | 9–1 |
| 2 |  |
Roger Williams University | Hawks | 7–3 |
| 3 |  |
Brown University | Bears | 6–4 |
| 4 |  |
Harvard University | Crimson | 4–6 |
| 5 |  |
Boston College | Eagles | 3–7 |
| 6 |  |
Boston University | Terriers | 1–9 |
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 31,338 team race matches sailed before 2026-10-24, using the line-ups that actually raced. It called 16 of 30 matches (53%) with a log-loss of 0.696 (a coin flip scores 0.693), so the event went poorly for the forecast. 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 | Tufts University | 7.74 | 9.93 | 9–1 | 5.8 | +2.20 | 4.5 | 2% |
| 4 | Harvard University | 5.95 | 7.30 | 4–6 | 1.7 | +1.35 | 2.4 | 6% |
| 2 | Roger Williams University | 7.73 | 8.43 | 7–3 | 5.7 | +0.70 | 0.6 | 28% |
| 3 | Brown University | 8.50 | 7.68 | 6–4 | 7.5 | −0.82 | 0.9 | 94% |
| 6 | Boston University | 6.11 | 5.03 | 1–9 | 2.1 | −1.08 | 0.8 | 94% |
| 5 | Boston College | 8.38 | 6.20 | 3–7 | 7.2 | −2.18 | 6.6 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Jumbos | Hawks | Bears | Crimson | Eagles | Terriers | |
|---|---|---|---|---|---|---|---|---|
| Tufts University Jumbos | 5–0 | ✕ | W | W | W | W | W |
| Roger Williams University Hawks | 4–1 | L | ✕ | W | W | W | W |
| Brown University Bears | 2–3 | L | L | ✕ | W | L | W |
| Harvard University Crimson | 2–3 | L | L | L | ✕ | W | W |
| Boston College Eagles | 2–3 | L | L | W | L | ✕ | W |
| Boston University Terriers | 0–5 | L | L | L | L | L | ✕ |
| Team | Rec. | Jumbos | Hawks | Bears | Crimson | Eagles | Terriers | |
|---|---|---|---|---|---|---|---|---|
| Tufts University Jumbos | 4–1 | ✕ | W | W | L | W | W |
| Roger Williams University Hawks | 3–2 | L | ✕ | L | W | W | W |
| Brown University Bears | 4–1 | L | W | ✕ | W | W | W |
| Harvard University Crimson | 2–3 | W | L | L | ✕ | L | W |
| Boston College Eagles | 1–4 | L | L | L | W | ✕ | L |
| Boston University Terriers | 1–4 | L | L | L | L | W | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Bears | 1-2-4 | def. | |
Terriers | 3-5-6 |
| 2 | |
Crimson | 2-3-5 | def. | |
Eagles | 1-4-6 |
| 3 | |
Jumbos | 1-2-6 | def. | |
Hawks | 3-4-5 |
| 4 | |
Eagles | 1-2-3 | def. | |
Terriers | 4-5-6 |
| 5 | |
Jumbos | 2-3-4 | def. | |
Bears | 1-5-6 |
| 6 | |
Hawks | 1-2-5 | def. | |
Crimson | 3-4-6 |
| 7 | |
Jumbos | 1-2-4 | def. | |
Terriers | 3-5-6 |
| 8 | |
Hawks | 1-4-5 | def. | |
Eagles | 2-3-6 |
| 9 | |
Bears | 1-2-3 | def. | |
Crimson | 4-5-6 |
| 10 | |
Jumbos | 1-2-4 | def. | |
Eagles | 3-5-6 |
| 11 | |
Hawks | 1-2-4 | def. | |
Bears | 3-5-6 |
| 12 | |
Crimson | 2-3-5 | def. | |
Terriers | 1-4-6 |
| 13 | |
Eagles | 1-2-5 | def. | |
Bears | 3-4-6 |
| 14 | |
Jumbos | 1-2-3 | def. | |
Crimson | 4-5-6 |
| 15 | |
Hawks | 1-2-5 | def. | |
Terriers | 3-4-6 |
| 16 | |
Bears | 1-2-6 | def. | |
Terriers | 3-4-5 |
| 17 | |
Eagles | 1-2-5 | def. | |
Crimson | 3-4-6 |
| 18 | |
Jumbos | 2-3-4 | def. | |
Hawks | 1-5-6 |
| 19 | |
Terriers | 1-2-6 | def. | |
Eagles | 3-4-5 |
| 20 | |
Jumbos | 1-3-4 | def. | |
Bears | 2-5-6 |
| 21 | |
Hawks | 1-2-3 | def. | |
Crimson | 4-5-6 |
| 22 | |
Jumbos | 1-2-3 | def. | |
Terriers | 4-5-6 |
| 23 | |
Hawks | 1-3-6 | def. | |
Eagles | 2-4-5 |
| 24 | |
Bears | 1-2-3 | def. | |
Crimson | 4-5-6 |
| 25 | |
Jumbos | 1-2-5 | def. | |
Eagles | 3-4-6 |
| 26 | |
Bears | 1-2-3 | def. | |
Hawks | 4-5-6 |
| 27 | |
Crimson | 1-2-6 | def. | |
Terriers | 3-4-5 |
| 28 | |
Bears | 1-2-5 | def. | |
Eagles | 3-4-6 |
| 29 | |
Crimson | 2-3-4 | def. | |
Jumbos | 1-5-6 |
| 30 | |
Hawks | 1-2-4 | def. | |
Terriers | 3-5-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Tufts University | Jumbos | Grant Schmidt '28 Teddy Bower '30 Walter Mcfarland '29 |
Eliana Mopper '30 Sophia Corzine '30 Jack Poynter '29 |
|
Roger Williams University | Hawks | Connor Mchugh '28 Gavin Morris '29 Spencer Mazur '30 |
Maggie Fleming '27 Brielle Santala '29 Dominik Moncur '29 |
|
Brown University | Bears | Andrew Lamm '30 Charles Gish '28 William Baker '29 |
Ali Mcintyre '27 Kyoko Tonkin '29 Katlia Sherman '30 |
|
Harvard University | Crimson | Max Wolfensberger '30 Pax Huybers '30 Xavier Ayala Vermont '27 |
Elizabeth Jacobsson '30 Noelle Brighton '30 Julia Downey '27 |
|
Boston College | Eagles | Charlotte Macdonald '30 James O’Gwen '27 Sophie Niemann '30 |
Kylie Craig '28 Madeline Torrey '28 Damien Bocan '27 |
|
Boston University | Terriers | Aaron Toy-Lim '30 Benjamin Luu '27 Buck Rathbun '28 Graham Welsh '29 |
Molly Keane '30 Graham Welsh '29 Henry Gesing '29 Benjamin Luu '27 |
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 ±0.11 means a rating gap counts about 9% 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.
