| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Brown University | Bears | 10–0 |
| 2 |  |
Tufts University | Jumbos | 8–2 |
| 3 |  |
University of Rhode Island | Rams | 5–5 |
| 4 |  |
Boston University | Terriers | 4–6 |
| 5 |  |
Northeastern University | Huskies | 2–8 |
| 6 |  |
Bowdoin College | Polar Bears | 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 26,169 team race matches sailed before 2025-03-22, using the line-ups that actually raced. It called 28 of 30 matches (93%) with a log-loss of 0.330 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.35 ± 0.34: an orderly event, more orderly than 80% 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 | Brown University | 9.04 | 12.04 | 10–0 | 8.4 | ≥+3.00 | 2.6 | 14% |
| 5 | Northeastern University | 5.12 | 5.68 | 2–8 | 1.3 | +0.56 | 0.3 | 40% |
| 4 | Boston University | 6.61 | 6.94 | 4–6 | 3.5 | +0.34 | 0.1 | 48% |
| 2 | Tufts University | 8.91 | 8.76 | 8–2 | 8.2 | −0.16 | 0.0 | 76% |
| 3 | University of Rhode Island | 7.38 | 7.20 | 5–5 | 5.3 | −0.19 | 0.0 | 74% |
| 6 | Bowdoin College | 6.50 | 4.60 | 1–9 | 3.3 | −1.89 | 2.8 | 99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Charles Gish | Brown University | 2.82 | 5.82 | 6–0 | 5.5 | ≥+3.00 | 0.8 | 56% |
| Aidan Boni | Northeastern University | 1.91 | 2.54 | 2–4 | 1.3 | +0.63 | 0.3 | 38% |
| Gavin Monaghan | Boston University | 1.95 | 2.28 | 4–6 | 3.5 | +0.34 | 0.1 | 48% |
| Richard Kalich | Boston University | 1.81 | 2.15 | 4–6 | 3.5 | +0.34 | 0.1 | 48% |
| Grant Smith | Northeastern University | 0.97 | -2.02 | 0–4 | 0.1 | ≤−3.00 | 0.1 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Bears | Jumbos | Rams | Terriers | Huskies | Bears | |
|---|---|---|---|---|---|---|---|---|
| Brown University Bears | 5–0 | ✕ | W | W | W | W | W |
| Tufts University Jumbos | 4–1 | L | ✕ | W | W | W | W |
| University of Rhode Island Rams | 3–2 | L | L | ✕ | W | W | W |
| Boston University Terriers | 2–3 | L | L | L | ✕ | W | W |
| Northeastern University Huskies | 0–5 | L | L | L | L | ✕ | L |
| Bowdoin College Polar Bears | 1–4 | L | L | L | L | W | ✕ |
| Team | Rec. | Bears | Jumbos | Rams | Terriers | Huskies | Bears | |
|---|---|---|---|---|---|---|---|---|
| Brown University Bears | 5–0 | ✕ | W | W | W | W | W |
| Tufts University Jumbos | 4–1 | L | ✕ | W | W | W | W |
| University of Rhode Island Rams | 2–3 | L | L | ✕ | W | L | W |
| Boston University Terriers | 2–3 | L | L | L | ✕ | W | W |
| Northeastern University Huskies | 2–3 | L | L | W | L | ✕ | W |
| Bowdoin College Polar Bears | 0–5 | L | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Terriers | 1-2-5 | def. | |
Huskies | 3-4-6 |
| 2 | |
Bears | 1-2-3 | def. | |
Jumbos | 4-5-6 |
| 3 | |
Rams | 1-3-6 | def. | |
Polar Bears | 2-4-5 |
| 4 | |
Bears | 1-2-5 | def. | |
Terriers | 3-4-6 |
| 5 | |
Rams | 1-2-5 | def. | |
Huskies | 3-4-6 |
| 6 | |
Jumbos | 1-2-4 | def. | |
Polar Bears | 3-5-6 |
| 7 | |
Bears | 1-2-4 | def. | |
Rams | 3-5-6 |
| 8 | |
Jumbos | 1-2-5 | def. | |
Terriers | 3-4-6 |
| 9 | |
Polar Bears | 2-3-4 | def. | |
Huskies | 1-5-6 DNF |
| 10 | |
Jumbos | 1-3-5 | def. | |
Rams | 2-4-6 |
| 11 | |
Bears | 1-2-3 | def. | |
Huskies | 4-5-6 |
| 12 | |
Terriers | 1-2-5 | def. | |
Polar Bears | 3-4-6 |
| 13 | |
Jumbos | 1-2-4 | def. | |
Huskies | 3-5-6 |
| 14 | |
Rams | 1-2-4 | def. | |
Terriers | 3-5-6 |
| 15 | |
Bears | 1-2-4 | def. | |
Polar Bears | 3-5-6 |
| 16 | |
Bears | 1-2-4 | def. | |
Huskies | 3-5-6 |
| 17 | |
Rams | 1-2-5 | def. | |
Polar Bears | 3-4-6 |
| 18 | |
Jumbos | 1-2-5 | def. | |
Terriers | 3-4-6 |
| 19 | |
Bears | 1-2-3 | def. | |
Polar Bears | 4-5-6 |
| 20 | |
Jumbos | 1-2-4 | def. | |
Huskies | 3-5-6 |
| 21 | |
Rams | 2-3-5 | def. | |
Terriers | 1-4-6 |
| 22 | |
Jumbos | 1-2-5 | def. | |
Polar Bears | 3-4-6 |
| 23 | |
Bears | 1-2-3 | def. | |
Rams | 4-5-6 |
| 24 | |
Terriers | 1-2-6 | def. | |
Huskies | 3-4-5 |
| 25 | |
Jumbos | 2-3-5 | def. | |
Rams | 1-4-6 |
| 26 | |
Huskies | 1-2-5 | def. | |
Polar Bears | 3-4-6 |
| 27 | |
Bears | 1-2-4 | def. | |
Terriers | 3-5-6 |
| 28 | |
Huskies | 1-2-5 | def. | |
Rams | 3-4-6 |
| 29 | |
Bears | 1-2-4 | def. | |
Jumbos | 3-5-6 |
| 30 | |
Terriers | 1-2-3 | def. | |
Polar Bears | 4-5-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Brown University | Bears | Charles Gish '28 James Brock '28 Sidney Moyer '27 Tyler Lamm '28 |
Phoebe Hackett '28 Corinne Harrison '27 Janelle Li '25 Reese Corckran '28 |
|
Tufts University | Jumbos | Courtland Doyle '27 Devon Owen '27 Gus Macaulay '27 |
Magdelaina Putnam '25 Margaret Klein '26 Lucy Belknap '25 |
|
University of Rhode Island | Rams | Kytalin Hendrickson '26 Max Sigel '26 Olin Guck '26 |
Erin Little '28 Ava Deangelis '28 Olivia Dutra '28 |
|
Boston University | Terriers | Gavin Monaghan '26 Nathan Selian '25 Richard Kalich '26 |
Meg Woolverton '27 Grace Murphy '25 Benjamin Luu '27 |
|
Northeastern University | Huskies | Aidan Boni '26 Carter Anderson '27 Grant Smith '28 Isabella Cho '27 |
Hala Gilbert '26 Isabella Welch '25 Ryan Tedeschi '28 |
|
Bowdoin College | Polar Bears | Benjamin Stevens '25 Cole Amaral '28 Shea Mcgrath '27 |
Hazel Johnson '27 Ava Tobias '28 Posie Cabaniss '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 ±0.02 means a rating gap counts about 2% 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.
