| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Boston University | Terriers | 5–0 |
| 2 |  |
University of Rhode Island | Rams | 3–2 |
| 3 |  |
Bowdoin College | Polar Bears | 2–3 |
| 4 |  |
Roger Williams University | Hawks | 2–3 |
| 5 |  |
Connecticut College | Camels | 2–3 |
| 6 |  |
Tufts University | Jumbos | 1–4 |
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 25,143 team race matches sailed before 2025-03-01, using the line-ups that actually raced. It called 10 of 15 matches (67%) with a log-loss of 0.654 (a coin flip scores 0.693), so the event went poorly for the forecast. Orderliness −0.21 ± 0.73: a typical event, more orderly than 23% 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 | Boston University | 7.11 | 10.11 | 5–0 | 2.7 | ≥+3.00 | 4.4 | 4% |
| 2 | University of Rhode Island | 7.19 | 7.40 | 3–2 | 2.8 | +0.21 | 0.0 | 60% |
| 5 | Connecticut College | 6.62 | 6.59 | 2–3 | 2.0 | −0.03 | 0.0 | 68% |
| 6 | Tufts University | 6.06 | 5.74 | 1–4 | 1.3 | −0.33 | 0.1 | 78% |
| 4 | Roger Williams University | 7.09 | 6.50 | 2–3 | 2.7 | −0.59 | 0.3 | 87% |
| 3 | Bowdoin College | 7.77 | 6.38 | 2–3 | 3.6 | −1.39 | 1.6 | 98% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Elliott Mendenhall | Boston University | 2.53 | 5.53 | 5–0 | 2.7 | ≥+3.00 | 4.4 | 4% |
| Max Teo | Boston University | 1.95 | 4.95 | 5–0 | 2.7 | ≥+3.00 | 4.4 | 4% |
| Lilly Saffer | Connecticut College | 1.36 | 1.33 | 2–3 | 2.0 | −0.03 | 0.0 | 68% |
| Duncan Craine | Connecticut College | 2.10 | 2.06 | 2–3 | 2.0 | −0.03 | 0.0 | 68% |
| Jack Crager | Roger Williams University | 2.10 | 1.43 | 1–2 | 1.4 | −0.67 | 0.2 | 88% |
| Michelangelo Vecchio | Bowdoin College | 2.53 | 1.13 | 2–3 | 3.6 | −1.39 | 1.6 | 98% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Terriers | Rams | Bears | Hawks | Camels | Jumbos | |
|---|---|---|---|---|---|---|---|---|
| Boston University Terriers | 5–0 | ✕ | W | W | W | W | W |
| University of Rhode Island Rams | 3–2 | L | ✕ | W | W | L | W |
| Bowdoin College Polar Bears | 2–3 | L | L | ✕ | W | W | L |
| Roger Williams University Hawks | 2–3 | L | L | L | ✕ | W | W |
| Connecticut College Camels | 2–3 | L | W | L | L | ✕ | W |
| Tufts University Jumbos | 1–4 | L | L | W | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Hawks | 1-2-3 | def. | |
Camels | 4-5-6 |
| 2 | |
Terriers | 1-2-3 | def. | |
Jumbos | 4-5-6 |
| 3 | |
Rams | 1-2-3 | def. | |
Polar Bears | 4-5-6 |
| 4 | |
Terriers | 1-2-5 | def. | |
Camels | 3-4-6 |
| 5 | |
Rams | 1-2-6 | def. | |
Hawks | 3-4-5 |
| 6 | |
Jumbos | 2-3-5 | def. | |
Polar Bears | 1-4-6 |
| 7 | |
Terriers | 2-3-4 | def. | |
Rams | 1-5-6 |
| 8 | |
Camels | 1-2-3 | def. | |
Jumbos | 4-5-6 |
| 9 | |
Polar Bears | 1-2-5 | def. | |
Hawks | 3-4-6 |
| 10 | |
Rams | 1-2-6 | def. | |
Jumbos | 3-4-5 |
| 11 | |
Terriers | 1-2-5 | def. | |
Hawks | 3-4-6 |
| 12 | |
Polar Bears | 1-2-6 | def. | |
Camels | 3-4-5 |
| 13 | |
Hawks | 1-3-6 | def. | |
Jumbos | 2-4-5 |
| 14 | |
Camels | 1-2-6 | def. | |
Rams | 3-4-5 |
| 15 | |
Terriers | 1-4-5 | def. | |
Polar Bears | 2-3-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Boston University | Terriers | Dylan Balunas '28 Elliott Mendenhall '25 Max Teo '28 |
Tiare Sierra '25 Jack Cariaso '25 Ada Ucar '27 |
|
University of Rhode Island | Rams | Adam Strobridge '26 Christopher Chwalk '28 Max Sigel '26 Owen Grainger '28 |
Erin Little '28 Ava Deangelis '28 Ella Gibson '27 Emaline Ouellette '28 |
|
Bowdoin College | Polar Bears | Ethan Danielson '26 Kyra Phelan '26 Lauren Russler '26 Michelangelo Vecchio '27 |
Posie Cabaniss '27 Maizie Bartlett '27 Mairéad Reitzel '28 Elizabeth Wire '28 |
|
Roger Williams University | Hawks | Connor Mchugh '28 Edward Herman '28 Jack Crager '27 Jakub Fuja '27 |
Dawson Chambers-Tartaglino '27 Caroline Felser '28 Ethan Martin '28 |
|
Connecticut College | Camels | Duncan Craine '26 Lilly Saffer '27 Skylor Sweet '26 |
Sophia Rey '26 Madeleine Jarbeau '28 Madeline Synnestvedt '27 |
|
Tufts University | Jumbos | Blake Vogel '26 Brayden Benesch '28 Grant Schmidt '28 |
Thomas Mazzeo '26 Amelia Traver '28 Dory Russell '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 ±0.07 means a rating gap counts about 6% 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.
