| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Brown University | Bears | 8–2 |
| 2 |  |
Northeastern University | Huskies | 7–3 |
| 3 |  |
University of Vermont | Catamounts | 7–3 |
| 4 |  |
Boston University | Terriers | 4–6 |
| 5 |  |
Bentley University | Falcons | 2–8 |
| 6 |  |
Massachusetts Maritime Academy | Buccaneers | 2–8 |
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 25,847 team race matches sailed before 2025-03-15, using the line-ups that actually raced. It called 14 of 20 matches (70%) with a log-loss of 0.523 (a coin flip scores 0.693), so the event went about as expected for the forecast. Orderliness +0.08 ± 0.48: a typical event, more orderly than 51% 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.
| Place | School | Pred. | Strength | Boats (skipper / crew, boat value) | Pred. win % | Record | vs forecast |
|---|---|---|---|---|---|---|---|
| 1 | Brown University Bears | 1 | 5.75 school +0.40 | Daniel Van Heeckeren / Charles Case 1.92 Keller Morrison / Tucker Gibbs 1.69 Jean-Luc Depardieu / William Salerno | 71% | 6–2 (75%) | +0.3 |
| 2 | Northeastern University Huskies | 4 | 5.03 school +0.26 | Aidan Boni / Hala Gilbert 1.72 Carter Anderson / Matthew Chen 1.69 Isabella Cho / Ryan Tedeschi | 52% | 5–3 (62%) | +0.9 |
| 3 | University of Vermont Catamounts | 2 | 5.56 school −0.28 | Ethan Burt / Jack Taylor 2.36 Marco Welch / Rowan Henkes 1.81 Gavin Sanborn / Ryan Thompson 2.03 4–0 Ocean Smith / Lucy Murphy 1.25 1–3 | 61% | 5–3 (62%) | +0.1 |
| 4 | Boston University Terriers | 3 | 5.29 school +0.21 | William Wiegand / Zachary Fournier 1.91 Buck Rathbun / Danielle Bogacheva 1.81 Sage Andrews / Grace Murphy | 55% | 3–5 (38%) | −1.4 |
| 6 | Massachusetts Maritime Academy Buccaneers | 5 | 3.34 school +0.35, home +0.37 | Zach Earnshaw / Mallory Dietsch 1.22 Evan Tofolo / Nicholas Delvecchio Kevin Mcneill / Hugo Langlais | 11% | 1–7 (12%) | +0.1 |
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) |
|---|---|---|---|---|---|---|---|---|
| 2 | Northeastern University | 5.03 | 5.55 | 5–3 | 4.1 | +0.52 | 0.3 | 38% |
| 1 | Brown University | 5.75 | 5.94 | 6–2 | 5.7 | +0.20 | 0.0 | 58% |
| 6 | Massachusetts Maritime Academy | 3.34 | 3.51 | 1–7 | 0.9 | +0.17 | 0.0 | 60% |
| 3 | University of Vermont | 5.56 | 5.62 | 5–3 | 4.9 | +0.06 | 0.0 | 63% |
| 4 | Boston University | 5.29 | 4.41 | 3–5 | 4.4 | −0.88 | 0.9 | 93% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Aidan Boni | Northeastern University | 1.72 | 2.23 | 5–3 | 4.1 | +0.52 | 0.3 | 38% |
| Jean-Luc Depardieu | Brown University | 1.57 | 1.77 | 6–2 | 5.7 | +0.20 | 0.0 | 58% |
| Zach Earnshaw | Massachusetts Maritime Academy | 1.22 | 1.39 | 1–7 | 0.9 | +0.17 | 0.0 | 60% |
| Kevin Mcneill | Massachusetts Maritime Academy | 0.38 | 0.55 | 1–7 | 0.9 | +0.17 | 0.0 | 60% |
| William Wiegand | Boston University | 1.91 | 1.03 | 3–5 | 4.4 | −0.88 | 0.9 | 93% |
| Sage Andrews | Boston University | 1.12 | 0.24 | 3–5 | 4.4 | −0.88 | 0.9 | 93% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Bears | Huskies | Catamounts | Terriers | Falcons | Buccaneers | |
|---|---|---|---|---|---|---|---|---|
| Brown University Bears | 4–1 | ✕ | L | W | W | W | W |
| Northeastern University Huskies | 4–1 | W | ✕ | W | W | W | L |
| University of Vermont Catamounts | 3–2 | L | L | ✕ | W | W | W |
| Boston University Terriers | 1–4 | L | L | L | ✕ | L | W |
| Bentley University Falcons | 1–4 | L | L | L | W | ✕ | L |
| Massachusetts Maritime Academy Buccaneers | 2–3 | L | W | L | L | W | ✕ |
| Team | Rec. | Bears | Huskies | Catamounts | Terriers | Falcons | Buccaneers | |
|---|---|---|---|---|---|---|---|---|
| Brown University Bears | 4–1 | ✕ | W | L | W | W | W |
| Northeastern University Huskies | 3–2 | L | ✕ | W | L | W | W |
| University of Vermont Catamounts | 4–1 | W | L | ✕ | W | W | W |
| Boston University Terriers | 3–2 | L | W | L | ✕ | W | W |
| Bentley University Falcons | 1–4 | L | L | L | L | ✕ | W |
| Massachusetts Maritime Academy Buccaneers | 0–5 | L | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Terriers | 1-2-6 | def. | |
Buccaneers | 3-4-5 |
| 2 | |
Huskies | 1-2-3 | def. | |
Bears | 4-5-6 |
| 3 | |
Catamounts | 1-2-4 | def. | |
Falcons | 3-5-6 |
| 4 | |
Bears | 1-4-5 | def. | |
Terriers | 2-3-6 |
| 5 | |
Catamounts | 1-2-4 | def. | |
Buccaneers | 3-5-6 |
| 6 | |
Huskies | 1-3-5 | def. | |
Falcons | 2-4-6 |
| 7 | |
Bears | 3-4-5 | def. | |
Catamounts | 1-2-6 DSQ |
| 8 | |
Huskies | 1-2-6 | def. | |
Terriers | 3-4-5 |
| 9 | |
Buccaneers | 1-3-6 | def. | |
Falcons | 2-4-5 |
| 10 | |
Huskies | 1-2-6 | def. | |
Catamounts | 3-4-5 |
| 11 | |
Bears | 1-2-5 | def. | |
Buccaneers | 3-4-6 |
| 12 | |
Falcons | 1-2-5 | def. | |
Terriers | 3-4-6 |
| 13 | |
Buccaneers | 1-3-6 | def. | |
Huskies | 2-4-5 |
| 14 | |
Catamounts | 1-2-4 | def. | |
Terriers | 3-5-6 |
| 15 | |
Bears | 1-3-4 | def. | |
Falcons | 2-5-6 |
| 16 | |
Terriers | 1-3-4 | def. | |
Buccaneers | 2-5-6 |
| 17 | |
Bears | 1-4-5 | def. | |
Huskies | 2-3-6 |
| 18 | |
Catamounts | 1-2-5 | def. | |
Falcons | 3-4-6 |
| 19 | |
Bears | 2-3-4 | def. | |
Terriers | 1-5-6 |
| 20 | |
Catamounts | 1-2-5 | def. | |
Buccaneers | 3-4-6 |
| 21 | |
Huskies | 1-3-5 | def. | |
Falcons | 2-4-6 |
| 22 | |
Catamounts | 1-2-5 | def. | |
Bears | 3-4-6 |
| 23 | |
Terriers | 1-2-3 | def. | |
Huskies | 4-5-6 |
| 24 | |
Falcons | 1-2-6 | def. | |
Buccaneers | 3-4-5 |
| 25 | |
Huskies | 2-3-5 | def. | |
Catamounts | 1-4-6 |
| 26 | |
Bears | 1-2-5 | def. | |
Buccaneers | 3-4-6 |
| 27 | |
Terriers | 1-3-6 | def. | |
Falcons | 2-4-5 |
| 28 | |
Huskies | 1-2-4 | def. | |
Buccaneers | 3-5-6 |
| 29 | |
Catamounts | 1-2-5 | def. | |
Terriers | 3-4-6 |
| 30 | |
Bears | 1-2-6 | def. | |
Falcons | 3-4-5 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Brown University | Bears | Daniel Van Heeckeren '26 Jean-Luc Depardieu '27 Keller Morrison '25 |
Charles Case '26 William Salerno '25 Tucker Gibbs '27 |
|
Northeastern University | Huskies | Aidan Boni '26 Carter Anderson '27 Isabella Cho '27 |
Hala Gilbert '26 Matthew Chen '27 Ryan Tedeschi '28 |
|
University of Vermont | Catamounts | Ethan Burt '26 Gavin Sanborn '25 Marco Welch '28 Ocean Smith '28 |
Jack Taylor '27 Ryan Thompson '26 Rowan Henkes '28 Lucy Murphy '28 |
|
Boston University | Terriers | Buck Rathbun '28 Sage Andrews '28 William Wiegand '25 |
Danielle Bogacheva '27 Grace Murphy '25 Zachary Fournier '26 |
|
Massachusetts Maritime Academy | Buccaneers | Evan Tofolo '28 Kevin Mcneill '28 Zach Earnshaw '27 |
Nicholas Delvecchio '27 Hugo Langlais '28 Mallory Dietsch '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 ±0.04 means a rating gap counts about 3% 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.
