| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Brown University | Bears | 9–1 |
| 1 |  |
Roger Williams University | Hawks | 9–1 |
| 3 |  |
U. S. Coast Guard Academy | Bears | 5–5 |
| 4 |  |
Boston College | Eagles | 5–5 |
| 5 |  |
Connecticut College | Camels | 1–9 |
| 5 |  |
Massachusetts Institute of Technology | Engineers | 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 29,914 team race matches sailed before 2026-03-22, using the line-ups that actually raced. It called 27 of 30 matches (90%) with a log-loss of 0.335 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.17 ± 0.33: a typical event, more orderly than 63% 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 | 8.97 | 10.98 | 9–1 | 7.0 | +2.01 | 2.6 | 8% |
| 3 | U. S. Coast Guard Academy | 6.62 | 8.12 | 5–5 | 2.9 | +1.50 | 2.3 | 8% |
| 1 | Roger Williams University | 10.40 | 10.18 | 9–1 | 9.2 | −0.23 | 0.0 | 81% |
| 5 | Massachusetts Institute of Technology | 5.95 | 4.99 | 1–9 | 1.9 | −0.96 | 0.6 | 92% |
| 5 | Connecticut College | 6.16 | 5.08 | 1–9 | 2.1 | −1.08 | 0.8 | 94% |
| 4 | Boston College | 8.87 | 7.46 | 5–5 | 6.9 | −1.41 | 2.0 | 98% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Bears | Hawks | Bears | Eagles | Camels | Engineers | |
|---|---|---|---|---|---|---|---|---|
| Brown University Bears | 5–0 | ✕ | W | W | W | W | W |
| Roger Williams University Hawks | 4–1 | L | ✕ | W | W | W | W |
| U. S. Coast Guard Academy Bears | 3–2 | L | L | ✕ | W | W | W |
| Boston College Eagles | 2–3 | L | L | L | ✕ | W | W |
| Connecticut College Camels | 1–4 | L | L | L | L | ✕ | W |
| Massachusetts Institute of Technology Engineers | 0–5 | L | L | L | L | L | ✕ |
| Team | Rec. | Bears | Hawks | Bears | Eagles | Camels | Engineers | |
|---|---|---|---|---|---|---|---|---|
| Brown University Bears | 4–1 | ✕ | L | W | W | W | W |
| Roger Williams University Hawks | 5–0 | W | ✕ | W | W | W | W |
| U. S. Coast Guard Academy Bears | 2–3 | L | L | ✕ | L | W | W |
| Boston College Eagles | 3–2 | L | L | W | ✕ | W | W |
| Connecticut College Camels | 0–5 | L | L | L | L | ✕ | L |
| Massachusetts Institute of Technology Engineers | 1–4 | L | L | L | L | W | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Bears | 1-2-4 | def. | |
Camels | 3-5-6 |
| 2 | |
Bears | 1-2-5 | def. | |
Eagles | 3-4-6 |
| 3 | |
Hawks | 1-2-3 | def. | |
Engineers | 4-5-6 |
| 7 | |
Eagles | 1-2-4 | def. | |
Camels | 3-5-6 |
| 8 | |
Bears | 1-3-6 | def. | |
Hawks | 2-4-5 |
| 9 | |
Bears | 1-3-4 | def. | |
Engineers | 2-5-6 DNF |
| 13 | |
Hawks | 1-2-3 | def. | |
Camels | 4-5-6 |
| 14 | |
Eagles | 1-2-3 | def. | |
Engineers | 4-5-6 DNS,DNS,DNS |
| 15 | |
Bears | 1-3-6 | def. | |
Bears | 2-4-5 |
| 19 | |
Hawks | 1-2-5 | def. | |
Eagles | 3-4-6 |
| 20 | |
Bears | 1-2-3 | def. | |
Engineers | 4-5-6 |
| 21 | |
Bears | 1-2-3 | def. | |
Camels | 4-5-6 DNF |
| 25 | |
Bears | 1-2-4 | def. | |
Eagles | 3-5-6 |
| 26 | |
Hawks | 1-2-5 | def. | |
Bears | 3-4-6 |
| 27 | |
Camels | 1-3-6 DNF | def. | |
Engineers | 2-4-5 |
| 4 | |
Bears | 1-2-5 | def. | |
Camels | 3-4-6 |
| 5 | |
Eagles | 2-3-4 | def. | |
Bears | 1-5-6 |
| 6 | |
Hawks | 1-2-4 | def. | |
Engineers | 3-5-6 |
| 10 | |
Eagles | 1-2-4 | def. | |
Camels | 3-5-6 |
| 11 | |
Hawks | 2-3-5 | def. | |
Bears | 1-4-6 |
| 12 | |
Bears | 1-4-5 | def. | |
Engineers | 2-3-6 DNS |
| 16 | |
Hawks | 1-2-3 | def. | |
Camels | 4-5-6 |
| 17 | |
Eagles | 1-2-3 | def. | |
Engineers | 4-5-6 |
| 18 | |
Bears | 1-3-4 | def. | |
Bears | 2-5-6 |
| 22 | |
Hawks | 1-2-3 | def. | |
Eagles | 4-5-6 |
| 23 | |
Bears | 1-2-5 | def. | |
Engineers | 3-4-6 |
| 24 | |
Bears | 2-3-5 | def. | |
Camels | 1-4-6 |
| 28 | |
Bears | 1-2-4 | def. | |
Eagles | 3-5-6 |
| 29 | |
Hawks | 1-2-4 | def. | |
Bears | 3-5-6 |
| 30 | |
Engineers | 1-3-6 | def. | |
Camels | 2-4-5 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Brown University | Bears | Julian Dahiya '28 Noah Stapleton '29 William Baker '29 |
Elena Sun '29 Marin Soderberg '28 Talia Levine '26 |
|
Roger Williams University | Hawks | Drew Mastovsky '26 Parker Moore '29 Tristan Mcdonald '28 |
Maddy Martin '29 Peter Cotoia '26 Sophia Litos '29 |
|
U. S. Coast Guard Academy | Bears | Ella Demand '28 Madeline Murphy '29 Meara Conley '28 Tomas Riccio '28 |
Sydney Zylinski '29 Olivia Spada '28 Ella Demand '28 Austin White '27 |
|
Boston College | Eagles | Aidan Cunningham '26 Brady Kennedy '29 Griffin Gigliotti '26 |
Lauren Leonard '29 Abbie Catalano '28 Ainsley West '28 |
|
Connecticut College | Camels | Alexandra Daigle '29 Julia Scipione '29 Lilly Saffer '27 Natalie Fear '28 |
Madeleine Jarbeau '28 June Roe '28 Alexandra Daigle '29 Sienna Young '29 |
|
Massachusetts Institute of Technology | Engineers | Conrad Straden '28 Kaitlyn Beaver '29 Lucas Escandon '26 |
Diba Demir '29 Ada Kilian '29 Ade Larsen '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 1% 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.
