| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
St. Mary's College of Maryland | Seahawks | 5–0 |
| 2 |  |
SUNY Maritime College | Privateers | 4–1 |
| 3 |  |
University of Michigan | Wolverines | 3–2 |
| 4 |  |
Fordham University | Rams | 2–3 |
| 5 |  |
Washington College | Shoremen | 1–4 |
| 6 |  |
Princeton University | Tigers | 0–5 |
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 13 of 15 matches (87%) with a log-loss of 0.291 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.30 ± 0.46: a typical event, more orderly than 76% 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 | St. Mary's College of Maryland | 6.69 | 9.69 | 5–0 | 4.7 | ≥+3.00 | 0.4 | 77% |
| 2 | SUNY Maritime College | 3.64 | 6.08 | 4–1 | 2.5 | +2.44 | 2.6 | 9% |
| 3 | University of Michigan | 4.53 | 4.46 | 3–2 | 3.1 | −0.07 | 0.0 | 75% |
| 5 | Washington College | 2.27 | 1.62 | 1–4 | 1.3 | −0.65 | 0.2 | 89% |
| 4 | Fordham University | 4.41 | 3.38 | 2–3 | 2.9 | −1.03 | 0.7 | 94% |
| 6 | Princeton University | 1.96 | -1.04 | 0–5 | 0.5 | ≤−3.00 | 0.7 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Joseph Marynowski | St. Mary's College of Maryland | 1.96 | 4.96 | 5–0 | 4.7 | ≥+3.00 | 0.4 | 77% |
| Max Kleha | St. Mary's College of Maryland | 2.25 | 5.25 | 5–0 | 4.7 | ≥+3.00 | 0.4 | 77% |
| Mats Braaten | St. Mary's College of Maryland | 1.99 | 4.99 | 5–0 | 4.7 | ≥+3.00 | 0.4 | 77% |
| Luke Barker | SUNY Maritime College | 1.18 | 3.62 | 4–1 | 2.5 | +2.44 | 2.6 | 9% |
| Austin Latimer | Washington College | 0.81 | 0.22 | 1–2 | 1.3 | −0.59 | 0.1 | 89% |
| Joseph Bonacci | Washington College | 1.46 | 0.87 | 1–2 | 1.3 | −0.59 | 0.1 | 89% |
| James Owen | Fordham University | 2.09 | 1.05 | 2–3 | 2.9 | −1.03 | 0.7 | 94% |
| Berkley Yiu | Princeton University | 0.58 | -2.42 | 0–5 | 0.5 | ≤−3.00 | 0.7 | >99% |
| Evelyn Walsh | Princeton University | 0.53 | -2.47 | 0–5 | 0.5 | ≤−3.00 | 0.7 | >99% |
| William Roberts | Princeton University | 0.84 | -2.16 | 0–5 | 0.5 | ≤−3.00 | 0.7 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Seahawks | Privateers | Wolverines | Rams | Shoremen | Tigers | |
|---|---|---|---|---|---|---|---|---|
| St. Mary's College of Maryland Seahawks | 5–0 | ✕ | W | W | W | W | W |
| SUNY Maritime College Privateers | 4–1 | L | ✕ | W | W | W | W |
| University of Michigan Wolverines | 3–2 | L | L | ✕ | W | W | W |
| Fordham University Rams | 2–3 | L | L | L | ✕ | W | W |
| Washington College Shoremen | 1–4 | L | L | L | L | ✕ | W |
| Princeton University Tigers | 0–5 | L | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Privateers | 1-3-4 | def. | |
Tigers | 2-5-6 |
| 2 | |
Seahawks | 1-2-4 | def. | |
Wolverines | 3-5-6 |
| 3 | |
Rams | 1-2-3 | def. | |
Shoremen | 4-5-6 |
| 4 | |
Privateers | 2-3-4 | def. | |
Wolverines | 1-5-6 |
| 5 | |
Shoremen | 1-2-4 | def. | |
Tigers | 3-5-6 |
| 6 | |
Seahawks | 1-2-6 | def. | |
Rams | 3-4-5 |
| 7 | |
Wolverines | 1-3-4 | def. | |
Shoremen | 2-5-6 |
| 8 | |
Seahawks | 2-3-4 | def. | |
Privateers | 1-5-6 |
| 9 | |
Rams | 1-2-4 | def. | |
Tigers | 3-5-6 |
| 10 | |
Seahawks | 1-2-3 | def. | |
Shoremen | 4-5-6 |
| 11 | |
Wolverines | 1-2-6 | def. | |
Tigers | 3-4-5 |
| 12 | |
Privateers | 1-2-6 | def. | |
Rams | 3-4-5 |
| 13 | |
Seahawks | 1-2-3 | def. | |
Tigers | 4-5-6 |
| 14 | |
Privateers | 1-2-4 | def. | |
Shoremen | 3-5-6 |
| 15 | |
Wolverines | 1-2-5 | def. | |
Rams | 3-4-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
St. Mary's College of Maryland | Seahawks | Joseph Marynowski '28 Mats Braaten '27 Max Kleha '25 |
Elise Jones '28 Hattie Rigney '26 Gina Bonazelli '26 |
|
SUNY Maritime College | Privateers | Isabelle Gautier '26 Jeremy Lunati '27 Luke Barker '28 |
Grace Wilson '28 Juliana Sarich '28 Andrew Mccarthy '28 |
|
University of Michigan | Wolverines | Billy Vogel '25 Jack Hammett '26 Jack Homa '27 |
Grace Redner '27 Abigail Paul '25 Ben Visco '28 |
|
Fordham University | Rams | Brendan Sheeran '26 James Owen '25 Lauren Murray '28 |
Isabela Hillmann '27 Alana Shigekane '27 Ava Belli '28 |
|
Washington College | Shoremen | Austin Latimer '27 George Wood '27 Imogene Nuss '28 Joseph Bonacci '25 Matthew Nadolny '27 |
Nora Ciak '27 Ethan Rower '28 Rachel Morgen '26 Lucy Sunderland '28 |
|
Princeton University | Tigers | Berkley Yiu '25 Evelyn Walsh '26 William Roberts '26 |
Zachary Meisel '27 Kristine Roegner '28 John Morgan Griffith '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 ±0.06 means a rating gap counts about 5% 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.
