| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
St. Mary's College of Maryland | Seahawks | 9–1 |
| 2 |  |
Tufts University | Jumbos | 9–1 |
| 3 |  |
U. S. Naval Academy | Midshipmen | 6–4 |
| 4 |  |
Fordham University | Rams | 4–6 |
| 5 |  |
Hobart and William Smith Colleges | Statesmen | 3–4 |
| 6 |  |
Washington College | Shoremen | 2–5 |
| 7 |  |
University of Michigan | Wolverines | 1–6 |
| 8 |  |
Princeton University | Tigers | 0–7 |
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 22,767 team race matches sailed before 2024-03-16, using the line-ups that actually raced. It called 28 of 35 matches (80%) with a log-loss of 0.406 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.05 ± 0.30: a typical event, more orderly than 47% 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 | 7.29 | 9.05 | 10–1 | 7.9 | +1.76 | 2.4 | 9% |
| 6 | Washington College | 3.10 | 4.66 | 2–5 | 0.6 | +1.56 | 1.7 | 12% |
| 4 | Fordham University | 4.41 | 5.72 | 4–6 | 2.2 | +1.31 | 1.8 | 11% |
| 2 | Tufts University | 7.89 | 7.72 | 9–2 | 9.2 | −0.17 | 0.0 | 75% |
| 3 | U. S. Naval Academy | 6.68 | 6.41 | 6–4 | 6.4 | −0.27 | 0.1 | 78% |
| 5 | Hobart and William Smith Colleges | 5.71 | 5.06 | 3–4 | 3.7 | −0.66 | 0.3 | 89% |
| 7 | University of Michigan | 5.01 | 2.95 | 1–6 | 2.9 | −2.06 | 2.6 | 99% |
| 8 | Princeton University | 4.38 | 1.38 | 0–7 | 2.1 | ≤−3.00 | 4.3 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Austin Latimer | Washington College | 0.41 | 2.59 | 2–2 | 0.5 | +2.19 | 2.6 | 8% |
| Max Kleha | St. Mary's College of Maryland | 1.95 | 3.71 | 10–1 | 7.9 | +1.76 | 2.4 | 9% |
| Nathan Jensen | St. Mary's College of Maryland | 2.44 | 4.20 | 10–1 | 7.9 | +1.76 | 2.4 | 9% |
| Lucas Thress | Fordham University | 1.93 | 3.24 | 4–6 | 2.2 | +1.31 | 1.8 | 11% |
| James Owen | Fordham University | 1.58 | 2.89 | 4–6 | 2.2 | +1.31 | 1.8 | 11% |
| Connor Rosow | Tufts University | 2.59 | 2.42 | 9–2 | 9.2 | −0.17 | 0.0 | 75% |
| Adrien Bellanger | Tufts University | 2.35 | 2.18 | 9–2 | 9.2 | −0.17 | 0.0 | 75% |
| Kate Zurinskas | U. S. Naval Academy | 1.09 | 0.91 | 4–2 | 4.2 | −0.18 | 0.0 | 77% |
| Tanner Kelly | U. S. Naval Academy | 2.60 | 2.32 | 6–4 | 6.4 | −0.27 | 0.1 | 78% |
| Nicolas Garcia-Castrillon | Hobart and William Smith Colleges | 1.87 | 1.21 | 3–4 | 3.7 | −0.66 | 0.3 | 89% |
| Carly Mraz | Princeton University | 1.28 | -1.72 | 0–7 | 2.1 | ≤−3.00 | 4.3 | >99% |
| Asher Green | Princeton University | 1.98 | -1.02 | 0–7 | 2.1 | ≤−3.00 | 4.3 | >99% |
| Bryan Lawrence | Princeton University | 1.23 | -1.77 | 0–7 | 2.1 | ≤−3.00 | 4.3 | >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 | Jumbos | Midshipmen | Rams | Statesmen | Shoremen | Wolverines | Tigers | |
|---|---|---|---|---|---|---|---|---|---|---|
| St. Mary's College of Maryland Seahawks | 7–0 | ✕ | W | W | W | W | W | W | W |
| Tufts University Jumbos | 6–1 | L | ✕ | W | W | W | W | W | W |
| U. S. Naval Academy Midshipmen | 5–2 | L | L | ✕ | W | W | W | W | W |
| Fordham University Rams | 4–3 | L | L | L | ✕ | W | W | W | W |
| Hobart and William Smith Colleges Statesmen | 3–4 | L | L | L | L | ✕ | W | W | W |
| Washington College Shoremen | 2–5 | L | L | L | L | L | ✕ | W | W |
| University of Michigan Wolverines | 1–6 | L | L | L | L | L | L | ✕ | W |
| Princeton University Tigers | 0–7 | L | L | L | L | L | L | L | ✕ |
| Team | Rec. | Seahawks | Jumbos | Midshipmen | Rams | |
|---|---|---|---|---|---|---|
| St. Mary's College of Maryland Seahawks | 3–1 | ✕ | W | W | W |
| Tufts University Jumbos | 3–1 | L | ✕ | W | W |
| U. S. Naval Academy Midshipmen | 1–2 | L | L | ✕ | W |
| Fordham University Rams | 0–3 | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Statesmen | 1-2-6 | def. | |
Wolverines | 3-4-5 |
| 2 | |
Midshipmen | 1-2-3 | def. | |
Rams | 4-5-6 |
| 3 | |
Seahawks | 1-2-6 | def. | |
Jumbos | 3-4-5 |
| 4 | |
Shoremen | 1-2-3 | def. | |
Tigers | 4-5-6 |
| 5 | |
Midshipmen | 1-2-6 | def. | |
Wolverines | 3-4-5 |
| 6 | |
Seahawks | 1-3-5 | def. | |
Statesmen | 2-4-6 |
| 7 | |
Rams | 1-2-4 | def. | |
Shoremen | 3-5-6 |
| 8 | |
Jumbos | 1-2-4 | def. | |
Tigers | 3-5-6 |
| 9 | |
Seahawks | 2-3-4 | def. | |
Midshipmen | 1-5-6 |
| 10 | |
Shoremen | 1-2-6 | def. | |
Wolverines | 3-4-5 |
| 11 | |
Jumbos | 1-2-6 | def. | |
Statesmen | 3-4-5 |
| 12 | |
Rams | 1-2-4 | def. | |
Tigers | 3-5-6 |
| 13 | |
Seahawks | 1-2-3 | def. | |
Shoremen | 4-5-6 |
| 14 | |
Jumbos | 1-3-5 | def. | |
Midshipmen | 2-4-6 |
| 15 | |
Rams | 2-3-4 | def. | |
Wolverines | 1-5-6 |
| 16 | |
Statesmen | 1-2-6 | def. | |
Tigers | 3-4-5 |
| 17 | |
Jumbos | 1-2-5 | def. | |
Shoremen | 3-4-6 |
| 18 | |
Seahawks | 1-3-6 | def. | |
Rams | 2-4-5 |
| 19 | |
Midshipmen | 1-2-6 | def. | |
Statesmen | 3-4-5 |
| 20 | |
Wolverines | 1-2-5 | def. | |
Tigers | 3-4-6 |
| 21 | |
Jumbos | 1-2-5 | def. | |
Rams | 3-4-6 |
| 22 | |
Statesmen | 1-2-6 | def. | |
Shoremen | 3-4-5 |
| 23 | |
Seahawks | 1-2-5 | def. | |
Wolverines | 3-4-6 |
| 24 | |
Midshipmen | 1-2-3 | def. | |
Tigers | 4-5-6 |
| 25 | |
Rams | 1-3-6 | def. | |
Statesmen | 2-4-5 |
| 26 | |
Jumbos | 1-2-4 | def. | |
Wolverines | 3-5-6 |
| 27 | |
Midshipmen | 2-3-4 | def. | |
Shoremen | 1-5-6 |
| 28 | |
Seahawks | 1-2-4 | def. | |
Tigers | 3-5-6 |
| 29 | |
Jumbos | 1-2-6 | def. | |
Midshipmen | 3-4-5 |
| 30 | |
Seahawks | 2-3-4 | def. | |
Rams | 1-5-6 |
| 31 | |
Jumbos | 1-2-3 | def. | |
Rams | 4-5-6 |
| 32 | |
Seahawks | 1-2-6 | def. | |
Midshipmen | 3-4-5 |
| 33 | |
Midshipmen | 1-2-3 | def. | |
Rams | 4-5-6 |
| 34 | |
Jumbos | 1-2-4 | def. | |
Seahawks | 3-5-6 |
| 35 | |
Seahawks | 2-3-4 | def. | |
Jumbos | 1-5-6 |
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 ±0.01 means a rating gap counts about 1% 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.
