| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 | Tulane University | Green Wave | 9–3 | |
| 2 | Roger Williams University | Hawks | 8–4 | |
| 3 | College of Charleston | Cougars | 8–4 | |
| 4 | Massachusetts Institute of Technology | Engineers | 5–7 | |
| 5 | Jacksonville University | Fins | 0–12 |
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 28,606 team race matches sailed before 2026-03-07, using the line-ups that actually raced. It called 25 of 30 matches (83%) with a log-loss of 0.400 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.08 ± 0.57: 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 | Tulane University Green Wave | 3 | 8.17 school −0.10 | Oakley Cunningham / Caroline Caudron 2.48 Lola Kohl / Skye Terrell 2.32 Ava Anderson / Ella May Corckran 3.42 | 58% | 9–3 (75%) | +2.0 |
| 2 | Roger Williams University Hawks | 1 | 8.75 school +0.46 | Lucy Meagher / Maren Matthews 3.14 Tavia Smith / Mackenzie Speece 2.84 Katherine Mcgagh / Elyssa Franklin 2.27 | 73% | 8–4 (67%) | −0.7 |
| 3 | College of Charleston Cougars | 2 | 8.54 school +0.32 | Ashley Alfortish / Lucy Zinn 2.78 Bella Shakespeare / Lucy Elvart 3.12 Georgia Shuster / Gaelen Adam 2.28 | 68% | 8–4 (67%) | −0.1 |
| 4 | Massachusetts Institute of Technology Engineers | 4 | 7.84 school +0.18 | Brooke Barry / Sophia Woodbury 2.75 Karya Basaraner / Alice Colby 2.51 Emma Wang / Layla Bursor 2.31 | 51% | 5–7 (42%) | −1.1 |
| 5 | Jacksonville University Fins | 5 | 2.61 school −0.29 | Fiona Froelich / Cheyenne Dooley 1.96 Kaitlyn Anderson / Annie Mckenzie 0.72 Frances Hanson / Amelia Sulciner | 0% | 0–12 (0%) | −0.0 |
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 | Tulane University | 8.17 | 9.10 | 9–3 | 7.0 | +0.93 | 1.3 | 16% |
| 3 | College of Charleston | 8.54 | 8.49 | 8–4 | 8.1 | −0.05 | 0.0 | 67% |
| 2 | Roger Williams University | 8.75 | 8.41 | 8–4 | 8.7 | −0.34 | 0.2 | 80% |
| 4 | Massachusetts Institute of Technology | 7.84 | 7.23 | 5–7 | 6.1 | −0.61 | 0.5 | 87% |
| 5 | Jacksonville University | 2.61 | -0.39 | 0–12 | 0.0 | ≤−3.00 | 0.1 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Wave | Hawks | Cougars | Engineers | Fins | |
|---|---|---|---|---|---|---|---|
| Tulane University Green Wave | 2–2 | ✕ | L | L | W | W | |
| Roger Williams University Hawks | 3–1 | W | ✕ | W | L | W | |
| College of Charleston Cougars | 3–1 | W | L | ✕ | W | W | |
| Massachusetts Institute of Technology Engineers | 2–2 | L | W | L | ✕ | W | |
| Jacksonville University Fins | 0–4 | L | L | L | L | ✕ |
| Team | Rec. | Wave | Hawks | Cougars | Engineers | Fins | |
|---|---|---|---|---|---|---|---|
| Tulane University Green Wave | 3–1 | ✕ | W | L | W | W | |
| Roger Williams University Hawks | 2–2 | L | ✕ | W | L | W | |
| College of Charleston Cougars | 3–1 | W | L | ✕ | W | W | |
| Massachusetts Institute of Technology Engineers | 2–2 | L | W | L | ✕ | W | |
| Jacksonville University Fins | 0–4 | L | L | L | L | ✕ |
| Team | Rec. | Wave | Hawks | Cougars | Engineers | Fins | |
|---|---|---|---|---|---|---|---|
| Tulane University Green Wave | 4–0 | ✕ | W | W | W | W | |
| Roger Williams University Hawks | 3–1 | L | ✕ | W | W | W | |
| College of Charleston Cougars | 2–2 | L | L | ✕ | W | W | |
| Massachusetts Institute of Technology Engineers | 1–3 | L | L | L | ✕ | W | |
| Jacksonville University Fins | 0–4 | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | Engineers | 1-2-6 | def. | Hawks | 3-4-5 | ||
| 2 | Cougars | 1-2-4 | def. | Green Wave | 3-5-6 | ||
| 3 | Engineers | 2-3-4 | def. | Fins | 1-5-6 | ||
| 4 | Hawks | 1-3-6 | def. | Green Wave | 2-4-5 | ||
| 5 | Cougars | 1-2-5 | def. | Engineers | 3-4-6 | ||
| 6 | Hawks | 1-2-4 | def. | Fins | 3-5-6 | ||
| 7 | Green Wave | 1-2-3 | def. | Engineers | 4-5-6 | ||
| 8 | Hawks | 1-2-5 | def. | Cougars | 3-4-6 | ||
| 9 | Green Wave | 1-2-6 | def. | Fins | 3-4-5 | ||
| 10 | Cougars | 1-2-4 | def. | Fins | 3-5-6 | ||
| 11 | Engineers | 1-2-3 | def. | Hawks | 4-5-6 | ||
| 12 | Cougars | 1-2-5 | def. | Green Wave | 3-4-6 | ||
| 13 | Engineers | 1-2-3 | def. | Fins | 4-5-6 | ||
| 14 | Green Wave | 1-2-3 | def. | Hawks | 4-5-6 | ||
| 15 | Cougars | 2-3-4 | def. | Engineers | 1-5-6 | ||
| 16 | Hawks | 1-2-3 | def. | Fins | 4-5-6 | ||
| 17 | Green Wave | 1-2-6 | def. | Engineers | 3-4-5 | ||
| 18 | Hawks | 1-2-5 | def. | Cougars | 3-4-6 | ||
| 19 | Green Wave | 1-2-3 | def. | Fins | 4-5-6 | ||
| 20 | Cougars | 1-2-4 | def. | Fins | 3-5-6 | ||
| 21 | Green Wave | 2-3-5 | def. | Engineers | 1-4-6 | ||
| 22 | Hawks | 1-3-4 | def. | Cougars | 2-5-6 | ||
| 23 | Engineers | 1-2-3 | def. | Fins | 4-5-6 | ||
| 24 | Green Wave | 1-3-6 | def. | Cougars | 2-4-5 | ||
| 25 | Hawks | 1-2-6 DNF | def. | Engineers | 3-4-5 | ||
| 26 | Green Wave | 1-2-4 | def. | Fins | 3-5-6 | ||
| 27 | Cougars | 1-2-4 | def. | Engineers | 3-5-6 | ||
| 28 | Green Wave | 2-3-5 | def. | Hawks | 1-4-6 | ||
| 29 | Cougars | 1-2-4 | def. | Fins | 3-5-6 | ||
| 30 | Hawks | 1-2-4 | def. | Fins | 3-5-6 | ||
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
| Tulane University | Green Wave | Ava Anderson '27 Lola Kohl '28 Oakley Cunningham '27 |
Ella May Corckran '26 Skye Terrell '29 Caroline Caudron '27 |
|
| Roger Williams University | Hawks | Katherine Mcgagh '26 Lucy Meagher '27 Tavia Smith '27 |
Elyssa Franklin '26 Maren Matthews '26 Mackenzie Speece '28 |
|
| College of Charleston | Cougars | Ashley Alfortish '27 Bella Shakespeare '27 Georgia Shuster '29 |
Lucy Zinn '28 Lucy Elvart '28 Gaelen Adam '29 |
|
| Massachusetts Institute of Technology | Engineers | Brooke Barry '26 Emma Wang '27 Karya Basaraner '28 |
Sophia Woodbury '28 Layla Bursor '29 Alice Colby '29 |
|
| Jacksonville University | Fins | Fiona Froelich '28 Frances Hanson '29 Kaitlyn Anderson '29 |
Cheyenne Dooley '28 Amelia Sulciner '28 Annie Mckenzie '29 |
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 4% 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.