| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Stanford University | Cardinal | 6–0 |
| 2 |  |
University of Hawaii | Rainbows | 2–4 |
| 3 |  |
University of California at Berkeley | Ursas | 1–5 |
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 27,057 team race matches sailed before 2025-04-04, using the line-ups that actually raced. It called 8 of 9 matches (89%) with a log-loss of 0.398 (a coin flip scores 0.693), so the event went well for the forecast. 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 | Stanford University Cardinal | 1 | 11.55 school +0.33 | Vanessa Lahrkamp / Shay Wood 4.22 Ellie Harned / Kit Harned 3.44 Sophie Fisher / Alice Schmid 3.56 | 100% | 6–0 (100%) | +0.0 |
| 2 | University of Hawaii Rainbows | 2 | 6.62 school −0.19, home +0.36 | Martha Schuessler / Morgan Carew 2.34 Sophia Shaeffer / Malia Johnson 1.44 Vivian Bonsager / Stella Taherian 2.64 | 49% | 2–4 (33%) | −0.9 |
| 3 | University of California at Berkeley Ursas | 3 | 3.07 school +0.11 | Katherine Olsen / Catherine Arcaris 1.59 Alyssa Cunningham Barkus / Aliyah Al-Khafaji Bianca Weber / Viola Phillips Frank | 2% | 1–5 (17%) | +0.9 |
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 | Stanford University | 11.55 | 14.55 | 6–0 | 6.0 | ≥+3.00 | 0.0 | 98% |
| 3 | University of California at Berkeley | 3.07 | 5.88 | 1–5 | 0.1 | +2.81 | 2.4 | 8% |
| 2 | University of Hawaii | 6.62 | 3.79 | 2–4 | 2.9 | −2.83 | 2.5 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Ellie Harned | Stanford University | 3.44 | 6.44 | 6–0 | 6.0 | ≥+3.00 | 0.0 | 98% |
| Katherine Olsen | University of California at Berkeley | 1.59 | 4.41 | 1–5 | 0.1 | +2.81 | 2.4 | 8% |
| Alyssa Cunningham Barkus | University of California at Berkeley | 1.02 | 3.83 | 1–5 | 0.1 | +2.81 | 2.4 | 8% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Cardinal | Rainbows | Ursas | |
|---|---|---|---|---|---|
| Stanford University Cardinal | 2–0 | ✕ | W | W |
| University of Hawaii Rainbows | 1–1 | L | ✕ | W |
| University of California at Berkeley Ursas | 0–2 | L | L | ✕ |
| Team | Rec. | Cardinal | Rainbows | Ursas | |
|---|---|---|---|---|---|
| Stanford University Cardinal | 2–0 | ✕ | W | W |
| University of Hawaii Rainbows | 1–1 | L | ✕ | W |
| University of California at Berkeley Ursas | 0–2 | L | L | ✕ |
| Team | Rec. | Cardinal | Rainbows | Ursas | |
|---|---|---|---|---|---|
| Stanford University Cardinal | 2–0 | ✕ | W | W |
| University of Hawaii Rainbows | 0–2 | L | ✕ | L |
| University of California at Berkeley Ursas | 1–1 | L | W | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Cardinal | 1-2-3 | def. | |
Ursas | 4-5-6 |
| 2 | |
Rainbows | 1-2-3 | def. | |
Ursas | 4-5-6 |
| 3 | |
Cardinal | 1-2-5 | def. | |
Rainbows | 3-4-6 |
| 4 | |
Cardinal | 1-2-3 | def. | |
Ursas | 4-5-6 |
| 5 | |
Rainbows | 1-2-3 | def. | |
Ursas | 4-5-6 |
| 6 | |
Cardinal | 1-2-5 | def. | |
Rainbows | 3-4-6 |
| 7 | |
Cardinal | 1-2-3 | def. | |
Ursas | 4-5-6 |
| 8 | |
Ursas | 1-3-6 | def. | |
Rainbows | 2-4-5 |
| 9 | |
Cardinal | 1-2-3 | def. | |
Rainbows | 4-5-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Stanford University | Cardinal | Ellie Harned '26 Sophie Fisher '26 Vanessa Lahrkamp '26 |
Kit Harned '27 Alice Schmid '27 Shay Wood '27 |
|
University of Hawaii | Rainbows | Martha Schuessler '27 Sophia Shaeffer '25 Vivian Bonsager '25 |
Morgan Carew '25 Malia Johnson '25 Stella Taherian '27 |
|
University of California at Berkeley | Ursas | Alyssa Cunningham Barkus '26 Bianca Weber '26 Katherine Olsen '25 |
Aliyah Al-Khafaji '27 Viola Phillips Frank '26 Catherine Arcaris '26 |
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 ±0.00 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.
