| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 | Stanford University | Cardinal | 9–0 | |
| 2 | University of Hawaii | Rainbow Wahine | 5–4 | |
| 3 | University of Washington | Husky Women | 3–6 | |
| 4 | Western Washington University | Viking Women | 1–8 |
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 23,921 team race matches sailed before 2024-04-06, using the line-ups that actually raced. It called 17 of 18 matches (94%) with a log-loss of 0.239 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.06 ± 0.47: a typical event, more orderly than 49% 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 | Stanford University Cardinal | 1 | 10.29 school +0.29 | Hannah Freeman / Grace Austin 3.51 6–0 Michelle Lahrkamp / Ellie Harned 3.82 6–0 Vanessa Lahrkamp / Gwendolyn Donahue 3.77 6–0 Grace Austin / Hannah Freeman 3–0 Ellie Harned / Michelle Lahrkamp 3.26 3–0 Gwendolyn Donahue / Vanessa Lahrkamp 3–0 | 99% | 9–0 (100%) | +0.1 |
| 2 | University of Hawaii Rainbow Wahine | 2 | 5.91 school −0.25 | Mercy Tangredi / Morgan Carew 2.17 Vivian Bonsager / Anna Kalabukhova 2.21 Martha Schuessler / Peyton Lieser 1.74 5–1 Martha Schuessler / Malia Johnson 1.75 0–3 | 55% | 5–4 (56%) | +0.1 |
| 3 | University of Washington Husky Women | 3 | 4.97 | Erin Pamplin / Grace Smith 1.75 Sammy Farkas / Maya Outhred 1.70 Emily Smith / Julia Oglevie 1.46 | 36% | 3–6 (33%) | −0.3 |
| 4 | Western Washington University Viking Women | 4 | 3.51 | Mary D’Arcy / Faith Burton 1.41 Anna Morrow / Kerry Wier 0.64 Ellie Blakemore / Ella Barnard | 9% | 1–8 (11%) | +0.2 |
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 | 10.29 | 13.29 | 9–0 | 9.0 | ≥+3.00 | 0.1 | 95% |
| 4 | Western Washington University | 3.51 | 3.71 | 1–8 | 0.9 | +0.19 | 0.0 | 60% |
| 2 | University of Hawaii | 5.91 | 6.00 | 5–4 | 4.9 | +0.09 | 0.0 | 71% |
| 3 | University of Washington | 4.97 | 4.72 | 3–6 | 3.3 | −0.25 | 0.0 | 78% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Hannah Freeman | Stanford University | 3.51 | 6.51 | 6–0 | 6.0 | ≥+3.00 | 0.0 | 98% |
| Grace Austin | Stanford University | 2.74 | 5.74 | 3–0 | 3.0 | ≥+3.00 | 0.0 | 97% |
| Ellie Harned | Stanford University | 3.26 | 6.26 | 3–0 | 3.0 | ≥+3.00 | 0.0 | 97% |
| Gwendolyn Donahue | Stanford University | 1.79 | 4.79 | 3–0 | 3.0 | ≥+3.00 | 0.0 | 97% |
| Mary D’Arcy | Western Washington University | 1.41 | 1.60 | 1–8 | 0.9 | +0.19 | 0.0 | 60% |
| Anna Morrow | Western Washington University | 0.64 | 0.83 | 1–8 | 0.9 | +0.19 | 0.0 | 60% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Cardinal | Wahine | Women | Women | |
|---|---|---|---|---|---|---|
| Stanford University Cardinal | 3–0 | ✕ | W | W | W | |
| University of Hawaii Rainbow Wahine | 2–1 | L | ✕ | W | W | |
| University of Washington Husky Women | 1–2 | L | L | ✕ | W | |
| Western Washington University Viking Women | 0–3 | L | L | L | ✕ |
| Team | Rec. | Cardinal | Wahine | Women | Women | |
|---|---|---|---|---|---|---|
| Stanford University Cardinal | 3–0 | ✕ | W | W | W | |
| University of Hawaii Rainbow Wahine | 2–1 | L | ✕ | W | W | |
| University of Washington Husky Women | 1–2 | L | L | ✕ | W | |
| Western Washington University Viking Women | 0–3 | L | L | L | ✕ |
| Team | Rec. | Cardinal | Wahine | Women | Women | |
|---|---|---|---|---|---|---|
| Stanford University Cardinal | 3–0 | ✕ | W | W | W | |
| University of Hawaii Rainbow Wahine | 1–2 | L | ✕ | W | L | |
| University of Washington Husky Women | 1–2 | L | L | ✕ | W | |
| Western Washington University Viking Women | 1–2 | L | W | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | Cardinal | 1-2-3 | def. | Rainbow Wahine | 4-5-6 | ||
| 2 | Cardinal | 1-2-3 | def. | Husky Women | 4-5-6 | ||
| 3 | Cardinal | 1-2-5 | def. | Viking Women | 3-4-6 | ||
| 4 | Rainbow Wahine | 2-3-4 | def. | Husky Women | 1-5-6 | ||
| 5 | Rainbow Wahine | 1-2-5 | def. | Viking Women | 3-4-6 | ||
| 6 | Husky Women | 2-3-4 | def. | Viking Women | 1-5-6 | ||
| 7 | Husky Women | 1-3-4 | def. | Viking Women | 2-5-6 | ||
| 8 | Rainbow Wahine | 1-2-3 | def. | Viking Women | 4-5-6 | ||
| 9 | Cardinal | 1-2-3 | def. | Viking Women | 4-5-6 | ||
| 10 | Rainbow Wahine | 1-2-4 | def. | Husky Women | 3-5-6 | ||
| 11 | Cardinal | 1-2-4 | def. | Husky Women | 3-5-6 | ||
| 12 | Cardinal | 1-2-4 | def. | Rainbow Wahine | 3-5-6 | ||
| 13 | Viking Women | 1-2-6 | def. | Rainbow Wahine | 3-4-5 | ||
| 14 | Cardinal | 1-2-3 | def. | Rainbow Wahine | 4-5-6 | ||
| 15 | Rainbow Wahine | 1-3-5 | def. | Husky Women | 2-4-6 | ||
| 16 | Cardinal | 1-2-6 | def. | Viking Women | 3-4-5 | ||
| 17 | Husky Women | 1-2-3 | def. | Viking Women | 4-5-6 | ||
| 18 | Cardinal | 1-2-4 | def. | Husky Women | 3-5-6 | ||
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
| Stanford University | Cardinal | Ellie Harned '26 Grace Austin '24 Gwendolyn Donahue '24 Hannah Freeman '24 Michelle Lahrkamp '23 Vanessa Lahrkamp '26 |
Michelle Lahrkamp '23 Hannah Freeman '24 Vanessa Lahrkamp '26 Grace Austin '24 Ellie Harned '26 Gwendolyn Donahue '24 |
|
| University of Hawaii | Rainbow Wahine | Martha Schuessler '27 Mercy Tangredi '25 Vivian Bonsager '25 |
Malia Johnson '25 Peyton Lieser '26 Morgan Carew '25 Anna Kalabukhova '24 |
|
| University of Washington | Husky Women | Emily Smith '25 Erin Pamplin '24 Sammy Farkas '27 |
Julia Oglevie '26 Grace Smith '24 Maya Outhred '24 |
|
| Western Washington University | Viking Women | Anna Morrow '25 Ellie Blakemore '27 Mary D’Arcy '25 |
Kerry Wier '25 Ella Barnard '24 Faith Burton '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 ±0.07 means a rating gap counts about 6% 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.