| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Bowdoin College | Polar Bears | 8–0 |
| 2 |  |
U. S. Coast Guard Academy | Bears | 5–3 |
| 3 |  |
University of Rhode Island | Rams | 4–4 |
| 4 |  |
Connecticut College | Camels | 2–6 |
| 5 |  |
University of Vermont | Catamounts | 1–7 |
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 26,645 team race matches sailed before 2025-03-29, using the line-ups that actually raced. It called 12 of 14 matches (86%) with a log-loss of 0.285 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.22 ± 0.44: a typical event, more orderly than 68% 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 | Bowdoin College Polar Bears | 1 | 8.52 home +0.36 | Lauren Russler / Luisa Louchheim 2.91 Kyra Phelan / Mairéad Reitzel 2.77 Rebecca Schill / Kaile Olson 2.47 | 94% | 8–0 (100%) | +0.5 |
| 2 | U. S. Coast Guard Academy Bears | 2 | 6.42 school +0.13 | Julia Conneely / Allison Nystrom 2.51 Caroline Odell / Charlotte Mccarthy Ella Demand / Olivia Spada 2.01 | 54% | 3–3 (50%) | −0.2 |
| 3 | University of Rhode Island Rams | 3 | 5.81 school −0.08 | Kytalin Hendrickson / Erin Little 2.61 Ariana Schwartz / Kaylee Good Emaline Ouellette / Jane Lally 1.68 | 40% | 2–4 (33%) | −0.4 |
| 4 | Connecticut College Camels | 5 | 5.59 school +0.35 | Izzy Wu-Karr / Aurora Kreyche 2.01 Lilly Saffer / Clifton Carragher 1.53 Natalie Fear / Vivian Smith | 5% | 0–2 (0%) | −0.1 |
| 5 | University of Vermont Catamounts | 4 | 4.55 school −0.25 | Audrey Commerford / Lane Kaeyer 2.02 Caitlin Derby / Dee Mccormick 1.74 Jordynn Johnson / Lucy Murphy 1.01 | 12% | 1–5 (17%) | +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 | Bowdoin College | 8.52 | 11.52 | 8–0 | 7.5 | ≥+3.00 | 0.7 | 61% |
| 5 | University of Vermont | 4.55 | 4.92 | 1–5 | 0.7 | +0.37 | 0.1 | 56% |
| 2 | U. S. Coast Guard Academy | 6.42 | 6.14 | 3–3 | 3.2 | −0.27 | 0.0 | 80% |
| 3 | University of Rhode Island | 5.81 | 5.38 | 2–4 | 2.4 | −0.43 | 0.1 | 83% |
| 4 | Connecticut College | 5.59 | 2.59 | 0–2 | 0.1 | ≤−3.00 | 0.1 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Lauren Russler | Bowdoin College | 2.91 | 5.91 | 8–0 | 7.5 | ≥+3.00 | 0.7 | 61% |
| Audrey Commerford | University of Vermont | 2.02 | 2.38 | 1–5 | 0.7 | +0.37 | 0.1 | 56% |
| Jordynn Johnson | University of Vermont | 1.01 | 1.38 | 1–5 | 0.7 | +0.37 | 0.1 | 56% |
| Ariana Schwartz | University of Rhode Island | 1.53 | 1.10 | 2–4 | 2.4 | −0.43 | 0.1 | 83% |
| Emaline Ouellette | University of Rhode Island | 1.68 | 1.25 | 2–4 | 2.4 | −0.43 | 0.1 | 83% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Bears | Bears | Rams | Camels | Catamounts | |
|---|---|---|---|---|---|---|---|
| Bowdoin College Polar Bears | 4–0 | ✕ | W | W | W | W |
| U. S. Coast Guard Academy Bears | 3–1 | L | ✕ | W | W | W |
| University of Rhode Island Rams | 2–2 | L | L | ✕ | W | W |
| Connecticut College Camels | 1–3 | L | L | L | ✕ | W |
| University of Vermont Catamounts | 0–4 | L | L | L | L | ✕ |
| Team | Rec. | Bears | Bears | Rams | Camels | Catamounts | |
|---|---|---|---|---|---|---|---|
| Bowdoin College Polar Bears | 4–0 | ✕ | W | W | W | W |
| U. S. Coast Guard Academy Bears | 2–2 | L | ✕ | L | W | W |
| University of Rhode Island Rams | 2–2 | L | W | ✕ | W | L |
| Connecticut College Camels | 1–3 | L | L | L | ✕ | W |
| University of Vermont Catamounts | 1–3 | L | L | W | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Polar Bears | 1-2-4 | def. | |
Camels | 3-5-6 |
| 2 | |
Bears | 1-3-6 | def. | |
Rams | 2-4-5 |
| 3 | |
Polar Bears | 1-2-5 | def. | |
Catamounts | 3-4-6 |
| 4 | |
Bears | 1-2-6 | def. | |
Camels | 3-4-5 |
| 5 | |
Polar Bears | 1-2-5 | def. | |
Rams | 3-4-6 |
| 6 | |
Camels | 1-2-3 | def. | |
Catamounts | 4-5-6 |
| 7 | |
Polar Bears | 1-2-4 | def. | |
Bears | 3-5-6 |
| 8 | |
Rams | 1-2-3 | def. | |
Catamounts | 4-5-6 |
| 9 | |
Rams | 2-3-5 | def. | |
Camels | 1-4-6 |
| 10 | |
Bears | 1-2-6 | def. | |
Catamounts | 3-4-5 |
| 11 | |
Polar Bears | 1-2-3 | def. | |
Catamounts | 4-5-6 |
| 12 | |
Bears | 1-2-6 | def. | |
Camels | 3-4-5 |
| 13 | |
Catamounts | 1-2-5 | def. | |
Rams | 3-4-6 |
| 14 | |
Polar Bears | 1-2-3 | def. | |
Bears | 4-5-6 |
| 15 | |
Camels | 1-4-5 | def. | |
Catamounts | 2-3-6 |
| 16 | |
Polar Bears | 1-2-5 | def. | |
Rams | 3-4-6 |
| 17 | |
Bears | 1-3-5 | def. | |
Catamounts | 2-4-6 |
| 18 | |
Rams | 1-2-3 | def. | |
Camels | 4-5-6 |
| 19 | |
Polar Bears | 1-2-5 | def. | |
Camels | 3-4-6 |
| 20 | |
Rams | 1-2-3 | def. | |
Bears | 4-5-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Bowdoin College | Polar Bears | Kyra Phelan '26 Lauren Russler '26 Rebecca Schill '27 |
Mairéad Reitzel '28 Luisa Louchheim '25 Kaile Olson '27 |
|
U. S. Coast Guard Academy | Bears | Caroline Odell '27 Ella Demand '28 Julia Conneely '26 |
Charlotte Mccarthy '25 Olivia Spada '28 Allison Nystrom '26 |
|
University of Rhode Island | Rams | Ariana Schwartz '27 Emaline Ouellette '28 Kytalin Hendrickson '26 |
Kaylee Good '26 Jane Lally '25 Erin Little '28 |
|
Connecticut College | Camels | Izzy Wu-Karr '26 Lilly Saffer '27 Natalie Fear '28 |
Aurora Kreyche '25 Clifton Carragher '25 Vivian Smith '27 |
|
University of Vermont | Catamounts | Audrey Commerford '25 Caitlin Derby '26 Jordynn Johnson '27 |
Lane Kaeyer '27 Dee Mccormick '28 Lucy Murphy '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 ±0.01 means a rating gap counts about 1% 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.
