| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Washington College | Shoremen | 12–0 |
| 2 |  |
Princeton University | Tigers | 8–4 |
| 3 |  |
Columbia University | Lions | 7–5 |
| 4 |  |
SUNY Stony Brook | Seawolves | 3–9 |
| 5 |  |
University of Delaware | Blue Hens | 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 16,158 team race matches sailed before 2022-03-05, using the line-ups that actually raced. It called 28 of 30 matches (93%) with a log-loss of 0.281 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.58 ± 0.36: an orderly event, more orderly than 96% 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 | Washington College Shoremen | 1 | 3.18 school −0.28, home +0.35 | Alex Heim / Kennedy Jones Joseph Bonacci / Emma Macturk Matthew Collinson / Megan Callis | 74% | 12–0 (100%) | +3.1 |
| 2 | Princeton University Tigers | 3 | 2.50 | Jasper Waldman / Eddie O’Keefe Bryan Lawrence / Aliya Ismagilova Carly Mraz / Robert Rubin 6–3 William Mandelbaum / Robert Rubin -0.22 2–1 | 60% | 8–4 (67%) | +0.8 |
| 3 | Columbia University Lions | 2 | 2.83 | Leopold Brandl / Jasmine Chen Ava Rotondo / Alexandra Barron Alexander Yuen / Alison Keenan | 71% | 7–5 (58%) | −1.5 |
| 4 | SUNY Stony Brook Seawolves | 4 | 1.73 | Kristin Hess / Margaret Myers-Aldous Ryan Magill / Morgan Bittmann Mallory Reading / Gerrit Bittmann 0–6 Gerrit Bittmann / Mallory Reading 3–3 | 41% | 3–9 (25%) | −2.0 |
| 5 | University of Delaware Blue Hens | 5 | -0.90 | Tamryn Whyte / Evan Walter Laura Macmillan / Ian Kaplan Addie Perez / Logan Devaric | 3% | 0–12 (0%) | −0.4 |
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 | Washington College | 3.18 | 6.18 | 12–0 | 8.9 | ≥+3.00 | 5.2 | 2% |
| 2 | Princeton University | 2.50 | 2.87 | 8–4 | 7.2 | +0.37 | 0.2 | 42% |
| 3 | Columbia University | 2.83 | 2.12 | 7–5 | 8.5 | −0.71 | 0.8 | 92% |
| 4 | SUNY Stony Brook | 1.73 | 0.31 | 3–9 | 4.9 | −1.42 | 1.8 | 98% |
| 5 | University of Delaware | -0.90 | -3.90 | 0–12 | 0.4 | ≤−3.00 | 0.5 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Alex Heim | Washington College | 1.27 | 4.27 | 12–0 | 8.9 | ≥+3.00 | 5.2 | 2% |
| Joseph Bonacci | Washington College | 0.90 | 3.90 | 12–0 | 8.9 | ≥+3.00 | 5.2 | 2% |
| William Mandelbaum | Princeton University | -0.22 | 1.10 | 2–1 | 1.0 | +1.32 | 0.9 | 28% |
| Bryan Lawrence | Princeton University | 0.87 | 1.25 | 8–4 | 7.2 | +0.37 | 0.2 | 42% |
| Carly Mraz | Princeton University | 0.03 | -0.11 | 6–3 | 6.2 | −0.14 | 0.0 | 73% |
| Gerrit Bittmann | SUNY Stony Brook | 0.53 | -0.17 | 3–3 | 3.4 | −0.70 | 0.2 | 91% |
| Leopold Brandl | Columbia University | 1.81 | 1.10 | 7–5 | 8.5 | −0.71 | 0.8 | 92% |
| Ava Rotondo | Columbia University | 0.04 | -0.67 | 7–5 | 8.5 | −0.71 | 0.8 | 92% |
| Alexander Yuen | Columbia University | 0.37 | -0.34 | 7–5 | 8.5 | −0.71 | 0.8 | 92% |
| Kristin Hess | SUNY Stony Brook | 0.39 | -1.03 | 3–9 | 4.9 | −1.42 | 1.8 | 98% |
| Ryan Magill | SUNY Stony Brook | 0.35 | -1.07 | 3–9 | 4.9 | −1.42 | 1.8 | 98% |
| Tamryn Whyte | University of Delaware | -0.57 | -3.57 | 0–12 | 0.4 | ≤−3.00 | 0.5 | >99% |
| Laura Macmillan | University of Delaware | -0.44 | -3.44 | 0–12 | 0.4 | ≤−3.00 | 0.5 | >99% |
| Addie Perez | University of Delaware | -0.50 | -3.50 | 0–12 | 0.4 | ≤−3.00 | 0.5 | >99% |
| Mallory Reading | SUNY Stony Brook | 0.21 | -2.79 | 0–6 | 1.5 | ≤−3.00 | 2.4 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Shoremen | Tigers | Lions | Seawolves | Hens | |
|---|---|---|---|---|---|---|---|
| Washington College Shoremen | 4–0 | ✕ | W | W | W | W |
| Princeton University Tigers | 3–1 | L | ✕ | W | W | W |
| Columbia University Lions | 2–2 | L | L | ✕ | W | W |
| SUNY Stony Brook Seawolves | 1–3 | L | L | L | ✕ | W |
| University of Delaware Blue Hens | 0–4 | L | L | L | L | ✕ |
| Team | Rec. | Shoremen | Tigers | Lions | Seawolves | Hens | |
|---|---|---|---|---|---|---|---|
| Washington College Shoremen | 4–0 | ✕ | W | W | W | W |
| Princeton University Tigers | 2–2 | L | ✕ | L | W | W |
| Columbia University Lions | 3–1 | L | W | ✕ | W | W |
| SUNY Stony Brook Seawolves | 1–3 | L | L | L | ✕ | W |
| University of Delaware Blue Hens | 0–4 | L | L | L | L | ✕ |
| Team | Rec. | Shoremen | Tigers | Lions | Seawolves | Hens | |
|---|---|---|---|---|---|---|---|
| Washington College Shoremen | 4–0 | ✕ | W | W | W | W |
| Princeton University Tigers | 3–1 | L | ✕ | W | W | W |
| Columbia University Lions | 2–2 | L | L | ✕ | W | W |
| SUNY Stony Brook Seawolves | 1–3 | L | L | L | ✕ | W |
| University of Delaware Blue Hens | 0–4 | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Tigers | 1-2-3 | def. | |
Blue Hens | 4-5-6 |
| 2 | |
Lions | 1-2-4 | def. | |
Seawolves | 3-5-6 |
| 3 | |
Shoremen | 1-2-4 | def. | |
Blue Hens | 3-5-6 |
| 4 | |
Tigers | 1-4-5 | def. | |
Lions | 2-3-6 |
| 5 | |
Shoremen | 1-2-3 | def. | |
Seawolves | 4-5-6 |
| 6 | |
Lions | 1-2-3 | def. | |
Blue Hens | 4-5-6 |
| 7 | |
Tigers | 1-2-6 | def. | |
Seawolves | 3-4-5 |
| 8 | |
Shoremen | 1-3-4 | def. | |
Lions | 2-5-6 |
| 9 | |
Seawolves | 1-2-3 | def. | |
Blue Hens | 4-5-6 |
| 10 | |
Shoremen | 1-2-5 | def. | |
Tigers | 3-4-6 |
| 11 | |
Tigers | 1-3-4 | def. | |
Blue Hens | 2-5-6 |
| 12 | |
Lions | 1-2-4 | def. | |
Seawolves | 3-5-6 |
| 13 | |
Shoremen | 1-2-3 | def. | |
Blue Hens | 4-5-6 |
| 14 | |
Lions | 1-2-5 | def. | |
Tigers | 3-4-6 |
| 15 | |
Shoremen | 1-2-4 | def. | |
Seawolves | 3-5-6 |
| 16 | |
Lions | 1-2-6 | def. | |
Blue Hens | 3-4-5 |
| 17 | |
Tigers | 2-3-4 | def. | |
Seawolves | 1-5-6 |
| 18 | |
Shoremen | 1-4-5 | def. | |
Lions | 2-3-6 |
| 19 | |
Seawolves | 1-2-6 | def. | |
Blue Hens | 3-4-5 |
| 20 | |
Shoremen | 1-3-6 | def. | |
Tigers | 2-4-5 |
| 21 | |
Tigers | 1-2-5 | def. | |
Blue Hens | 3-4-6 DNF |
| 22 | |
Lions | 1-2-5 | def. | |
Seawolves | 3-4-6 |
| 23 | |
Shoremen | 1-2-4 | def. | |
Blue Hens | 3-5-6 |
| 24 | |
Tigers | 1-4-5 | def. | |
Lions | 2-3-6 |
| 25 | |
Shoremen | 1-4-5 | def. | |
Seawolves | 2-3-6 |
| 26 | |
Lions | 1-2-3 | def. | |
Blue Hens | 4-5-6 |
| 27 | |
Tigers | 1-2-5 | def. | |
Seawolves | 3-4-6 |
| 28 | |
Shoremen | 1-2-4 | def. | |
Lions | 3-5-6 |
| 29 | |
Seawolves | 1-2-5 | def. | |
Blue Hens | 3-4-6 |
| 30 | |
Shoremen | 2-3-4 | def. | |
Tigers | 1-5-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Washington College | Shoremen | Alex Heim '24 Joseph Bonacci '25 Matthew Collinson '24 |
Kennedy Jones '24 Emma Macturk '23 Megan Callis '24 |
|
Princeton University | Tigers | Bryan Lawrence '24 Carly Mraz '25 Jasper Waldman '25 William Mandelbaum '22 |
Aliya Ismagilova '22 Robert Rubin '23 Eddie O’Keefe '25 |
|
Columbia University | Lions | Alexander Yuen '25 Ava Rotondo '24 Leopold Brandl '24 |
Alison Keenan '22 Alexandra Barron '24 Jasmine Chen '25 |
|
SUNY Stony Brook | Seawolves | Gerrit Bittmann '24 Kristin Hess '22 Mallory Reading '24 Ryan Magill '22 |
Mallory Reading '24 Margaret Myers-Aldous '25 Gerrit Bittmann '24 Morgan Bittmann '24 |
|
University of Delaware | Blue Hens | Addie Perez '25 Laura Macmillan '24 Tamryn Whyte '23 |
Logan Devaric '25 Ian Kaplan '25 Evan Walter '23 |
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 ±0.06 means a rating gap counts about 5% 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.
