| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Boston University | Terriers | 10–2 |
| 2 |  |
Yale University | Bulldogs | 9–3 |
| 3 |  |
Boston College | Eagles | 5–7 |
| 4 |  |
Harvard University | Crimson | 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 13,135 team race matches sailed before 2019-03-24, using the line-ups that actually raced. It called 18 of 20 matches (90%) with a log-loss of 0.306 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.03 ± 0.40: a typical event, more orderly than 45% 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 | Boston University Terriers | 3 | 8.06 school −0.10, home +0.37 | Raymond Groble Iv / Trent Chismar Casey Cabot / Erica Brown 2.88 Kyle Dochoda / Shannon Macdonald 2.96 | 59% | 10–2 (83%) | +3.0 |
| 2 | Yale University Bulldogs | 1 | 9.66 school +0.25 | Dylan Dimarchi / Anisha Arcot 2.95 Nicholas Marwell / Helena Ware 2.74 Louisa Nordstrom / Kira Woods 3.71 | 91% | 6–2 (75%) | −1.3 |
| 3 | Boston College Eagles | 2 | 7.53 school +0.24 | Cameron Mcmanus / Catherine Roughneen Griffin Elliott / Ginny Alex 2.82 Jack Denatale / Elizabeth Matheson 2.89 | 66% | 4–4 (50%) | −1.3 |
| 4 | Harvard University Crimson | 4 | 4.69 | Andrew Puopolo / Gayatri Balasubramanian 2.61 Matthew Dickey / Emily Malpass Paul Kuechler / Lisa Van Der Sluijs | 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 | Boston University | 8.06 | 10.00 | 10–2 | 7.0 | +1.94 | 4.0 | 2% |
| 3 | Boston College | 7.53 | 6.38 | 4–4 | 5.3 | −1.15 | 1.0 | 96% |
| 2 | Yale University | 9.66 | 8.18 | 6–2 | 7.3 | −1.48 | 1.5 | 98% |
| 4 | Harvard University | 4.69 | 1.69 | 0–12 | 0.4 | ≤−3.00 | 0.5 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Raymond Groble Iv | Boston University | 1.71 | 3.65 | 10–2 | 7.0 | +1.94 | 4.0 | 2% |
| Cameron Mcmanus | Boston College | 1.33 | 0.18 | 4–4 | 5.3 | −1.15 | 1.0 | 96% |
| Dylan Dimarchi | Yale University | 2.95 | 1.46 | 6–2 | 7.3 | −1.48 | 1.5 | 98% |
| Andrew Puopolo | Harvard University | 2.61 | -0.39 | 0–12 | 0.4 | ≤−3.00 | 0.5 | >99% |
| Paul Kuechler | Harvard University | 1.11 | -1.89 | 0–12 | 0.4 | ≤−3.00 | 0.5 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Rd | # | Winner | Loser | P(winner) | |
|---|---|---|---|---|---|
| 1 | 1 | Boston University | Harvard University | 97% | |
| 1 | 3 | Yale University | Boston University | 85% | |
| 1 | 4 | Boston College | Harvard University | 94% | |
| 1 | 5 | Yale University | Harvard University | 99% | |
| 1 | 6 | Boston University | Boston College | 64% | |
| 2 | 8 | Boston University | Harvard University | 97% | |
| 2 | 9 | Boston College | Harvard University | 94% | |
| 2 | 10 | Boston University | Yale University | 17% | upset |
| 2 | 11 | Yale University | Harvard University | 99% | |
| 2 | 12 | Boston University | Boston College | 63% | |
| 3 | 13 | Yale University | Boston University | 83% | |
| 3 | 14 | Boston College | Harvard University | 94% | |
| 3 | 16 | Boston University | Harvard University | 97% | |
| 3 | 17 | Boston University | Boston College | 62% | |
| 3 | 18 | Yale University | Harvard University | 99% | |
| 4 | 19 | Boston College | Harvard University | 94% | |
| 4 | 20 | Boston University | Yale University | 18% | upset |
| 4 | 21 | Boston University | Harvard University | 96% | |
| 4 | 23 | Boston University | Boston College | 62% | |
| 4 | 24 | Yale University | Harvard University | 99% |
| Team | Rec. | Terriers | Bulldogs | Eagles | Crimson | |
|---|---|---|---|---|---|---|
| Boston University Terriers | 2–1 | ✕ | L | W | W |
| Yale University Bulldogs | 2–1 | W | ✕ | L | W |
| Boston College Eagles | 2–1 | L | W | ✕ | W |
| Harvard University Crimson | 0–3 | L | L | L | ✕ |
| Team | Rec. | Terriers | Bulldogs | Eagles | Crimson | |
|---|---|---|---|---|---|---|
| Boston University Terriers | 3–0 | ✕ | W | W | W |
| Yale University Bulldogs | 2–1 | L | ✕ | W | W |
| Boston College Eagles | 1–2 | L | L | ✕ | W |
| Harvard University Crimson | 0–3 | L | L | L | ✕ |
| Team | Rec. | Terriers | Bulldogs | Eagles | Crimson | |
|---|---|---|---|---|---|---|
| Boston University Terriers | 2–1 | ✕ | L | W | W |
| Yale University Bulldogs | 3–0 | W | ✕ | W | W |
| Boston College Eagles | 1–2 | L | L | ✕ | W |
| Harvard University Crimson | 0–3 | L | L | L | ✕ |
| Team | Rec. | Terriers | Bulldogs | Eagles | Crimson | |
|---|---|---|---|---|---|---|
| Boston University Terriers | 3–0 | ✕ | W | W | W |
| Yale University Bulldogs | 2–1 | L | ✕ | W | W |
| Boston College Eagles | 1–2 | L | L | ✕ | W |
| Harvard University Crimson | 0–3 | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Terriers | 1-3-4 | def. | |
Crimson | 2-5-6 |
| 2 | |
Eagles | 1-2-5 | def. | |
Bulldogs | 3-4-6 |
| 3 | |
Bulldogs | 1-3-6 | def. | |
Terriers | 2-4-5 |
| 4 | |
Eagles | 1-2-5 | def. | |
Crimson | 3-4-6 |
| 5 | |
Bulldogs | 1-2-3 | def. | |
Crimson | 4-5-6 |
| 6 | |
Terriers | 1-2-6 | def. | |
Eagles | 3-4-5 |
| 7 | |
Bulldogs | 1-2-5 | def. | |
Eagles | 3-4-6 |
| 8 | |
Terriers | 1-2-3 | def. | |
Crimson | 4-5-6 |
| 9 | |
Eagles | 1-2-6 | def. | |
Crimson | 3-4-5 |
| 10 | |
Terriers | 1-2-5 | def. | |
Bulldogs | 3-4-6 |
| 11 | |
Bulldogs | 1-2-3 | def. | |
Crimson | 4-5-6 |
| 12 | |
Terriers | 1-2-6 | def. | |
Eagles | 3-4-5 |
| 13 | |
Bulldogs | 1-2-6 | def. | |
Terriers | 3-4-5 |
| 14 | |
Eagles | 2-3-4 | def. | |
Crimson | 1-5-6 |
| 15 | |
Bulldogs | 1-2-6 | def. | |
Eagles | 3-4-5 |
| 16 | |
Terriers | 1-2-3 | def. | |
Crimson | 4-5-6 |
| 17 | |
Terriers | 1-2-4 | def. | |
Eagles | 3-5-6 |
| 18 | |
Bulldogs | 1-2-5 | def. | |
Crimson | 3-4-6 |
| 19 | |
Eagles | 2-3-4 | def. | |
Crimson | 1-5-6 |
| 20 | |
Terriers | 1-2-3 | def. | |
Bulldogs | 4-5-6 |
| 21 | |
Terriers | 1-2-3 | def. | |
Crimson | 4-5-6 |
| 22 | |
Bulldogs | 1-2-5 | def. | |
Eagles | 3-4-6 |
| 23 | |
Terriers | 1-2-5 | def. | |
Eagles | 3-4-6 |
| 24 | |
Bulldogs | 1-2-5 | def. | |
Crimson | 3-4-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Boston University | Terriers | Casey Cabot '21 Kyle Dochoda '21 Raymond Groble Iv '21 |
Erica Brown '21 Shannon Macdonald '21 Trent Chismar '22 |
|
Yale University | Bulldogs | Dylan Dimarchi '20 Louisa Nordstrom '20 Nicholas Marwell '21 |
Anisha Arcot '23 Kira Woods '19 Helena Ware '23 |
|
Boston College | Eagles | Cameron Mcmanus '21 Griffin Elliott '19 Jack Denatale '22 |
Catherine Roughneen '20 Ginny Alex '22 Elizabeth Matheson '20 |
|
Harvard University | Crimson | Andrew Puopolo '19 Matthew Dickey '22 Paul Kuechler '22 |
Gayatri Balasubramanian '21 Emily Malpass '21 Lisa Van Der Sluijs '21 |
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 ±0.03 means a rating gap counts about 3% 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.
