| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Fordham University | Rams | 10–2 |
| 2 |  |
U. S. Naval Academy | Midshipmen | 9–3 |
| 3 |  |
University of Pennsylvania | Quakers | 8–4 |
| 4 |  |
Washington College | Shoremen | 2–10 |
| 5 |  |
University of Virginia | Wahoos | 1–11 |
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 12,061 team race matches sailed before 2019-03-02, using the line-ups that actually raced. It called 25 of 30 matches (83%) with a log-loss of 0.438 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness −0.18 ± 0.31: a typical event, more orderly than 25% 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 | Fordham University Rams | 1 | 8.17 school +0.18 | Eduardo Mintzias / Makena Masterson 3.05 Thomas Capozzi / Sarah Jackman 1.85 Porter Kavle / Brigid Murphy | 86% | 10–2 (83%) | −0.3 |
| 2 | U. S. Naval Academy Midshipmen | 3 | 6.14 school +0.25 | Tyler Fleig / Madeline Pruzan 2.55 Jack Carminati / Bartholomew Winn Louis Margay / Fiona Lobon | 48% | 9–3 (75%) | +3.2 |
| 3 | University of Pennsylvania Quakers | 2 | 7.62 school +0.10 | Amanda Majernik / Adam Hano Ava Esquier / Kelly Hanlon 2.64 Lenox Butcher / Jenna Weiner | 77% | 8–4 (67%) | −1.2 |
| 4 | Washington College Shoremen | 5 | 3.93 school −0.34, home +0.39 | Andrew Vernon / John Mecca 1.10 Paul Hart / Lindsay Fullerton 1.56 Henry Proud / Eloise Lienert | 8% | 2–10 (17%) | +1.0 |
| 5 | University of Virginia Wahoos | 4 | 5.28 school +0.21 | Colin Suvak / Hannah Lothrop 2.50 Ian Palmer / Claire Miller 1.15 Trent Levy / Will Ayscue 1.28 | 30% | 1–11 (8%) | −2.7 |
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) |
|---|---|---|---|---|---|---|---|---|
| 2 | U. S. Naval Academy | 6.14 | 8.04 | 9–3 | 5.8 | +1.90 | 4.5 | 2% |
| 4 | Washington College | 3.93 | 4.79 | 2–10 | 1.0 | +0.87 | 0.7 | 27% |
| 1 | Fordham University | 8.17 | 7.89 | 10–2 | 10.4 | −0.28 | 0.1 | 79% |
| 3 | University of Pennsylvania | 7.62 | 6.85 | 8–4 | 9.2 | −0.77 | 0.7 | 92% |
| 5 | University of Virginia | 5.28 | 2.97 | 1–11 | 3.7 | −2.30 | 4.0 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Jack Carminati | U. S. Naval Academy | 1.25 | 3.15 | 9–3 | 5.8 | +1.90 | 4.5 | 2% |
| Andrew Vernon | Washington College | 1.10 | 1.97 | 2–10 | 1.0 | +0.87 | 0.7 | 27% |
| Paul Hart | Washington College | 1.56 | 2.43 | 2–10 | 1.0 | +0.87 | 0.7 | 27% |
| Henry Proud | Washington College | 0.87 | 1.74 | 2–10 | 1.0 | +0.87 | 0.7 | 27% |
| Eduardo Mintzias | Fordham University | 3.05 | 2.78 | 10–2 | 10.4 | −0.28 | 0.1 | 79% |
| Amanda Majernik | University of Pennsylvania | 2.40 | 1.63 | 8–4 | 9.2 | −0.77 | 0.7 | 92% |
| Ava Esquier | University of Pennsylvania | 2.64 | 1.88 | 8–4 | 9.2 | −0.77 | 0.7 | 92% |
| Colin Suvak | University of Virginia | 2.50 | 0.20 | 1–11 | 3.7 | −2.30 | 4.0 | >99% |
| Ian Palmer | University of Virginia | 1.15 | -1.15 | 1–11 | 3.7 | −2.30 | 4.0 | >99% |
| Trent Levy | University of Virginia | 1.28 | -1.02 | 1–11 | 3.7 | −2.30 | 4.0 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Rams | Midshipmen | Quakers | Shoremen | Wahoos | |
|---|---|---|---|---|---|---|---|
| Fordham University Rams | 3–1 | ✕ | L | W | W | W |
| U. S. Naval Academy Midshipmen | 3–1 | W | ✕ | L | W | W |
| University of Pennsylvania Quakers | 3–1 | L | W | ✕ | W | W |
| Washington College Shoremen | 1–3 | L | L | L | ✕ | W |
| University of Virginia Wahoos | 0–4 | L | L | L | L | ✕ |
| Team | Rec. | Rams | Midshipmen | Quakers | Shoremen | Wahoos | |
|---|---|---|---|---|---|---|---|
| Fordham University Rams | 4–0 | ✕ | W | W | W | W |
| U. S. Naval Academy Midshipmen | 2–2 | L | ✕ | L | W | W |
| University of Pennsylvania Quakers | 3–1 | L | W | ✕ | W | W |
| Washington College Shoremen | 1–3 | L | L | L | ✕ | W |
| University of Virginia Wahoos | 0–4 | L | L | L | L | ✕ |
| Team | Rec. | Rams | Midshipmen | Quakers | Shoremen | Wahoos | |
|---|---|---|---|---|---|---|---|
| Fordham University Rams | 3–1 | ✕ | L | W | W | W |
| U. S. Naval Academy Midshipmen | 4–0 | W | ✕ | W | W | W |
| University of Pennsylvania Quakers | 2–2 | L | L | ✕ | W | W |
| Washington College Shoremen | 0–4 | L | L | L | ✕ | L |
| University of Virginia Wahoos | 1–3 | L | L | L | W | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Quakers | 1-2-5 | def. | |
Midshipmen | 3-4-6 |
| 2 | |
Rams | 1-2-3 | def. | |
Wahoos | 4-5-6 |
| 3 | |
Midshipmen | 1-2-4 | def. | |
Shoremen | 3-5-6 |
| 4 | |
Rams | 1-2-4 | def. | |
Quakers | 3-5-6 |
| 5 | |
Shoremen | 1-2-4 | def. | |
Wahoos | 3-5-6 |
| 6 | |
Midshipmen | 1-4-5 | def. | |
Rams | 2-3-6 |
| 7 | |
Quakers | 1-2-3 | def. | |
Wahoos | 4-5-6 |
| 8 | |
Rams | 1-2-3 | def. | |
Shoremen | 4-5-6 |
| 9 | |
Midshipmen | 1-2-3 | def. | |
Wahoos | 4-5-6 |
| 10 | |
Quakers | 1-2-5 | def. | |
Shoremen | 3-4-6 |
| 11 | |
Quakers | 1-2-6 | def. | |
Midshipmen | 3-4-5 |
| 12 | |
Rams | 1-2-3 | def. | |
Wahoos | 4-5-6 |
| 13 | |
Midshipmen | 1-2-3 | def. | |
Shoremen | 4-5-6 |
| 14 | |
Rams | 1-3-6 | def. | |
Quakers | 2-4-5 |
| 15 | |
Shoremen | 1-3-4 | def. | |
Wahoos | 2-5-6 |
| 16 | |
Rams | 1-2-3 | def. | |
Midshipmen | 4-5-6 |
| 17 | |
Quakers | 1-2-3 | def. | |
Wahoos | 4-5-6 |
| 18 | |
Rams | 1-2-3 | def. | |
Shoremen | 4-5-6 |
| 19 | |
Midshipmen | 1-2-3 | def. | |
Wahoos | 4-5-6 |
| 20 | |
Quakers | 1-2-6 | def. | |
Shoremen | 3-4-5 |
| 21 | |
Midshipmen | 2-3-5 | def. | |
Quakers | 1-4-6 |
| 22 | |
Rams | 1-2-3 | def. | |
Wahoos | 4-5-6 |
| 23 | |
Midshipmen | 1-2-3 | def. | |
Shoremen | 4-5-6 |
| 24 | |
Rams | 1-2-6 | def. | |
Quakers | 3-4-5 |
| 25 | |
Wahoos | 1-3-6 | def. | |
Shoremen | 2-4-5 |
| 26 | |
Midshipmen | 1-3-6 | def. | |
Rams | 2-4-5 |
| 27 | |
Quakers | 1-2-5 | def. | |
Wahoos | 3-4-6 |
| 28 | |
Rams | 1-2-3 | def. | |
Shoremen | 4-5-6 |
| 29 | |
Midshipmen | 1-2-4 | def. | |
Wahoos | 3-5-6 |
| 30 | |
Quakers | 1-2-3 | def. | |
Shoremen | 4-5-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Fordham University | Rams | Eduardo Mintzias '21 Porter Kavle '22 Thomas Capozzi '19 |
Makena Masterson '19 Brigid Murphy '20 Sarah Jackman '21 |
|
U. S. Naval Academy | Midshipmen | Jack Carminati '22 Louis Margay '22 Tyler Fleig '19 |
Bartholomew Winn '21 Fiona Lobon '22 Madeline Pruzan '21 |
|
University of Pennsylvania | Quakers | Amanda Majernik '22 Ava Esquier '20 Lenox Butcher '20 |
Adam Hano '23 Kelly Hanlon '21 Jenna Weiner '21 |
|
Washington College | Shoremen | Andrew Vernon '20 Henry Proud '21 Paul Hart '19 |
John Mecca '21 Eloise Lienert '20 Lindsay Fullerton '21 |
|
University of Virginia | Wahoos | Colin Suvak '19 Ian Palmer '19 Trent Levy '21 |
Hannah Lothrop '21 Claire Miller '22 Will Ayscue '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 ±0.01 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.
