| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Boston College | Eagles | 6–1 |
| 2 |  |
Harvard University | Crimson | 6–1 |
| 3 |  |
Yale University | Bulldogs | 5–2 |
| 4 |  |
Massachusetts Institute of Technology | Engineers | 4–3 |
| 5 |  |
Brown University | Bears | 3–4 |
| 6 |  |
Tufts University | Jumbos | 2–5 |
| 7 |  |
Roger Williams University | Hawks | 1–6 |
| 8 |  |
University of Rhode Island | Rams | 1–6 |
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 19,353 team race matches sailed before 2023-03-05, using the line-ups that actually raced. It called 22 of 28 matches (79%) with a log-loss of 0.446 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness −0.15 ± 0.34: a typical event, more orderly than 28% 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.
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 College | 9.41 | 10.54 | 6–1 | 5.0 | +1.12 | 0.8 | 32% |
| 2 | Harvard University | 9.65 | 10.44 | 6–1 | 5.3 | +0.79 | 0.4 | 44% |
| 8 | University of Rhode Island | 5.21 | 5.96 | 1–6 | 0.6 | +0.75 | 0.2 | 48% |
| 4 | Massachusetts Institute of Technology | 8.18 | 8.82 | 4–3 | 3.3 | +0.64 | 0.3 | 41% |
| 6 | Tufts University | 7.17 | 6.89 | 2–5 | 2.2 | −0.27 | 0.0 | 80% |
| 7 | Roger Williams University | 6.26 | 5.90 | 1–6 | 1.2 | −0.36 | 0.1 | 83% |
| 3 | Yale University | 9.95 | 9.36 | 5–2 | 5.6 | −0.59 | 0.3 | 87% |
| 5 | Brown University | 9.34 | 7.67 | 3–4 | 4.7 | −1.67 | 2.1 | 99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Sarah Burn | Harvard University | 3.06 | 3.85 | 6–1 | 5.3 | +0.79 | 0.4 | 44% |
| Cordelia Burn | Harvard University | 3.00 | 3.80 | 6–1 | 5.3 | +0.79 | 0.4 | 44% |
| Okyanus Arıkan | University of Rhode Island | 2.42 | 3.17 | 1–6 | 0.6 | +0.75 | 0.2 | 48% |
| Lily Moore | University of Rhode Island | 0.63 | 1.38 | 1–6 | 0.6 | +0.75 | 0.2 | 48% |
| Katherine Mcgagh | Roger Williams University | 1.15 | 1.07 | 1–3 | 1.0 | −0.08 | 0.0 | 79% |
| Annika Fedde | Tufts University | 2.20 | 1.92 | 2–5 | 2.2 | −0.27 | 0.0 | 80% |
| Claire Siegel-Wilson | Roger Williams University | 2.43 | 2.07 | 1–6 | 1.2 | −0.36 | 0.1 | 83% |
| Emma Cowles | Yale University | 3.35 | 2.76 | 5–2 | 5.6 | −0.59 | 0.3 | 87% |
| Alexandra Chigas | Roger Williams University | 1.82 | -1.18 | 0–3 | 0.2 | ≤−3.00 | 0.3 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Eagles | Crimson | Bulldogs | Engineers | Bears | Jumbos | Hawks | Rams | |
|---|---|---|---|---|---|---|---|---|---|---|
| Boston College Eagles | 6–1 | ✕ | W | W | W | W | L | W | W |
| Harvard University Crimson | 6–1 | L | ✕ | W | W | W | W | W | W |
| Yale University Bulldogs | 5–2 | L | L | ✕ | W | W | W | W | W |
| Massachusetts Institute of Technology Engineers | 4–3 | L | L | L | ✕ | W | W | W | W |
| Brown University Bears | 3–4 | L | L | L | L | ✕ | W | W | W |
| Tufts University Jumbos | 2–5 | W | L | L | L | L | ✕ | W | L |
| Roger Williams University Hawks | 1–6 | L | L | L | L | L | L | ✕ | W |
| University of Rhode Island Rams | 1–6 | L | L | L | L | L | W | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Engineers | 1-2-3 | def. | |
Hawks | 4-5-6 |
| 2 | |
Crimson | 1-2-5 | def. | |
Jumbos | 3-4-6 |
| 3 | |
Bears | 2-4-5 | def. | |
Rams | 1-3-6 DSQ |
| 4 | |
Eagles | 1-2-6 | def. | |
Bulldogs | 3-4-5 |
| 5 | |
Crimson | 1-3-5 | def. | |
Engineers | 2-4-6 |
| 6 | |
Bears | 2-3-5 | def. | |
Hawks | 1-4-6 |
| 7 | |
Bulldogs | 1-2-4 | def. | |
Jumbos | 3-5-6 |
| 8 | |
Eagles | 1-2-4 | def. | |
Rams | 3-5-6 |
| 9 | |
Crimson | 2-3-5 | def. | |
Bears | 1-4-6 |
| 10 | |
Bulldogs | 1-2-3 | def. | |
Engineers | 4-5-6 |
| 11 | |
Hawks | 2-4-5 | def. | |
Rams | 1-3-6 DSQ |
| 12 | |
Jumbos | 2-3-4 | def. | |
Eagles | 1-5-6 |
| 13 | |
Bulldogs | 1-2-5 | def. | |
Bears | 3-4-6 |
| 14 | |
Crimson | 1-2-5 | def. | |
Rams | 3-4-6 |
| 15 | |
Engineers | 1-3-6 | def. | |
Jumbos | 2-4-5 |
| 16 | |
Eagles | 1-2-4 | def. | |
Hawks | 3-5-6 |
| 17 | |
Bulldogs | 1-2-4 | def. | |
Rams | 3-5-6 |
| 18 | |
Bears | 1-2-5 | def. | |
Jumbos | 3-4-6 |
| 19 | |
Crimson | 1-2-4 | def. | |
Hawks | 3-5-6 |
| 20 | |
Eagles | 1-2-5 | def. | |
Engineers | 3-4-6 |
| 21 | |
Rams | 1-3-6 | def. | |
Jumbos | 2-4-5 |
| 22 | |
Bulldogs | 1-2-4 | def. | |
Hawks | 3-5-6 |
| 23 | |
Engineers | 2-3-6 | def. | |
Bears | 1-4-5 DSQ |
| 24 | |
Eagles | 1-2-5 | def. | |
Crimson | 3-4-6 |
| 25 | |
Jumbos | 1-2-4 | def. | |
Hawks | 3-5-6 |
| 26 | |
Engineers | 1-2-5 | def. | |
Rams | 3-4-6 |
| 27 | |
Crimson | 2-3-4 | def. | |
Bulldogs | 1-5-6 |
| 28 | |
Eagles | 1-2-5 | def. | |
Bears | 3-4-6 |
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 ±0.00 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.
