| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 | Roger Williams University | Hawks | 12–3 | |
| 2 | Boston University | Terriers | 12–3 | |
| 3 | Harvard University | Crimson | 8–7 | |
| 4 | Massachusetts Institute of Technology | Engineers | 7–8 | |
| 5 | Bowdoin College | Polar Bears | 5–10 | |
| 6 | Salve Regina University | Seahawks | 1–14 |
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 10,346 team race matches sailed before 2018-03-24, using the line-ups that actually raced. It called 34 of 45 matches (76%) with a log-loss of 0.454 (a coin flip scores 0.693), so the event went about as expected for the forecast. Orderliness −0.09 ± 0.26: a typical event, more orderly than 33% 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 | Roger Williams University | 7.82 | 8.74 | 12–3 | 10.1 | +0.92 | 1.2 | 17% |
| 3 | Harvard University | 6.99 | 7.34 | 8–7 | 7.1 | +0.35 | 0.2 | 40% |
| 5 | Bowdoin College | 5.97 | 6.27 | 5–10 | 4.4 | +0.30 | 0.1 | 45% |
| 6 | Salve Regina University | 4.70 | 4.50 | 1–14 | 1.2 | −0.20 | 0.0 | 72% |
| 4 | Massachusetts Institute of Technology | 7.46 | 6.71 | 7–8 | 8.9 | −0.75 | 1.0 | 94% |
| 2 | Boston University | 9.07 | 8.30 | 12–3 | 13.4 | −0.77 | 0.8 | 93% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Grace Vincens | Salve Regina University | 1.71 | 2.11 | 1–11 | 0.7 | +0.40 | 0.1 | 52% |
| Taylor Gavula | Harvard University | 2.49 | 2.85 | 8–7 | 7.1 | +0.35 | 0.2 | 40% |
| Louis Frumer | Bowdoin College | 1.90 | 2.20 | 5–10 | 4.4 | +0.30 | 0.1 | 45% |
| Claire Havig | Bowdoin College | 1.76 | 2.06 | 5–10 | 4.4 | +0.30 | 0.1 | 45% |
| Allison Deluca | Salve Regina University | 0.99 | 1.28 | 1–8 | 0.8 | +0.29 | 0.0 | 57% |
| Sean Beaulieu | Salve Regina University | 2.30 | 2.10 | 1–14 | 1.2 | −0.20 | 0.0 | 72% |
| Alex Moreno | Boston University | 2.81 | 2.52 | 8–1 | 8.2 | −0.29 | 0.0 | 82% |
| Ivan Shestopalov | Massachusetts Institute of Technology | 2.77 | 2.02 | 7–8 | 8.9 | −0.75 | 1.0 | 94% |
| James Peraire-Bueno | Massachusetts Institute of Technology | 1.90 | 1.14 | 7–8 | 8.9 | −0.75 | 1.0 | 94% |
| Joey Lark | Salve Regina University | 1.36 | -1.64 | 0–9 | 0.9 | ≤−3.00 | 1.4 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Hawks | Terriers | Crimson | Engineers | Bears | Seahawks | |
|---|---|---|---|---|---|---|---|---|
| Roger Williams University Hawks | 3–2 | ✕ | L | W | L | W | W | |
| Boston University Terriers | 4–1 | W | ✕ | W | L | W | W | |
| Harvard University Crimson | 3–2 | L | L | ✕ | W | W | W | |
| Massachusetts Institute of Technology Engineers | 4–1 | W | W | L | ✕ | W | W | |
| Bowdoin College Polar Bears | 1–4 | L | L | L | L | ✕ | W | |
| Salve Regina University Seahawks | 0–5 | L | L | L | L | L | ✕ |
| Team | Rec. | Hawks | Terriers | Crimson | Engineers | Bears | Seahawks | |
|---|---|---|---|---|---|---|---|---|
| Roger Williams University Hawks | 4–1 | ✕ | W | L | W | W | W | |
| Boston University Terriers | 4–1 | L | ✕ | W | W | W | W | |
| Harvard University Crimson | 3–2 | W | L | ✕ | W | L | W | |
| Massachusetts Institute of Technology Engineers | 2–3 | L | L | L | ✕ | W | W | |
| Bowdoin College Polar Bears | 2–3 | L | L | W | L | ✕ | W | |
| Salve Regina University Seahawks | 0–5 | L | L | L | L | L | ✕ |
| Team | Rec. | Hawks | Terriers | Crimson | Engineers | Bears | Seahawks | |
|---|---|---|---|---|---|---|---|---|
| Roger Williams University Hawks | 5–0 | ✕ | W | W | W | W | W | |
| Boston University Terriers | 4–1 | L | ✕ | W | W | W | W | |
| Harvard University Crimson | 2–3 | L | L | ✕ | W | L | W | |
| Massachusetts Institute of Technology Engineers | 1–4 | L | L | L | ✕ | W | L | |
| Bowdoin College Polar Bears | 2–3 | L | L | W | L | ✕ | W | |
| Salve Regina University Seahawks | 1–4 | L | L | L | W | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | Crimson | 1-4-5 | def. | Engineers | 2-3-6 | ||
| 2 | Hawks | 1-2-5 | def. | Polar Bears | 3-4-6 | ||
| 3 | Terriers | 1-2-4 | def. | Seahawks | 3-5-6 | ||
| 4 | Crimson | 1-3-5 | def. | Polar Bears | 2-4-6 | ||
| 5 | Engineers | 2-3-5 | def. | Seahawks | 1-4-6 | ||
| 6 | Terriers | 1-2-5 | def. | Hawks | 3-4-6 | ||
| 7 | Polar Bears | 2-3-4 | def. | Seahawks | 1-5-6 | ||
| 8 | Hawks | 1-3-4 | def. | Crimson | 2-5-6 | ||
| 9 | Engineers | 1-3-4 | def. | Terriers | 2-5-6 | ||
| 10 | Hawks | 1-2-4 | def. | Seahawks | 3-5-6 | ||
| 11 | Engineers | 1-2-5 | def. | Polar Bears | 3-4-6 | ||
| 12 | Terriers | 1-2-5 | def. | Crimson | 3-4-6 | ||
| 13 | Engineers | 1-2-3 | def. | Hawks | 4-5-6 | ||
| 14 | Crimson | 1-2-3 | def. | Seahawks | 4-5-6 | ||
| 15 | Terriers | 1-2-5 | def. | Polar Bears | 3-4-6 | ||
| 16 | Crimson | 1-2-4 | def. | Engineers | 3-5-6 | ||
| 17 | Hawks | 1-2-6 | def. | Polar Bears | 3-4-5 | ||
| 18 | Terriers | 1-2-6 | def. | Seahawks | 3-4-5 | ||
| 19 | Hawks | 1-2-6 | def. | Engineers | 3-4-5 | ||
| 20 | Terriers | 1-2-4 | def. | Crimson | 3-5-6 | ||
| 21 | Polar Bears | 1-2-6 | def. | Seahawks | 3-4-5 | ||
| 22 | Hawks | 1-2-6 | def. | Terriers | 3-4-5 | ||
| 23 | Engineers | 1-2-4 | def. | Polar Bears | 3-5-6 | ||
| 24 | Crimson | 2-3-5 | def. | Seahawks | 1-4-6 | ||
| 25 | Terriers | 1-2-6 | def. | Polar Bears | 3-4-5 | ||
| 26 | Crimson | 1-2-6 | def. | Hawks | 3-4-5 | ||
| 27 | Engineers | 1-2-3 | def. | Seahawks | 4-5-6 | ||
| 28 | Polar Bears | 1-4-5 | def. | Crimson | 2-3-6 | ||
| 29 | Terriers | 1-2-5 | def. | Engineers | 3-4-6 | ||
| 30 | Hawks | 1-3-4 | def. | Seahawks | 2-5-6 | ||
| 31 | Hawks | 1-2-6 | def. | Terriers | 3-4-5 | ||
| 32 | Crimson | 1-2-3 | def. | Seahawks | 4-5-6 | ||
| 33 | Engineers | 1-2-4 | def. | Polar Bears | 3-5-6 | ||
| 34 | Terriers | 1-2-4 | def. | Seahawks | 3-5-6 | ||
| 35 | Hawks | 1-3-5 | def. | Engineers | 2-4-6 | ||
| 36 | Polar Bears | 1-2-3 | def. | Crimson | 4-5-6 | ||
| 37 | Seahawks | 1-3-6 | def. | Engineers | 2-4-5 | ||
| 38 | Terriers | 1-2-6 | def. | Crimson | 3-4-5 | ||
| 39 | Hawks | 1-2-5 | def. | Polar Bears | 3-4-6 | ||
| 40 | Crimson | 1-2-5 | def. | Engineers | 3-4-6 | ||
| 41 | Hawks | 1-2-4 | def. | Seahawks | 3-5-6 | ||
| 42 | Terriers | 1-2-6 | def. | Polar Bears | 3-4-5 | ||
| 43 | Hawks | 1-2-5 | def. | Crimson | 3-4-6 | ||
| 44 | Terriers | 1-3-6 | def. | Engineers | 2-4-5 | ||
| 45 | Polar Bears | 1-3-4 | def. | Seahawks | 2-5-6 | ||
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
| Roger Williams University | Hawks | Kelsey Shakin '19 Peter Neal '20 Preston Duclos '19 |
Kristi Dolan '20 Rachel Holick '22 Kylie Freitas '20 |
|
| Boston University | Terriers | Alex Moreno '19 Casey Cabot '21 Josh Dochoda '20 Kyle Dochoda '21 Sam Morrell '21 |
Skye Shepherd '20 Emily Walker '19 Erica Brown '21 |
|
| Harvard University | Crimson | Jackson Wagner '19 Owen Schafer '21 Taylor Gavula '19 |
Gayatri Balasubramanian '21 Emily Malpass '21 Emily Wang '21 |
|
| Massachusetts Institute of Technology | Engineers | Ivan Shestopalov '21 James Peraire-Bueno '19 Stephen Duncan '20 |
Fiona Mckellar '20 Elizabeth Obermaier '21 Lynn Liu '20 |
|
| Bowdoin College | Polar Bears | Claire Havig '21 Louis Frumer '18 Rowan Byrne '21 |
Martinique Ogle '18 Isabelle Austin-Green '19 Kelsey Slack '21 |
|
| Salve Regina University | Seahawks | Allison Deluca '21 Grace Vincens '20 Joey Lark '21 Sean Beaulieu '18 |
Mary Grace Bean '18 Jennifer Ryan '19 Grace Benzal '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 ±0.02 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.