| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Roger Williams University | Hawks | 13–0 |
| 2 |  |
Boston College | Eagles | 9–4 |
| 3 |  |
Tufts University | Jumbos | 8–5 |
| 4 | |
Tufts University | Jumbalaya | 4–9 |
| 5 |  |
Brown University | Bears | 2–8 |
| 6 |  |
Harvard University | Crimson | 0–10 |
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 1,673 team race matches sailed before 2013-10-19, using the line-ups that actually raced. It called 34 of 36 matches (94%) with a log-loss of 0.244 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.61 ± 0.30: an orderly event, more orderly than 97% 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 Hawks | 10.05 | 13.05 | 13–0 | 10.7 | ≥+3.00 | 3.6 | 7% |
| 2 | Boston College Eagles | 9.04 | 9.51 | 9–4 | 8.0 | +0.48 | 0.3 | 37% |
| 4 | Tufts University Jumbalaya | 7.68 | 7.55 | 4–9 | 4.2 | −0.13 | 0.0 | 70% |
| 3 | Tufts University Jumbos | 9.46 | 8.89 | 8–5 | 9.2 | −0.58 | 0.5 | 89% |
| 5 | Brown University Bears | 7.23 | 6.37 | 2–8 | 3.0 | −0.86 | 0.6 | 92% |
| 6 | Harvard University Crimson | 5.79 | 2.79 | 0–10 | 0.8 | ≤−3.00 | 1.2 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| J. Jacob | Roger Williams University | 3.15 | 6.14 | 13–0 | 10.7 | ≥+3.00 | 3.6 | 7% |
| Connor Needham | Roger Williams University | 3.19 | 6.19 | 13–0 | 10.7 | ≥+3.00 | 3.6 | 7% |
| Connor Corgard | Roger Williams University | 3.37 | 6.37 | 13–0 | 10.7 | ≥+3.00 | 3.6 | 7% |
| Domenic Bove | Boston College | 2.81 | 3.29 | 9–4 | 8.0 | +0.48 | 0.3 | 37% |
| Henry Dumke | Boston College | 2.47 | 2.94 | 9–4 | 8.0 | +0.48 | 0.3 | 37% |
| Maxwell Simmons | Boston College | 2.99 | 3.47 | 9–4 | 8.0 | +0.48 | 0.3 | 37% |
| James Moody | Tufts University | 2.58 | 2.45 | 4–9 | 4.2 | −0.13 | 0.0 | 70% |
| Rolfe Glover | Tufts University | 2.20 | 2.07 | 4–9 | 4.2 | −0.13 | 0.0 | 70% |
| Scott Barbano | Tufts University | 2.28 | 2.15 | 4–9 | 4.2 | −0.13 | 0.0 | 70% |
| Willem Sandberg | Tufts University | 3.31 | 2.74 | 8–5 | 9.2 | −0.58 | 0.5 | 89% |
| Charles Proctor | Tufts University | 2.86 | 2.28 | 8–5 | 9.2 | −0.58 | 0.5 | 89% |
| Duncan Swain | Tufts University | 3.00 | 2.42 | 8–5 | 9.2 | −0.58 | 0.5 | 89% |
| Emmett Weeks | Brown University | 2.00 | 1.15 | 2–8 | 3.0 | −0.86 | 0.6 | 92% |
| Reid Secondo | Brown University | 1.80 | 0.94 | 2–8 | 3.0 | −0.86 | 0.6 | 92% |
| Nathan Allman | Brown University | 2.68 | 1.82 | 2–8 | 3.0 | −0.86 | 0.6 | 92% |
| Richard Bergsund | Harvard University | 2.17 | -0.83 | 0–10 | 0.8 | ≤−3.00 | 1.2 | >99% |
| Bennett Capozzi | Harvard University | 1.86 | -1.14 | 0–10 | 0.8 | ≤−3.00 | 1.2 | >99% |
| William Bloxham | Harvard University | 1.23 | -1.77 | 0–10 | 0.8 | ≤−3.00 | 1.2 | >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 | Eagles | Jumbos | Jumbalaya | Bears | Crimson | |
|---|---|---|---|---|---|---|---|---|
| Roger Williams University Hawks | 5–0 | ✕ | W | W | W | W | W |
| Boston College Eagles | 4–1 | L | ✕ | W | W | W | W |
| Tufts University Jumbos | 5–5 | L | L | ✕ | ✕ | W | W |
| Tufts University Jumbalaya | 5–5 | L | L | ✕ | ✕ | W | W |
| Brown University Bears | 1–4 | L | L | L | L | ✕ | W |
| Harvard University Crimson | 0–5 | L | L | L | L | L | ✕ |
| Team | Rec. | Hawks | Eagles | Jumbos | Jumbalaya | Bears | Crimson | |
|---|---|---|---|---|---|---|---|---|
| Roger Williams University Hawks | 8–0 | ✕ | W | W | W | W | W |
| Boston College Eagles | 5–3 | L | ✕ | W | W | W | W |
| Tufts University Jumbos | 7–9 | L | L | ✕ | ✕ | W | W |
| Tufts University Jumbalaya | 7–9 | L | L | ✕ | ✕ | W | W |
| Brown University Bears | 1–4 | L | L | L | L | ✕ | W |
| Harvard University Crimson | 0–5 | L | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Eagles | 1-3-5 | def. | |
Jumbalaya | 2-4-6 |
| 2 | |
Jumbos | 2-3-4 | def. | |
Bears | 1-5-6 DNF |
| 3 | |
Hawks | 1-2-5 | def. | |
Crimson | 3-4-6 |
| 4 | |
Eagles | 1-2-3 | def. | |
Jumbos | 4-5-6 |
| 5 | |
Jumbalaya | 1-4-5 | def. | |
Crimson | 2-3-6 |
| 6 | |
Hawks | 1-2-5 | def. | |
Bears | 3-4-6 |
| 7 | |
Jumbos | 1-2-5 | def. | |
Crimson | 3-4-6 |
| 8 | |
Eagles | 1-2-5 | def. | |
Bears | 3-4-6 |
| 9 | |
Hawks | 1-2-4 | def. | |
Jumbalaya | 3-5-6 |
| 10 | |
Bears | 1-2-5 | def. | |
Crimson | 3-4-6 |
| 11 | |
Jumbos | 1-2-5 | def. | |
Jumbalaya | 3-4-6 |
| 12 | |
Hawks | 1-2-5 | def. | |
Eagles | 3-4-6 |
| 13 | |
Jumbalaya | 1-2-4 | def. | |
Bears | 3-5-6 |
| 14 | |
Eagles | 1-2-5 | def. | |
Crimson | 3-4-6 |
| 15 | |
Hawks | 1-2-3 | def. | |
Jumbos | 4-5-6 |
| 16 | |
Eagles | 1-2-4 | def. | |
Jumbalaya | 3-5-6 |
| 17 | |
Jumbos | 1-2-3 | def. | |
Bears | 4-5-6 |
| 18 | |
Hawks | 1-2-3 | def. | |
Crimson | 4-5-6 |
| 19 | |
Eagles | 1-2-5 | def. | |
Jumbos | 3-4-6 |
| 20 | |
Jumbalaya | 1-2-6 | def. | |
Crimson | 3-4-5 |
| 21 | |
Hawks | 1-2-5 | def. | |
Bears | 3-4-6 |
| 22 | |
Jumbos | 1-2-6 | def. | |
Crimson | 3-4-5 |
| 23 | |
Eagles | 2-3-5 | def. | |
Bears | 1-4-6 |
| 24 | |
Hawks | 1-2-3 | def. | |
Jumbalaya | 4-5-6 |
| 25 | |
Bears | 1-3-5 | def. | |
Crimson | 2-4-6 |
| 26 | |
Jumbos | 1-3-5 | def. | |
Jumbalaya | 2-4-6 |
| 27 | |
Hawks | 1-2-6 | def. | |
Eagles | 3-4-5 |
| 28 | |
Jumbalaya | 2-3-4 | def. | |
Bears | 1-5-6 |
| 29 | |
Eagles | 1-2-3 | def. | |
Crimson | 4-5-6 |
| 30 | |
Hawks | 1-2-6 | def. | |
Jumbos | 3-4-5 |
| 31 | |
Jumbos | 1-2-5 | def. | |
Eagles | 3-4-6 |
| 32 | |
Hawks | 1-2-3 | def. | |
Jumbalaya | 4-5-6 |
| 33 | |
Eagles | 1-4-5 | def. | |
Jumbalaya | 2-3-6 |
| 34 | |
Hawks | 1-2-3 | def. | |
Jumbos | 4-5-6 |
| 35 | |
Jumbos | 1-2-4 | def. | |
Jumbalaya | 3-5-6 |
| 36 | |
Hawks | 1-2-3 | def. | |
Eagles | 4-5-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Roger Williams University | Hawks | Connor Corgard '16 Connor Needham '14 J. Jacob '16 |
Abby Preston '15 Sara Swanson '16 Samantha Bobo '15 |
|
Boston College | Eagles | Domenic Bove '15 Henry Dumke '17 Maxwell Simmons '17 |
Isabelle Salvaterra '14 Caroline Drury '14 Kaitlin Driscoll '16 |
|
Tufts University | Jumbos | Charles Proctor '14 Duncan Swain '15 Willem Sandberg '14 |
Elizabeth Keys '14 Julie Pringle '14 Mara Porter '14 |
|
Tufts University | Jumbalaya | James Moody '16 Rolfe Glover '16 Scott Barbano '17 |
Eliza White '14 Leah Fletcher '17 Caitlin Durand '15 |
|
Brown University | Bears | Emmett Weeks '14 Nathan Allman '16 Reid Secondo '16 |
Olivia Lord '17 Ragna Eide '16 Katherine Sudol '16 |
|
Harvard University | Crimson | Bennett Capozzi '17 Richard Bergsund '15 William Bloxham '17 |
Daniel Leichus '16 Olivia Kjorlien '17 Victor Kamenker '17 |
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 ±0.09 means a rating gap counts about 8% 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.
