| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Tufts University | Jumbos | 8–1 |
| 2 |  |
Bowdoin College | Polar Bears | 7–2 |
| 3 |  |
Maine Maritime Academy | Mariners | 2–7 |
| 4 |  |
Bates College | Bobcats | 1–8 |
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 13,225 team race matches sailed before 2019-03-30, using the line-ups that actually raced. It called 15 of 18 matches (83%) with a log-loss of 0.299 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.18 ± 0.40: a typical event, more orderly than 63% 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 | Tufts University Jumbos | 2 | 6.10 school +0.15 | Andrew Savage / Kahler Newsham 1.98 John Duncan / Michaela Morris 1.58 Ryutaro Sochi / Mallory Hood | 72% | 8–1 (89%) | +1.5 |
| 2 | Bowdoin College Polar Bears | 1 | 6.88 school +0.25, home +0.38 | Emmett Ulian / Eliza Jevon Kelsey Slack / Caitlin Tardio Perham Black / Gigi Diserio 2.36 | 87% | 7–2 (78%) | −0.8 |
| 3 | Maine Maritime Academy Mariners | 3 | 4.11 | Luke Healy / August Campbell Mott Blair / Owen White Olivia Mitchell / David Estes | 31% | 2–7 (22%) | −0.8 |
| 4 | Bates College Bobcats | 4 | 3.04 | Jack Valentino / Anna Landgren Sarah Herde / Sam Gilman Peter Galloway / Gillian Coyne | 11% | 1–8 (11%) | +0.0 |
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 | Tufts University | 6.10 | 7.73 | 8–1 | 6.4 | +1.64 | 1.7 | 15% |
| 4 | Bates College | 3.04 | 3.07 | 1–8 | 1.0 | +0.03 | 0.0 | 67% |
| 3 | Maine Maritime Academy | 4.11 | 3.36 | 2–7 | 2.8 | −0.75 | 0.4 | 90% |
| 2 | Bowdoin College | 6.88 | 6.10 | 7–2 | 7.8 | −0.78 | 0.5 | 92% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Andrew Savage | Tufts University | 1.98 | 3.61 | 8–1 | 6.4 | +1.64 | 1.7 | 15% |
| John Duncan | Tufts University | 1.58 | 3.22 | 8–1 | 6.4 | +1.64 | 1.7 | 15% |
| Ryutaro Sochi | Tufts University | 2.15 | 3.79 | 8–1 | 6.4 | +1.64 | 1.7 | 15% |
| Jack Valentino | Bates College | 1.00 | 1.04 | 1–8 | 1.0 | +0.03 | 0.0 | 67% |
| Mott Blair | Maine Maritime Academy | 1.65 | 0.90 | 2–7 | 2.8 | −0.75 | 0.4 | 90% |
| Emmett Ulian | Bowdoin College | 1.38 | 0.60 | 7–2 | 7.8 | −0.78 | 0.5 | 92% |
| Kelsey Slack | Bowdoin College | 2.27 | 1.48 | 7–2 | 7.8 | −0.78 | 0.5 | 92% |
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 | Bowdoin College | Maine Maritime Academy | 94% | |
| 1 | 2 | Tufts University | Bates College | 97% | |
| 1 | 3 | Tufts University | Bowdoin College | 31% | upset |
| 1 | 4 | Maine Maritime Academy | Bates College | 77% | |
| 1 | 5 | Tufts University | Maine Maritime Academy | 88% | |
| 1 | 6 | Bowdoin College | Bates College | 98% | |
| 2 | 7 | Tufts University | Maine Maritime Academy | 88% | |
| 2 | 8 | Bowdoin College | Bates College | 98% | |
| 2 | 9 | Bates College | Maine Maritime Academy | 27% | upset |
| 2 | 10 | Bowdoin College | Tufts University | 69% | |
| 2 | 11 | Tufts University | Bates College | 95% | |
| 2 | 12 | Bowdoin College | Maine Maritime Academy | 94% | |
| 3 | 13 | Tufts University | Bates College | 95% | |
| 3 | 14 | Bowdoin College | Maine Maritime Academy | 94% | |
| 3 | 15 | Tufts University | Bowdoin College | 31% | upset |
| 3 | 16 | Maine Maritime Academy | Bates College | 72% | |
| 3 | 17 | Bowdoin College | Bates College | 97% | |
| 3 | 18 | Tufts University | Maine Maritime Academy | 88% |
| Team | Rec. | Jumbos | Bears | Mariners | Bobcats | |
|---|---|---|---|---|---|---|
| Tufts University Jumbos | 3–0 | ✕ | W | W | W |
| Bowdoin College Polar Bears | 2–1 | L | ✕ | W | W |
| Maine Maritime Academy Mariners | 1–2 | L | L | ✕ | W |
| Bates College Bobcats | 0–3 | L | L | L | ✕ |
| Team | Rec. | Jumbos | Bears | Mariners | Bobcats | |
|---|---|---|---|---|---|---|
| Tufts University Jumbos | 2–1 | ✕ | L | W | W |
| Bowdoin College Polar Bears | 3–0 | W | ✕ | W | W |
| Maine Maritime Academy Mariners | 0–3 | L | L | ✕ | L |
| Bates College Bobcats | 1–2 | L | L | W | ✕ |
| Team | Rec. | Jumbos | Bears | Mariners | Bobcats | |
|---|---|---|---|---|---|---|
| Tufts University Jumbos | 3–0 | ✕ | W | W | W |
| Bowdoin College Polar Bears | 2–1 | L | ✕ | W | W |
| Maine Maritime Academy Mariners | 1–2 | L | L | ✕ | W |
| Bates College Bobcats | 0–3 | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Polar Bears | 1-2-3 | def. | |
Mariners | 4-5-6 |
| 2 | |
Jumbos | 1-2-6 | def. | |
Bobcats | 3-4-5 |
| 3 | |
Jumbos | 1-3-6 | def. | |
Polar Bears | 2-4-5 |
| 4 | |
Mariners | 2-3-4 | def. | |
Bobcats | 1-5-6 |
| 5 | |
Jumbos | 1-2-4 | def. | |
Mariners | 3-5-6 |
| 6 | |
Polar Bears | 1-2-4 | def. | |
Bobcats | 3-5-6 |
| 7 | |
Jumbos | 1-2-3 | def. | |
Mariners | 4-5-6 |
| 8 | |
Polar Bears | 2-3-4 | def. | |
Bobcats | 1-5-6 |
| 9 | |
Bobcats | 1-2-5 | def. | |
Mariners | 3-4-6 |
| 10 | |
Polar Bears | 2-3-4 | def. | |
Jumbos | 1-5-6 |
| 11 | |
Jumbos | 1-2-4 | def. | |
Bobcats | 3-5-6 |
| 12 | |
Polar Bears | 1-3-6 | def. | |
Mariners | 2-4-5 |
| 13 | |
Jumbos | 1-2-5 | def. | |
Bobcats | 3-4-6 |
| 14 | |
Polar Bears | 1-3-6 | def. | |
Mariners | 2-4-5 |
| 15 | |
Jumbos | 1-3-5 | def. | |
Polar Bears | 2-4-6 |
| 16 | |
Mariners | 1-2-3 | def. | |
Bobcats | 4-5-6 |
| 17 | |
Polar Bears | 1-3-6 | def. | |
Bobcats | 2-4-5 |
| 18 | |
Jumbos | 2-3-4 | def. | |
Mariners | 1-5-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Tufts University | Jumbos | Andrew Savage '19 John Duncan '19 Ryutaro Sochi '22 |
Kahler Newsham '19 Michaela Morris '20 Mallory Hood '22 |
|
Bowdoin College | Polar Bears | Emmett Ulian '19 Kelsey Slack '21 Perham Black '22 |
Eliza Jevon '21 Caitlin Tardio '19 Gigi Diserio '22 |
|
Maine Maritime Academy | Mariners | Luke Healy '22 Mott Blair '22 Olivia Mitchell '22 |
August Campbell '22 Owen White '22 David Estes '22 |
|
Bates College | Bobcats | Jack Valentino '22 Peter Galloway '21 Sarah Herde '21 |
Anna Landgren '22 Gillian Coyne '19 Sam Gilman '22 |
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 2% 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.
