| # | School | Sailor | TOT | |
|---|---|---|---|---|
| 1 |  |
Brown University | Lindsey Baab '18 | 6 |
| 2 |  |
U. S. Coast Guard Academy | Dana Rohde '18 | 16 |
| 3 |  |
Boston College | Isabella Loosbrock '19 | 18 |
| 4 |  |
Connecticut College | Charlotte List '18 | 24 |
| 5 |  |
Harvard University | Taylor Ladd '18 | 40 |
| 6 | |
U. S. Coast Guard Academy | Madelynn Widmeier '19 | 42 |
| 7 |  |
Tufts University | Amanda Sommi '16 | 43 |
| 8 | |
Connecticut College | Alexandra Maurillo '18 | 46 |
| 9 | |
Harvard University | Taylor Gavula '19 | 55 |
| 10 |  |
University of Vermont | Amina Brown '17 | 57 |
| 11 | |
Tufts University | Molly Pleskus '18 | 60 |
| 12 | |
U. S. Coast Guard Academy | Kayla Ellis '16 | 63 |
| 13 | |
Connecticut College | Haley Kachmar '18 | 84 |
| School | Sailor | R1 | R2 | R3 | R4 | R5 | R6 | TOT | |
|---|---|---|---|---|---|---|---|---|---|
|
Brown University | Lindsey Baab '18 | 1 | 1 | 1 | 1 | 1 | 1 | 6 |
|
U. S. Coast Guard Academy | Dana Rohde '18 | 3 | 5 | 2 | 2 | 2 | 2 | 16 |
|
Boston College | Isabella Loosbrock '19 | 2 | 3 | 4 | 3 | 3 | 3 | 18 |
|
Connecticut College | Charlotte List '18 | 4 | 2 | 5 | 4 | 4 | 5 | 24 |
|
Harvard University | Taylor Ladd '18 | 5 | 8 | 7 | 6 | 6 | 8 | 40 |
|
U. S. Coast Guard Academy | Madelynn Widmeier '19 | 6 | 7 | 3 | 8 | 8 | 10 | 42 |
|
Tufts University | Amanda Sommi '16 | 7 | 6 | 11 | 5 | 10 | 4 | 43 |
|
Connecticut College | Alexandra Maurillo '18 | DNF | 4 | 8 | 9 | 5 | 6 | 46 |
|
Harvard University | Taylor Gavula '19 | 11 | 12 | 6 | 7 | 12 | 7 | 55 |
|
University of Vermont | Amina Brown '17 | 8 | 11 | 9 | 11 | 9 | 9 | 57 |
|
Tufts University | Molly Pleskus '18 | 10 | 9 | 10 | 12 | 7 | 12 | 60 |
|
U. S. Coast Guard Academy | Kayla Ellis '16 | 9 | 10 | 12 | 10 | 11 | 11 | 63 |
|
Connecticut College | Haley Kachmar '18 | DNF | DNS | DNS | DNS | DNS | DNS | 84 |
Performance rating asks, for each skipper: holding every other boat fixed, which rating makes my actual race-by-race finishes least surprising? Boats are valued with the singlehanded rating rather than the fleet rating: 0.79 × the skipper's fleet rating from the week before the event (unrated skippers start at 1.11); the skipper's own singlehanded offset. Strength differences are scaled by 0.80 before they become probabilities, the value that calibrates the model on seasons it had not seen. Non-finishes (OCS, DNF and similar) are left out of the fitting, as in the rating model.
Percentile places a rating among the 309 ICSA sailors with a singlehanded rating who raced the discipline in the last three seasons. Surprise is how many bits more surprising the finishes were at the pre-event rating than at the performance rating. P(this good or better) simulates the event 3,000 times at the pre-event ratings, with the same regatta-form model as the fleet analysis pages, and reports how often the skipper would score this many points or fewer in the races they sailed.
The singlehanded offsets are the current ones (the discipline files keep no weekly history), so a skipper's own offset has already seen this event; offsets are shrunk hard, so the effect is a few hundredths at most. Only skippers are rated.
| Fin | Skipper | School | Races | Rating before |
Perf. rating |
Δ | Percentile before → perf. |
Surprise (bits) |
P(this good or better) |
Avg finish actual / exp. |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Lindsey Baab '18 | Brown University | 6/6 | 2.54 | 8.75+ | +6.21 | 66th → 99th | 18.1 | <1% | 1.0 / 5.9 |
| 2 | Dana Rohde '18 | U. S. Coast Guard Academy Bears 1 | 6/6 | 2.75 | 4.21 | +1.45 | 73rd → 97th | 3.2 | 4% | 2.7 / 5.5 |
| 3 | Isabella Loosbrock '19 | Boston College | 6/6 | 1.99 | 4.06 | +2.07 | 51st → 95th | 6.2 | 2% | 3.0 / 7.0 |
| 4 | Charlotte List '18 | Connecticut College Camels 2 | 6/6 | 2.08 | 3.43 | +1.35 | 54th → 89th | 3.1 | 11% | 4.0 / 6.8 |
| 5 | Taylor Ladd '18 | Harvard University Crimson 2 | 6/6 | 2.09 | 2.38 | +0.28 | 55th → 61st | 0.2 | 50% | 6.7 / 6.8 |
| 6 | Madelynn Widmeier '19 | U. S. Coast Guard Academy Bears 3 | 6/6 | 1.85 | 2.20 | +0.35 | 47th → 58th | 0.3 | 47% | 7.0 / 7.3 |
| 7 | Amanda Sommi '16 | Tufts University Jumbos 2 | 6/6 | 1.81 | 2.03 | +0.22 | 44th → 53rd | 0.1 | 49% | 7.2 / 7.3 |
| 8 | Alexandra Maurillo '18 | Connecticut College Camels 3 | 6/6 | 1.65 | 2.46 | +0.82 | 41st → 62nd | 1.1 | 52% | 7.7 / 7.6 |
| 9 | Taylor Gavula '19 | Harvard University Crimson 1 | 6/6 | 1.65 | 0.56 | −1.09 | 41st → 15th | 1.9 | 76% | 9.2 / 7.6 |
| 10 | Amina Brown '17 | University of Vermont | 6/6 | 2.37 | 1.30 | −1.06 | 61st → 30th | 3.2 | 92% | 9.5 / 6.3 |
| 11 | Molly Pleskus '18 | Tufts University Jumbos 1 | 6/6 | 1.87 | 0.72 | −1.15 | 47th → 17th | 2.8 | 89% | 10.0 / 7.3 |
| 12 | Kayla Ellis '16 | U. S. Coast Guard Academy Bears 2 | 6/6 | 2.26 | 0.74 | −1.52 | 59th → 17th | 6.2 | 97% | 10.5 / 6.5 |
| 13 | Haley Kachmar '18 | Connecticut College Camels 1 | 6/6 | 0.96 | — | — | 22nd → — | 0.0 | >99% | 14.0 / 8.9 |
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 ±0.12 means a rating gap counts about 10% 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.
