| # | School | Team | A | TOT | |
|---|---|---|---|---|---|
| 1 | Brown University | Bears | 38 | 38 | |
| 2 | Roger Williams University | Hawks | 43 | 43 | |
| 3 | Yale University | Bulldogs | 51 | 51 | |
| 4 | Boston College | Eagles | 56 | 56 | |
| 5 | University of Rhode Island | Rams | 60 | 60 | |
| 6 | U. S. Coast Guard Academy | Bears 1 | 73 | 73 | |
| 7 | U. S. Coast Guard Academy | Bears 2 | 89 | 89 | |
| 8 | Connecticut College | Camels | 89 | 89 |
| School | Team | R1 | R2 | R3 | R4 | R5 | R6 | R7 | R8 | R9 | R10 | R11 | R12 | R13 | R14 | TOT | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Brown University | Bears | 2 | 3 | 2 | 1 | 2 | 1 | 3 | 1 | 2 | 4 | 2 | 3 | 4 | 8 | 38 | |
| Roger Williams University | Hawks | 5 | 4 | 1 | 4 | 4 | 4 | 2 | 4 | 1 | 2 | 4 | 4 | 2 | 2 | 43 | |
| Yale University | Bulldogs | 6 | 7 | 6 | 3 | 5 | RDG | 1 | 2 | 6 | 1 | 1 | 2 | 3 | 4 | 51 | |
| Boston College | Eagles | 3 | 6 | 5 | 6 | 1 | 3 | 5 | 5 | 3 | 7 | 5 | 5 | 1 | 1 | 56 | |
| University of Rhode Island | Rams | 7 | 2 | 3 | 2 | 7 | 2 | 6 | 8 | 5 | 3 | 3 | 1 | 6 | 5 | 60 | |
| U. S. Coast Guard Academy | Bears 1 | 4 | 1 | 7 | 8 | 3 | 5 | 4 | 6 | 7 | 5 | 7 | 6 | 7 | 3 | 73 | |
| U. S. Coast Guard Academy | Bears 2 | 1 | 5 | 4 | 7 | 6 | 6 | 8 | RDG | 8 | 8 | 8 | 7 | 8 | 7 | 89 | |
| Connecticut College | Camels | 8 | 8 | 8 | 5 | 8 | 7 | 7 | 3 | 4 | 6 | 6 | 8 | 5 | 6 | 89 |
| School | Team | Sailors | |
|---|---|---|---|
| Boston College | Eagles | SkipperPeter Busch '26 CrewMadeline Torrey '28 CrewPeter Joslin '26 CrewTor Svendsen '27 |
|
| Brown University | Bears | SkipperGuthrie Braun '26 CrewKatherine McNamara '26 CrewCharles Gish '28 CrewCam Spriggs '27 |
|
| Connecticut College | Camels | SkipperWells Connor '29 CrewKeegan Chatburn '29 CrewCharlotte McDonald '29 CrewJake Demos '27 |
|
| Roger Williams University | Hawks | SkipperCarlos de Castro '26 CrewAddyson Fisher '27 CrewDrew Mastovsky '26 CrewTristan McDonald '28 |
|
| U. S. Coast Guard Academy | Bears 1 | SkipperTomas Riccio '28 CrewSarah Evans '28 CrewEdward Jobson '27 CrewCharles Pohl '26 |
|
| U. S. Coast Guard Academy | Bears 2 | SkipperConnor Boudreau '26 CrewMara Maas '27 CrewCharlotte Waring '26 CrewKeith Teague '27 |
|
| University of Rhode Island | Rams | SkipperTyler Nash '26 CrewParker Brown '26 CrewCooper Newton '26 CrewMiles Silverman '27 |
|
| Yale University | Bulldogs | SkipperMorgan Pinckney '27 CrewAnnabel Woodworth '28 CrewMathias Reimer '27 CrewAlex Adams '26 |
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 keelboat rating rather than the fleet rating: 0.41 × the skipper's fleet rating from the week before the event (unrated skippers start at 0.47); 0.28 × the mean fleet rating of the rated crew aboard; the skipper's own keelboat offset; the school's program effect. Non-finishes (OCS, DNF and similar) are left out of the fitting, as in the rating model.
Percentile places a rating among the 207 ICSA sailors with a keelboat 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 keelboat 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 | Guthrie Braun '26 | Brown University | 14/14 | 3.23 | 3.27 | +0.04 | 99th → 99th | 0.0 | 34% | 2.7 / 3.2 |
| 2 | Carlos de Castro '26 | Roger Williams University | 14/14 | 2.78 | 3.26 | +0.48 | 99th → 99th | 1.4 | 25% | 3.1 / 3.9 |
| 3 | Morgan Pinckney '27 | Yale University | 14/14 | 2.92 | 2.75 | −0.17 | 99th → 99th | 0.2 | 64% | 4.0 / 3.7 |
| 3 | Peter Busch '26 | Boston College | 14/14 | 2.71 | 2.58 | −0.14 | 99th → 99th | 0.1 | 54% | 4.0 / 4.0 |
| 5 | Tyler Nash '26 | University of Rhode Island | 14/14 | 1.79 | 2.48 | +0.69 | 96th → 99th | 2.7 | 18% | 4.3 / 5.2 |
| 6 | Tomas Riccio '28 | U. S. Coast Guard Academy Bears 1 | 14/14 | 2.08 | 1.93 | −0.15 | 99th → 98th | 0.2 | 65% | 5.2 / 4.8 |
| 7 | Wells Connor '29 | Connecticut College | 14/14 | 1.52 | 1.21 | −0.31 | 91st → 82nd | 0.5 | 76% | 6.4 / 5.6 |
| 8 | Connor Boudreau '26 | U. S. Coast Guard Academy Bears 2 | 14/14 | 1.58u | 1.19 | −0.38 | 91st → 81st | 0.7 | 89% | 6.6 / 5.6 |
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 ±0.02 means a rating gap counts about 2% 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.