| # | School | Team | A | TOT | |
|---|---|---|---|---|---|
| 1 | University of Chicago | Maroons | 1 | 1 | |
| 2 | Ohio State University | Buckeyes | 2 | 2 | |
| 3 | University of Wisconsin | Badgers | 3 | 3 | |
| 4 | University of Saint Thomas | Tommies | 4 | 4 | |
| 5 | University of Michigan | Wolverines | 5 | 5 | |
| 6 | Purdue University | Boilermakers | 6 | 6 |
| School | Team | R1 | TOT | |
|---|---|---|---|---|
| University of Chicago | Maroons | 1 | 1 | |
| Ohio State University | Buckeyes | 2 | 2 | |
| University of Wisconsin | Badgers | 3 | 3 | |
| University of Saint Thomas | Tommies | 4 | 4 | |
| University of Michigan | Wolverines | 5 | 5 | |
| Purdue University | Boilermakers | 6 | 6 |
| School | Team | Sailors | |
|---|---|---|---|
| Ohio State University | Buckeyes | SkipperNadia Reynolds '25 CrewNick Robertson '27 CrewJohn Sullivan '25 |
|
| Purdue University | Boilermakers | SkipperJoseph Mowrey '25 CrewNok In Chan '25 CrewMathis Destouches '25 CrewCharlotte Bach '28 |
|
| University of Chicago | Maroons | SkipperMax Zhalilo '26 CrewEliot Hack '28 CrewJames Leavitt '27 CrewIris Badezet Delory '27 |
|
| University of Michigan | Wolverines | SkipperRiver Servia '27 CrewBryson DenUyl '24 CrewCaroline Grin '25 CrewEleanor Ervine '27 |
|
| University of Saint Thomas | Tommies | SkipperGreg Bittle '25 CrewAustin Shaw '27 CrewRakesh Dhiman '26 CrewGeorgia Green '28 |
|
| University of Wisconsin | Badgers | SkipperSeamus Hendrickson '25 CrewDavid Tofer '24 CrewMaddy Netzer '26 CrewCarter Harms '27 |
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 | Max Zhalilo '26 | University of Chicago | 1/1 | 1.40 | 7.00+ | +5.60 | 88th → 99th | 1.7 | 29% | 1.0 / 2.7 |
| 2 | Nadia Reynolds '25 | Ohio State University | 1/1 | 0.34 | 2.28 | +1.94 | 40th → 99th | 1.2 | 25% | 2.0 / 3.8 |
| 3 | Seamus Hendrickson '25 | University of Wisconsin | 1/1 | 1.20 | 1.17 | −0.03 | 81st → 79th | 0.0 | 64% | 3.0 / 2.9 |
| 4 | Greg Bittle '25 | University of Saint Thomas | 1/1 | 0.96 | 0.48 | −0.47 | 72nd → 49th | 0.1 | 77% | 4.0 / 3.2 |
| 5 | River Servia '27 | University of Michigan | 1/1 | 0.24 | -0.16 | −0.40 | 36th → 10th | 0.1 | 76% | 5.0 / 4.0 |
| 6 | Joseph Mowrey '25 | Purdue University | 1/1 | -0.26 | — | — | 6th → — | 1.3 | >99% | 6.0 / 4.4 |
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 ±0.17 means a rating gap counts about 15% 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.