| # | School | Team | TOT | |
|---|---|---|---|---|
| 1 |  |
Texas A&M University at Galveston | Sea Aggies | 51 |
| 2 |  |
Texas A&M University | Aggies | 81 |
| 3 |  |
Louisiana Tech University | Bulldogs | 96 |
| 4 |  |
Rice University | Owls | 106 |
| 5 |  |
University of Texas | Longhorns | 127 |
| 6 |  |
University of Kansas | Jayhawks | 168 |
| School | Team | R1 | R2 | R3 | R4 | R5 | R6 | R7 | R8 | TOT | Sailors | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
Louisiana Tech University | Bulldogs A | 3 | 3 | 1 | 1 | 1 | 2 | 2 | 3 | 16 | |
|
Texas A&M University at Galveston | Sea Aggies A | 1 | 1 | 4 | 2 | 2 | 1 | 1 | 5 | 17 | Zachary Brown '30 [1-8] Colton Oliver '28 [1-6] Evelyn Chase '28 [7-8] |
|
Texas A&M University at Galveston | Sea Aggies B | 4 | 4 | 3 | 5 | 6 | 3 | 5 | 4 | 34 | Blake Polsen '29 Jake Boss '28 |
|
Rice University | Owls A | 2 | 5 | 5 | 4 | 5 | 6 | 7 | 6 | 40 | Lewis Forrest '29 [1-8] Oliver Zhu '28 [1-2] Naayaa Mehta '27 [3-6] James Gonzalez '30 [7-8] |
|
Texas A&M University | Aggies B | 9 | 6 | 6 | 7 | 3 | 4 | 4 | 1 | 40 | Zachary Aronson '27 [1-2] Matthew Schloemer '29 [3-8] Ben Ratterree '29 [1-4, 7-8] Zachary Aronson '27 [5-6] |
|
Texas A&M University | Aggies A | 6 | 2 | 2 | 3 | 7 | 5 | 3 | DNS | 41 | Jack Riley '29 [1-4, 7-8] Ben Ratterree '29 [5-6] Charlotte Heaney '28 [1-4, 7-8] Jack Riley '29 [5-6] |
|
University of Texas | Longhorns A | 8 | 8 | 7 | 8 | 4 | 7 | 9 | 7 | 58 | Mark Carella '27 [1-8] Karina Davis '29 [1-6] Teju Nadimpalli '29 [7-8] |
|
Rice University | Owls B | 7 | 9 | 8 | 6 | 8 | 8 | 10 | 10 | 66 | Collin Wilson '30 [1-4, 7-8] Oliver Zhu '28 [5-6] James Gonzalez '30 [1-2, 5-6] Blake Brown '28 [3-4] Oliver Zhu '28 [7-8] |
|
University of Texas | Longhorns B | 12 | 10 | 10 | 9 | 9 | 11 | 6 | 2 | 69 | Eric Li '29 [1-6] Matias Martin '27 [7-8] Anya Rodricks '28 [1-2, 5-6] Charbel Issa '27 [3-4] Daniel Gluckman '30 [7-8] |
|
Louisiana Tech University | Bulldogs B | 5 | 7 | DNS | DNS | DNS | DNS | 8 | 8 | 80 | |
|
University of Kansas | Jayhawks A | 10 | 12 | 9 | 10 | 10 | 10 | 11 | 9 | 81 | Robert Scheer '27 [1-2] Maxwell Walstien '30 [3-8] Cooper Grotzinger Frerichs '29 [1-2, 5-8] Robert Scheer '27 [3-4] |
|
University of Kansas | Jayhawks B | 11 | 11 | 11 | 11 | 11 | 9 | 12 | 11 | 87 | Iris Miculek '28 [1-4, 7-8] Keifer Yim '28 [5-6] Keifer Yim '28 [1-2] Sarah Brockus '29 [3-8] |
| Team | 1A | 2A | 3A | 4A | 5A | 6A | 7A | 8A | |
|---|---|---|---|---|---|---|---|---|---|
| University of Kansas Jayhawks | 5 | 5 | 6 | 6 | 7 | 7 | 8 | 8 |
| Louisiana Tech University Bulldogs | 1 | 1 | 2 | 2 | 3 | 3 | 4 | 4 |
| Rice University Owls | 2 | 2 | 3 | 3 | 4 | 4 | 5 | 5 |
| University of Texas Longhorns | 6 | 6 | 7 | 7 | 8 | 8 | 9 | 9 |
| Texas A&M University Aggies | 3 | 3 | 4 | 4 | 5 | 5 | 6 | 6 |
| Texas A&M University at Galveston Sea Aggies | 4 | 4 | 5 | 5 | 6 | 6 | 7 | 7 |
| Team | 1B | 2B | 3B | 4B | 5B | 6B | 7B | 8B | |
|---|---|---|---|---|---|---|---|---|---|
| University of Kansas Jayhawks | 11 | 11 | 12 | 12 | 1 | 1 | 2 | 2 |
| Louisiana Tech University Bulldogs | 7 | 7 | 8 | 8 | 9 | 9 | 10 | 10 |
| Rice University Owls | 8 | 8 | 9 | 9 | 10 | 10 | 11 | 11 |
| University of Texas Longhorns | 12 | 12 | 1 | 1 | 2 | 2 | 3 | 3 |
| Texas A&M University Aggies | 9 | 9 | 10 | 10 | 11 | 11 | 12 | 12 |
| Texas A&M University at Galveston Sea Aggies | 10 | 10 | 11 | 11 | 12 | 12 | 1 | 1 |
Orderliness is how tightly the finishing order followed the pre-regatta ratings, relative to a typical event (0). Positive is the favourites’ day: the ratings carried more weight than usual and the top seeds finished where expected. Negative is the underdogs’ day: the fleet compressed and the favourites came back to the pack. A value of ±0.06 means a rating gap counts about 5% more than on a typical day.
The breeze reading is the chart’s value at this regatta’s wind direction and speed (the star): this venue’s pattern of which directions bring order and which bring upsets, with breeze generally orderly and light air surprising. The fleet adjustment comes from the entry list: the stronger and more experienced the fleet, the more surprising the racing. How this is estimated · compare venues.
Short write-ups of what the ratings and results show, with the numbers and how they were computed.
