| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
University of Texas | Longhorns | 7–2 |
| 2 |  |
Texas A&M University | Aggies | 6–3 |
| 3 |  |
Rice University | Owls | 5–4 |
| 4 |  |
Texas A&M University at Galveston | Sea Aggies | 0–9 |
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 24,953 team race matches sailed before 2025-02-01, using the line-ups that actually raced. It called 5 of 9 matches (56%) with a log-loss of 0.688 (a coin flip scores 0.693), so the event went poorly for the forecast. 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 | University of Texas Longhorns | 1 | 4.63 school −0.09, home +0.39 | Matias Martin / Oliver Fenner Reese Zebrowski / Sophia Herrada 1.77 Rohit Rajan / Dennis Kostjuhin 0.47 | 80% | 4–2 (67%) | −0.8 |
| 2 | Texas A&M University Aggies | 3 | 3.20 school −0.12 | Sydney Krahulik / Kennedy Long 0.92 Kate Hennig / Drew Gourley 1.15 Ryan Ingram / Evelyn Dubois 1.23 | 33% | 3–3 (50%) | +1.0 |
| 3 | Rice University Owls | 2 | 3.31 school −0.36 | Ricky Miller / Aidan Murphy 1.72 Joe Slipper / Leo Marek Arthur Unger / Marc Rode 0.58 | 37% | 2–4 (33%) | −0.2 |
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) |
|---|---|---|---|---|---|---|---|---|
| 2 | Texas A&M University | 3.20 | 3.98 | 3–3 | 2.0 | +0.78 | 0.6 | 31% |
| 3 | Rice University | 3.31 | 3.13 | 2–4 | 2.2 | −0.18 | 0.0 | 74% |
| 1 | University of Texas | 4.63 | 3.94 | 4–2 | 4.8 | −0.69 | 0.4 | 90% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Sydney Krahulik | Texas A&M University | 0.92 | 1.70 | 3–3 | 2.0 | +0.78 | 0.6 | 31% |
| Joe Slipper | Rice University | 1.23 | 1.05 | 2–4 | 2.2 | −0.18 | 0.0 | 74% |
| Arthur Unger | Rice University | 0.58 | 0.40 | 2–4 | 2.2 | −0.18 | 0.0 | 74% |
| Reese Zebrowski | University of Texas | 1.77 | 1.08 | 4–2 | 4.8 | −0.69 | 0.4 | 90% |
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 | 2 | University of Texas | Rice University | 81% | |
| 1 | 3 | University of Texas | Texas A&M University | 81% | |
| 1 | 6 | Texas A&M University | Rice University | 48% | upset |
| 2 | 8 | Rice University | University of Texas | 21% | upset |
| 2 | 9 | Texas A&M University | University of Texas | 19% | upset |
| 2 | 12 | Texas A&M University | Rice University | 47% | upset |
| 3 | 14 | University of Texas | Rice University | 78% | |
| 3 | 15 | University of Texas | Texas A&M University | 81% | |
| 3 | 18 | Rice University | Texas A&M University | 54% |
| Team | Rec. | Longhorns | Aggies | Owls | Aggies | |
|---|---|---|---|---|---|---|
| University of Texas Longhorns | 3–0 | ✕ | W | W | W |
| Texas A&M University Aggies | 2–1 | L | ✕ | W | W |
| Rice University Owls | 1–2 | L | L | ✕ | W |
| Texas A&M University at Galveston Sea Aggies | 0–3 | L | L | L | ✕ |
| Team | Rec. | Longhorns | Aggies | Owls | Aggies | |
|---|---|---|---|---|---|---|
| University of Texas Longhorns | 1–2 | ✕ | L | L | W |
| Texas A&M University Aggies | 3–0 | W | ✕ | W | W |
| Rice University Owls | 2–1 | W | L | ✕ | W |
| Texas A&M University at Galveston Sea Aggies | 0–3 | L | L | L | ✕ |
| Team | Rec. | Longhorns | Aggies | Owls | Aggies | |
|---|---|---|---|---|---|---|
| University of Texas Longhorns | 3–0 | ✕ | W | W | W |
| Texas A&M University Aggies | 1–2 | L | ✕ | L | W |
| Rice University Owls | 2–1 | L | W | ✕ | W |
| Texas A&M University at Galveston Sea Aggies | 0–3 | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Aggies | 1-2-5 | def. | |
Sea Aggies | 3-4-6 |
| 2 | |
Longhorns | 1-2-6 | def. | |
Owls | 3-4-5 |
| 3 | |
Longhorns | 1-4-5 | def. | |
Aggies | 2-3-6 |
| 4 | |
Owls | 1-2-5 | def. | |
Sea Aggies | 3-4-6 |
| 5 | |
Longhorns | 1-2-5 | def. | |
Sea Aggies | 3-4-6 |
| 6 | |
Aggies | 1-2-5 | def. | |
Owls | 3-4-6 |
| 7 | |
Aggies | 1-2-4 | def. | |
Sea Aggies | 3-5-6 |
| 8 | |
Owls | 1-2-4 | def. | |
Longhorns | 3-5-6 |
| 9 | |
Aggies | 1-3-4 | def. | |
Longhorns | 2-5-6 |
| 10 | |
Owls | 1-2-4 | def. | |
Sea Aggies | 3-5-6 |
| 11 | |
Longhorns | 1-2-5 | def. | |
Sea Aggies | 3-4-6 |
| 12 | |
Aggies | 1-3-4 | def. | |
Owls | 2-5-6 |
| 13 | |
Aggies | 1-2-4 | def. | |
Sea Aggies | 3-5-6 |
| 14 | |
Longhorns | 1-2-5 | def. | |
Owls | 3-4-6 |
| 15 | |
Longhorns | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 16 | |
Owls | 1-2-3 | def. | |
Sea Aggies | 4-5-6 |
| 17 | |
Longhorns | 1-2-4 | def. | |
Sea Aggies | 3-5-6 |
| 18 | |
Owls | 1-2-3 | def. | |
Aggies | 4-5-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
University of Texas | Longhorns | Matias Martin '27 Reese Zebrowski '26 Rohit Rajan '26 |
Oliver Fenner '26 Sophia Herrada '24 Dennis Kostjuhin '27 |
|
Texas A&M University | Aggies | Kate Hennig '26 Ryan Ingram '25 Sydney Krahulik '27 |
Drew Gourley '27 Evelyn Dubois '27 Kennedy Long '26 |
|
Rice University | Owls | Arthur Unger '25 Joe Slipper '28 Ricky Miller '26 |
Marc Rode '28 Leo Marek '26 Aidan Murphy '25 |
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 ±0.07 means a rating gap counts about 6% 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.
