| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Tulane University | Green Wave | 4–0 |
| 2 |  |
University of Texas | Longhorns | 3–1 |
| 3 |  |
Texas A&M University | Aggies | 2–2 |
| 4 |  |
Texas A&M University at Galveston | Sea Aggies | 1–3 |
| 5 |  |
Texas A&M University at Corpus Christi | Islanders | 0–4 |
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 27,096 team race matches sailed before 2025-04-05, using the line-ups that actually raced. It called 9 of 10 matches (90%) with a log-loss of 0.122 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.47 ± 0.68: a typical event, more orderly than 92% of college team race events (temperature of the forecast log-odds that best fits the results, relative to the league average; nothing about the field, venue or wind predicts it, see the Weather tab). 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 | Tulane University Green Wave | 1 | 10.97 school −0.06, home +0.35 | Hamilton Barclay / Matheo Graham-Capasso 3.61 Christian Ebbin / Ryan Ehnot 3.61 Kelly Holthus / Sloane Mullin 3.45 | 100% | 4–0 (100%) | +0.0 |
| 2 | University of Texas Longhorns | 2 | 4.28 school −0.18 | Matias Martin / Oliver Fenner 2.11 Reese Zebrowski / Rohit Rajan 1.83 Lucas Tenrreiro / Dennis Kostjuhin | 69% | 3–1 (75%) | +0.2 |
| 3 | Texas A&M University Aggies | 3 | 2.89 | Kate Hennig / Sydney Krahulik 1.21 Zachary Aronson / Menya Bird 0.39 Ryan Ingram / Drew Gourley 1.27 | 50% | 2–2 (50%) | +0.0 |
| 4 | Texas A&M University at Galveston Sea Aggies | 5 | 0.76 school −0.15 | Ethan Polsen / Stetson Mcdonald 0.81 Jack Meyer / Evelyn Chase -0.09 Macie Bettis / Isabella Mattison | 16% | 1–3 (25%) | +0.4 |
| 5 | Texas A&M University at Corpus Christi Islanders | 4 | 0.77 school +0.10 | Nicholas Carew / Mandy Gergen 0.77 Maddy Lee / Destini Sanchez-Warren 0.45 Noah Aycock / Jordan Wilcox | 16% | 0–4 (0%) | −0.7 |
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) |
|---|---|---|---|---|---|---|---|---|
| 1 | Tulane University | 10.97 | 13.97 | 4–0 | 4.0 | ≥+3.00 | 0.0 | >99% |
| 2 | University of Texas | 4.28 | 7.01 | 3–1 | 2.7 | +2.73 | 0.3 | 76% |
| 4 | Texas A&M University at Galveston | 0.76 | 1.68 | 1–3 | 0.6 | +0.92 | 0.3 | 56% |
| 3 | Texas A&M University | 2.89 | 2.95 | 2–2 | 2.0 | +0.06 | 0.0 | 83% |
| 5 | Texas A&M University at Corpus Christi | 0.77 | -2.23 | 0–4 | 0.7 | ≤−3.00 | 1.2 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Reese Zebrowski | University of Texas | 1.83 | 4.56 | 3–1 | 2.7 | +2.73 | 0.3 | 76% |
| Jack Meyer | Texas A&M University at Galveston | -0.09 | 0.83 | 1–3 | 0.6 | +0.92 | 0.3 | 56% |
| Macie Bettis | Texas A&M University at Galveston | 0.05 | 0.97 | 1–3 | 0.6 | +0.92 | 0.3 | 56% |
| Maddy Lee | Texas A&M University at Corpus Christi | 0.45 | -2.55 | 0–4 | 0.7 | ≤−3.00 | 1.2 | >99% |
| Noah Aycock | Texas A&M University at Corpus Christi | -0.72 | -3.72 | 0–4 | 0.7 | ≤−3.00 | 1.2 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Wave | Longhorns | Aggies | Aggies | Islanders | |
|---|---|---|---|---|---|---|---|
| Tulane University Green Wave | 4–0 | ✕ | W | W | W | W |
| University of Texas Longhorns | 3–1 | L | ✕ | W | W | W |
| Texas A&M University Aggies | 2–2 | L | L | ✕ | W | W |
| Texas A&M University at Galveston Sea Aggies | 1–3 | L | L | L | ✕ | W |
| Texas A&M University at Corpus Christi Islanders | 0–4 | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Green Wave | 1-2-3 | def. | |
Islanders | 4-5-6 |
| 2 | |
Longhorns | 1-2-4 | def. | |
Sea Aggies | 3-5-6 |
| 3 | |
Green Wave | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 4 | |
Longhorns | 1-3-4 | def. | |
Islanders | 2-5-6 |
| 5 | |
Aggies | 1-3-5 | def. | |
Sea Aggies | 2-4-6 |
| 6 | |
Green Wave | 1-2-3 | def. | |
Longhorns | 4-5-6 |
| 7 | |
Aggies | 1-2-3 | def. | |
Islanders | 4-5-6 |
| 8 | |
Green Wave | 1-2-3 | def. | |
Sea Aggies | 4-5-6 |
| 9 | |
Longhorns | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 10 | |
Sea Aggies | 1-2-5 | def. | |
Islanders | 3-4-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Tulane University | Green Wave | Christian Ebbin '28 Hamilton Barclay '27 Kelly Holthus '27 |
Ryan Ehnot '26 Matheo Graham-Capasso '26 Sloane Mullin '27 |
|
University of Texas | Longhorns | Lucas Tenrreiro '27 Matias Martin '27 Reese Zebrowski '26 |
Dennis Kostjuhin '27 Oliver Fenner '26 Rohit Rajan '26 |
|
Texas A&M University | Aggies | Kate Hennig '26 Ryan Ingram '25 Zachary Aronson '27 |
Sydney Krahulik '27 Drew Gourley '27 Menya Bird '26 |
|
Texas A&M University at Galveston | Sea Aggies | Ethan Polsen '27 Jack Meyer '27 Macie Bettis '28 |
Stetson Mcdonald '28 Evelyn Chase '28 Isabella Mattison '25 |
|
Texas A&M University at Corpus Christi | Islanders | Maddy Lee '27 Nicholas Carew '27 Noah Aycock '26 |
Destini Sanchez-Warren '27 Mandy Gergen '28 Jordan Wilcox '26 |
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 1% 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.
