| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Tulane University | Green Wave | 8–0 |
| 2 |  |
Texas A&M University | Aggies | 5–3 |
| 3 |  |
Texas A&M University at Galveston | Aggies | 5–3 |
| 4 |  |
University of Texas | Longhorns | 2–6 |
| 5 |  |
Texas A&M University at Corpus Christi | Islanders | 0–8 |
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 23,921 team race matches sailed before 2024-04-06, using the line-ups that actually raced. It called 18 of 20 matches (90%) with a log-loss of 0.207 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.30 ± 0.46: a typical event, more orderly than 77% 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 | 8.94 school +0.08 | Hamilton Barclay / Claire Lewis 3.28 Jack Solmo / Caroline Caudron 2.50 Kelly Holthus / Parker Kumler 2.98 | 100% | 8–0 (100%) | +0.0 |
| 2 | Texas A&M University Aggies | 2 | 4.17 school −0.26 | Michael Morse / Sydney Krahulik 2.10 Cole Broberg / Colton Redding 0.84 Hanna Progelhof / Kate Hennig 1.43 | 62% | 5–3 (62%) | +0.1 |
| 3 | Texas A&M University at Galveston Aggies | 3 | 3.12 school −0.31 | William Tebrake / Jack Meyer Jacob Granberry / Brett Pearson 0.99 Ethan Polsen / Isabella Mattison 0.60 | 42% | 5–3 (62%) | +1.6 |
| 4 | University of Texas Longhorns | 4 | 3.13 home +0.42 | Reese Zebrowski / Sean Padilla 1.55 Oliver Fenner / Sophia Herrada 0.73 Rohit Rajan / Dennis Kostjuhin 0.37 | 42% | 2–6 (25%) | −1.3 |
| 5 | Texas A&M University at Corpus Christi Islanders | 5 | 0.80 school +0.19 | Nicholas Carew / Hailey Howerton 0.96 Maddy Lee / Celesta Stinson 0.08 Noah Aycock / Robin Loessin | 5% | 0–8 (0%) | −0.4 |
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 | 8.94 | 11.94 | 8–0 | 8.0 | ≥+3.00 | 0.0 | 97% |
| 3 | Texas A&M University at Galveston | 3.12 | 4.81 | 5–3 | 3.4 | +1.69 | 1.9 | 13% |
| 2 | Texas A&M University | 4.17 | 4.27 | 5–3 | 4.9 | +0.10 | 0.0 | 70% |
| 4 | University of Texas | 3.13 | 1.75 | 2–6 | 3.3 | −1.37 | 1.3 | 97% |
| 5 | Texas A&M University at Corpus Christi | 0.80 | -2.20 | 0–8 | 0.4 | ≤−3.00 | 0.6 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Jack Solmo | Tulane University | 2.50 | 5.50 | 8–0 | 8.0 | ≥+3.00 | 0.0 | 97% |
| Jacob Granberry | Texas A&M University at Galveston | 0.99 | 2.68 | 5–3 | 3.4 | +1.69 | 1.9 | 13% |
| Cole Broberg | Texas A&M University | 0.84 | 0.94 | 5–3 | 4.9 | +0.10 | 0.0 | 70% |
| Hanna Progelhof | Texas A&M University | 1.43 | 1.53 | 5–3 | 4.9 | +0.10 | 0.0 | 70% |
| Reese Zebrowski | University of Texas | 1.55 | 0.18 | 2–6 | 3.3 | −1.37 | 1.3 | 97% |
| Oliver Fenner | University of Texas | 0.73 | -0.65 | 2–6 | 3.3 | −1.37 | 1.3 | 97% |
| Maddy Lee | Texas A&M University at Corpus Christi | 0.08 | -2.92 | 0–8 | 0.4 | ≤−3.00 | 0.6 | >99% |
| Noah Aycock | Texas A&M University at Corpus Christi | -0.62 | -3.62 | 0–8 | 0.4 | ≤−3.00 | 0.6 | >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 | Aggies | Aggies | Longhorns | Islanders | |
|---|---|---|---|---|---|---|---|
| Tulane University Green Wave | 4–0 | ✕ | W | W | W | W |
| Texas A&M University Aggies | 2–2 | L | ✕ | L | W | W |
| Texas A&M University at Galveston Aggies | 3–1 | L | W | ✕ | W | W |
| University of Texas Longhorns | 1–3 | L | L | L | ✕ | W |
| Texas A&M University at Corpus Christi Islanders | 0–4 | L | L | L | L | ✕ |
| Team | Rec. | Wave | Aggies | Aggies | Longhorns | Islanders | |
|---|---|---|---|---|---|---|---|
| Tulane University Green Wave | 4–0 | ✕ | W | W | W | W |
| Texas A&M University Aggies | 3–1 | L | ✕ | W | W | W |
| Texas A&M University at Galveston Aggies | 2–2 | L | L | ✕ | W | W |
| University of Texas Longhorns | 1–3 | L | L | L | ✕ | W |
| Texas A&M University at Corpus Christi Islanders | 0–4 | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Aggies | 1-2-3 | def. | |
Islanders | 4-5-6 |
| 2 | |
Green Wave | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 3 | |
Longhorns | 1-2-4 | def. | |
Islanders | 3-5-6 |
| 4 | |
Aggies | 3-4-6 | def. | |
Aggies | 1-2-5 DSQ |
| 5 | |
Green Wave | 1-2-3 | def. | |
Longhorns | 4-5-6 |
| 6 | |
Aggies | 1-2-5 | def. | |
Islanders | 3-4-6 |
| 7 | |
Aggies | 1-2-4 | def. | |
Longhorns | 3-5-6 |
| 8 | |
Green Wave | 1-2-3 | def. | |
Islanders | 4-5-6 |
| 9 | |
Aggies | 1-2-4 | def. | |
Longhorns | 3-5-6 |
| 10 | |
Green Wave | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 11 | |
Aggies | 1-2-4 | def. | |
Islanders | 3-5-6 |
| 12 | |
Green Wave | 1-2-4 | def. | |
Aggies | 3-5-6 |
| 13 | |
Longhorns | 1-3-5 | def. | |
Islanders | 2-4-6 |
| 14 | |
Aggies | 2-3-4 | def. | |
Aggies | 1-5-6 |
| 15 | |
Green Wave | 1-2-3 | def. | |
Longhorns | 4-5-6 |
| 16 | |
Aggies | 1-2-4 | def. | |
Islanders | 3-5-6 |
| 17 | |
Aggies | 1-2-6 | def. | |
Longhorns | 3-4-5 |
| 18 | |
Green Wave | 1-2-3 | def. | |
Islanders | 4-5-6 |
| 19 | |
Aggies | 1-2-3 | def. | |
Longhorns | 4-5-6 |
| 20 | |
Green Wave | 1-2-3 | def. | |
Aggies | 4-5-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Tulane University | Green Wave | Hamilton Barclay '27 Jack Solmo '25 Kelly Holthus '27 |
Claire Lewis '27 Caroline Caudron '27 Parker Kumler '27 |
|
Texas A&M University | Aggies | Cole Broberg '25 Hanna Progelhof '25 Michael Morse '25 |
Colton Redding '23 Kate Hennig '26 Sydney Krahulik '27 |
|
Texas A&M University at Galveston | Aggies | Ethan Polsen '27 Jacob Granberry '26 William Tebrake '27 |
Isabella Mattison '25 Brett Pearson '26 Jack Meyer '27 |
|
University of Texas | Longhorns | Oliver Fenner '26 Reese Zebrowski '26 Rohit Rajan '26 |
Sophia Herrada '24 Sean Padilla '27 Dennis Kostjuhin '27 |
|
Texas A&M University at Corpus Christi | Islanders | Maddy Lee '27 Nicholas Carew '27 Noah Aycock '25 |
Celesta Stinson '24 Hailey Howerton '24 Robin Loessin '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 ±0.07 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.
