| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Texas A&M University at Galveston | Aggies | 6–0 |
| 2 |  |
Tulane University | Green Wave | 4–2 |
| 3 |  |
University of Texas | Longhorns | 1–5 |
| 4 |  |
Texas A&M University | Aggies | 1–5 |
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 11,468 team race matches sailed before 2018-04-08, using the line-ups that actually raced. It called 15 of 19 matches (79%) with a log-loss of 0.326 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness −0.04 ± 0.49: a typical event, more orderly than 38% 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 | Texas A&M University at Galveston Aggies | 1 | 7.03 school −0.30, home +0.43 | John Hanna / John Jacobs 2.94 Jonathan Sager / Ava Cares 1.55 Alex Schwinn / Lyndsey Sager 2.22 | 93% | 9–1 (90%) | −0.3 |
| 2 | Tulane University Green Wave | 2 | 4.97 | Harris Cram / Katherine Robinson James Mcavoy / Sophia Ricker 1.89 Caelan Watts / Grace Bloomfield | 46% | 5–5 (50%) | +0.4 |
| 3 | University of Texas Longhorns | 4 | 0.34 school −0.18 | Aaron Comen / Jordin Perry -0.13 Emily Verdoia / Arosh Chaudhari 0.54 Michael Hernandez / Gabriella Wong | 28% | 4–5 (44%) | +1.5 |
| 4 | Texas A&M University Aggies | 3 | 0.38 school −0.10 | Christopher Suarez / Shelby Click 0.44 Trenton Seely / Gabby Spring Alexandra Oyston / Charlie Hickman | 28% | 1–8 (11%) | −1.6 |
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) |
|---|---|---|---|---|---|---|---|---|
| 3 | University of Texas | 0.34 | 1.67 | 4–5 | 2.5 | +1.32 | 1.4 | 18% |
| 2 | Tulane University | 4.97 | 5.45 | 5–5 | 4.6 | +0.47 | 0.1 | 50% |
| 1 | Texas A&M University at Galveston | 7.03 | 6.60 | 9–1 | 9.3 | −0.43 | 0.1 | 86% |
| 4 | Texas A&M University | 0.38 | -1.05 | 1–8 | 2.6 | −1.43 | 1.5 | 97% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Aaron Comen | University of Texas | -0.13 | 1.20 | 4–5 | 2.5 | +1.32 | 1.4 | 18% |
| Emily Verdoia | University of Texas | 0.54 | 1.87 | 4–5 | 2.5 | +1.32 | 1.4 | 18% |
| Michael Hernandez | University of Texas | -0.07 | 1.26 | 4–5 | 2.5 | +1.32 | 1.4 | 18% |
| Harris Cram | Tulane University | 1.29 | 1.77 | 5–5 | 4.6 | +0.47 | 0.1 | 50% |
| James Mcavoy | Tulane University | 1.89 | 2.36 | 5–5 | 4.6 | +0.47 | 0.1 | 50% |
| Caelan Watts | Tulane University | 1.38 | 1.85 | 5–5 | 4.6 | +0.47 | 0.1 | 50% |
| John Hanna | Texas A&M University at Galveston | 2.94 | 2.50 | 9–1 | 9.3 | −0.43 | 0.1 | 86% |
| Jonathan Sager | Texas A&M University at Galveston | 1.55 | 1.11 | 9–1 | 9.3 | −0.43 | 0.1 | 86% |
| Alex Schwinn | Texas A&M University at Galveston | 2.22 | 1.79 | 9–1 | 9.3 | −0.43 | 0.1 | 86% |
| Trenton Seely | Texas A&M University | -0.60 | -2.03 | 1–8 | 2.6 | −1.43 | 1.5 | 97% |
| Alexandra Oyston | Texas A&M University | 0.18 | -1.25 | 1–8 | 2.6 | −1.43 | 1.5 | 97% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Aggies | Wave | Longhorns | Aggies | |
|---|---|---|---|---|---|---|
| Texas A&M University at Galveston Aggies | 3–0 | ✕ | W | W | W |
| Tulane University Green Wave | 2–1 | L | ✕ | W | W |
| University of Texas Longhorns | 1–2 | L | L | ✕ | W |
| Texas A&M University Aggies | 0–3 | L | L | L | ✕ |
| Team | Rec. | Aggies | Wave | Longhorns | Aggies | |
|---|---|---|---|---|---|---|
| Texas A&M University at Galveston Aggies | 3–0 | ✕ | W | W | W |
| Tulane University Green Wave | 2–1 | L | ✕ | W | W |
| University of Texas Longhorns | 0–3 | L | L | ✕ | L |
| Texas A&M University Aggies | 1–2 | L | L | W | ✕ |
| Team | Rec. | Aggies | Wave | Longhorns | Aggies | |
|---|---|---|---|---|---|---|
| Texas A&M University at Galveston Aggies | 2–1 | ✕ | W | – | – |
| Tulane University Green Wave | 1–2 | L | ✕ | – | – |
| University of Texas Longhorns | 3–0 | – | – | ✕ | W |
| Texas A&M University Aggies | 0–3 | – | – | L | ✕ |
| Team | Rec. | Aggies | Wave | |
|---|---|---|---|---|
| Texas A&M University at Galveston Aggies | 1–0 | ✕ | W |
| Tulane University Green Wave | 0–1 | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Aggies | 1-2-6 | def. | |
Green Wave | 3-4-5 |
| 2 | |
Longhorns | 1-2-6 | def. | |
Aggies | 3-4-5 |
| 3 | |
Aggies | 1-2-3 | def. | |
Longhorns | 4-5-6 |
| 4 | |
Green Wave | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 5 | |
Green Wave | 1-2-3 | def. | |
Longhorns | 4-5-6 |
| 6 | |
Aggies | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 14 | |
Aggies | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 15 | |
Green Wave | 1-2-4 | def. | |
Longhorns | 3-5-6 |
| 16 | |
Green Wave | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 17 | |
Aggies | 1-2-3 | def. | |
Longhorns | 4-5-6 |
| 18 | |
Aggies | 1-2-3 | def. | |
Green Wave | 4-5-6 |
| 19 | |
Aggies | 1-2-6 | def. | |
Longhorns | 3-4-5 |
| 7 | |
Longhorns | 1-3-4 | def. | |
Aggies | 2-5-6 |
| 8 | |
Longhorns | 1-2-5 | def. | |
Aggies | 3-4-6 |
| 9 | |
Longhorns | 1-3-5 | def. | |
Aggies | 2-4-6 |
| 11 | |
Green Wave | 1-3-4 | def. | |
Aggies | 2-5-6 |
| 12 | |
Aggies | 1-2-3 | def. | |
Green Wave | 4-5-6 |
| 13 | |
Aggies | 1-2-4 | def. | |
Green Wave | 3-5-6 |
| 10 | |
Aggies | 1-2-6 | def. | |
Green Wave | 3-4-5 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Texas A&M University at Galveston | Aggies | Alex Schwinn '19 John Hanna '19 Jonathan Sager '20 |
Lyndsey Sager '21 John Jacobs '19 Ava Cares '20 |
|
Tulane University | Green Wave | Caelan Watts '21 Harris Cram '19 James Mcavoy '20 |
Grace Bloomfield '19 Katherine Robinson '19 Sophia Ricker '19 |
|
University of Texas | Longhorns | Aaron Comen '18 Emily Verdoia '20 Michael Hernandez '20 |
Jordin Perry '20 Arosh Chaudhari '20 Gabriella Wong '20 |
|
Texas A&M University | Aggies | Alexandra Oyston '18 Christopher Suarez '18 Trenton Seely '18 |
Charlie Hickman '21 Shelby Click '18 Gabby Spring '20 |
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 ±0.09 means a rating gap counts about 7% 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.
