| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Texas A&M University at Galveston | Aggies | 9–0 |
| 2 |  |
Tulane University | Green Wave | 5–4 |
| 3 |  |
Texas A&M University | Aggies | 4–5 |
| 4 |  |
University of Texas | Longhorns | 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 8,652 team race matches sailed before 2017-04-08, using the line-ups that actually raced. It called 17 of 18 matches (94%) with a log-loss of 0.137 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.34 ± 0.44: a typical event, more orderly than 79% 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 | 7.71 school −0.20, home +0.37 | John Hanna / Megan Ferguson 3.36 Alex Schwinn / Amanda Olson 2.06 Alexander Thompson / Aspen Spiker 1.88 | 99% | 9–0 (100%) | +0.1 |
| 2 | Tulane University Green Wave | 2 | 3.68 school −0.07 | James Mcavoy / Stephen Hahn Miia Newman / Malcolm Kriegel David Graf / Sophia Ricker | 54% | 5–4 (56%) | +0.2 |
| 3 | Texas A&M University Aggies | 3 | 3.08 school −0.14 | Benjamin Lipari / Meiling Chan Chow 1.14 Julian Martin / Morgan Frakes Walter Pospick / Catherine Bristow | 42% | 4–5 (44%) | +0.2 |
| 4 | University of Texas Longhorns | 4 | 0.82 school −0.07 | Aaron Comen / Carter Young Alexander Judd / Arosh Chaudhari 1.06 Emily Verdoia / Michael Hernandez | 5% | 0–9 (0%) | −0.5 |
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 | Texas A&M University at Galveston | 7.71 | 10.71 | 9–0 | 8.9 | ≥+3.00 | 0.1 | 92% |
| 2 | Tulane University | 3.68 | 3.88 | 5–4 | 4.8 | +0.20 | 0.0 | 66% |
| 3 | Texas A&M University | 3.08 | 3.27 | 4–5 | 3.8 | +0.19 | 0.0 | 62% |
| 4 | University of Texas | 0.82 | -2.18 | 0–9 | 0.4 | ≤−3.00 | 0.6 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| John Hanna | Texas A&M University at Galveston | 3.36 | 6.36 | 9–0 | 8.9 | ≥+3.00 | 0.1 | 92% |
| Alex Schwinn | Texas A&M University at Galveston | 2.06 | 5.06 | 9–0 | 8.9 | ≥+3.00 | 0.1 | 92% |
| Alexander Thompson | Texas A&M University at Galveston | 1.88 | 4.88 | 9–0 | 8.9 | ≥+3.00 | 0.1 | 92% |
| James Mcavoy | Tulane University | 1.56 | 1.76 | 5–4 | 4.8 | +0.20 | 0.0 | 66% |
| Miia Newman | Tulane University | 0.97 | 1.17 | 5–4 | 4.8 | +0.20 | 0.0 | 66% |
| David Graf | Tulane University | 0.70 | 0.91 | 5–4 | 4.8 | +0.20 | 0.0 | 66% |
| Benjamin Lipari | Texas A&M University | 1.14 | 1.34 | 4–5 | 3.8 | +0.19 | 0.0 | 62% |
| Walter Pospick | Texas A&M University | -0.09 | 0.11 | 4–5 | 3.8 | +0.19 | 0.0 | 62% |
| Aaron Comen | University of Texas | -0.68 | -3.68 | 0–9 | 0.4 | ≤−3.00 | 0.6 | >99% |
| Alexander Judd | University of Texas | 1.06 | -1.94 | 0–9 | 0.4 | ≤−3.00 | 0.6 | >99% |
| Emily Verdoia | University of Texas | 0.00 | -3.00 | 0–9 | 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. | Aggies | Wave | Aggies | Longhorns | |
|---|---|---|---|---|---|---|
| Texas A&M University at Galveston Aggies | 3–0 | ✕ | W | W | W |
| Tulane University Green Wave | 2–1 | L | ✕ | W | W |
| Texas A&M University Aggies | 1–2 | L | L | ✕ | W |
| University of Texas Longhorns | 0–3 | L | L | L | ✕ |
| Team | Rec. | Aggies | Wave | Aggies | Longhorns | |
|---|---|---|---|---|---|---|
| Texas A&M University at Galveston Aggies | 3–0 | ✕ | W | W | W |
| Tulane University Green Wave | 1–2 | L | ✕ | L | W |
| Texas A&M University Aggies | 2–1 | L | W | ✕ | W |
| University of Texas Longhorns | 0–3 | L | L | L | ✕ |
| Team | Rec. | Aggies | Wave | Aggies | Longhorns | |
|---|---|---|---|---|---|---|
| Texas A&M University at Galveston Aggies | 3–0 | ✕ | W | W | W |
| Tulane University Green Wave | 2–1 | L | ✕ | W | W |
| Texas A&M University Aggies | 1–2 | L | L | ✕ | W |
| University of Texas Longhorns | 0–3 | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Aggies | 1-2-4 | def. | |
Green Wave | 3-5-6 |
| 2 | |
Aggies | 1-2-3 | def. | |
Longhorns | 4-5-6 |
| 3 | |
Aggies | 1-2-3 | def. | |
Longhorns | 4-5-6 |
| 4 | |
Green Wave | 1-2-5 | def. | |
Aggies | 3-4-6 |
| 5 | |
Green Wave | 1-3-4 | def. | |
Longhorns | 2-5-6 |
| 6 | |
Aggies | 1-2-4 | def. | |
Aggies | 3-5-6 |
| 7 | |
Green Wave | 1-3-4 | def. | |
Longhorns | 2-5-6 |
| 8 | |
Aggies | 1-2-4 | def. | |
Aggies | 3-5-6 |
| 9 | |
Aggies | 1-3-6 | def. | |
Green Wave | 2-4-5 |
| 10 | |
Aggies | 1-2-3 | def. | |
Longhorns | 4-5-6 |
| 11 | |
Aggies | 1-2-3 | def. | |
Longhorns | 4-5-6 |
| 12 | |
Aggies | 1-2-3 | def. | |
Green Wave | 4-5-6 |
| 13 | |
Aggies | 1-3-4 | def. | |
Longhorns | 2-5-6 |
| 14 | |
Aggies | 1-2-4 | def. | |
Green Wave | 3-5-6 |
| 15 | |
Aggies | 1-2-3 | def. | |
Longhorns | 4-5-6 |
| 16 | |
Green Wave | 1-2-6 | def. | |
Aggies | 3-4-5 |
| 17 | |
Aggies | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 18 | |
Green Wave | 1-2-4 | def. | |
Longhorns | 3-5-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Texas A&M University at Galveston | Aggies | Alex Schwinn '19 Alexander Thompson '18 John Hanna '19 |
Amanda Olson '19 Aspen Spiker '19 Megan Ferguson '17 |
|
Tulane University | Green Wave | David Graf '19 James Mcavoy '20 Miia Newman '17 |
Sophia Ricker '19 Stephen Hahn '20 Malcolm Kriegel '18 |
|
Texas A&M University | Aggies | Benjamin Lipari '18 Julian Martin '20 Walter Pospick '17 |
Meiling Chan Chow '20 Morgan Frakes '17 Catherine Bristow '17 |
|
University of Texas | Longhorns | Aaron Comen '18 Alexander Judd '16 Emily Verdoia '20 |
Carter Young '20 Arosh Chaudhari '20 Michael Hernandez '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 ±0.22 means a rating gap counts about 19% 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.
