| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Tulane University | Green Wave | 9–0 |
| 2 |  |
University of Texas | Longhorns | 6–3 |
| 3 |  |
Texas A&M University at Galveston | Aggies | 3–6 |
| 4 |  |
Loyola University New Orleans | Wolfpack | 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 15,606 team race matches sailed before 2021-04-24, using the line-ups that actually raced. It called 18 of 18 matches (100%) with a log-loss of 0.038 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.38 ± 0.45: a typical event, more orderly than 83% 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 | 8.34 school −0.09 | William Keenan / Andrea Riefkohl Gonzalez 2.60 Cameron Giblin / Lydia Brown 3.48 Caelan Watts / Gillian Perrell 2.32 | 100% | 9–0 (100%) | +0.0 |
| 2 | University of Texas Longhorns | 2 | 3.92 school −0.10, home +0.36 | Ethan Froelich / John Mason Frederik Winguth / Warren Wegener 0.81 Karina Bertelsmann / Lillian Andersen 1.05 | 63% | 6–3 (67%) | +0.3 |
| 3 | Texas A&M University at Galveston Aggies | 3 | 1.79 school −0.16 | Jonathan Sager / Lorin Dollar 1.95 Brandon Foster / Gunnar Pierson Wes Sholders / Kayla Costigan 0–6 Wes Sholders / Jacob Carcasi 3–0 | 34% | 3–6 (33%) | −0.0 |
| 4 | Loyola University New Orleans Wolfpack | 4 | -0.52 school −0.32 | Matthew Mastin / Giovanna Pastrone Sydney Rockwell / Leila Avery Natalie Kulka / Phillip Lopez -0.78 | 3% | 0–9 (0%) | −0.3 |
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 | 8.34 | 11.34 | 9–0 | 9.0 | ≥+3.00 | 0.1 | 96% |
| 2 | University of Texas | 3.92 | 5.08 | 6–3 | 5.7 | +1.16 | 0.2 | 71% |
| 3 | Texas A&M University at Galveston | 1.79 | 1.71 | 3–6 | 3.0 | −0.08 | 0.0 | 82% |
| 4 | Loyola University New Orleans | -0.52 | -3.52 | 0–9 | 0.3 | ≤−3.00 | 0.4 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| William Keenan | Tulane University | 2.60 | 5.60 | 9–0 | 9.0 | ≥+3.00 | 0.1 | 96% |
| Caelan Watts | Tulane University | 2.32 | 5.32 | 9–0 | 9.0 | ≥+3.00 | 0.1 | 96% |
| Frederik Winguth | University of Texas | 0.81 | 1.97 | 6–3 | 5.7 | +1.16 | 0.2 | 71% |
| Karina Bertelsmann | University of Texas | 1.05 | 2.21 | 6–3 | 5.7 | +1.16 | 0.2 | 71% |
| Jonathan Sager | Texas A&M University at Galveston | 1.95 | 1.87 | 3–6 | 3.0 | −0.08 | 0.0 | 82% |
| Brandon Foster | Texas A&M University at Galveston | -0.43 | -0.51 | 3–6 | 3.0 | −0.08 | 0.0 | 82% |
| Wes Sholders | Texas A&M University at Galveston | 0.05 | -0.03 | 3–6 | 3.0 | −0.08 | 0.0 | 82% |
| Matthew Mastin | Loyola University New Orleans | 0.92 | -2.08 | 0–9 | 0.3 | ≤−3.00 | 0.4 | >99% |
| Sydney Rockwell | Loyola University New Orleans | -0.68 | -3.68 | 0–9 | 0.3 | ≤−3.00 | 0.4 | >99% |
| Natalie Kulka | Loyola University New Orleans | -0.78 | -3.77 | 0–9 | 0.3 | ≤−3.00 | 0.4 | >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 | Wolfpack | |
|---|---|---|---|---|---|---|
| Tulane University Green Wave | 3–0 | ✕ | W | W | W |
| University of Texas Longhorns | 2–1 | L | ✕ | W | W |
| Texas A&M University at Galveston Aggies | 1–2 | L | L | ✕ | W |
| Loyola University New Orleans Wolfpack | 0–3 | L | L | L | ✕ |
| Team | Rec. | Wave | Longhorns | Aggies | Wolfpack | |
|---|---|---|---|---|---|---|
| Tulane University Green Wave | 3–0 | ✕ | W | W | W |
| University of Texas Longhorns | 2–1 | L | ✕ | W | W |
| Texas A&M University at Galveston Aggies | 1–2 | L | L | ✕ | W |
| Loyola University New Orleans Wolfpack | 0–3 | L | L | L | ✕ |
| Team | Rec. | Wave | Longhorns | Aggies | Wolfpack | |
|---|---|---|---|---|---|---|
| Tulane University Green Wave | 3–0 | ✕ | W | W | W |
| University of Texas Longhorns | 2–1 | L | ✕ | W | W |
| Texas A&M University at Galveston Aggies | 1–2 | L | L | ✕ | W |
| Loyola University New Orleans Wolfpack | 0–3 | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Green Wave | 1-2-3 | def. | |
Wolfpack | 4-5-6 |
| 2 | |
Longhorns | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 3 | |
Green Wave | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 4 | |
Longhorns | 1-2-3 | def. | |
Wolfpack | 4-5-6 |
| 5 | |
Aggies | 1-2-5 | def. | |
Wolfpack | 3-4-6 |
| 6 | |
Green Wave | 1-2-3 | def. | |
Longhorns | 4-5-6 |
| 7 | |
Green Wave | 1-2-3 | def. | |
Wolfpack | 4-5-6 |
| 8 | |
Longhorns | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 9 | |
Green Wave | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 10 | |
Longhorns | 1-2-3 | def. | |
Wolfpack | 4-5-6 |
| 11 | |
Aggies | 1-2-5 | def. | |
Wolfpack | 3-4-6 |
| 12 | |
Green Wave | 1-2-3 | def. | |
Longhorns | 4-5-6 |
| 13 | |
Green Wave | 1-2-3 | def. | |
Wolfpack | 4-5-6 |
| 14 | |
Longhorns | 1-2-4 | def. | |
Aggies | 3-5-6 |
| 15 | |
Green Wave | 1-2-3 | def. | |
Aggies | 4-5-6 |
| 16 | |
Longhorns | 1-2-3 | def. | |
Wolfpack | 4-5-6 |
| 17 | |
Aggies | 1-2-4 | def. | |
Wolfpack | 3-5-6 |
| 18 | |
Green Wave | 1-2-5 | def. | |
Longhorns | 3-4-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Tulane University | Green Wave | Caelan Watts '21 Cameron Giblin '23 William Keenan '23 |
Gillian Perrell '24 Lydia Brown '23 Andrea Riefkohl Gonzalez '24 |
|
University of Texas | Longhorns | Ethan Froelich '24 Frederik Winguth '21 Karina Bertelsmann '22 |
John Mason '23 Warren Wegener '23 Lillian Andersen '21 |
|
Texas A&M University at Galveston | Aggies | Brandon Foster '23 Jonathan Sager '20 Wes Sholders '21 |
Gunnar Pierson '24 Lorin Dollar '22 Kayla Costigan '21 Jacob Carcasi '23 |
|
Loyola University New Orleans | Wolfpack | Matthew Mastin '22 Natalie Kulka '21 Sydney Rockwell '23 |
Giovanna Pastrone '23 Phillip Lopez '24 Leila Avery '23 |
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 ±0.08 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.
