| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
California Maritime Academy | Keelhaulers | 4–0 |
| 2 |  |
University of California at Los Angeles | Bruins | 2–2 |
| 2 |  |
University of Southern California | Trojans | 2–2 |
| 4 |  |
Cal Poly University S.L.O. | Mustangs | 2–2 |
| 5 |  |
University of California at Santa Cruz | Banana Slugs | 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 21,802 team race matches sailed before 2024-02-03, using the line-ups that actually raced. It called 8 of 10 matches (80%) with a log-loss of 0.413 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.64 ± 0.68: a typical event, more orderly than 98% 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.
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 | California Maritime Academy | 6.49 | 9.49 | 4–0 | 3.4 | ≥+3.00 | 0.8 | 55% |
| 4 | Cal Poly University S.L.O. | 4.44 | 5.05 | 2–2 | 1.5 | +0.61 | 0.2 | 48% |
| 2 | University of California at Los Angeles | 4.62 | 5.04 | 2–2 | 1.7 | +0.42 | 0.1 | 56% |
| 2 | University of Southern California | 5.23 | 4.87 | 2–2 | 2.3 | −0.36 | 0.1 | 82% |
| 5 | University of California at Santa Cruz | 4.17 | 1.17 | 0–4 | 1.1 | ≤−3.00 | 1.9 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Ryan Downey | California Maritime Academy | 1.83 | 4.83 | 4–0 | 3.4 | ≥+3.00 | 0.8 | 55% |
| Samuel Groom | Cal Poly University S.L.O. | 0.93 | 1.54 | 2–2 | 1.5 | +0.61 | 0.2 | 48% |
| Luke Harris | University of Southern California | 2.12 | 1.76 | 2–2 | 2.3 | −0.36 | 0.1 | 82% |
| Blake Roberts | University of California at Santa Cruz | 1.35 | -1.65 | 0–4 | 1.1 | ≤−3.00 | 1.9 | >99% |
| Andrew Ring | University of California at Santa Cruz | 1.37 | -1.63 | 0–4 | 1.1 | ≤−3.00 | 1.9 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Keelhaulers | Bruins | Trojans | Mustangs | Slugs | |
|---|---|---|---|---|---|---|---|
| California Maritime Academy Keelhaulers | 4–0 | ✕ | W | W | W | W |
| University of California at Los Angeles Bruins | 2–2 | L | ✕ | W | L | W |
| University of Southern California Trojans | 2–2 | L | L | ✕ | W | W |
| Cal Poly University S.L.O. Mustangs | 2–2 | L | W | L | ✕ | W |
| University of California at Santa Cruz Banana Slugs | 0–4 | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Keelhaulers | 1-2-6 | def. | |
Bruins | 3-4-5 |
| 2 | |
Trojans | 1-2-4 | def. | |
Mustangs | 3-5-6 |
| 3 | |
Keelhaulers | 1-3-4 | def. | |
Banana Slugs | 2-5-6 |
| 4 | |
Bruins | 1-2-5 | def. | |
Trojans | 3-4-6 |
| 5 | |
Mustangs | 1-4-5 | def. | |
Banana Slugs | 2-3-6 |
| 6 | |
Keelhaulers | 1-2-6 | def. | |
Trojans | 3-4-5 |
| 7 | |
Mustangs | 1-3-5 | def. | |
Bruins | 2-4-6 |
| 8 | |
Trojans | 1-2-6 | def. | |
Banana Slugs | 3-4-5 |
| 9 | |
Keelhaulers | 1-2-4 | def. | |
Mustangs | 3-5-6 |
| 10 | |
Bruins | 1-2-6 | def. | |
Banana Slugs | 3-4-5 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
California Maritime Academy | Keelhaulers | Clay Myers '25 Nicholas Mueller '27 Ryan Downey '25 |
Etienne Quille '25 Logan Chapman '26 Sam Jennings '27 |
|
University of California at Los Angeles | Bruins | Brendan Connelly '27 Daren Sathasivam '25 Ian Wells '24 |
Teresa Dang '24 Aki Schuessler-Langeheine '24 Conrad Kistler '26 Katinka Lennemann '26 Aidan Araoz '25 |
|
University of Southern California | Trojans | Hudson Mayfield '27 Jack Blackman '24 Luke Harris '27 |
Anthony Torrez '25 Genaro Flores - Machorro '25 Ava Bergan '27 |
|
Cal Poly University S.L.O. | Mustangs | Max Case '24 Robert Bloomfield '26 Samuel Groom '24 |
Mira Shupe '26 Annika Burns '27 Claire Wiley '27 |
|
University of California at Santa Cruz | Banana Slugs | Andrew Ring '25 Blake Roberts '25 Colin Olson '26 |
Carter Anderson '27 Asha Myers '26 Maggie Mceachen '27 |
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 ±0.12 means a rating gap counts about 10% 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.
