Methodology
FleetEdge combines certificate data, race results, and environmental context into a consistent performance-archetype framework.
FleetEdge's Multi-dimensional Performance Archetype Engine combines three independent data authorities into a single analytical framework. The preceding pages — Hull Efficiency, Rating & Classification, The Physics — each describe one layer of input. This page shows what happens when they converge.
Ocean and atmosphere, sampled at the race.
ERA5 Atmosphere ERA5 is the ECMWF global atmospheric reanalysis — wind, wave, pressure, and boundary-layer state on a common hourly grid, retrospectively computed against the full observation network. FleetEdge samples ERA5 at race-leg centroids and venue bounding boxes, timed to each race's actual window, and associates the atmospheric state per boat via race participation. Atmospheric enrichment is corpus-wide: every scored race carries ERA5-derived dimensions, and weather-dependent features fold into the archetype engine uniformly.
HYCOM Ocean HYCOM GLBy 93.0 is the Hybrid Coordinate Ocean Model global reanalysis at 1/12° horizontal resolution — surface currents, temperature, and sea-surface height retrospectively computed against the global ocean-observation network. FleetEdge samples HYCOM at the same race-leg centroids and venue bounding boxes as ERA5, extracting surface-current magnitude and direction timed to each boat's actual race geometry rather than to a generic venue average.
Coverage posture. ERA5 atmospheric enrichment covers the scored race set. HYCOM ocean-current enrichment focuses on the five IRC offshore classics where tidal flow is a first-order variable rather than a rounding error — Cowes, Fastnet, Rolex Middle Sea, Sydney–Hobart, and RORC Caribbean 600. Both layers fold into the unified environmental input to the archetype framework, and current-derived context is labeled where it is used. See Ocean Intelligence for the race-by-race current treatment.
The signals that describe performance.
Each boat in the fleet is described by a set of features drawn from the three data authorities — the kinds of parameters naval architects, rating engineers, and physicists use to characterise a sailing yacht's performance envelope. FleetEdge groups them into five families.
| Family | What it captures | Source Authority |
|---|---|---|
| Hull efficiency | Length, displacement, wetted-surface, and form indicators from rating certificates. | ORC Certificate |
| Stability | Righting-moment and angle-of-vanishing-stability indicators from rating certificates. | ORC Certificate |
| Rig performance | Sail-area and rig-proportion indicators. | ORC Certificate |
| Rating position | Corrected-time and rating-band context. | ORC Scoring |
| Physics delta | FleetEdge/SailEdge comparative performance indicators. | SailEdge vs ORC baseline |
Finding the axes that matter.
The raw signals overlap. Hull length tracks displacement; rig height tracks sail area. FleetEdge reduces the measured signals into a smaller, cleaner set of design axes — the dimensions along which boats genuinely differ from one another, stripped of correlation and noise.
Five design axes capture most of how boats differ: hull form (overall size and power), hull efficiency (how cleanly the hull moves through the water), heel sensitivity (how much realized speed depends on holding a narrow heel angle), directional bias (whether a boat is stronger upwind or downwind — its regime affinity), and platform stability (how much righting moment the boat carries relative to its displacement).
These design axes are the reduced result — distinct from the measured feature families above, which are the raw inputs before reduction. Together the axes place every boat at a specific point in a shared design space, and the eleven archetypes are the natural groupings that emerge within it.
Many signals → five stable design axes
Eleven natural groupings.
The five design axes define a space in which every boat occupies a specific position. Boats that share structural strategies group together in this space. The question is where to draw the boundaries.
FleetEdge uses multiple independent clustering checks and accepts only stable groupings — those that persist regardless of the method. This eliminates method-dependent artifacts and produces stable, reproducible archetype assignments.
Five design axes → multiple independent clustering checks → consensus → 11 archetypes
Five structural families, eleven archetypes.
Aero-Driven
AEROMAX and AEROBLADE — boats whose identity is set by rig power, with sail-area efficiency and upwind VMG characteristics that dominate the structural signature.
Balance-Sensitive
KEELFLEX — a design that operates inside a narrow stability envelope where small changes in heel angle and trim produce large changes in speed.
Downwind-Optimized
GLIDEFORM and GRAVITYRUN — hull forms that trade upwind rig power for low-drag profiles and reaching-and-running leverage, with strong downwind VMG relative to upwind.
Platform-Rigid
IRONWIND, STEELFORM, STEELCORE, and DEEPFRAME — stiff, high-righting-moment platforms with predictable behavior under load and conservative rig-to-displacement ratios.
Mixed-Mode-Power
STORMLINE and HEADFORCE — designs that combine high rig power with sensitivity traits (heel response, drag penalties, condition dependence) and the widest spread between best and worst corrected-time finishes in the fleet.
Signal strengthens with data.
Archetype assignments are not static labels. As new race data is processed, confidence accumulates. A boat with few observations has a provisional assignment — the structural position is identified, but the confidence bounds are wide.
Confidence increases as a boat accumulates observations across varied conditions — a boat with many observations has a high-confidence profile, with a stable archetype assignment and precisely resolved coordinates.
The methodology itself is validated against the fleet. The share of the fleet's structural signal the five design axes capture is not a target — it is a measurement of how well the structure fits the fleet.
The eleven archetypes are not imposed — they emerge from the data through consensus clustering. As the fleet grows and new events are processed, these numbers update. The methodology is transparent and reproducible.
The white paper.
The engine behind this page — the Multi-dimensional Performance Archetype Engine — is documented publicly by SailrScience Research: what it measures, the five-axis vessel fingerprint, and how the eleven archetypes are recovered and held stable across releases. The full white paper, including the complete algorithmic detail, is available on request through the research site.
Validation evidence publishes on this site as it clears — each artifact carries its evidence badge, moving from Validation to Latest published view when a run completes. The current artifacts live on Validation Analyses.
Read the methodology at the source: The archetype model at SailrScience Research → — overview public, full white paper by request.
Three floors. Every page obeys the same rule.
Structural readouts — archetype distribution, designer or class signatures, dimensional profiles — publish for any fleet that exists. Describing what a fleet IS requires only that it exists.
Comparative or result-ranking narratives — who finished where, which archetype performed better on this course, who closed the gap — require a sufficient number of boats. Comparison across too few boats is anecdote, not analysis.
Crew-attribution or performance-residual narratives — decomposing a result into what the boat gave and what the crew added — require a substantial number of boats within a single event. Below that, noise dominates the residual.
Cohorts below the applicable floor carry a Low-sample badge and limit themselves to the structural tier; comparative narrative is suppressed. The policy itself is the public invariant every page is measured against today.
Five public evidence badges.
Every analytical card on FleetEdge carries a badge telling you what kind of claim it is. The lexicon is closed: five values, stable, auditable.
- Latest published view
- Live fleet-wide measurement. Results are stable enough for comparative use.
- Validation
- Methodology is under on-site validation. Results are directional while the validation run completes.
- Structural-only
- Dimensional or archetype analysis without race-result attribution. Describes what the fleet IS, not what it did.
- Low-sample
- Cohort is below the narrative floor for comparative analysis. The card ships a structural readout only; no comparative takeaways.
- Pre-race scenario
- Forward-looking analysis using forecast or historical-prior inputs. Not a measurement; a projection under stated conditions.
Badges say what kind of claim a figure makes; its scope label says what it counts. The cohort vocabulary behind every FleetEdge count — ORC-rated, mapped-IRC, classified, race data vs. authority counts — is defined on the Data Definitions page.
See Methodology in the Sydney Hobart fleet.
Sydney Hobart racing brings methodology into sharp relief — see how the physics meets the fleet's regime and rivalries.
Explore Sydney HobartRigorous methodology. Transparent pipeline. Every boat measured the same way.
A consistent performance-archetype framework, applied to every boat in the ORC fleet.