Roadmap
Where FleetEdge is today and where it is going.
FleetEdge is live. Production infrastructure is in place; capabilities expand against a disclosed roadmap. The core analytical framework — archetype assignment, dimensional profiling, fleet-scale pattern analysis — is production-ready and available today. Additional capabilities are validated and hardened for release on a continuous basis.
This roadmap describes three tiers: capabilities that are available now, features in validation with proven methodology, and capabilities that are planned for future releases. SailrScience does not publish release dates — each capability ships when it meets the quality and accuracy standards required for production use.
Available now.
Fleet Analytics
Archetype distributions, dimensional comparisons, and structural pattern analysis across the fleet. Visualise how 11,207 boats cluster into 11 performance archetypes and explore the dimensional features that define each cluster.
Team Diagnostics
Individual boat profiling with 31-feature decomposition. See where a specific boat sits within its archetype cluster, which dimensional features define its competitive position, and how it compares to fleet-wide benchmarks.
Crew Performance Residual
Isolation of the crew's contribution from the boat's design contribution. Boats with race results receive crew residual measurement — a multi-dimensional signal showing where crew execution adds to, or subtracts from, what the boat's archetype predicts. The analytical framework is live; the signal sharpens as the race-results dataset grows.
Hull Efficiency & Rating Analysis
Six hull efficiency parameters (L/Disp, SA/WS, Cp, RM@25, BWL/TC, displacement/length), rating decomposition (GPH, TCC, scoring allowances), and classification analysis — the dimensional foundation for understanding each boat's design identity.
The MPAE Framework
The Multi-Parameter Archetype Engine: 31 features extracted from certificate and physics data, reduced to 4 latent factors (87.14% variance explained), classified into 11 archetypes through ensemble clustering consensus across 11,207 boats.
ORC + IRC Twins.
Synthetic Twin process matches each IRC certificate to its ORC design-family equivalent using measured hull dimensions — validated against dual-rated boats where both certificates exist. 1,600+ IRC boats that have never held an ORC certificate now analysed with ORC-grade physics. The first physics-based bridge between the two systems; every twin transparently labelled as a class-sibling projection.
Race Micro-Cohorts.
Filter to a specific regatta and see every boat that competed — with full dimensional analytics. Pre-race intelligence for teams; class assessment for naval architects. 1,645 boats linked to events across the race-results corpus.
Weather Intelligence. Live.
Per-race atmospheric context — wind speed, wind direction, wave height, wave period, surface pressure — derived from ECMWF ERA5 reanalysis at 31 km horizontal resolution, sampled against race-leg centroids and venue bounding boxes. Corpus-wide coverage across FleetEdge's race record.
Ocean Currents. Live.
Per-boat ocean-current profiles at race venues and along long-distance waypoints — derived from HYCOM GLBy 93.0 reanalysis. Live coverage spans Cowes, Fastnet, Rolex Middle Sea, Sydney–Hobart, and RORC Caribbean 600.
In validation.
The following capabilities have validated methodology and are being hardened for production deployment. The analytical frameworks are complete and have been tested against the full dataset. Runtime computation and operational integration are underway.
Condition & Tactical Dimensions
Wind response profiles, sea state adaptation characteristics, and tactical decision quality metrics. The feature extraction framework is designed and calibrated against race-level condition data. Production integration depends on the availability of granular condition data from event scoring systems.
Planned.
The following capabilities are planned for future development. They represent extensions of FleetEdge's dimensional analysis framework into new analytical domains.
Opponent Modelling
Head-to-head dimensional comparison across the fleet — identifying where two boats diverge in their performance profiles and what conditions favour each design strategy.
Boat Maintenance Signals
Performance degradation detection over time — identifying when a boat's empirical results begin to diverge from its dimensional profile in ways that suggest maintenance or condition factors.
FleetEdge is evolving.
Contact SailrScience for early access or to discuss upcoming capabilities.