A public-facing map of the systems behind CoLab: motion proof, athlete analytics, coaching loops, academy packaging, and commerce paths that keep the next action attached to what the athlete just did.
This page explains what CoLab has built without publishing private benchmark tables, admin-only controls, provider details, or fragile heuristics. LAB is the primary analytics contract. AEON, POWER, Trace-era artifacts, and other legacy fields are supporting context.
Movement proof
A coaching layer that turns short athlete video into movement phases, scored context, cue paths, and next actions. Trace remains legacy/internal naming; the public product language is ECHO.
Where it shows up
Clip capture, phase review, coach cue routing, team packages.
Canonical analytics
The athlete decision anchor: Load, Adaptation, and Bounce. LAB keeps readiness, learning quality, and motion quality in one explainable hierarchy with confidence attached.
Where it shows up
Athlete status, coach snapshots, analytics summaries.
Supporting views
AEON radial views and POWER profiles are useful drill-downs for skill learning, sport-specific work, goals, and capacity. They should support LAB rather than compete with it as the headline score.
Where it shows up
Performance sheets, power profile cards, coach context.
Cue response
A cue and response path built from saved ECHO sources. HERO carries the coaching moment into voice, narrative, feedback, and the next athlete action.
Where it shows up
Academy feedback, clip response, coach narration.
Strategy engine
Sport-specific pattern cards and heatmaps for tennis, swimming, and triathlon. Patterns turn athlete context into practical structures, pressure scenarios, cues, and risks.
Where it shows up
Playbook strategy, academy pattern generation, heatmaps.
Reference intelligence
A GOAT/reference movement model for comparing athlete motion to sport-specific ideals, without reducing coaching to imitation. It identifies meaningful gaps and phase priorities.
Where it shows up
Reference scoring, GOAT comparison, movement roadmap.
Comparison layer
Mirror aligns two clips for side-by-side review. Reverb summarizes motion similarity across timing, path, angles, and smoothness in coach-friendly language.
Where it shows up
Filmroom compare, phase gaps, coach review.
Clip substrate
A short-form capture and taxonomy layer for sport, view, skill, environment, athlete, and tags. BURST keeps raw movement moments small enough to analyze and compare.
Where it shows up
Filmroom upload, clip intake, ECHO source prep.
Video tests
POWR video-derived jump, agility, broad jump, and VBT testing that feeds motion-quality signals into Bounce and broader LAB analytics.
Where it shows up
Testing page, training toolkit, movement summaries.
Knowledge loop
A creator-knowledge and athlete-context loop that turns uploaded methods, session state, products, and performance material into practical coaching next actions.
Where it shows up
Smart coach, PK agent, academy-specific assistants.
Review workflow
The video review layer that keeps clip capture, mirror comparison, ECHO output, coach notes, roster context, and the next session in one workflow.
Where it shows up
Filmroom, Performance Lab, team review.
Runtime bands
Versioned sport, skill, phase, and view-specific benchmark profiles that make vision analysis readable as ranked coaching context.
Where it shows up
Vision Analysis cards, ECHO phase rankings.
Ball and rotation
A ball-sport and rotational scorecard for line, separation, sequencing, velocity, lower-body power, upper-body power, and sport expression.
Where it shows up
Tennis, golf, ball motion, rotational skill review.
Human signal R&D
Experimental affect, movement-context, and mirror-neuron research surfaces. These labs explore how attention, joy, motor context, and perception can support learning.
Where it shows up
R&D, future learning signals, academy experiments.
Spatial proof
Spatial rendering and reconstruction workflows that turn movement media into depth-aware, reviewable scenes and package-ready learning assets.
Where it shows up
ECHO spatial, XR pipeline, 6DoF package outputs.
Commerce to performance
Reusable product storytelling systems that connect gear, memberships, training blocks, recovery, content, and checkout to the athlete's performance context.
Where it shows up
Product pages, kits, concept offers, branded stacks.
Entitlement IP
Membership, assignment, sponsored-team, and academy access flows that package coaching knowledge, ECHO content, and team workflows around who should see what.
Where it shows up
Academies, team licenses, ECHO assignments.
Operator surface
Internal workspaces for validating Gnosis, POWER, vision bands, Muse Joy, Neuro, XR, ECHO metadata, and product systems.
Movement surface
The clip review and motion stack layer: BURST intake, Mirror, Reverb, ECHO packages, spatial review, and coach-facing proof.
Athlete surface
The applied performance layer for POWR, Bounce, LAB, patterns, readiness context, personal bests, and session planning.
Public product surface
The public framing for Smart Loop, Loopmark, ECHO Studio, GOAT references, blocks, stacks, and the product narrative.
Packaging surface
The route layer for kits, memberships, academies, team access, branded products, and commerce attached to performance use.
Public movement product
Use ECHO for Motion Stack Analysis. Treat Trace as legacy/internal terminology where older code and package paths still exist.
Headline analytics contract
LAB should remain the primary athlete status model. Readiness, AEON, POWER, Trace, and legacy scores belong underneath it.
Supporting capacity view
POWER explains strength, work, capacity, and mobility/stability context. It should not replace LAB as the main decision anchor.
Applied testing protocol
POWR is the video-test layer for jump, agility, broad jump, and VBT captures that feed Bounce and LAB.
Similarity language
Reverb is the public-friendly language for movement comparison, closeness, timing, path, and smoothness.
Biomechanical pillar
Bounce is the user-facing biomechanical state inside LAB and replaces older internal CME language.
Context loop
Loop is the cross-product pattern that keeps plan, proof, product, coach, and next action connected.
Keep this page focused on product methods, language, and system relationships. Legal filings, exact score weights, private benchmark tables, and admin-only validation controls should remain in internal documents.
