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str8bat — The Motion Intelligence Layer for Sport
The Physical AI era

Movement, made machine‑readable.

AI learned to read text, images, speech and code. It still can't read how a body moves. str8bat is building the motion intelligence layer that changes that — and today it already powers multi-sport analysis, live broadcasting and talent scouting.

The missing modality

Every modality got a representation before AI could use it. Motion never did.

Text became tokens. Images became embeddings. Sound became spectrograms. Once each was represented in a form machines could compute, AI transformed it. Human movement — the way we run, swing, throw and balance — is the last major modality still locked in raw video and human intuition.

Text→ tokens & embeddingsSolved
Images→ pixels & vision embeddingsSolved
Speech→ waveforms & spectrogramsSolved
Code→ syntax trees & tokensSolved
Motion→ str8bat motion representationBeing built
Nine years, one representation
~8M
Sensor-measured, labelled swings
~25,000
Players in the dataset
15+
Countries
3
Patents granted, +1 in filing
2 mo.
To port the stack from cricket to running
The platform

A deterministic, full-stack motion system — owned end to end.

Raw signal enters at the bottom. Structured, machine-readable motion comes out the top. The same stack runs whether the athlete holds a bat, a racquet, or nothing at all.

Applications Motion Intelligence Motion Signatures Representation Motion Capture increasing abstraction
  • Motion Capture
    Signal from sensors, wearables, embedded equipment and cameras. The source becomes interchangeable; the motion layer is the standard.
  • Representation
    Raw signal turned into a structured, sport-agnostic description of movement.
  • Motion Signatures
    Each athlete's distinct movement fingerprint, stable enough to recognise and compare.
  • Motion Intelligence
    Models that read signatures to diagnose technique, compare athletes and surface change over time.
  • Applications
    Multi-sport, broadcast, scouting and research — all on the same underlying layer.
Multi-sport by design

One spectrum of human movement.

Sports look different, but movement sits on a spectrum — from rotational, impact-driven actions to cyclical, locomotive ones. str8bat proved the stack at one pole in cricket, then ported it to the other pole in running in about two months. Everything in between is the same problem in a different shape.

Rotational · Impactpower delivered in a single strike
Cyclical · Locomotionpower delivered in repetition
Cricket
Proven
Golf
On roadmap
Tennis
On roadmap
Baseball
On roadmap
Running
Ported · ~2mo

Proving both poles — and porting between them fast — is the evidence that the representation generalises, not just the product.

The enterprise solution

One motion layer. Three ways it already earns its place.

The same representation powers everything above it. Today it shows up in three enterprise products that are live in the real world — not slideware.

Cricket live · more sports next
01

Multi-sport analysis

Coaching and performance analytics built on motion, not outcomes. Proven in professional cricket, ported to running, extending across the movement spectrum.

See the spectrum →
Live pilot · India–England 2026
02

Broadcasting

Motion on air. Bat speed, timing and a Power Index rendered live, with bat-path graphics and model-written analysis that explain why a shot worked.

See broadcasting →
Commercially live
03

Talent scouting · scout

Every batter at a trial measured on one scale, ranked into a single board before anyone leaves the ground. Pick with proof, not gut feel.

See scout →
Solution 02 · Broadcasting

Explain why the shot worked. Live, on air.

Today's broadcast explains outcomes. str8bat adds the cause — the mechanics behind the moment — as metrics, graphics and narrative, generated in the flow of play.

Bat speed
118 km/h
Timing index
86%
Power index
92/100
LIVE · BAT-PATH OVERLAYstr8bat motion feed
  • 01
    MetricsBat speed, timing index and a 0–100 Power Index that combines impact and timing into one honest read.
  • 02
    NarrativeModel-generated analysis for the pre, live and post-match windows — the story behind the number.
  • 03
    Rendered videoBat-path visualisation and superimposed metrics on the broadcast frame.

A live broadcasting pilot is running with a Tier-1 broadcaster and OTT platform on the 2026 India–England series. Broadcasting patent in filing.

Solution 03 · Talent scouting

Every batter. One board. Pick with proof.

Every player at a trial bats with str8bat batting tech, and scout turns the session into one ranked board. Everyone measured on the same scale — the standouts already at the top before anyone has left the ground.

SELECTION BOARDRanked by player score
The headline number

One Player Score on top. Five reads underneath.

One number out of 100 rolls every metric into a single read. Sort the trial by it, see who rises, and start your shortlist from the top. The full breakdown is always one tap away.

BUILT ON STR8BAT'S CORE SIGNALS  ·  Bat Speed  ·  Impact Speed  ·  Timing Index  ·  Sweet Spot %  ·  Swing Path  ·  Bat Lift
Validation · Auction trials

What the data saw, the auction confirmed.

At a premier T20 franchise auction trial, about 80 players used str8bat. We ranked the top 25 on the data alone — before any eye test.

Case study · Rajasthan Royals × str8bat

Scouted at 13. Record-breaker at 14.

How Rajasthan Royals used str8bat batting tech to spot — then sharpen — a teenage batter before the rest of the league caught on.

How a trial runs on scout

No setup. No spreadsheets.

01

STR8BAT TECH ON EVERY BAT

Every player bats with the same precision read. No one is judged on a better net or a kinder bowler.

02

TAG THE MATCHUP AS THEY BAT

Mark pace or spin, the arm, the phase, the angle — a few taps per spell. Context turns raw shots into a real scouting read.

03

OPEN THE RANKED BOARD

The pool sorts itself by Player Score before the kit is packed. Study the splits, export a clean report for the panel.

Run your next trial on scout TRIALS · ACADEMIES · ASSOCIATIONS  ·  #pickwithproof
The moat

The moat isn't the sensor. It's the representation and the data behind it.

Models get commoditised. A proprietary representation, trained on nine years of real athlete motion — roughly eight million labelled swings across 15+ countries, protected by granted patents — compounds. Every trial, every broadcast, every session makes the layer harder to replicate and more useful to build on.

"str8bat will be a game-changer for batting coaching, and will change the way we watch batting in the future."
Greg Chappell — Former Australia Captain & India Head Coach, str8bat Advisor
Backed by the game

Built with elite programs, national setups and legends.

Advised by James Sutherland (former CEO, Cricket Australia), Greg Chappell and R Ashwin. Trusted on record by Sunil Gavaskar, Harmanpreet Kaur, Zubin Bharucha (Head of Cricket, RR) and Chris Rogers, among others.

The direction of travel

Where this goes.

As the layer matures, every athlete can carry a living model of how they move and where they're at risk, and movement becomes searchable across a connected graph of athletes. The end state is a shared reference system for understanding human motion.

A note on how we talk about this: the claims about where movement intelligence is headed are ours to make boldly. The claims about str8bat are deliberately bounded — one sport proven, a second ported, products live in broadcasting and scouting, a dataset built over nine years. We keep the two clearly separate.

Let's talk motion.

Investor, federation, broadcaster, academy or team — if you work with human movement, we should talk.

Talk to us