AI video analysis at the nets, in three taps

Good cricket coaches already know what to look for: line and length, the shoulder line at release, elbow angle, head position, the shape of a follow-through. What they've never had is a way to capture that analysis and get it to the player without a six-figure rig and a control room. The tools that do this properly have lived at first-class grounds. The academy nets — where most actual coaching happens — run on a coach's phone and a memory that fades by the weekend.

SKrutin is built to close that gap. One iPad at the nets becomes a full coaching lab, and the analysis reaches the player's phone in three taps — before they've left the ground.

Why the nets, specifically

The constraint that shapes everything is the environment. Academy nets are outdoors, often with patchy connectivity, run back-to-back across squads, with a single coach watching several lanes. Any tool that assumes a wired control room, a calibrated multi-camera rig, or a reliable connection simply doesn't survive contact with a Tuesday-evening session.

So SKrutin is offline-first by design. It records, processes, and produces a shareable analysis on the device, then syncs when a connection returns. The coach never waits on a network to give feedback, and nothing is lost if the signal drops mid-session.

What actually happens between delivery and feedback

The pipeline is deliberately compressed so it fits the rhythm of a net session:

• Capture at 240fps. High-frame-rate recording is what makes the difference between "you dropped your elbow" and showing the elbow drop frame by frame. SKrutin records at up to 240fps on the iPad.
• AI-interpolated slow motion. Using RIFE frame interpolation, even a lower-frame-rate capture becomes smooth slow-motion on-device — so the coach can scrub the moment of release without it stuttering.
• Ball tracking with line and length. Computer-vision tracking overlays the delivery's line, length, and pitch zone, turning a vague impression into a repeatable record across a spell.
• Biomechanics scoring. Pose estimation breaks the action into the things coaches actually cue on — shoulder line, elbow angle, head position, follow-through — and scores each with a recommendation.
• A coaching note, written for the player. The technical output is turned into a plain, age-appropriate note in the player's language, so a twelve-year-old gets feedback they can act on, not a heatmap they can't read.
• Three taps to the phone. The coach reviews, then shares a browser link — no app install for the player or parent. From the bowler's mark to the parent's phone before the player has left the ground.

Analysis is only useful if it's shared

The quiet failure of most "video coaching" is that the footage never leaves the coach's device. Clips pile up, nobody reviews them, and the report gets written from memory weeks later — if at all. The discipline SKrutin enforces is that the output is a shareable artefact by default, produced in the session, not a file that requires editing later.

That changes the feedback loop from "next month, maybe" to "tonight, definitely" — which is the difference between video that improves players and video that just accumulates.

One vision pipeline, two products

SKrutin doesn't stand alone. It shares its AI vision pipeline with FlikVault, the cricket academy operating system — so the same ball-tracking and biomechanics that power a nets session also flow into a player's report inside the academy's system of record. Capture the analysis once; use it in coaching and in the academy's reporting.

That's the same principle we keep returning to across the sports vertical: the value is in capturing reality well once and letting every surface render from it, rather than rebuilding it each time.

If you run an academy or coach individually and want analysis that actually reaches your players, we'd be glad to talk.