Building a Data-Led Cricket Coaching System with AI Video Intelligence

Client Overview

Cricket coaching in the United States is entering a new phase with structured, data-driven, and performance-focused training. As the ecosystem matures, leading academies are adopting technologies that align coaching with modern player expectations and global benchmarks.

One such leading cricket academy partnered with BOSC Tech Labs to develop a complete AI-powered video intelligence platform built using computer vision, pose detection, motion-tracking models, automated video segmentation pipelines, and real-time inference systems.

  • Icon

    Shift coaching from intuition-driven to measurable, objective, and data-backed

  • Icon

    Enable AI-powered player development

  • Icon

    Preserve the coach’s instincts & decision-making

  • Icon

    Develop a platform that acts as a true coaching partner

Business Challenges

  • Icon

    Manual video review was slow, repetitive, and inconsistent across coaching sessions.

  • Icon

    Delivering real-time, personalized feedback was difficult during high-volume training periods.

  • Icon

    Inconsistent video inputs, such as angles, lighting, player distance, and camera stability, made analysis unreliable.

  • Icon

    Long-term progress tracking lacked structure, standardized metrics, and objective baselines.

  • Icon

    Players displayed wide variations in skill level and playing style, requiring individualized training plans.

  • Icon

    Parents expected measurable reports and transparency, not generic verbal feedback.

The BOSC Tech Labs’ Approach

BOSC Tech Labs followed a structured, problem-first approach to ensure the academy received the right AI coaching partner.

  • Icon

    Understood authentic coaching needs through discussions with coaches (including IPL-level experts like Dishant Yagnik), parents, and players.

  • Icon

    Mapped the complete performance workflow, from recording sessions to reviewing footage, sharing feedback, and tracking improvements.

  • Icon

    Identified clear AI intervention points such as automated clipping, pose & motion recognition, technique assessment, personalized drills, and progress visualization.

  • Icon

    Defined success outcomes like faster session analysis, consistent feedback, structured player growth, and reduced manual review for coaches.

  • Icon

    Designed a scalable AI architecture optimized for real-time processing and accurate analysis across varied video quality.

The Impact at a Glance

This implementation delivered measurable improvements across efficiency, performance feedback, and stakeholder satisfaction by replacing manual processes with AI-driven analysis.

Solution we Provided

We built CricVision as a plug-and-play AI system that integrates with how a cricket academy already trains in the United States, without requiring them to change their workflow or invest in new hardware. Our team engineered a computer-vision-driven pipeline that reviews raw training footage, automatically processes it, and delivers structured insights that cricket coaches can act on instantly. Here’s what the solution provides in practice:

We designed CricVision to work with the academy’s existing devices. The app automatically adapts to footage from any smartphone or standard camera, letting coaches record sessions the way they always have, no additional hardware, calibration, or setup required.

Once the session footage is uploaded, our backend pipeline classifies, trims, and structures the footage. Long practice videos are instantly organized into player- and drill-wise segments, eliminating manual searching, tagging, or file management.

We engineered a custom computer-vision model trained on cricket biomechanics. It identifies key actions like stance, stride, release, bat swing, & follow-through, and measures posture, alignment, and motion for each frame. This creates a precise, technique-oriented breakdown of every moment.

The app automatically extracts the most relevant clips from the entire session. Coaches receive highlight reels focused solely on actionable moments, helping them review sessions more quickly and ensure consistent feedback across players.

Our recommendation engine evaluates technique patterns, recent sessions, and player roles to suggest targeted drills. Each player gets a guided improvement path built from both performance data and expert coaching logic.

We built structured dashboards that translate AI analysis into simple insights, including technique scores, weekly snapshots, growth charts, and trend lines. Players, coaches, and parents can track development with complete transparency.

CricVision includes a dedicated messaging and sharing system. Coaches can send clips, notes, and progress updates directly through the platform to players & parents, creating a connected training ecosystem and removing scattered WhatsApp messages or offline notes.

We enabled round-the-clock access to session data and insights. Players and coaches can revisit clips, summaries, and recommendations anytime, supporting continuous learning even outside scheduled practice hours.

Let’s Build Something Impactful

Share your requirements and we’ll help you design a scalable AI-driven solution.