Shreya AmbaliyaShreya A.• Lead Flutter Developer
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Sports / Video

E-Track

Sports Performance & Video Analysis

Solving a complex sports video analysis challenge.

Role: Lead Flutter Developer

FlutterHigh-FPS VideoBiomechanicsLocal StorageCloud

01

Overview

E-Track is a sports performance application that converts high-speed video into measurable performance insights for athletes and coaches.

02

Client Situation

The client required a sports performance application capable of converting high-speed video into meaningful performance insights—not a standard media player, but an analysis product.

03

Challenge

The application required advanced workflows: high-frame-rate video handling, processing, calibration, movement detection, and performance visualization—all inside a Flutter client.

04

My Approach

Instead of treating it as a standard video application, I designed the workflow around the complete analysis process—from capture through metrics and visualization.

05

Technical Decisions

  • Modeled the product as an end-to-end analysis pipeline rather than isolated video screens.
  • Separated capture/import, processing, calibration, and results so each stage could be validated independently.
  • Balanced local data handling with upload/retry workflows for unreliable network conditions.
  • Prioritized performance visualization that reflected calculated metrics, not decorative charts.

06

What I Built

  • Video capture and import workflows
  • High-frame-rate processing support
  • Calibration flows
  • Frame analysis and movement-related workflows
  • Performance metric calculation surfaces
  • Local data handling and upload/retry paths
  • Sports performance visualization

07

Architecture

A Flutter analysis pipeline connecting video input to frame analysis, calibration, movement detection, metric calculation, and performance visualization—with local storage and cloud processing where needed.

  1. Video
  2. Frame Analysis
  3. Calibration
  4. Movement Detection
  5. Metric Calculation
  6. Performance Visualization

08

Technical Challenges

  • Handling high-frame-rate video workflows inside Flutter without breaking the analysis UX.
  • Building calibration and detection steps that users could complete reliably.
  • Managing local data, uploads, and retries around heavy media operations.

09

Solution

I implemented specialized Flutter workflows for each stage of the analysis process, keeping media handling, calibration, and results presentation as connected but maintainable pieces.

10

Outcome

Created a specialized Flutter application capable of handling complex sports performance workflows from footage to insights.

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