Padelize - AI-Driven Padel Sports Analytics
Project Overview
Padelize is a comprehensive AI-powered sports analytics platform built to elevate how padel players, coaches, and clubs analyze performance, track fitness, and engage as a community. By combining advanced video analysis, intelligent insights, and social engagement features, Padelize transforms match recordings into actionable data and shareable moments, bridging performance improvement with motivation and community. Codetratives partnered on shaping the product as a scalable, insight-driven platform, balancing advanced AI capabilities with a simple, intuitive user experience suitable for both amateur and competitive players.
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Padelize AITeam
- Toba Samuel (UI/UX Designer)
- Nathaniel Peter (Mobile Developer)
- Sodiq Farayola (Backend Engineer)
- Saifullah Ahmed (Project Manager)
Year
April - October 2025
Challenges
Padelize tackled a range of technical and user-experience challenges:
- AI Video Analysis Complexity
Designing algorithms that reliably identify and classify shots, court movement, rallies, and activity metrics from user-captured match footage presented significant modeling challenges. The system needed to handle variable angles, lighting conditions, and video quality. - Actionable Analytics Across User Levels
The product had to deliver insights that are meaningful to both casual weekend players and competitive athletes, balancing depth with accessibility. - Scalable Community Features
Building a social layer (profiles, leaderboards, progress sharing) demanded careful design to avoid clutter while promoting engagement and friendly competition.
Deliverables:
The following core features were delivered in the Padelize MVP:
AI-Powered Player Insights
- Shot Success/Fail Rates: AI analyzes match recordings and computes success statistics.
- Movement Heatmaps: Visual representation of court coverage and player movement.
- Distance Covered: Total running distance estimated via motion tracking.
- Calories Burned: Energy expenditure estimates based on match data.
Match Highlights
- Automatic generation of short, shareable highlight reels showcasing key moments such as best shots, long rallies, and critical points.
- Highlights are easily shareable within the native community feed or externally on social platforms.
Community Features
- Customizable player profiles with performance summaries.
- Progress sharing feeds (stats, videos, achievements).
- Local and global leaderboards for comparative insights.
- Engagement tools including likes, comments, and achievement badges (e.g., “100 Matches Played”).
Standard App Functionality
- Onboarding: Interactive walkthrough and preference setup through email/social sign-in.
- Subscription Management: Tiered plans with Stripe payments allowing upgrades, downgrades, and cancellations.
- Multi-Tier Access: Basic, Premium, and Coach/Club subscription options.
Landing Page
- Optimization: landing page optimized for high conversion. .
Technologies Used:
- Machine learning models for video analysis and shot classification
- Motion estimation algorithms for movement, distance, and heatmaps
- Cloud infrastructure (AWS/Azure) for secure video storage and processing
- Scalable APIs supporting community interactions and analytics
- Stripe for subscription payments and management
- React & React Native for frontend.
Impact
Padelize established a strong foundation for data-driven padel performance analysis and community engagement.
The platform enables players to objectively measure progress, share achievements, and stay motivated through insights and social interaction. For clubs and coaches, it creates a clear pathway toward structured performance tracking and scalable athlete development.
Padelize demonstrates how AI can be applied practically to sports, turning everyday matches into insights, highlights, and meaningful engagement.
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