Inspiration
Youth football is one of the most popular sports globally, yet many young players suffer preventable injuries due to poor warm-ups, excessive training load, ignored pain and lack of guidance. I was inspired by the fact that most injuries don’t happen suddenly, they build up over time. PlaySafe AI was created to help youth footballers identify injury risks early and take simple preventive actions before injuries occur.
What it does
PlaySafe AI is a web-based injury prevention platform designed for youth footballers. It: Assesses a player’s injury risk before training or matches Calculates a clear risk score and risk level (Low, Medium, High) Generates a personalized injury prevention plan Tracks recurring pain and provides early warning alerts Helps players, parents and coaches make safer training decisions The system focuses on prevention, not diagnosis.
How I built it
PlaySafe AI was built as a full-stack web application using: HTML & CSS for structure and styling JavaScript for interactivity PHP for backend logic and risk calculations MySQL for storing assessments and injury logs A rule-based injury scoring system was implemented to analyze: Training and match workload Previous injuries Warm-up and cool-down habits Recent pain reports The backend dynamically generates prevention advice and detects recurring pain patterns to trigger early warnings.
Challenges I ran into
Designing an injury risk system that is useful but not medical Keeping the logic simple, transparent and explainable Balancing feature scope to fit hackathon time limits Translating sports injury concepts into clear technical logic Ensuring the system works smoothly without requiring user accounts
Accomplishments that I'm proud of
Building a working full-stack system, not just a static website Implementing a clear and explainable injury risk scoring engine Creating personalized prevention plans dynamically Adding an early-warning pain tracking feature Keeping the project youth-safe, ethical and realistic
What I learned
Injury prevention can be modeled effectively using simple logic Clear problem definition matters more than complex technology Rule-based systems can be powerful when designed well Simplicity improves usability, especially for young users Explaining why a system makes decisions builds trust
What's next for PlaySafe AI
Future improvements could include: Coach and team dashboards Team-level injury analytics Mobile-first enhancements Integration with wearable devices AI-driven injury prediction using real-world data Notifications for parents and coaches PlaySafe AI has the potential to grow into a practical safety tool for football academies and youth teams.
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