Player Performance Summary Dashboard Card

[zepor]

Comprehensive Requirement Document for "Player Performance Summary" Dashboard Card Overview This document outlines the requirements for developing a "Player Performance Summary" dashboard card. This card will provide an intuitive and detailed summary of an individual player's performance metrics using data from the Sports Radar API. It is designed to be dynamic, adapting to the player and their position, and aims to be the best tool for player performance analysis in the market.

1. Description A dashboard card showing a summary of an individual player's performance metrics, including passing yards, rushing yards, touchdowns, interceptions, and overall rating.
2. User Story As a user (coach, player, analyst, or fan), I want to see a comprehensive summary of a specific player's performance metrics so I can make informed assessments about their abilities and contributions.
3. Acceptance Criteria • Display Key Metrics: Show key performance metrics such as passing yards, rushing yards, touchdowns, interceptions, and overall rating. • Dynamic Data: Metrics are dynamic and change based on the selected player and their position. • User-Friendly Interface: The card must be aesthetically pleasing, easy to navigate, and interactive. • Reliable Data: Use data directly from the Sports Radar API, ensuring accurate and up-to-date information. • Responsive Design: Ensure the card is fully responsive, working seamlessly across all devices (desktop, tablet, mobile).
4. User Flow
   1. Login/Authentication: ○ Users log in using secure authentication methods (e.g., OAuth2 via Auth0).
   2. Navigate to Dashboard: ○ Upon successful login, users navigate to the main dashboard.
   3. Select Player: ○ Users select a specific player from a list or search bar.
   4. View Player Performance Summary: ○ The dashboard dynamically updates to show the selected player's performance metrics.
   5. Interact with Data: ○ Users can hover over metrics to see detailed tooltips, click on elements for more detailed views, and switch between different metrics.
   6. Logout: ○ Users log out of the dashboard.
5. Data Sources and Integration Utilized Data Sources: • Player Stats: ○ GET /players/{player_id}/statistics • Game Logs: ○ GET /players/{player_id}/game_logs • Career Stats: ○ GET /players/{player_id}/career_stats Example Data Points from the Sports Radar API: • Player information (name, team, position) • Season statistics (passing yards, rushing yards, touchdowns, interceptions) • Game-by-game performance (specific statistics for each game played) • Career statistics (aggregate performance metrics over the player's career)
6. Framework and Tools
   1. Frontend: ○ React.js: For building the interactive UI. ○ Redux: For state management. ○ Chart.js/D3.js: For data visualizations. ○ Styled Components/Material-UI: For consistent and responsive design.
   2. Backend: ○ Node.js/Express.js: To serve backend APIs. ○ Redis: Caching frequently accessed data for performance optimization. ○ Axios: For making HTTP requests to the Sports Radar API.
   3. Database and Storage: ○ PostgreSQL: For structured data storage. ○ Azure Data Lake: For storing historical data when necessary.
   4. Deployment and CI/CD: ○ Docker: For containerization. ○ Kubernetes: For orchestration. ○ GitHub Actions: For continuous integration and deployment.
   5. Monitoring and Analytics: ○ New Relic/Prometheus/Grafana: For monitoring system performance and data quality. ○ Sentry: For error tracking and monitoring.
7. Detailed Implementation Steps 7.1 Data Integration
   1. Set up API Integration: ○ Task: Integrate with Sports Radar API to fetch player stats, game logs, and career stats. ○ Steps:
      1. Register and obtain API keys from Sports Radar.
      2. Store API keys securely in environment variables or configuration files.
      3. Establish connection to the API using Axios for HTTP requests.
      4. Implement error handling for API requests.
   2. Fetch Data: ○ Task: Fetch data from Sports Radar API based on the selected player. ○ Endpoints: § Player Stats: GET /players/{player_id}/statistics § Game Logs: GET /players/{player_id}/game_logs § Career Stats: GET /players/{player_id}/career_stats
   3. Data Transformation: ○ Task: Transform the raw data into a format suitable for visualization. ○ Steps:
      1. Normalize the data structure to ensure consistency.
      2. Calculate additional metrics (e.g., overall rating) if not provided by the API.
      3. Cache transformed data in Redis for performance optimization. 7.2 Backend Development
   4. Set up Express.js Server: ○ Task: Create RESTful APIs to serve player performance data to the frontend. ○ Endpoints: § GET /api/player/{player_id}/stats: Fetch player statistics. § GET /api/player/{player_id}/game_logs: Fetch player game logs. § GET /api/player/{player_id}/career_stats: Fetch player career stats.
   5. Caching Mechanism: ○ Task: Implement caching for frequently accessed data. ○ Steps:
      1. Use Redis to cache responses for player statistics.
      2. Set appropriate expiration times for cache entries.
      3. Implement cache invalidation logic for updating data. 7.3 Frontend Development
   6. Design UI Components: ○ Task: Design reusable React components for the player performance summary card. ○ Components: § PlayerInfo: Displays name, team, and position. § StatCard: Shows individual metrics such as passing yards, rushing yards, etc. § Chart: Visualizes data trends over time. § Tooltip: Provides detailed information on hover.
   7. Interactive Features: ○ Task: Add interactivity to the dashboard card. ○ Features: § Hover tooltips: Show detailed stats on hover. § Click interactions: Expand charts or show detailed views. § Filters: Allow users to filter data by season or game.
   8. Data Visualization: ○ Task: Visualize performance metrics using Chart.js or D3.js. ○ Charts: § Line chart for performance trends over time. § Bar chart for game-by-game performance. § Pie chart for distribution of different metrics. 7.4 Testing and Deployment
   9. Unit and Integration Testing: ○ Task: Ensure all components and APIs are thoroughly tested. ○ Tools: Jest for unit tests, Cypress for integration tests. ○ Coverage: Aim for 90%+ test coverage.
   10. Continuous Integration/Continuous Deployment (CI/CD): ○ Task: Automate the build, test, and deployment process. ○ Tools: GitHub Actions for CI/CD pipelines. ○ Containers: Use Docker for containerization, deploy using Kubernetes.
   11. Monitoring and Error Tracking: ○ Task: Monitor performance and track errors in production. ○ Tools: New Relic/Prometheus/Grafana for monitoring, Sentry for error tracking.
8. Security and Compliance • Data Security: Ensure all data is transmitted securely using SSL/TLS. • Authentication and Authorization: Use Auth0 for secure authentication and authorization. • Compliance: Regularly audit data handling practices to ensure compliance with industry standards and privacy regulations.
9. Documentation and Training • User Guides: Create comprehensive user guides for interacting with the dashboard. • Developer Documentation: Maintain detailed API documentation, setup guides, and implementation notes. • Training Sessions: Conduct training sessions and webinars for new users.

API Requests Examples: Player Statistics:

GET /api/player/{player_id}/stats { "player_id": "12345", "name": "John Doe", "team": "Team Name", "position": "Quarterback", "stats": { "passing_yards": 3500, "rushing_yards": 500, "touchdowns": 30, "interceptions": 10, "overall_rating": 95 } } Game Logs:

GET /api/player/{player_id}/game_logs [ { "game_id": "game_123", "date": "2023-09-10", "opponent": "Opponent Team", "passing_yards": 300, "rushing_yards": 50, "touchdowns": 2, "interceptions": 1 }, ... ] Career Stats:

GET /api/player/{player_id}/career_stats { "player_id": "12345", "name": "John Doe", "team": "Team Name", "position": "Quarterback", "career_stats": { "seasons_played": 10, "total_passing_yards": 30000, "total_rushing_yards": 2000, "total_touchdowns": 250, "total_interceptions": 75, "overall_rating": 98 } }

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