PranayN23/NFLResourceAnalysis
Apr 2025 – Apr 2025
1 Month active
Languages Used
CSSJSXJavaScriptPython
Technical Skills
API DevelopmentBackend DevelopmentDatabase IntegrationFlaskFrontend DevelopmentMongoDB
hfu314
PROFILE
Hfu314
During April 2025, PranayN23 developed a comprehensive Player Data Page for the NFLResourceAnalysis repository, focusing on end-to-end integration between a Flask backend and a React frontend. Leveraging Python and JavaScript, PranayN23 connected a MongoDB database to deliver dynamic player data retrieval by name, position, team, and year. The frontend incorporated position-specific statistics and a Recharts-powered line chart visualizing PFF score progression against league and team averages. This feature enabled richer player analytics and supported faster scouting decisions. The work demonstrated depth in API development, database integration, and data visualization, establishing a robust foundation for future data-driven enhancements.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
1
Lines of code
3,157
Activity Months1
Your Network
108 people
Work History
April 2025
3 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for PranayN23/NFLResourceAnalysis. Delivered end-to-end Player Data Page featuring API integration with the MongoDB backend, a dynamic frontend UI, and a performance visualization to support data-driven player insights. The feature enables dynamic data fetch by name/position/team/year, adds position-specific statistics on the frontend, and introduces a PFF score progression line chart compared to the league/team average. This work enables faster scouting decisions and richer player analytics while laying the groundwork for additional data-driven features.
3 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for PranayN23/NFLResourceAnalysis. Delivered end-to-end Player Data Page featuring API integration with the MongoDB backend, a dynamic frontend UI, and a performance visualization to support data-driven player insights. The feature enables dynamic data fetch by name/position/team/year, adds position-specific statistics on the frontend, and introduces a PFF score progression line chart compared to the league/team average. This work enables faster scouting decisions and richer player analytics while laying the groundwork for additional data-driven features.
April 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture73.4%
Performance80.0%
AI Usage33.4%
Skills & Technologies
Programming Languages
CSSJSXJavaScriptPython
Technical Skills
API DevelopmentBackend DevelopmentDatabase IntegrationFlaskFrontend DevelopmentMongoDBREST APIsReactRecharts
Repositories Contributed To
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