Develop an interactive sports analytics visualization system that analyzes player performance, team statistics, match outcomes, and historical trends. The system should enable coaches, analysts, and fans to explore performance metrics, compare players, and identify winning patterns through dynamic and comparative visual dashboards.
Collect sports datasets (e.g., cricket, football, basketball) including player stats, match results, scores, rankings, and seasons.
Clean and preprocess structured and semi-structured sports data.
Design a relational database schema for teams, players, matches, and tournaments.
Implement ETL processes to aggregate season-wise and player-wise statistics.
Define KPIs such as strike rate, scoring average, win ratio, player efficiency rating, and team performance index.
Develop backend APIs for dynamic data retrieval and comparison.
Build interactive dashboards using Tableau, Power BI, or Plotly/D3.js.
Implement filtering by season, team, venue, and tournament.
Add drill-down features from team-level overview to individual player statistics.
Integrate predictive visualization for match outcome probability.
Optimize dashboard responsiveness for large historical datasets.
Conduct usability testing and validate analytical insights.
Document system design, visualization techniques, and performance insights derived from the system.
