Player Trend Analysis Report Generator (Multi-Season)
About Project
- Type: Longitudinal Sports Analytics Reporting
- Focus: Multi-season trend tracking, development signal detection, and coach-ready takeaways
- Deliverables: One report per player with year-by-year metrics, trend charts, and an overall development index
Objective
Track how a player’s key metrics evolve across seasons and convert raw changes into clear, coach-friendly insights—highlighting what improved, what regressed, and where to focus training next.
Tools & Features
Python, Pandas, Excel Automation, PDF Reporting, Percentile Benchmarking, Time-Series Aggregations, Rolling Averages, YoY Deltas & % Change, Visualization, Data Quality Checks
Key Work & Impact
Standardized multi-year player data (naming, units, missing values) so comparisons are reliable and repeatable across seasons.
Benchmarked each season using percentile rankings relative to the player’s cohort, making performance changes interpretable even when raw distributions shift year-to-year.
Generated automated trend signals: year-over-year deltas, directionality-aware metrics (e.g., faster sprint times score higher), and clear indicators of meaningful jumps or declines.
Created an “Overall Development Index” that summarizes a player’s multi-metric progress into a single, explainable snapshot for quick decision-making.
Built a coach-first layout with scanable sections: top strength, biggest improvement, latest-season summary, and charts that visually show development over time.
Designed the pipeline to be robust to real-world data: supports metrics appearing/disappearing by season and prevents missing values from breaking reporting.