🏏 IPL Playing XI Predictor (Strategy-Aware)

A strategy-aware IPL Playing XI prediction engine built using Python, Pandas, SQLite, and Streamlit.

The system generates a cricket-realistic Playing XI for any IPL team based on Aggressive, Balanced, or Defensive strategies, while strictly enforcing official IPL-style constraints.

This project is designed for hackathons, analytics demos, and learning constraint-based team selection systems.

🚀 Features

✅ Hard IPL Constraints (Always Enforced)

• ▸Exactly 11 players in the Playing XI.
• ▸Exactly 4 overseas players (Maximum).
• ▸At least 3 pure bowlers (Based on CSV role text, not assumptions).
• ▸At least 1 wicketkeeper.
• ▸Impact Player is never a wicketkeeper.

🧠 Strategy-Aware Selection

• ▸Aggressive: Prefers batters with high strike rates; bowling is respected but secondary.
• ▸Balanced: Maintains a balanced weighting between batting and bowling metrics.
• ▸Defensive: Prioritizes reliable batters (high average) and bowlers with strong economy rates.

🎳 Cricket-Correct Bowler Detection

• ▸Bowlers are detected using actual role values from the CSV.
• ▸Keywords detected: Bowler, Fast, Pace, Medium, Spin, Spinner, Leg Break, Off Break, Orthodox, Left Arm, Right Arm.
• ▸Bowling statistics are used only for ranking, not for classification.
• ▸All-rounders are explicitly excluded from the pure bowler count to ensure bowling depth.

🖥️ Interactive UI (Streamlit)

• ▸Team selection dropdown.
• ▸Strategy toggle (Aggressive / Balanced / Defensive).
• ▸Formatted Playing XI table.
• ▸Impact Player recommendation display.