🦊 Leicester City 2016: The Tactical Blueprint (Kanté & Mahrez)

This project provides a deep-dive data analysis into the tactical synergy between N'Golo Kanté and Riyad Mahrez during Leicester City's historic 2016 Premier League season. Using StatsBomb event data, we visualize how defensive solidity was transformed into attacking efficiency.

📋 Project Overview

The goal of this analysis is to decode the "Low Block & Counter-Attack" strategy used by Claudio Ranieri, focusing on:

1. Defensive Solidity: How Kanté acted as a defensive anchor.
2. Attacking Efficiency: How Mahrez served as the creative engine.

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🛠️ Project Structure

The analysis is divided into three main notebooks:

1. 01_data_exploration.ipynb

• Initial data fetching and cleaning using statsbombpy.
• Setting up the match environment (Leicester City vs. Bournemouth, 2016).

2. 02_defensive_solidity.ipynb

• Defensive Gravity Center: Visualizing the team's "Low Block" through Kanté's average position.
• Heatmaps & Intensity: Mapping Kanté’s 40+ defensive interventions across the pitch.

3. 03_attacking_efficiency.ipynb

• Creative Influence: Mapping Mahrez's "Golden Wing" and his tendency to cut inside.
• Passing Networks: Analyzing Mahrez's 78% pass success rate and vertical progression.
• 1vs1 Mastery: Evaluating dribbling performance in high-value zones.

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⚽ Key Tactical Insights

• The "Black Hole" Effect: Kanté's defensive gravity center proves that Leicester invited pressure deep into their half before reclaiming the ball.
• Transition Speed: The synergy between a deep defense and Mahrez's high-density creative zones allowed for lethal counter-attacks.
• Efficiency over Possession: The data confirms that tactical discipline (Low Block) and specialized roles (The Architect vs. The Destroyer) were the keys to Leicester's success.

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🚀 Tech Stack

• Language: Python
• Data Source: StatsBomb Open Data
• Libraries: pandas, matplotlib, seaborn, mplsoccer, statsbombpy

📈 Visualizations

• Tactical Heatmaps (Kernel Density Estimation)
• Pass Maps (Arrow Distributions)
• Spatial Centroids (Gravity Center Analysis)

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👨‍💻 Author

[Amr Alaa , Amor296]
Football Data Enthusiast | Python Developer