NFL In-Game Player Interaction Network Analysis
For my Network Science course, I created this capstone paper analyzing in-game player interactions in NFL games.
Overview
This project applies network science methodologies to understand how NFL players interact during games. By modeling player interactions as a network, we can identify key players, analyze team cohesion, and discover patterns that traditional statistics might miss.
Key Findings
The paper covers:
- Network Construction: Building player interaction networks from play-by-play data
- Key Player Identification: Using centrality metrics to identify influential players
- Modularity Analysis: Examining how players cluster into functional groups
- Team Dynamics: Understanding how team structure affects performance
Methodology
The analysis uses Python for data processing and network construction, with Gephi for visualization and RStudio for statistical analysis. The project demonstrates how network science can provide unique insights into team sports.