La Liga Analytics Dashboard

This repository contains an interactive dashboard designed to provide an in-depth analysis of team performance, player contributions, and transfer strategies within the La Liga football league. The project uses R and Shiny to visualize various metrics and trends, offering insights to analysts, coaches, and fans alike.

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Contents

Main Files

1. DOCUMENTATION.docx

   • Detailed project documentation, including the problem description, design process, and implementation details.

2. LALIGA_RSHINY.R

   • Main R script for the Shiny dashboard implementation.
   • Contains data preprocessing, interactive visualization components, and dashboard structure.

3. LaLiga_Stadiums.csv

   • Dataset containing stadium locations for all La Liga teams.

4. combined_data_laliga.csv

   • Core dataset with match results and performance statistics from 2014 to 2020.

5. primera-division.csv_2010_2020.csv

   • Dataset with player transfer details from 2010 to 2020.

6. filtered_players_stats.csv

   • Preprocessed dataset with player performance metrics.

7. player_id_mapping.csv

   • Maps player IDs to their respective names.

8. season_mapping.csv

   • Maps season IDs to season names, renaming "Primera Division" to "La Liga."

9. es_10km.shp

   • Shapefile for visualizing geographical data on La Liga stadium locations.

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Dashboard Structure

The interactive dashboard is divided into five main tabs:

1. Introduction

   • Overview of the project objectives and insights.
   • Interactive introductory plot showcasing team performance metrics.

2. Teams Performance Dashboard

   • Geographic and temporal analysis of team performance metrics (e.g., goals, wins, losses).
   • Interactive map and bar chart for comparing teams across metrics and seasons.

3. Player Performance Dashboard

   • Analysis of individual player statistics (e.g., goals, assists, dribbles).
   • Focus on top-performing players and goalkeepers across seasons.

4. Transfers Dashboard

   • Analysis of club spending and revenue in the transfer market.
   • Highlights the top 10 transfers for the top 3 spending clubs.

5. Conclusion

   • Summarizes key findings and provides recommendations.

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Setup and Usage

Prerequisites

• Install R and RStudio.
• Install required R packages using the following script (included in LALIGA_RSHINY.R):

necessary_packages <- c("shiny", "shinydashboard", "dplyr", "ggplot2", "lubridate", "readr", "tidyr", "stringr", "plotly", "sf", "leaflet", "ggrepel", "shinyjs")

for (package in necessary_packages) {
  if (!requireNamespace(package, quietly = TRUE)) {
    install.packages(package)
  }
}

Steps to Run

1. Clone the repository:

   git clone https://github.com/your-username/LaLiga-Dashboard.git

2. Open LALIGA_RSHINY.R in RStudio.
3. Run the script to start the Shiny dashboard.
4. Open the provided localhost URL in your browser to view the dashboard.

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Key Features

• Interactive Visualizations: Dropdowns, sliders, and tooltips for an engaging user experience.
• Geospatial Analysis: Choropleth maps showing team performance by region.
• Player Insights: Top performers in goals, assists, and goalkeeping.
• Financial Analysis: Detailed view of club spending and revenue in the transfer market.

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Data Sources

• La Liga Stadium Data
• Primera Division Match Data (2010-2020)
• Player Performance Data

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Contributions

Contributions are welcome! Feel free to submit pull requests for enhancements or bug fixes. Contact me at aadhikary252000@gmail.com

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License

This project is licensed under GNU (General Public License). See the LICENSE file for details.