Women's Tennis Performance Analysis

Are You Better Off Focusing on Court Surface, Break Point Conversion Rate, or Your Dominant Hand to Win in Tennis? Insights from Women’s Grand Slam Matches (2018-2022)

This project performs a statistical analysis of women's tennis performance, focusing on the relationship between various factors (such as court surface) and player success. Specifically, the analysis addresses research questions such as:

• Does the type of court surface affect the number of wins per player?
• Are certain players more successful on specific court surfaces?
• How does the surface type correlate with match outcomes?

Table of Contents

• Introduction
• Data
• Research Questions
• Analysis Methods
• Prerequisites
• Installation/How to Run
• Repository Structure
• Results
• License

Introduction

This project uses statistical methods to analyze women's tennis data to explore key research questions in the sport. The goal is to provide insights into factors that may influence performance and guide further research.

Data

Data sources include official tennis tournament databases and player performance statistics. The analysis uses WTA grand slam matches data from 2018 to 2022, containing detailed match statistics including:

• Player information (rank, handedness)
• Match conditions (surface type)
• Performance metrics (aces, break points, etc.)

Research Questions

This analysis explores several key questions about women's tennis performance:

1. Is Court Surface associated with Number of Aces per Match?
2. Is Player Rank associated with Break-point Conversion Rate?
3. Is Player Handedness associated with Match Outcome?

Analysis Methods

The study employs various statistical methods including:

• ANOVA tests
• Chi-square tests of independence
• Post-hoc analyses
• Descriptive statistics and data visualization

Requirements

To run this project, you'll need:

• R Studio(version 4.x or higher)
• Required packages (listed in requirements.txt)

Installation/How to Run

1. Clone the repository:

git clone https://github.com/marzafiee/Womens-Tennis-Performance-Analysis.git
cd tennis-performance-analysis

2. Install required packages:

# Install required R packages
install.packages(c("readr", "descr", "stats", "dplyr", "knitr", "ggplot2"))

3. Alternative package installation using requirements file:

pip install -r requirements.txt

4. Knit the analysis/code script in R Studio:

# Open the R Markdown file in RStudio and click the "Knit" button
# Or use the following command in R console:
rmarkdown::render("WTA_R_Code.Rmd")

Repository Structure

• WTA_R_Code.Rmd: R Markdown document with code and documentation
• requirements.txt: List of required packages

Results

Key findings from the analysis include:

• Court surface significantly affects player win rates.
• Certain players show a strong preference for specific surfaces.
• The analysis provides a model for predicting match outcomes based on surface type.

License

This project is licensed under the MIT License - see the LICENSE file for details.