Welcome to the "Player Analysis - Babar Azam" repository. This project focuses on analyzing the performance of Babar Azam, the current captain of the Pakistan Cricket Team, using a dataset containing key statistical metrics.
- Introduction
- Data Sources
- Data Description
- Data Fields
- Analysis
- Sneak Peek
- Usage
- How to Get Started
- Contributing
- License
- Contact Me
Babar Azam, often regarded as one of the finest contemporary batsmen in the world, has made significant contributions to the Pakistan Cricket Team. This project aims to analyze his performance using a dataset of key statistics, providing insights into his batting prowess.
The dataset used in this project has been sourced from reliable cricket statistics providers and may include information from international matches, domestic leagues, and more. Please refer to the specific data source for further details.
The dataset contains Babar Azam's performance metrics, including runs scored, boundaries (4s and 6s), and strike rate, against various opposition teams. It offers a snapshot of his batting performance in different match scenarios.
The dataset includes the following key fields:
- Opposition: The name of the opposing cricket team.
- Runs: The total runs scored by Babar Azam in the match.
- 4s: The number of boundaries hit for four runs.
- 6s: The number of sixes hit for six runs.
- Strike Rate: The strike rate is calculated as (Runs / Balls Faced) * 100.
The analysis in this project includes:
- Visualizations and insights into Babar Azam's performance against different opposition teams.
- Trends and patterns in his runs, boundaries, and strike rate.
- Statistical comparisons and observations.
This is the sneak peek of the Babar Azam Runs
This project is a valuable resource for cricket enthusiasts, analysts, and fans interested in exploring Babar Azam's batting performance. You can use the dataset and analysis to gain a deeper understanding of his strengths and contributions to the Pakistan Cricket Team.
- Clone the Repository: Start by cloning this repository to your local machine using the following command:
1. Clone the Repository:
git clone https://github.com/Mujtaba-12390//player-analysis-Babar-Azam.git
2. Install Dependencies: Ensure you have Jupyter Notebook installed. If not, you can install it using:
pip install jupyter
3. Launch Jupyter Notebook:
jupyter notebook
4. New way to kick-start How to kick-start a data science project
Old way 🥴
- import libraries you'll need
- dealing with import-related errors
- search the correct import statement on Google
(repeat the cycle, depending on the project's complexity)
New way 🤓
- pip install pyforest
PyForet gives you an unfair advantage to jumpstart any data science projects With just one line of code, you can import the 40 most commonly used Python libraries Libraries are loaded on-demand, consuming memory space only when a specific function or method is invoked This saves you time and ensures that your code doesn't slow down due to unnecessary imports I can't believe I wasted so much time hunting down imports statements!
5. Install all Python libraries: You must install Python and its libraries. If not, you can install it using:
pip install pyforest
6. Explore the Analysis: Dive into the analysis by opening the Babar Azam Data Visualization.ipynb file in your preferred Python environment.
We welcome contributions from the cricket community. If you have additional data sources, statistical analysis, or insights related to Babar Azam's performance, please feel free to contribute to this project.
This dataset and analysis are made available under an open-source license (if applicable). Please review the specific license details in the dataset folder for more information on usage and distribution.
If you have questions, or suggestions, or want to discuss this project further, please feel free to reach out. I welcome collaboration and feedback.
- Email: Email Address
- Buy My Services: Get services
- GitHub: GitHub Profile
- LinkedIn: My LinkedIn Profile
- Medium Articles: Medium Profile
I look forward to connecting with you and exploring the fascinating world of data together.
Thank you for joining us on this journey of exploring Babar Azam's cricketing talent. Feel free to delve into the data, contribute your insights, and enjoy the world of cricket analysis. 🏏 #CricketAnalysis #BabarAzam #PakistanCricket #CricketStats #DataDrivenDecisions