Hockey Skaters Stats Analysis

Statistical analysis of National Hockey League players, using a dataset from MoneyPuck.

Goals

• Explore the dataset to understand its structure and variables.
• Apply descriptive and inferential statistical techniques.
• Experiment with data visualization approaches.
• Prepare potential predictive models (future stage).

Dataset

• Source: MoneyPuck.com
• Type: NHL skaters statistics for the 2024/25 season.
• Format: CSV.

Environment

This project is designed to be run in a Jupyter Notebook environment for interactive data analysis and visualization.

Technologies Used

• Language: Python 3
• Main Libraries:
  • pandas – data manipulation and analysis.
  • numpy – numerical computations and array handling.
  • matplotlib / seaborn – data visualization.
  • empiricaldist – working with empirical distributions.
  • scipy – advanced statistical functions.
  • statsmodels – statistical modeling and regression.
  • scikit-learn – machine learning and predictive modeling.

Project Status

🚧 In Development
Currently working on:

• Data cleaning and preparation.
• Descriptive statistical analysis.
• Initial data visualization.

How to Run

1. Clone the repository:

   git clone https://github.com/thedanicode24/moneypuck-data.git
   cd moneypuck-data

2. Install dependencies:

   pip install -r requirements.txt

References

• Think Stats: Exploratory Data Analysis in Python, 3rd Edition
• Money Puck

License

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