This repository contains a UFC prediction model built to forecast the outcomes of UFC fights. The model is developed using machine learning techniques and aims to provide insights and predictions for upcoming UFC matches.
- Develop a predictive model for UFC fight outcomes and methods.
- Utilize machine learning algorithms to analyze historical UFC data.
- Provide accurate predictions for upcoming UFC fights.
- Evaluate the performance and accuracy of the prediction model.
- Explore different approaches and techniques to improve the model's performance.
The data for this project is collected using ParseHub, a web scraping tool, to extract UFC data from "ufcstats.com". The collected data includes information about fighters, event details, fight outcomes, statistical metrics, and other relevant features.
The collected data is then manually cleaned and processed to ensure consistency and accuracy. Categorical variables are encoded or transformed as necessary, and missing values are handled appropriately. Numerical features are scaled or normalized to ensure fair comparisons.
Please note that this is an ongoing project, and more detailed information, code examples, and documentation will be added to the repository soon.