Tennis Betting - LISA EXAM PROJECT

This project is built in Python and it uses machine learning to create a prediction model for tennis matches (between 2013-2020).

The project is based on realizing a prediction algorithm to “beat bookmakers” and gaining an advantage in making choices while betting on matches. We choose tennis as a sport where betting in for some reasons:

1. Variables in tennis are easier analyzable than other sports since we have found the elements of a good betting-strategy and this ones are more distinguishable and “evident” than other sports (for example the surface, the winning streak) ;
2. Tennis is a zero-sum-game and this is a prerogative for applying powerful features that we have decided to use such as Elo rating for example;
3. The datasets on the internet that we have found are well-made.

In this project we will first of all import the dataset and clean the data, then we will proceed by adding new features to improve the accuracy of the predictions. After a fine tune of the best classificator, we will conclude with a study on how to maximize the return on investment for a betting strategy.

How to run

Just open and run the Python Notebook file "main.ipynb"

For more informations about the project, features, prediction models and conclusion please refer to the pdf report.