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Football Analysis Program

This Python script, named football_analysis.py, is designed to analyze football match data and make predictions based on the provided data. It includes functions for calculating team strengths, simulating tournaments, and finding hot favorites.

To use this program effectively, follow these steps:

Make sure you have the necessary Python libraries installed. You can install them using pip if they are not already installed: pip install pandas numpy

python football_analysis.py The script will analyze the provided football match data, calculate team strengths, simulate tournaments, and find hot favorites.

convert_str(a) This function converts input values a into a numerical score. It is used to convert data from the CSV files into match scores.

The script loads football match data from CSV files (fd.csv, fd2015.csv, fd2016.csv) and processes it for analysis. Team Strength Calculation

The script calculates team strengths and stores them in the graph variable as a 2D list.

uniform_distri(x, max_margin, min_margin): Calculates a uniform distribution value for a given score. intimidation_factor(team1_str, team2_str): Calculates an intimidation factor between two teams based on their strengths. who_will_win(team1_str, team2_str): Predicts the winner between two teams based on a combination of past results and intimidation factors.

choose_two_teams(available_players): Randomly selects two teams from the list of available players. simulate_tournament(): Simulates a tournament and determines the winner.

find_hot_favorites(): Simulates multiple tournaments to find the teams with the most wins, indicating the hot favorites.

Contributions to this script are welcome. If you want to contribute, please fork the repository, make your changes, and submit a pull request.

For questions or support, please contact devanshu3 at [email protected].