Introduction

American Football is the nation’s highest grossing and most popular sport, with 37% of American adults selecting it as their preferred sport. However, its popularity and financial success is pushed even further by fantasy football.

In fantasy football, fans act as the owners of their own imaginary football teams and assemble rosters composed of real NFL players. The fans track the statistics of these real players across the season to determine the success of their fantasy teams.

Before the rise of fantasy football, most fans would only watch their favorite team’s games. But now, each and every game across the NFL has become critical to the success of their fantasy teams.

Fantasy football is a $70 billion industry, with the biggest companies involved in the practice being media giants like ESPN, Yahoo, and CBS. Newer companies, such as FanDuel which started in 2009, began with fantasy football as the cornerstone of their business, and are now worth billions of dollars. The popularity of fantasy football is also driven by the huge prize money involved. DraftKings expects to pay out close to $2 billion in prizes, and some fantasy football games pay out as much as $10 million a week.

There are many different strategies to create a winning fantasy roster. One of the most popular methods is tracking player data. This project shows the creation of a data frame from web scraping and analyzing football players for the ideal fantasy team picks.