Choosing the right university is one of the biggest decisions that someone can make in their early life. There are multiple different factors that play a role in shaping the future for the individual and open up a series of doors, this is magnified for students looking to play college sports, specifically college football. When deciding on a college football program to go to, a lot of students sway their decisions one way or another based on amenities such as fancy locker rooms and the best weight rooms. The flashy additions are something that a lot of student athletes take into consideration but these aren’t always the best choices for collegiate athletes. The first step in the process of deciding which college program to commit to is to decide what is important to you, this could be academics, going to the National Football League, tuition, class size, if they have your major, ect… For this analysis I wanted to see what college football team is the best program for someone to go to if they wanted to expand their career into the National Football League. By analyzing the National Football League Statistics dataset which I found on Kaggle I was able to find a few common trends in the National Football League.
The first step and challenge that I found in my analysis was to go through and find what I wanted the data to tell me, the National Football League Statistics datasets that were presented on Kaggle had 19 individual datasets and each of those had 26 columns and over 4000 rows making it incredibly hard for the data to tell a specific story. From this I decided that the most exciting data would be the basic National Football League statistics which included categories such as age, college, experience, height, position, and weight. Since this data is useless though without joining it with any other data set, I went through and joined the data from the basic National Football League statistics with quarterback statistics as well as running back, wide receiver, and tight end statistics. From combining these datasets I was able to get a grasp on what colleges were producing the most National Football League drafts and what positions they were. I was also able to derive what college program had the most touchdowns in the National Football League.
The first analysis that I wanted to find out was which college was sending the most recruits to the National Football League. To do this I ran a value_counts function to find out which college had the most recruits and plot this on Tableau using the data gathered from the python notebook I had created.