When I was in elementary school, I remember Googling various football statistics, running down to my parents, and telling them, for example, “Ben Roethlisberger had 4,328 passing yards in 2009!” I played football for eight years from elementary school to high school, and I was good with working with numbers. I found that sports analytics was a great combination of the two. In high school, I entered a sports analytics competition, where my project was to determine what would happen if onside kicks in football would be replaced with a 4th down and 15, and I absolutely loved it. Now, I’m fascinated with data science as a whole– being able to make a computer do something that we could never imagine doing as humans is an amazing feeling for me.
Since the sports analytics competition, I’ve been doing anything and everything I could related to data science. Some of the research I’m currently working on includes sports team values, kickstarter data, and sportswashing (for example, Qatar holding the World Cup amidst some controversial political issues). I also had a job this year working for a company called Scouting Heroes, where I logged basic statistics for the FSU football team. (More information on what the data I collected was for can be found at https://simplebet.io/nfl.html.) I’ve also worked on creating data visualizations based on football data. For example, this past summer I created over 20 graphs that can be found at https://twitter.com/a_graph_a_day .
In one of my classes, one of my (now) coworkers, William-Elijah Clark, posted the opening for the STEM Libraries Data Fellowship in the class’s GroupMe, and I was eager to apply. Something I’m super excited for with this Data Fellowship is that I really want to translate my skills into some real-world experience. Instead of simply creating graphs or finding statistics on my own, I want to have a tangible impact with regard to data. I hope to be able to help students out with their needs or be able to have my data analysis translate into a decision being made that affects people. In a way, it would signify that my hard work on data analysis is paying off.
One of the projects that I’m super interested in working on as a Data Fellow is the use of Jupyter Books to assist users in learning more about how to code and analyze data as a whole. By offering interactive code blocks and giving users the opportunity to run code on their own, they may be more willing to learn about the data analysis techniques used. Furthermore, I hope that by implementing sports analytics examples, specifically football, people who are interested in sports may be more willing to learn how to use data analysis techniques with respect to sports.
As a whole, I’m very excited to learn more about data analysis techniques here at the FSU libraries and as well as apply my skills to tangibly help others at Florida State as a whole.
This blog post was written by Sahil Chugani, STEM Data Fellow at FSU Libraries.
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