Football Analytics with Python & R

Chapter 9. Advanced Tools and Next Steps

This book has focused on the basics of football analytics using Python and R. We personally use both on a regular basis. However, we also use tools beyond these two programming languages. For people who want to keep growing, you will need to leave your comfort zone. This chapter provides an overview of other tools we use. We start with modeling tools that we use but have not mentioned yet, either because the topics are too advanced or because we could not find public data that would easily allow you to code along.

We then move on to computer tools. The topics are both disjointed and interwoven at the same time: you can learn one skill independently, but often, using one skill works best with other skills. As a football comparison, a linebacker needs to be able to defend the run, rush the passer, and cover players who are running pass routes, often in the same series of a game. Some skills (such as the ability to read a play) and player traits (such as speed) will help with all three linebacker situations, but they are often drilled separately. The most valuable players are great at all three.

This chapter is based on our experiences working as data scientists as well as an article Richard wrote for natural resource managers (“Paths to Computational Fluency for Natural Resource Educators, Researchers, and Managers”). We suggest you learn the topics in the order we present them, and we list reasons in Table 9-1. Once you gain some comfort ...