Football, Python and R

A few weeks ago, I was introduced to FC Python on Twitter and followed up a link to FC Python’s blog.

I was delighted to read on the blog landing page:

FC Python is a project that aims to put accessible resources for learning basic Python, programming & data skills in the hands of people interested in sport. Whether you are a Sports Science student, a coach, or anyone with a passing interest in football – the tools shown across these pages will help you to get started with programming and using data with Python.

I think this is a wonderful approach to take.

Rob Carroll hosted an FC Python blog post (Why Programming Matters) on his Video Analyst blog on 9 February that extended the reach and appeal of FC Python’s work.

In that post, FC Python observes:

There has never been a more important time for Sports Science students to take responsibility for their own development through learning programming skills. With over 10,000 students (and growing) graduating from sports-related courses every year, the problems facing job seekers are well-documented. Taking the time to learn is by far the best investment that you can make to ensure that you’ll be towards the top of the application pile.

I agree absolutely with these sentiments.

My approach in recent years has been to create, aggregate and share open educational resources. My WikiEducator course, Sport Informatics and Analytics, has an R component. I have added a Python page too, that points to FC Python’s inspirational sharing of Python programming and data skills.

My advocacy for Python is in part a lament.

When I worked at the Australian Institute of Sport, my colleague Bob Buckley was a Python specialist. I missed an important opportunity to accelerate and champion Bob’s work. It took me a decade to catch up with where he was in 2006. Bob moved on from the AIS shortly after I left. He is using his skills now as a Computational Genomic Specialist at John Curtin School of Medical Research at the Australian National University.

Shortly after finding FC Python, I was introduced to Tyler Bosch from the University of Minnesota.

I am sorry not to have found Tyler sooner. I am grateful to Jamie Coles for the introduction. Like FC Python, Tyler has a profound educational commitment to sharing. He ran an Introduction course for R in January and some of his resources are shared on Patreon.

I do try to monitor developments in R and in recent months have been guided by Mara Averick’s links. I shared some of these links in a post for the Irish Performance Analysis Exchange.

Yesterday, I discovered that FC Python had nurtured an R response, FC rSTATS. There is a blog site to accompany the Twitter account. On the home page is this acknowledgement:

The R conversion of @FC_Python. Not associated with the original but have given a thumbs up to convert their resources.

This is another important step in open sharing. It also provides a crosswalk for anyone interested in learning R and Python with association football data as the domain example.

The authors of FC Python and FC rSTATS have chosen to remain anonymous. This is a profound commitment to the essence of open educational resources. Each of us can make our own judgements about the probity of the material shared on each site.

For my part, I am in awe of what they are doing … and Tyler too.

Photo Credit

Racing ahead (Keith Lyons, CC BY 4.0)