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Showing posts from June, 2020

Application of PCA in data driven recruitment

When I first started to learn R, after 4/5 weeks I decided to answer a recruitment based question concerning Oxford United and the right back position. This lead me to creating a piece utilising Principal Component Analysis (PCA) at a very basic level, to see if there is a quick and efficient way to categorise and analyse player styles. Can this then form the basis of an indicator highlighting those players with similar playing styles and such, play a role in replacing players/finding players to fit a specific system? My original piece is here . Its always weird to read stuff back, but I will try to build on this! There is a quick and brief explanation into PCA there along with a few other links to PCA within football. Since I produced the above, Mark Carey has done some great work applying PCA to midfielders in the top 5 leagues. This is an area that has aways intrigued me, however after some limited work in professional football I'm certain PCA can play a large role in gui

Using Wyscout in R

It's pretty clear that within a football setting, clubs are largely using the same data. Most clubs will be using Wyscout/Instat...others may have access to StatsBomb and Metrica. None the less, data quality discussion aside, Wyscout is used predominantly to quickly gain an overview of players (both from a video and data perspective). This dovetails with people up-skilling through the lockdown, taking various courses and becoming increasingly proficient in languages such as R and Python. This is a big asset within football! Those that have read previously know that I am self teaching R and sharing any learnings that may be of interest around football analytics to others. By no means am I an authority on this, I've just found something that works, that might help others...I'm always happy to be corrected! Anyway, the aim is to: - Download Wyscout data - Import into R - Clean the headers - Re-format the data from "wide" to "long" format - Some e