This project aims to examine football match data from European league matches and use AI/ML to determine how influential referees' decisions are on the outcome of the match. These decisions include detecting fouls, cards, free kicks, corners, off-sides, out-of-bounds, usage of VAR, etc.
These positions can often make-or-break a team's chances of scoring, and it is important to demonstrate this for reliability and tactical purposes. If match officials are too influential and make incorrect calls, this could hurt a team significantly. If match officials are too influential with their awarding of set-pieces, a manager could see this as an opportunity to capitalize by focusing their team on these set-pieces.
This topic has been discussed in households, bars, stadiums, and board meetings for quite some time now. It would be valuable to see a data science approach to this question, and understand the implications that lie therein.
Feel free to read the finalized results in the unofficial writeup.
This project was started as the final assignment for STA325 at Duke University
This data uses the Open Database License and was not created by me.