RefInsight is an analytics project that examines football refereeing patterns using historical match data, focusing on officiating consistency, home–away bias, and the impact of VAR through structured statistical analysis and interactive visualizations.
This repository contains a python script that calculates the posterior probability for a team playing in Premier League to win it's next match against a random opponent, when the referee that will be responsible for the match is known. Data set locations (https://datahub.io/sports-data/english-premier-league) / (https://github.com/terrydolan/lfc)
An end-to-end data project that scrapes and analyzes 5,900+ NCAA basketball games to map referee travel, build structured datasets, and visualize insights through an R Shiny dashboard. Built entirely without an API using Python and R.
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