Football is increasingly shaped by data and AI. Using freely available statistics, we'll explore how basic economic and analytical models can predict football match outcomes. Starting from simple techniques, this talk shows what anyone can do to forecast who might lift the Premier League trophy in May 2027.
Economics studies the allocation of scarce resources, and in particular the decisions dictating those allocations. This may sound quite dry, so applying this to particular situations is helpful. Arsenal, Liverpool, Manchester City, perhaps Chelsea and even at a stretch Manchester United planned for the current Premier League season with one goal in mind - to win the Premier League. Managers were switched or retained, playing staff released or recruited, training began in earnest even while the FIFA World Cup was taking place across North America. How do clubs make such decisions? We are in the midst of a data revolution alongside the AI revolution sweeping the global economy, and though football often resists such changes, a game that is as fiercely competitive, with fans demanding everything is done to gain each competitive edge is bound to be as close to the frontier as it can be. In this talk though we’ll start from basics. What could you do with your own computer, given the amount of freely available data out there? We’ll build some basic models of predicting football match outcomes, and look at what they can tell us about who will be crowned Premier League champions in May 2027.
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