Poisson Modeling and Predicting English Premier League Goal Scoring

TL;DR

This paper demonstrates that goal scoring in the English Premier League follows Poisson and related distributions, and uses Poisson regression to predict season outcomes with high accuracy.

Contribution

It verifies the applicability of Poisson models to Premier League goal scoring and introduces a predictive framework for season outcomes using Poisson regression.

Findings

Poisson process accurately models goal scoring

Poisson regression effectively predicts season outcomes

Simulation results provide insights into team standings and relegation risks

Abstract

The English Premier League is well-known for being not only one of the most popular professional sports leagues in the world, but also one of the toughest competitions to predict. The first purpose of this research was to verify the consistency between goal scoring in the English Premier League and the Poisson process; specifically, the relationships between the number of goals scored in a match and the Poisson distribution, the time between goals throughout the course of a season and the exponential distribution, and the time location of goals during football games and the continuous uniform distribution. We found that the Poisson process and the three probability distributions accurately describe Premier League goal scoring. In addition, Poisson regression was utilized to predict outcomes for a Premier League season, using different sets of season data and with a large number of simulations being involved. We examined and compared various soccer metrics from our simulation results, including an English club's chances of being the champions, finishing in the top four and bottom three, and relegation points.