Find out how your football team will do this season, before a ball has been kicked
02 August 2018
Football economists at the University of Reading have predicted the most likely score in every Premier League and Championship game on the opening weekend of the season.
The most likely score in each game is calculated using a complex metric that analyses historic results for each team, as well as things like form, league position and even the day of the week the match is played. This gives an estimated number of goals for both sides in any given fixture, allowing the most likely result and score to be given.
Using predicted scores for every round of fixtures throughout the 2018/19 season, they have also predicted the finishing positions for each of the 20 clubs in the Premier League and 24 in the Championship.
See predicted scores and league positions here >>>
Tests comparing actual results from previous years with what would have been predicted by the model shows it is competitive with, and often beats, predictions made by experts over the course of a season.
Dr James Reade, Associate Professor in the Department of Economics at the University of Reading, said: “With just days to go before the new football season kicks off, fans up and down the country are excitedly wondering how their team will fare, and if this could be their year. This new model at least offers an early indication while we wait for the real action to start, and allows fans to start dreaming – or some fans anyway.”
Dr Carl Singleton, Lecturer in Economics at the University of Reading, said: “No prediction is ever 100% accurate, as there are so many uncertainties such as team selection or unexpected events during matches. This model was born out of curiosity over whether a computer could do a better job than fans like us, or experts in the media, at predicting scores. The signs are that it can.”
Find out more about the model and see more predictions at https://econscorecast.wordpress.com/
The predictions produced by the model are only the most likely outcomes (rounded to the nearest decimal place), and show the chance of it occurring as a percentage. Please note that some teams are predicted to finish in the same position - this is because it was the most common finishing position for both teams after multiple simulations of the season.
They are therefore not 100% accurate and intended to provide a rough guide to the most likely results, which can be influenced by several factors, such as team selection, and unpredictable events during a match. The University of Reading does not promote gambling and does not intend for the predictions to be used as a guide for this purpose.