A smart method of developing football odds using Markov chain process: a case study of FC Barcelona against Real Madrid FC

Ohakwe, Johnson ORCID: https://orcid.org/0009-0003-1608-5280, Ofori, Derrick, Ifeagwu, Canice Chimdike, Mishra, Bhuphesh Kumar and Ogbajie, Daniel Emeka (2026) A smart method of developing football odds using Markov chain process: a case study of FC Barcelona against Real Madrid FC. Journal of Quantitative Analysis in Sports. doi:10.1515/jqas-2025-0038 (In Press)

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Abstract

This study utilises the Markov Chain process to generate football odds, focusing on historic La Liga matches between FC Barcelona and Real Madrid. Using data from 93 encounters, it categorises matches based on home and away performances. Transition matrices derived from historical results calculate probabilities for match outcomes (win, draw, loss) and over/under goal markets, which are then converted into betting odds. Findings reveal Barcelona’s strong home advantage, with a 55 % probability of winning (odds: 1.82), while Real Madrid has a 59 % probability at home (odds: 1.69). However, both teams experience a significant drop when playing away – Barcelona with 24 % (odds: 4.17) and Real Madrid with 23 % (odds: 4.35). The study also shows a higher likelihood of over 1.5 and 2.5 goals in their matches. This research highlights the Markov Chain process as an effective tool for improving football odds accuracy, offering a data-driven alternative to subjective betting models.

Item Type:	Article
Article Type:	Article
Uncontrolled Keywords:	football; sports analytics; Markov chain process; long-run probability; stochastic modelling; odds
Subjects:	G Geography. Anthropology. Recreation > GV Recreation Leisure G Geography. Anthropology. Recreation > GV Recreation Leisure > GV557 Sports G Geography. Anthropology. Recreation > GV Recreation Leisure > GV557 Sports > GV861 Ball games: Baseball, football, golf, etc. H Social Sciences > HA Statistics
Divisions:	Schools and Research Institutes > School of Education, Health and Sciences
Depositing User:	Charlotte Crutchlow
Date Deposited:	02 Jun 2026 09:31
Last Modified:	02 Jun 2026 09:45
URI:	https://eprints.glos.ac.uk/id/eprint/16320

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