Determining the level of ability of football teams by dynamic ratings based on the relative discrepancies in scores between adversaries
Open accessAbstract
A rating system provides relative measures of superiority between adversaries. We propose a novel and simple approach, which we call pi-rating, for dynamically rating Association Football teams solely on the basis of the relative discrepancies in scores through relevant match instances. The pi-rating system is applicable to any other sport where the score is considered as a good indicator for prediction purposes, as well as determining the relative performances between adversaries. In an attempt to examine how well the ratings capture a team’s performance, we have a) assessed them against two recently proposed football ELO rating variants and b) used them as the basis of a football betting strategy against published market odds. The results show that the pi-ratings outperform considerably the widely accepted ELO ratings and, perhaps more importantly, demonstrate profitability over a period of five English Premier League seasons (2007/2008–2011/2012), even allowing for the bookmakers’ built-in profit margin. This is the first academic study to demonstrate profitability against market odds using such a relatively simple technique, and the resulting pi-ratings can be incorporated as parameters into other more sophisticated models in an attempt to further enhance forecasting capability.
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- Authors
- Constantinou, A. C., & Fenton, N. E.
- Affiliations
- Queen Mary University of London (GB)
- Corresponding author
- Constantinou, Anthony Costa
- Venue
- Journal of Quantitative Analysis in Sports
- Publisher
- Walter de Gruyter GmbH
- Published
- 2013-03-30
- Volume
- 9
- Issue
- 1
- Pages
- 37-50
- ISSN
- 1559-0410 (ISSN-L)
- 2194-6388
- OpenAlex
- W2112428422
- Cited by
- 72
- References
- 1
- Citations by year
- 2026: 10 · 2025: 7 · 2024: 7 · 2023: 5 · 2022: 3 · 2021: 6 · 2020: 7 · 2019: 5 · 2018: 9 · 2017: 3 · 2015: 2 · 2014: 5 · 2013: 3
- FWCI
- 7.83
- Type
- journal article
- Language
- en
- Open access
- green
- qmro.qmul.ac.uk
- Locations
- Journal of Quantitative Analysis in Sports (publishedVersion)
- Queen Mary Research Online (Queen Mary University of London) (submittedVersion)
- Funders
- Engineering and Physical Sciences Research Council
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Sports Analytics and Performance
- Health Sciences › Medicine › Orthopedics and Sports Medicine › Sports Performance and Training
- Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
- Keywords
- dynamic rating, betting odds, English Premier League, match outcome prediction, team performance comparison
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