Typologies of Online Gambling Behaviours in Great Britain: Insights from Geographic Smart Data Analysis

Session Title

Gambling Research: Measurement & Online Patterns

Presentation Type

Paper Presentation

Start Date

28-5-2026 12:00 AM

Abstract

This paper offers a unique opportunity to advance understanding of online gambling by moving beyond traditional survey-based evidence towards large-scale behavioural data. While surveys remain essential, they often provide only partial insight into gambling behaviours. Drawing on detailed transactional and registration data from approximately 1.2 million online gambling accounts in Great Britain (GB) during 2022, the study provides a behaviour-led view of how individuals engage with online gambling platforms over time. Supplied by a major British gambling operator, the data capture verified customer activity across a full year, enabling the identification of distinct patterns of play. Using dimensionality reduction and clustering techniques, the paper identifies twelve distinct gambling behaviour profiles. A small-area estimation approach then translates these profiles into neighbourhood-level estimates across GB by combining operator data with Census population data and national gambling prevalence benchmarks, producing calibrated local estimates of how different forms of online gambling engagement are distributed across communities. The study is currently in preparation for submission to a peer-reviewed journal (as of 09/01/26). An open-access data product is available, including [interactive web maps](https://mapmaker.geods.ac.uk/#/gambling-behaviours?d=11110000&m=bg5&lon=-1.6984&lat=52.5475&zoom=5.86), behavioural summaries and full methodological [documentation](https://data.geods.ac.uk/dataset/great-britain-gambling-behaviours-classification-gb2c-lad-geography), with a more [geographically granular version](https://data.geods.ac.uk/dataset/great-britain-gambling-behaviours-classification-gb2c-lsoa-geography) available to approved users.

Author Bios

Lecturer at the University of Liverpool Management School. Interested in consumer data research, geo-demographics and the geographies of gambling behaviours. Experienced in analysing large-scale behavioural datasets and developing applied data products, including the Great Britain Gambling Behaviours Classification (GB2C). Trained as a quantitative human geographer, with a PhD in Social Data Science from University College London.

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May 28th, 12:00 AM

Typologies of Online Gambling Behaviours in Great Britain: Insights from Geographic Smart Data Analysis

This paper offers a unique opportunity to advance understanding of online gambling by moving beyond traditional survey-based evidence towards large-scale behavioural data. While surveys remain essential, they often provide only partial insight into gambling behaviours. Drawing on detailed transactional and registration data from approximately 1.2 million online gambling accounts in Great Britain (GB) during 2022, the study provides a behaviour-led view of how individuals engage with online gambling platforms over time. Supplied by a major British gambling operator, the data capture verified customer activity across a full year, enabling the identification of distinct patterns of play. Using dimensionality reduction and clustering techniques, the paper identifies twelve distinct gambling behaviour profiles. A small-area estimation approach then translates these profiles into neighbourhood-level estimates across GB by combining operator data with Census population data and national gambling prevalence benchmarks, producing calibrated local estimates of how different forms of online gambling engagement are distributed across communities. The study is currently in preparation for submission to a peer-reviewed journal (as of 09/01/26). An open-access data product is available, including [interactive web maps](https://mapmaker.geods.ac.uk/#/gambling-behaviours?d=11110000&m=bg5&lon=-1.6984&lat=52.5475&zoom=5.86), behavioural summaries and full methodological [documentation](https://data.geods.ac.uk/dataset/great-britain-gambling-behaviours-classification-gb2c-lad-geography), with a more [geographically granular version](https://data.geods.ac.uk/dataset/great-britain-gambling-behaviours-classification-gb2c-lsoa-geography) available to approved users.