EGM Occupancy Analysis: Contextual Modeling and Visualization for Machine Usage Patterns and Optimized Player Engagement

This project will analyze Electronic Gaming Machine (EGM) occupancy patterns and player behavior using anonymous spin-level data to optimize machine usage and support data-driven decision-making. By examining how players select machines based on availability, time of day, and traffic conditions, the research will generate actionable insights for International Game Technology (IGT) and its casino partners. IGT is a global leader in gaming technology, operating in over 100 countries and offering EGMs, lottery systems, sports betting platforms, and digital gaming solutions. In Canada, IGT supplies casinos and gaming operators with hardware, software, and analytics tools. Its advanced data infrastructure collects detailed machine performance and player behavior data in real time, enabling operational optimization and compliance. Despite this, transforming large-scale spin-level data into targeted, actionable insights remains challenging. IGT aims to better understand player movement between machines, identify popular games during low-traffic periods, model conditional game selection probabilities, and assess the impact of high-traffic conditions on occupancy. Within the 4-month project window, the emphasis will be on exploratory data analysis (EDA) and visualizations—such as time-based heatmaps and grid charts—to address these needs. The project will strengthen IGT’s ability to optimize gaming floor layouts, machine placement, and game offerings, potentially increasing player engagement, dwell time, and revenue. Visual analytics will support quicker, evidence-based decisions, improving operational efficiency for both IGT and its partners. Beyond immediate business gains, the work contributes to the advancement of Canadian gaming analytics expertise, fostering innovation in a sector that generates significant economic impact through employment, taxation, and tourism.

Faculty Supervisor:

Hung Cao

Student:

Partner:

IGT

Discipline:

Computer science

Sector:

Arts, entertainment and recreation; Information and cultural industries

University:

University of New Brunswick

Program: