Code: EDI-2019-7-IGT

Domain: Gaming


Insight into wager-based PC and mobile gaming sessions for different business users and derivation of player behaviour models.

Proposed by


International Game Technology (IGT) is a multinational gaming company that produces slot machines and other gaming technology. The company is headquartered in London.

The company is engaged in operating and providing an integrated portfolio of technology products and services across various gaming markets, including lottery management services, online lotteries, electronic gaming machines, sports betting, interactive gaming and commercial services.

IGT’s commitment to responsible gaming reflects its core values. Its goals include promoting protective tools to prevent problem gambling. The Company incorporates responsible gaming tools into its products and services to minimize potential risks, and works with appropriate stakeholders on responsible gaming issues to ensure the Company follows best practices and is aware of current responsible gaming research as it relates to IGT’s operations.


The challenge is about analysing gaming data to provide insight into wager-based PC and mobile gaming sessions for different business users and derivation of player behaviour models.

One of the key questions in the government regulated lottery and gaming industry is how to derive actionable insight from large amounts of game play and wagering data. IGT needs to understand player behaviour to responsibly improve game’s design, enhance player experience, and personalize or adapt game play.

Taking into account that IGT needs to provide insight to different business users (e.g., game designers, content managers, and marketing researchers), a successful analysis of gaming data sets, should allow IGT to: 1) identify common player styles and the unique characteristics of each player style, 2) to dig deeper into the data related to each style by exploring the corresponding data to discover interesting patterns that allow business users to better understand player behaviours.



The challenge has the following sample datasets available for download. Note that these datasets are fully anonymized and compliant with the E.U. General Data Protection Regulation and other relevant privacy legislation. 

Expected outcomes

  1. A scalable solution that supports ad-hoc queries to explore the data related to player styles in real-time or near real-time.
  2. Provide accurate identification of player behaviour through visualizations. Accuracy level still unknown and would like to use the historical data and subject matter experts to validate IGT’s assumptions.

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