The 6th Wave of Game Data

The impact today on how games are developed, maintained and generate revenue, is enormous. But game data can do more, and we are just now seeing the emergence of a 6th wave of game data, which seeks to push the use of behavioural data beyond the game, employing data to support creators, inform businesses and assist societally beneficial research.

[This article is an excerpt from this white paper from the Digital Observatory Research Cluster]

What are Game Data?

Game data is a somewhat nebulous concept but broadly refers to any data derived from game systems or the context in that games are played. This includes transactional data and data from our communities, used for example in sentiment analysis. We typically call this telemetry data. Additionally, we collect data from the agents of the game system, so we can monitor the behaviour and performance of e.g., AI bots. All of this is used to support decision-making in the industry – and it does so well.

Game Data Science

Game data are now used for a great variety of purposes within the games industry and academia. The field of game data science, or game analytics, has emerged over the past decade or so to support the use of game data across industry and academia. There is, however, no commonly accepted definition of what game data science is, but basically, game data science combines multiple disciplines towards extracting meaningful insights from game data.

While we are glossing over a considerable amount of complexity, it is safe to say that data are now foundational not just for the creation of games but also for how we manage them and make a living from them.

The History of Game Data

If we should try to summarize the roughly 20+ years of history in the use of game data – and game data science – we can identify 5 waves, with a 6th currently emerging.

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1. Data for User Research: The first wave stretches from perhaps the late 90s to the mid-2000s, which was a period when the use of telemetry data was relatively rare.

2. Rise of Social Media: The second wave arrived with the rise of social media, smartphones and the introduction of the Free-to-Play business strategy.

3. Enter the Algorithm: The third wave saw the introduction of machine learning. Anders/I was heavily involved in this wave. This was a renaissance period where data collection exploded, and the introduction of machine learning meant we could derive insights from data that were not possible before.

4. Looking for Why: The fourth wave saw game data science working closely in hand with game user research to broaden the scope of what we were doing, integrating psychological methods and cognitive theories to move beyond just looking at what players do, but also to draw inferences about why.

5. Maturity: The fifth wave is the one we are currently exiting. Covering the past 5-7 years, this wave saw the introduction of advanced machine learning and AI in the context of industrial game data science, and sophisticated tool generation. Interestingly, the use of game data to build experiences around games also proliferated, notably in esports where data are used by virtually everyone in the community.

6. Beyond the Game: The sixth wave is emerging. For the 6th wave of game data use, we are seeing new approaches towards transforming the business of games, supporting creators and audiences, and even using game data to understand human behaviour and benefit society.

The 6th Wave of Game Data

The 6th wave of game data is expanding analytics outside the confines of specific games and recognizing that experiences built around games are equally important to the user experience and the financial success of games. Furthermore, to map lessons learned from one game to other games in the portfolio. There is a big push happening toward building future virtual economies and figuring out what kinds of tools we need in a situation where game economies become interlaced and take on the complexity of real-world economic systems.

The 6th wave is also seeing much more detailed views on players and creators emerging, with traditional models and expectations about who players are and what they do giving way to much more sophisticated profiling and real-time adaptation.

For creators and players, game data are beginning to be used in combination with machine learning and creative AI to provide new insights into gameplay, new ways to interact with games and new ways to build experiences – and make a living – in the space inside and around games. The continued release of game data, combined with the emergence of walled gardens, is giving creators opportunities that did not exist a few years ago.

On the research side, we are seeing the emergence of the combination of game data with data from real-world contexts to generate socially positive research. For example, understanding human behaviour at huge scales, exploring economies and spending, connecting games and well-being, or studying human psychology.


With the realization that games are an integral part of society and that the experiences around games can be just as important as games themselves, comes a new frontier that has not been much explored, but holds substantial potential.

The data generated from games inform us not only about how we play games but also increasingly about the world beyond games. We have barely started exploring how we can use game data to understand social interaction, decision-making, wealth, emotional well-being and more.

For the industry and its creators, the 6th wave of game data offers unprecedented insights into how our users play our games. What works and what does not? Game data can inform our design and offers unprecedented ways of shaping the user experience around the individual and the context.

Despite its history of two decades, game data science has barely scraped the tip of the iceberg, and the 6th wave in many ways feels more like the beginning of a new paradigm for the use of game data than merely a new chapter.

This article is an excerpt from this white paper from the Digital Observatory Research Cluster.