Why Data Teams Are Critical for Modern Gaming Success

From understanding player behavior to refining game mechanics, the insights derived from data analytics can make or break a game’s performance. Yet success requires more than just collecting numbers—it depends on building cohesive, skilled teams that can prioritize high-value projects amid competing demands.

We sat down with Mehmet Turan, a veteran of Electronic Arts and 2K Games, to share his perspective on the challenges and strategies for leading impactful data teams in gaming.

The Biggest Challenges Facing Gaming Data Teams

Over the last 15 years, Mehmet has consistently seen three hurdles:

• Talent acquisition: Competing with tech giants makes hiring data talent tough.

• Data infrastructure: Legacy systems often aren’t built with data science in mind.

• Project prioritization: With endless requests, choosing the right projects is critical.

Talent Acquisition: Competing for the Best Minds

Gaming companies are in constant competition with broader tech firms for top data scientists. While recognition of data’s importance is improving, building world-class data teams remains a challenge for most studios.

Data Infrastructure and Its Limitations

Many existing infrastructures serve multiple business functions beyond data science. This misalignment can slow down analytics teams and reduce their effectiveness, especially when data engineering support is minimal.

Prioritizing Projects That Deliver Value

Deciding which projects to pursue requires balancing measurability, impact on profit and loss, and autonomy. Mehmet stresses that teams must be disciplined in focusing on initiatives that deliver quantifiable results while reducing reliance on external dependencies.

The Importance of Autonomy in Data Science Teams

High dependency on other teams often leads to delays and frustration. Mehmet emphasizes that autonomy in data collection, analysis, and operationalization allows teams to move faster and deliver results with greater control.

Communication and Collaboration Across Teams

Transparent communication is key to aligning data projects with broader company goals. Mehmet advises setting expectations clearly at the start of the year and maintaining ongoing collaboration with partner teams to ensure alignment and support.

Case Study: Combating Fraud and Toxicity with Machine Learning

While working on a major sports franchise, Mehmet’s team developed a semi-automated machine learning solution to detect virtual currency farming and fraudulent activity. By breaking the problem into discovery, labeling, detection, and action, they built a scalable solution that surpassed manual approaches.

The project improved detection accuracy, freed teams from manual monitoring, and fostered greater trust with leadership, opening the door for future innovative data-driven projects.

Proving Value to Executive Leadership

Communicating results in terms of business impact is essential. Mehmet demonstrated how his team’s anti-fraud solution reduced losses and justified expanding his team, underscoring the value of tying data science directly to company performance.

Lessons for Leading Data Teams in Gaming

• Invest in attracting and retaining talent despite competition.

• Build infrastructure tailored for data science.

• Prioritize projects that are measurable and high-impact.

• Ensure autonomy for faster execution.

• Communicate value clearly to executives and partners.

About Mehmet Turan

Mehmet Turan –
LinkedIn

Mehmet is a data professional and leader in the video game industry with more than 13 years of experience. With a PhD in Computer Information Systems, he has held diverse roles in leading gaming companies such as EA and 2K Games, where he established and managed data functions from inception. As the VP of Data and Analytics, he led large teams in data science, engineering and analytics. Currently, he serves as the Head of Data and Analytics at Horizon Blockchain Games, driving insights in this innovative space.