Sportian Introduces AI Agents to Enhance Team Performance

Sportian, the sports division of Globant, has launched a new suite of AI agents integrated into Sportian Performance, the company’s match data and video analysis platform, to help sports organizations and their fans understand and respond to changing game states.

These AI-driven tools will provide deeper, real-time insights into a player’s on-field impact, deliver predictions to prompt tactical changes, and monitor live data to assure against betting irregularities.

With the help of machine learning, computer vision, and predictive analytics, the new agents are designed to extract clearer insights from the vast quantity of eventing and tracking data that is collected real-time in every match, delivering predictive analytics that help coaching and executive teams to act sooner while also keeping fans engaged.

The AI tools are assigned to four key areas and use machine learning algorithms, computer vision and deep learning to refine the way match data is analyzed and presented.

• Attacking Potential: A metric that offers a new way to measure attacking players’ impact beyond goals and assists. By analyzing movement trajectories, positioning tendencies, and passing dynamics using deep learning models trained on extensive match footage, this tool offers a more holistic view of a player’s offensive contributions, thereby helping to quantify their impact on the game.
• Real-Time Performance Charts: This agent processes live match data to deliver new content visualizing shifting game states, detecting a change in team formations, passing patterns, or player workload for example. The agent will share this information with coaches to help them respond tactically, and can also share approved content with fans via social networks.
• Betting Controls: Using deep learning, this agent continuously analyzes betting market data alongside match events to detect potential anomalies indicative of match-fixing. Through anomaly detection techniques and historical data comparisons, the system provides match organizers with early-warning indicators of suspicious activity.
• Goal Probability: This evolution of the xGoal metric assesses historic and game state variables—including shot angle, player scoring records, defensive pressure, and goalkeeper positioning—to calculate a more accurate probability of a goal being scored. Trained on a deep repository of historical match data, this predictive model dynamically adjusts based on hundreds of in-game conditions, generating a % metric within match broadcasts. Already implemented in LALIGA, this metric offers a new level of real-time game analysis.

These new features are developed as part of Globant Sportian’s AI core, which underpins its suite of products and services. Driven by its data and AI team, Globant Sportian works alongside its global client base to trial new AI tools that can tackle specific sports challenges and help the industry’s development, with recent advancements in areas such as ticketing, sponsorship, and fan personalization

Sportian Performance is used by sports organizations across the world to generate a competitive edge, with AI playing an increasingly central role in unlocking new insights that can be used to reach new standards of coaching.

Gonzalo Zarza, Chief Data Officer at Sportian, commented:

“The need for AI in sports isn’t just to collect more data—it’s about generating more meaningful insights that help to raise the sporting spectacle and generate growth. These new agents are part of our mission to deliver quicker, sharper data to all of our clients that goes beyond the surface-level metrics, giving sports the tools they need to refine their approach on and off the pitch.”