Bundesliga 3D Data Challenge

Solution Space 

You will find all information regarding the goal, the requirements and the potential partner profile. 

Target 

The goal of this challenge is to unlock the value of 3D tracking data by developing solutions that meaningfully support the DFL and its ecosystem.  

Participants are encouraged to propose concepts or prototypes that demonstrate new insights, new formats, or new products that were not feasible with the previous 2D data infrastructure. 

The aim is to identify solutions that can be validated in early-stage pilots and potentially evolve into scalable products, tools or services within the DFL’s broader technological landscape. 

Potential Application Areas 

3D tracking data opens a broad spectrum of possible applications. The following areas are inspirational, not limiting.  For orientation, solutions can generally be grouped into two categories: 

A. New Visualisations:  Use cases that transform 3D data into innovative visual formats, such as: 

• volumetric or 3D tactical views 
• enhanced replay or highlight formats 
• immersive or interactive fan experiences 

B. New Computations: Use cases that derive new team- or player-related performance metrics or insights from the 3D positional data: 

• body posture, orientation or first-touch quality 
• space control, pressure zones or micro-events 
• tactical decision-making indicators 
• enriched or real-time analytical triggers 

These solutions can target different parts of the DFL ecosystem, including: 

• Performance & Clubs: insights for coaches, analysts, talent development or scouting 
• Media: enhanced storytelling, new broadcast or digital content formats 
• Betting Partner: enriched live data, predictive triggers or micro-event layers 
• Technology Partners (e.g. AWS, ServiceNow): computational enhancements, new KPIs 
• DFL Digital Sports (Bundesliga App/Website): interactive or educational fan-facing experiences 

Participants may suggest any meaningful application that respects the solution requirements and fits the DFL ecosystem. 

Solution Requirements 

Must-have criteria 

• Clearly define the end user (e.g. analyst, coach, broadcaster, partner, fan) and the concrete value created. 
• Be feasible based on the available data attributes and describe concretely how the 3D data will be used (input → processing → output → insight) 
• All solutions must be designed in a way that respects the DFL’s media rights structure and competitive boundaries. Specific constraints will be clarified with selected teams during validation 
• Consider integration into realistic workflows of the intended stakeholder groups. 
• Show adaptability for scaling or integration within existing DFL/STS product environments. 
• a long-term vision beyond the initial prototype 

Not in scope 

• Medical or health-related diagnostics 
• Use cases requiring private or unavailable data like Biometric, training or off-match data or player-provided inputs, apps, devices or wearables. 

Stakeholder-specific 

• Clubs & Performance: Must respect practical workflows of match analysts and coaching staff. 
• Media Partners (e.g. Sky, DAZN): Solutions must complement, not substitute, existing broadcast products. Commercialisation pathways depend on alignment with rights holders. 
• Betting / Data Operators: Solutions must comply with integrity, latency and auditability requirements. 
• DFL Digital Sports (Bundesliga App / Website): Solutions must enhance fan understanding without violating rights or competitive boundaries. 

Partner Requirements 

• Ability to work with structured 3D tracking datasets and produce functional prototypes or demonstrators. 
• Teams must be open to co-creation with DFL, clubs, and STS, as workflows and feasibility often depend on domain-specific realities 
• Transparency regarding team composition, maturity level, past references and comparable projects. 
• Early-stage teams are welcome if they can credibly demonstrate technical capability and a path to prototype.