Data Engineering
Transforming raw sports feeds into proprietary mathematical assets. We clean, model, and deploy custom football intelligence architectures to power elite decision-making pipelines.
Proprietary Engineering Focus
New Metrics
Developing structural formulas that quantify previously unmeasured phases of play. Raw signals are standardized and calculated into action-ready, granular metrics.
- Set-piece trajectory velocity tracking
- Defensive line destabilization rates
- Pass-lane opening mechanics
- High-pressure escape efficiency
Value Models
Translating structural actions into quantifiable currency. These mathematical models value player outputs based on context, spatial control, and situational efficiency.
- Corner Kick Expected Generation (xG)
- Spatial Territory Worth Evaluations
- Recruitment ROI Performance Mapping
- Isolated Action Risk vs Reward Yields
Predictive Models
Engineering robust algorithmic projections. By calculating historical team behaviors alongside real-time variations, these models forecast events before they happen.
- Pre-Match Set-Piece Tendency forecasting
- Opponent Defensive Shift Projections
- Player Aging Decay & Growth Trajectories
- Match-state Simulation Engine Analysis
Engineered Data Inputs
Our computational structures integrate multiple raw data types to build a single, cohesive analytics layer.
Event Data
On-ball micro-actions
Tracking Data
XY Spatial Vectors
Temporal Data
Match-phase Chronology
Context Data
Squad, Pitch & Weather