Integrated Sports Analytics Platform for Performance & Tactics
We built an integrated sports analytics platform that combines wearable sensors, video streams and contextual data to give coaches and performance staff a complete, real-time view of player performance. Our AI models fuse positional, biomechanical and game-event information into clear KPIs, injury risk indicators and tactical insights that are accessible from a single interface.
Instead of jumping between GPS dashboards, video tools, spreadsheets and medical notes, teams get one coherent story about each player and each session. The platform tracks load, intensity, movement quality, posture and tactical behaviour, and connects them to outcomes such as chances created, defensive actions or fatigue markers.
This foundation supports a wide range of use cases: posture and technique refinement, tactical analysis, injury prevention, return-to-play monitoring and long-term development planning across multiple seasons.
What this solves
Modern teams generate massive amounts of data: sensor readings from wearables, tracking data from cameras, event tags from analysts, wellness surveys, medical notes and match metadata. Most of this lives in separate systems that don’t talk to each other, forcing coaches and analysts to manually copy, reconcile and interpret information. Critical patterns can be missed, especially those that span biomechanics, load and tactical context.
Our platform bridges these silos by ingesting and synchronising data from sensors, video and existing tools into one timeline for each player and session. Coaches can see how posture and movement mechanics relate to speed, accelerations, decelerations, contacts, game situations and tactical roles. Automated reports highlight overload, asymmetries, unusual patterns and tactical tendencies, making it easier to adjust training plans, line-ups and in-game decisions.
How we did it
We designed a modular architecture that ingests data from wearable sensors (IMUs, GPS, heart rate), video camera systems and third-party event tagging tools. A synchronisation layer aligns all streams on a common time base, so any frame of video can be matched with physical load and positional metrics. Our AI models then compute derived KPIs such as acceleration profiles, intensity zones, posture and movement quality indicators, along with tactical features like spacing, pressing intensity and passing options.
The analytics engine feeds a web and mobile interface where users can explore sessions, filter by player or position group, compare training vs. match load and drill down into specific events. Injury-prevention modules flag combinations of risk factors, while tactical dashboards visualise patterns such as pressing triggers, build-up structures or transition behaviour. The platform is built to be sport-agnostic, with configurable templates that can be adapted for football, basketball, handball, rugby and other team sports where movement, posture and tactics are tightly connected.
Task
Develop an integrated sports analytics platform that fuses wearable sensor data, video footage and contextual information to provide a complete view of player performance, support injury prevention and deliver actionable tactical analysis to coaches and performance staff.