Author: Ben Dixon et al (2026)
Journal: BMJ Open Sport & Exercise Medicine

AI generated summary

The article explores how modern football has entered an era of data abundance, yet still struggles to consistently convert that data into better decisions. Clubs now collect vast quantities of information from GPS, tracking systems, event data and video, but raw data alone does not improve performance. The central challenge, the article argues, is moving effectively through the Data–Information–Knowledge–Wisdom (DIKW) hierarchy.

At the base of this hierarchy is data: millions of unprocessed data points such as positions, velocities, accelerations and events. On its own, data lacks meaning. The article highlights that many clubs fall into the trap of accumulating more data without first clarifying what problems they are trying to solve. This leads to noise, confusion and analysis overload rather than insight.

The next step is turning data into information by adding structure and context. This involves filtering, aggregating and visualising data so that it begins to describe what is happening on the pitch. Examples include summarising physical outputs, linking event data to specific game phases, or synchronising tracking data with video. At this stage, the quality of processing, definitions and consistency becomes critical, as poor data handling can easily distort conclusions.

Knowledge emerges when information is interpreted through football expertise and domain understanding. The article stresses that analysts do not work in isolation: coaches, scouts and performance staff are essential in shaping the right questions and validating interpretations. Knowledge is built by identifying patterns, trends and relationships that are meaningful within a tactical, physical or technical framework, rather than relying on generic metrics or league-wide benchmarks.

The highest level, wisdom, is where competitive advantage is created. Wisdom is not just knowing what happened or why, but understanding what to do next. This involves applying knowledge to real-world decisions in recruitment, game preparation, training design or player development. The article emphasises that wisdom requires integration across departments, alignment with the club’s playing philosophy, and the confidence to simplify complex analyses into clear, actionable messages.

Throughout the article, contributors from professional clubs and technology providers underline the importance of holistic thinking. Data, video and subjective insight should complement rather than compete with each other. Analysts must balance technical sophistication with clarity, ensuring that insights are timely, relevant and understandable to decision-makers.

In conclusion, the article argues that success in football analytics is not about having the most data or the most advanced models, but about building robust processes that consistently translate data into wisdom. Clubs that master this transformation are better equipped to make informed decisions, reduce uncertainty and gain a sustainable edge in an increasingly data-driven game.