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Turning Claude into a Football Opposition Analyst

Session Track: Data Intelligence

Session Time:

Session description

Analysis in sports is changing. Advanced statistics like Wins Above Replacement (WAR) or Expected Goals (xG) are making their way into TV punditry and conversations in bars. But the people who need the information the most, ex-professionals and coaches without a background in statistics, often shun it. Not because they don't see the value but because the language is impenetrable, the underlying data is overwhelming, and the insights are difficult to translate. Generative AI provides an opportunity to bridge the gap. In this talk, I'll share how I used Model Context Protocol (MCP) to turn Anthropic's Claude Desktop into a football opposition analyst by providing access to team and player performance event data and in turn lower the barriers so anyone can turn a sea of numbers into actions. This talk will cover: - How MCP enables AI to access and interpret domain-specific knowledge - Real examples of AI-generated football insights in action

Speaker

photo of Adam Cowley

Adam Cowley

Developer Advocate, Neo4j

Adam Cowley is a Staff Developer Advocate at Neo4j with two decades of experience spanning software development, data analysis, and product ownership. At Neo4j, he leads developer educational initiatives, including GraphAcademy, Neo4j’s free, self-paced learning platform. Drawing on his analytical mindset and cross-functional background—from data analyst to product owner—he champions data-driven solutions. Currently, he is passionate about Generative AI and the potential for personalised educational experiences for developers and data scientists. Outside of work, you’ll find him exploring football analytics or wielding a cue over a baize table.