Arsenal have an "AI dossier" which is reportedly powering Mikel Arteta's Premier League title pursuit, with the manager being assisted with input on transfers, tactics and even injuries. This quiet revolution is an attempt to build the most technologically advanced operation in English football. They have computer models humming with millions of data points to predict problems before they happen.
AI takes over Arsenal HQ
According to the the Gunners have rapidly expanded their data science department, investing heavily in artificial intelligence infrastructure. Competing with Europe’s elite clubs is no mean task, and Arsenal’s leadership have made it clear that they believe staying competitive requires not just talent on the pitch, but intelligence behind the scenes. A well-timed rotation could stop a key player from breaking down. One scouting insight could produce a bargain where others see no value. Arteta has already hinted, albeit cautiously, that the club’s adoption of AI is already underway.
"It’s in use already for many things and many processes that can help not just a team but an organisation as well," he said. "It will improve and it will give us good insight, or things at least to think about. I’m not an expert but it’s a valuable tool. We have developed certain things that in our opinion can help us to understand ourselves better and evaluate what we do and what we can improve."
Advertisement(C)Getty ImagesGunners have in-house performance models
The biggest breakthroughs at the club's London Colney base come through their tailor-made performance models, which are AI-driven programs designed internally by Arsenal's data scientists. Every day, enormous volumes of information are collected, including GPS sprint maps, recovery times, energy outputs, bio-mechanical readings, match actions, and even micro-movements during training drills. Unlike traditional analysis, which often relies on video clips and subjective assessments, these systems digest tens of thousands of data points from each session. The models then learn patterns about fatigue signals, mechanical inefficiencies, and subtle warning signs with a level of granularity no human eye could catch. The shift is profound as Arsenal are now preparing for what is about to happen, and not reacting to what has just happened.
Profiling every player: A live, evolving human data map
One major branch of Arsenal’s AI system is individual profiling. Every player, right from academy prospects to first-team starters, has a dynamic profile that logs sprint mechanics, joint stress patterns, muscle fatigue responses and changes under load. This gives Arsenal the ability to personalise training. No two players respond to stress in the same way, and machine learning allows coaches to tailor workloads to match bodies rather than the other way around. These profiles also highlight areas for improvement. Weaknesses can be addressed before they impact performance, which will allow players to train smarter, not harder.
The most critical area of Arsenal’s AI application is injury prevention. William Saliba’s back problem derailed Arsenal’s 2022-23 title charge, while last season Kai Havertz’s hamstring injury forced Mikel Merino into an improvised striker role. The models identify clues such as tiny drops in acceleration, altered stride patterns, and minor imbalances that can signal impending muscle injuries. Before a congested fixture, run the system flags players with elevated fatigue risk, which helps Arteta to make an informed decision.
Arsenal’s analytics tools also parse opposition patterns frame by frame. Machine learning evaluates how full-backs behave under pressure, how midfield shapes morph in transitions, and where passing lanes appear during pressing triggers. This gives Arteta’s staff the opportunity to build game plans not on hunches, but on probability maps.
GettyRecruitment rebuilt: Finding players who fit Arteta's blueprint
AI is also reshaping Arsenal’s transfer strategy. Beyond traditional metrics like goals or tackles, Arsenal’s models study adaptability across roles, physical intensity benchmarks, tactical compatibility with Arteta’s system, and log behavioural data from hundreds of match scenarios. Every role now has a detailed blueprint, such as what the physical output should look like, how quickly a player must transition, how he presses, and how he receives the ball under pressure. This tech-driven approach allows Arsenal to find undervalued players who might not shine in traditional stats but are ideal fits for Arteta’s structure. Arsenal’s technological leap is bold, advanced and path-breaking. However, whether it can end their 22-year wait for a Premier League title remains to be seen.