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Editorial illustration of a blue footballer surrounded by teammates on a pitch made from layered scouting sheets.
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Build or buy? Inside a football operating system.

AI makes software easier to start. Football makes it hard to finish.

Jonathan Hazut, Co-founder and Chief Technology Officer

A Serie A club was developing its own platform when another club hired its lead developer. The club told us:

“We have the car, but right now we’re missing the driver. This is a world where you have to keep updating and work on the details every day, because things change constantly. A finished, perfect product doesn’t exist.”

A Serie A club

A LaLiga club put the other side of the dilemma just as clearly:

“If I buy something from outside, it has to be very differentiating. Something I can’t develop, or something I can develop but don’t have the capacity to, either to build or to maintain.”

A LaLiga club

Everyone is building now

AI has turned build or buy into the question of the moment. Tools such as Claude and ChatGPT now write code and help maintain software, and companies in every industry are asking whether the systems they license could be built in-house within months. For a software company, that can be a sound bet. Building systems is what it does.

Football clubs are asking the same question. From inside a club, the answer looks very different.

A club is built to win matches

A club’s product is the result at the weekend. Its best people are hired to play, coach, scout, analyze and prepare, not to run a software company. Budgets move with results, transfer windows, qualification for continental competitions and relegation. Staff change when the manager or sporting director changes. Salaries for non-playing staff rarely compete with what technology companies pay the same engineers. And the next match is often three to five days away.

Clubs do have something no outside vendor starts with: the clearest understanding of what they need. Marquee was built on that understanding, through a feedback loop with leading practitioners and clubs in world football from day one. Today it spans the entire sporting side of a club, from internal analysis and squad management through player recruitment and all the way to match preparation.

Why clubs consider building

Most internal projects start with too much data and too little time. Data arrives from several providers, each with its own identifiers and definitions. Clubs pay for all of it, yet most use only 4 to 15 percent, because nobody has the hours to turn the rest into answers. Meanwhile, one small department supports recruitment, squad management, opposition analysis, post-match review and set-piece work.

The second reason is fit. Many clubs doubt that an outside product can work the way they think about football. A platform built for everyone, they fear, fits no one exactly.

Both concerns are fair. But building and maintaining a platform for years claims the same time and people the club is short of, and it is a financial bet on a product that may or may not work out. Here is what that commitment involves, starting with fit.

Built around each club’s football

Every Marquee client works in its own environment. During onboarding, we build the club’s sporting DNA profile: a detailed picture of how it thinks about football, how it plays, and where it wants to go this season and beyond.

That profile goes well beyond formation, possession phases and out-of-possession behavior. It defines each position by the type of player the club wants there: his archetype, his role within that archetype, what he contributes beyond his position, and the attributes the club values in that role. If a club uses two different types of winger, the system knows the difference.

Every output is read through that profile, and because football never stands still, neither does the profile. A new manager, a new owner or a change in the season’s targets can reshape what a club needs. Clubs can adjust their sporting DNA at any point in the season, and the platform recalibrates to match.

Fit also covers the work a club has already done. Marquee supports the club’s internal team rather than replacing it. Because the platform is data agnostic, internal models, scout grades and reports can be brought into the club’s environment, giving its analysts and engineers a foundation to build on.

One player, two clubs

Two clubs are considering the same midfielder. One is a dominant, possession-based team in its league’s top three. The other sits mid-table in a different league and plays through transitions. The player is in a third league, at a team that plays neither way.

His numbers describe what he does there, not whether he suits either club. That is where xFit, our one-to-ten Expected Club Fit score, comes in. It answers three questions against each club’s sporting DNA. System fit: does he play the football the team plays, and if not, can we predict that he will adapt? Squad fit: does he add something the squad is missing, and what is the trade-off with the player he would replace in the lineup? Projected output: how will he perform in his new team, given league strength, his individual qualities and team synergy, including potential partnerships with players he has never shared a pitch with?

The analysis separates individual quality from team strength and playing choice. A player may look better because of his teammates. A team that rarely plays long passes may be choosing not to. Marquee makes those distinctions automatically and clears out the noise before the club commits its limited video-analysis and live-scouting time. It narrows the field, and the judgment stays with the club. Our Squad Fit article explains how the squad’s needs shape that assessment.

From a brief, Marquee produces a shortlist of relevant players in seconds. From a flagged player, it generates a full scout report in under a minute.

A midfielder from League C assessed for two clubs: a dominant possession team in League A and a mid-table transition team in League B, each with its own xFit assessment.
One midfielder, two club contexts. The same player, assessed against two different football questions. Illustrative club contexts.

The same context drives squad management and match preparation. Before any shortlist exists, Marquee analyzes what the squad produces and what is missing. That matters because recruitment meetings bring competing priorities into one room. The owner wants a headline attacking signing. A scout backs the talent he has followed for months. The coach, under pressure for results, wants a defender. An objective evidence base lets the brief start from the team’s needs.

On the match side, the questions change every few days: how the next opponent will line up, where its threat comes from, which match-ups to target and how it defends set pieces. Pre-match, post-match and set-piece reports answer them in the club’s own context. Marq, our AI agent, lets staff explore all of this in football language. A sporting director can clarify a role, add a constraint or challenge an interpretation, and Marq refines its context. Every insight is traceable to its source, and every model output carries a confidence level.

Building this internally means building every one of these workflows, and the reasoning that connects them.

Beneath the answer

Marquee runs a pipeline of proprietary AI and machine-learning models in production, trained, validated and already supporting clubs around the world. Together they read the game, understand the player, the environment and the match, and support the final decision. Most use neural networks, including transformers and graph neural networks.

We cover 90 competitions and train on a cross-provider database drawing from eight data vendors. Coverage depth varies by competition and season. Many clubs buy 20 to 50 competitions from one or two providers, because broader access is expensive.

Scale brings its own problems. Records from different providers must refer to the same player and match, and similarly named metrics must keep their actual meaning, or a larger dataset teaches a model the wrong distinction. Models also depend on each other: change a learned player representation and the assessments built on it can shift, even when their own code has not.

Evaluation is where much of the research effort goes. We test on seasons the models have not seen and run ablation studies, removing components to understand what each contributes. For a question like club fit, deciding what counts as a good answer is itself part of the research. Evaluation continues after release, as new data and model updates raise new questions.

Every cycle, including experiments that never reach production, costs compute, time and expert review. Those cycles have already run behind the models a club can use today. Building internally means licensing the data, hiring the research team and funding every cycle from scratch.

Nothing stays still

The January transfer window changes squads, and the data has to keep up. A transfer can change a player’s league, provider identifiers and available coverage, and the system must not mistake a change in what can be observed for a change in the player.

Suppliers move too. Providers update their glossaries, new metrics arrive every month, and a club may switch providers overnight because the next annual fee no longer suits it. Each change reaches field meanings, identity matching and every analysis that uses them.

Marquee’s data-agnostic foundation absorbs these changes across the product. Our multi-tenant architecture keeps each club’s data and sporting DNA separate on a shared engineering foundation, and Kubernetes-managed deployments preserve every club’s configuration as models and software change.

For an internal build, this is the part that rarely appears in the original plan. It lasts as long as the system does.

The fixture list sets the deadline

Marquee’s match reports are ready the moment the providers’ data arrives, and a post-match report is a click away. Analysts spend the short window between matches applying their expertise, not digesting raw data.

We can have a club live in 48 hours. Building a platform of comparable breadth internally can take a season or more, and the fixture list has never been especially patient with a development backlog.

Protect the thinking behind the decision

A club’s shortlist, tactical principles and recruitment logic are competitive assets. Using AI and off-the-shelf large language models (LLMs) without exposing that knowledge is a serious engineering responsibility. Licensed football data also comes with strict contractual limits on its use in public models. Meanwhile, attackers now use AI to accelerate their own work.

Marquee has completed a SOC 2 Type II examination, in which an independent auditor tested our controls and how they operated over time. Tenant isolation separates club environments, encrypted storage protects data at rest, and access reviews, patching and audit logs are routine parts of running the service.

What we learn across clubs, such as which questions recur and which explanations need to be clearer, improves the product for every client. Each club’s sporting DNA, methods and data stay in its own environment. Club data remains the club’s, and is not used to train models for other organizations.

Any evaluation should establish which information can reach each model provider, and on what retention and training terms. Building internally means taking responsibility for those boundaries and the security work that maintains them.

It takes a team

Backed by investors who know the game and share our vision, including Axel Springer and APEX, we invest millions of dollars a year in the product: research, engineering, training compute and data.

A comparable internal effort needs software engineers, data scientists, DevOps specialists and a chief information security officer (CISO) or equivalent security leadership. At a club, those people also face the football department’s daily demands.

Continuity matters as much as hiring. When a system depends on one or two people, a single departure, often alongside a manager, can stall it. The club still owns the code, but it may have lost the only person who knows why it works. In the Serie A club’s words, the car is there, but the driver has gone.

The real cost of building

The club considered building because its people had too little time. Everything above would draw on those same people: scoping, hiring, licensing data, training and testing models, securing the system, then maintaining it through every glossary update, provider switch and change of manager. Every hour spent on the pipeline is an hour not spent on the next opponent or the next signing.

The return depends on scope, adoption and continuity. A project that absorbs the club’s scarce capacity for a season or more can defeat its own purpose. The comparison has to include the football work delayed along the way. None of this means throwing away what a club has built. The club puts trained models, connected data and ongoing platform engineering to work now, and points its own team at what is distinctive about its football.

Build or buy? Compare the continuing work.

Compare an internal platform of similar scope with the capability already operating at Marquee.

Comparison table of building internally versus using Marquee across time to first output, models, training, data, security, key-person risk, provider changes and ongoing commitment.
Build or buy: the continuing responsibilities of each route.

In either route, the club owns its football decisions and judges whether the analysis helps.

Bring us a football question

A recruitment brief, an upcoming opponent, a match to review or a set-piece problem. We’ll show you how Marquee approaches the work, so the build-or-buy conversation starts with something concrete.

Get in touch

About Marquee

Marquee turns football data into decision-ready insights in seconds, unifying external and internal data and filtering it through each club’s sporting DNA. Professional clubs use Marquee for recruitment, squad planning and analytics. Learn more at themarquee.ai.

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