AI in football — innovation, risks & the role of human judgement

Artificial intelligence (AI) is reshaping how football is played, judged, managed and experienced. From offside calls and player tracking to recruitment, integrity and reputation management, AI is now embedded across every layer of the sport. 

Here, Georgina Rothwell explores how AI is influencing the game on and off the pitch, highlighting the real-world examples of its impact and the risks that come with it. 

The rise of automated decisions & why VAR still matters

One of the most visible uses of AI in football is in officiating. After years of debate over VAR, the Premier League introduced semi-automated offside technology (SAOT) for the 2024/25 season. This system uses optical tracking and computer vision to speed up offside decisions, aiming to cut review times to around 30 seconds. It’s a big step towards the use of AI in the sport but isn’t fully automated as humans are still needed in the process to validate key elements.

Even with SAOT, VAR remains the safety net for edge cases and system failures. If the technology struggles with occlusion, subjective involvement or suffers from a technical outage, VAR will step in to keep the game moving. This layered approach reflects a broader lesson that while AI can enhance decision-making, it’s not infallible.

Football learned this the hard way during the infamous Luis Díaz offside error in a 2023 Liverpool FC match against Tottenham Hotspur. The mistake wasn’t caused by a technical fault but by a human communication breakdown while using AI-assisted systems. It underscored the need for robust protocols and clear checks when deploying AI in high-stakes environments like elite football.

Tracking players — performance data & privacy tensions

Beyond officiating, AI is transforming player monitoring. Clubs now combine optical tracking with wearables that capture GPS, accelerometery and sometimes biometric data. FIFA’s electronic performance and tracking systems (EPTS) programme certifies these devices for safety and accuracy but the data collected from the device is likely to be sensitive. Movement profiles and health indicators fall under special category personal data, meaning that when the Club is collecting and processing this data, they must ensure compliance with the data protections legislation, balancing fairness, transparency and privacy against the purposes — especially if wellness metrics start influencing selection or disciplinary decisions.

UK data protection guidance warns against using tech for solely automated decisions that can have significant effects on individuals where there are no safeguards in pace. Instead, it’s expected that safeguards including meaningful human review and clear governance will be implemented. In short, innovation is welcome but it needs guardrails to balance the use of AI with an individuals’ rights under the data protection legislation.

Recruitment — the glow-up & its blind spots

AI-driven recruitment tools promise to uncover undervalued talent and optimise squad building. First, they aggregate vast amounts of data from multiple sources including match performance stats, tracking data, injury history and market trends. This creates a richer picture of a player than traditional scouting reports alone. Next, machine learning models identify patterns between certain metrics and future success. For example, a player’s pressing intensity or progressive pass rate might predict suitability for a high-press system — even if headline stats like goals and assists look modest.

Clubs also use these tools to benchmark players against ideal role profiles. If a team needs a left-back who excels in overlapping runs and recovery speed, AI can scan thousands of players to find those who fit the brief. This is where market efficiency comes in. By spotting undervalued qualities, AI can highlight players who offer stronger performance for a lower transfer fee. 

Finally, some systems run scenario modelling to predict how a player might adapt to a new league or formation which helps to reduce risk in high-stakes transfers. It’s powerful but not perfect. Black-box algorithms can hard-code bias, exclude atypical profiles and nudge clubs towards risk-averse choices. It’s therefore important that clubs remember to be transparent — not just for compliance reasons but for competitive fairness.

Integrity & reputation — AI as a watchdog & shield

AI is also being deployed to protect the integrity of the game. Systems like Sportradar’s Universal Fraud Detection System (UFDS) monitor betting markets for anomalies, helping national governing bodies like FIFA to tackle match-fixing. These tools are powerful as they can scan thousands of markets in real time but still rely on human analysts to confirm suspicions raised.

Odds can shift for legitimate reasons — for example, injuries or tactical leaks — and a false positive automated accusation could unfairly damage someone’s reputation. That’s why human experts play a vital role. They can review context that algorithms can’t fully capture, weighing factors like local betting culture, tournament stakes and historical behaviour. Their involvement safeguards due process which is critical in cases related to someone’s integrity that could lead to bans or even criminal proceedings. 

In addition, human analysts can help the system to adapt to evolving threats, spotting patterns that don’t fit the model and feeding those insights back into the algorithm. In short, AI provides speed and scale but humans provide nuance, accountability and legal robustness.

The global use of AI-powered moderation to combat online abuse is increasing. FIFA’s Social Media Protection Service scanned millions of posts during the 2022 Men’s World Cup and 2023 Women’s World Cup, hiding abusive comments, flagging offenders and protecting players’ reputations. It’s a strong example of AI for good but it’s also raised questions about proportionality and free expression.

Broadcasting & commercial rights — data as an asset

AI isn’t just being used behind the scenes — it’s now part of the viewing experience. Through the Premier League’s partnership with Oracle, features like ‘Match Insights – Powered by Oracle Cloud’ deliver live win probabilities and momentum graphics to fans worldwide. While these innovations enhance storytelling and can help to make football more accessible, they also turn player data into commercial assets and raise questions about image rights and consent.

Players’ voice — data rights on the agenda

The FIFPRO Charter of Player Data Rights has set expectations for transparency and control over performance data. Aligned with EU GDPR, it ensures that players can access their personal data, be informed about how it’s used, transfer it, revoke consent and challenge automated decisions.

In addition to these rights, the Charter embeds EU GDPR principles of lawfulness, fairness and transparency, as well as data minimalisation and security — establishing standards for responsible data management. It also stresses proper governance through policies that safeguard data and promote fair use.

As a result, football’s data practices must be accountable and equitable by treating players as active stakeholders rather than passive data sources.

The big picture

AI won’t solve football’s controversies but it’s already changing how the game is played, officiated and consumed. The path towards successful adoption of AI is clear — clubs should explain what the technology does in plain language, keep a real human accountable for big decisions and treat player data as a shared responsibility rather than a one-way extraction by clubs. These are the foundations for trust and sustainable innovation.

Talk to us

As AI becomes embedded across football and the wider world of sport, the challenge is knowing which tools to trust, how to apply them responsibly and where the legal risks lie. 

Our nationally and internationally recognised sports law team stands as one of the largest and most experienced in the field. With strong expertise in sports technology and data protection, we support organisations in making confident decisions around governance, regulation and commercial growth.

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