This summer, global sport’s biggest event is coming to America. Part of what makes the World Cup so special is the storylines attached to the once-in-four-year event. This year’s tournament will likely be the last chapter in professional sport’s greatest ever rivalry, Messi vs. Ronaldo.
With the tournament fast approaching, attention is turning not only to elite performance but to the growing role of technology in keeping players fit and match‑ready. AI is increasingly being deployed to predict, prevent and manage injury risk in professional sport. For insurers and their legal advisers, these developments raise important opportunities, along with new questions.
Fixture congestion and player workload
Over the past few seasons, some of soccer’s biggest names have voiced their concern over the number of games the elite of the sport are expected to play. Many feel the elite players’ crowded schedule, complete with games in domestic club competitions, continental club competitions, international duty, and all of the associated travel, has become a problem for the sport. How then, can a club team protect itself from losing one of its best players to injury?
An injury to a key player can have a serious impact on a club team’s success. Missing a key player can result in poor performances, leading to relegation or failure to qualify for a European competition (e.g. Champions League). These negative results carry devastating financial effects for a club. To avoid the impact of losing a key player to injury, club teams may be forced to change recruitment strategies and spend large sums of money to bring in a new transfer player to fill the gaps left by injured players.
Injury prevention and sports science
Injury prevention has made significant advancements in recent years as clubs attempt to alleviate the risk of injury that overexertion and inadequate rest present. Sports science now utilizes AI to assist in monitoring player metrics and predicting injury. Predictive algorithms have been developed to track players’ sprinting, muscle impact, and other biometric data.
GPS trackers, wearable sensors and optical tracking systems collect real‑time data which machine‑learning models then analyze to identify patterns associated with increased injury risk, often before clinical symptoms develop.
Computer vision technology is becoming more mainstream. AI‑enabled video analysis allows sports teams to assess movement mechanics, jumping and landing technique, and biomechanical asymmetries without the need for wearable sensors. These tools are likely to play a role during the World Cup, where training time is limited but injury exposure is high.
A key area of focus is soft‑tissue injury, long recognized as a leading cause of time‑loss at major tournaments. Some studies reviewed in the British Journal of Sports Medicine indicate that machine‑learning tools can outperform traditional statistical approaches in predicting injury risk in footballers. However, while clinical utility remains under scrutiny, the direction of travel is clear: AI is increasingly shaping how athletes are trained, rested and selected ahead of high‑stakes competitions.
The FIFA Club Protection Programme
FIFA has implemented a program to compensate the club teams that employ international players injured during national team matches. The FIFA Club Protection Programme (CPP) covers injuries sustained during international duty, compensating clubs for wages paid to players during long-term injuries (28 days or more). CCP covers payment for temporary total disablement if a player is accidentally injured while on official national team duty. It does not include illness, permanent injury, death, or medical treatment costs. Payments are calculated on the player’s fixed salary only, and the CCP imposes limits on payments per player and per team. That capped rate ensures the most a player could be earning and have their salary matched completely by FIFA is roughly £120,000 (US$160,913) a week.
The CPP is often inadequate in protecting teams from the negative impacts that a serious injury to a key player presents. Many professional clubs carry insurance against player injury to protect against loss of income, wages, and potential devaluation of the player as an asset. Even some high-level players have famously taken out insurance policies, such as the reported €500 million coverage on Lionel Messi’s legs.
Comment
The increasing use of AI and data analytics in injury prevention has the potential to reshape both the risk profile and claims landscape for sports-related exposures.
For insurers, the benefits of these AI-driven injury prevention developments are potentially significant. Earlier identification of injury risk may reduce the frequency and severity of claims, shorten rehabilitation periods and improve return‑to‑play outcomes. Over time, access to objective, data‑driven insights may also support more granular underwriting and claims reserving.
At the same time, the increasing reliance on wearable tech and performance data raises data privacy and cyber risk considerations. Sensitive health and biometric data may become a target for breaches or misuse, creating additional lines of exposure that sit alongside traditional personal injury risk.
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