The reality of sports injury prediction: lots of effort with little reward

Qatar’s successful bid to host the 2022 football World Cup was atypical in that the World Cup usually takes place in June and July. The World Cup typically falls in the gap between the end and the beginning of most northern hemisphere professional football leagues, and players would have a short rest before returning to their clubs for another league season. However, the June-July World Cup window was unfeasible due to the extreme heat of the Qatari summer. So instead, the competition will take place from 20 November to 18 December, in the (relative) cool of the Qatari winter. This is unique because the major European Leagues will take a break throughout the World Cup, but players will return to action for their clubs immediately after Christmas.

This arrangement provides a unique challenge for footballers and their clubs worldwide, with many voicing concern over the capacity of footballers to maintain performance and remain injury free in the face of such a demanding schedule. These concerns are not unfounded. In 2020, a group of Israeli researchers published research quantifying the estimated financial costs of injuries to footballers in the British Premier League competition(1). They estimated that clubs lose, on average, one league position for every 271 days lost to injury. The financial cost of this to clubs in terms of reduced prize money, tv viewership, and access to more lucrative competitions is estimated to be £45 million. No wonder teams are nervous about their players returning from the World Cup tired and injured.

Sports science research has conclusively demonstrated that teams that manage to keep their players’ injury free perform better over the long term (2). In an effort to mitigate the negative effects of injuries, many professional sports organizations now employ sports and data scientists to monitor their athletes and guide them on preventing injuries. For example, in March 2021, Nature.com published an article describing how sports scientists working in professional football used artificial intelligence (AI) and advanced algorithms to “predict” sports injuries. This is an appealing concept! In addition, a modern understanding of training science suggests that injuries occur when players exceed a particular training load and become fatigued. Surely then, if we can measure all the loads that players are exposed to, we could “predict” injury risk and manage them away from it. Again, it is an appealing concept, but this assumption has several problems.

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