How technology is changing the world of sports
As new technologies are implemented more quickly, the pace at which advancements occur in sports will also take off. The future of sports is thrilling, with many developments on the horizon.
The role of AI in professional sports is rapidly transforming how teams make decisions about players, from recruitment and development to trades and benching. By leveraging large datasets, AI-based technologies are empowering front offices to make more precise, data-driven choices. This shift has the potential to permanently alter the landscape of all professional sports.
But will AI soon replace front-office staff entirely?
For now, AI is primarily a tool that enhances, rather than replaces, human decision-making. We’re not yet at a point where general managers or executive teams are expendable, in sports or other industries.
Enhanced Predictive Power
Among the many AI-driven solutions in sports, some focus on predicting athlete injuries and career longevity. Accurately forecasting injury risk can significantly influence recruitment, as teams would naturally prefer players with a lower likelihood of injury. While experience-based intuition has always been used to assess injury risks—considering factors like game time and physical “mileage”—it’s often hit-or-miss.
AI not only validates some of this conventional wisdom but also provides highly specific predictions. For example, AI can assess the probability that an NFL wide receiver over 30 is likely to face injury risks. Companies like Probility AI claim accuracy rates as high as 96% in forecasting which players will miss games in the next season. This level of precision lets executives shift from “I think” to “I know,” bolstering confidence in their decisions.
Moreover, AI dives deep into unique data points, combining NFL teams' internal data with public sources to analyze factors like a player’s college experience, coaching staff, and past workloads. These insights show how AI can uncover layers of predictive analysis beyond human intuition, allowing general managers to pinpoint the best players specifically suited to their teams, based on AI’s insights into injury and performance likelihood.
A Strategic Edge
Several NFL teams are adopting AI tools, recognizing the competitive advantage these insights can bring. By contrast, teams that ignore these advancements may find themselves lagging behind. This technology isn’t limited to football; soccer, basketball, and other sports are leveraging AI for similar decision-making advantages. Across business sectors, AI’s predictive power also helps drive productivity and improve decision-making, as seen in customer service, production, and logistics.
Augmentation, Not Replacement
Will AI replace front-office teams? Unlikely, at least for now. AI augments human decision-making, helping executives make more informed choices—especially in areas where human bias or intuition can fall short. While “Moneyball” ushered in a new era of data-driven decision-making based on player statistics, AI goes further, enabling more nuanced predictions around player performance.
With accurate availability forecasts for players, AI can guide three main decision areas:
Risk Management: If a star wide receiver is injury-prone, the team might invest more in backup players to cushion against performance dips during his absence.
Training and Interventions: AI can highlight injury risks for specific players, prompting teams to design targeted training, nutrition, or workload adjustments to reduce injury chances.
Personnel Choices: AI can help teams decide who to draft, trade, or retain based on injury risk and potential availability over the season.
AI also feeds these predictions into financial models, allowing teams to calculate productivity relative to cost. For instance, if a player is likely to miss half the games in a season, he becomes twice as costly compared to a similarly priced but consistently available player. Teams can, therefore, allocate resources more effectively, maximizing productivity per dollar spent.
Yet, while AI can crunch data and suggest optimal moves, the final decisions involve a level of human judgment, as leaders weigh trade-offs and strategic priorities.
Wider Applications Across Industries
AI’s predictive power has vast potential beyond sports. For example, it could forecast performance dips in labor-intensive industries or predict when heavy machinery might fail, enabling preventive measures. AI is already being used in areas from retail demand forecasting to competitive analysis, with startups in the AI sector drawing $1.4 billion in funding in 2022 alone.
Limitations and the Role of Human Judgment
Predictive AI has its limitations, reinforcing its role as a complement to, rather than a substitute for, human decision-makers. When assessing player health in the NFL, for example, AI can recommend trades or provide salary guidance based on injury risk. However, it’s up to coaches and executives to consider team dynamics and how new players fit in. While AI is advancing in assessing team-level dynamics, particularly in sports with smaller team sizes like hockey, human insight remains essential.
Additionally, AI predictions come with confidence intervals, which means they’re probabilistic, not definitive. Though these intervals will narrow as AI technology advances, the “human element” remains crucial for making final calls.
In summary, AI is transforming professional sports, granting front offices and coaches unprecedented tools for improving player health, performance, and strategic decisions. But it’s still about augmentation, not replacement. Leaders in sports, guided by AI, continue to rely on their experience, intuition, and accountability to make the best calls, both on the field and on the balance sheet.