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September 24, 2024

AI in the Sports Industry: 6 Use Cases for 2024

Author:




Artur Haponik

CEO & Co-Founder


Reading time:




12 minutes


When you think about AI, the sports industry is not the first one that comes to mind, but the truth is that this revolution is happening here, too! In this article, we’ll show you how artificial intelligence can be (and already is) used in this interesting market sector.

With the global sports industry set to achieve annual revenues of $260 billion by 2023[1], it’s no surprise that AI is playing a pivotal role in shaping its future. Although many experts remain mum about the profound impacts of AI on sports, it’s hard to overlook the positive effect this technology has had on the ground.

Today, we highlight some of the most notable use cases of artificial intelligence in the sports industry. Let’s jump straight into it.

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AI in the sports industry: A comprehensive overview

Technology in sports is nothing new, but the advent of AI in the sports industry could usher in a new age of innovation and efficiency. What was once thought of as a gimmick is now a staple for many aspects of the industry. We’re talking about everything from metrics and analytics to betting and fan engagement.

That said, the use of AI in sports is still in its infancy, but we’re witnessing unprecedented levels of AI use in the industry. All indicators point toward a technology-rich future in sports, with artificial intelligence and machine learning (ML) models at the center stage. In fact, according to Allied Market Research, the AI in sports market is expected to hit a staggering $29.7 billion by 2032[2].

AI in sports touches all key sectors of the industry, namely:

  • The teams: Improved decision-making with data-backed insights
  • Coaches and managers: Analytics and insights to improve a team’s success
  • The players: Injury prediction and custom training regimens
  • The fans: Enhanced fan engagement and immersive experience
  • Facilitators: More precise and accurate officiating

The use of AI will also affect the sports industry in other ways. For instance, sports betting will become more nuanced as enthusiasts can leverage AI to make more strategic bets. Sports teams can also use artificial intelligence to gain new perspectives on how they can market their merchandise or expand their reach by tapping into new demographics.

Artificial intelligence has also bridged the gap between smaller teams and larger, more prominent teams. The technology has allowed small teams to access the same informational resources that large teams use to strategize at a fraction of the cost. This has essentially leveled the playing field in sports, allowing hard work and player skills to be the differentiating factors rather than financing.

AI implementations in the sports business

Sports is a multi-billion-dollar industry with dozens of players spanning various sectors. This includes sports media, betting, sponsorships, merchandising, and equipment. Artificial intelligence is heavily applied in these sectors with overwhelming results.

For instance, thanks to artificial intelligence, journalists can provide more detailed reports on sports events. AI eliminates the need to have actual humans on the ground to keep track of every play and moment. Using generative AI, media houses can transform raw figures like the number of touchdowns, tackles, fouls, etc., into compelling narratives for their sports reports.

AI has also been a transformative marketing tool for merchandising and equipment manufacturing companies looking to grow their sales. These companies can leverage the technology for their targeted advertising campaigns and to analyze customer behavior and preferences. In doing so, they can market the right products to the right people at the most opportune time.

In sports betting, however, AI has become a double-edged sword. While betting companies can expand their reach with data-centric marketing campaigns, betters use predictive analytics to analyze vast amounts of data and make accurate predictions. As more of them catch on to this technology, betting becomes more predictable, and the house loses its edge.

6 key use cases of AI in sports

AI is steadily becoming a prominent technology in sports, both in and out of the field. Here are some of the most notable use cases of AI in sports:

1. Use of AI in game analytics

AI plays an important role in analyzing game statistics and drawing relevant conclusions from figures and charts. Statistics provide crucial insights into different aspects of sports, like player performance, overall team paying quality, and enhancing fan experience.

For instance, AI can accurately analyze match events, keeping tabs on crucial figures like:

  • Goals/buckets scored
  • Fouls committed
  • Distance traveled by each player
  • Number of substitutions

Besides data gathering, AI quickly analyzes and interprets sports data using machine learning algorithms and predictive analytics. Team managers can use AI tools to identify patterns in player behavior, uncover tactical inefficiencies, and assess opponents’ strategies. This information helps coaches get a hand over their opponents and make well-informed decisions about their teams’ lineups, formations, and approaches to different opponents.

2. AI in predicting player performance

In sports, players make or break a team’s success. Forward-thinking teams use predictive models to predict a player’s performance or physical fitness.

These models can predict with considerable accuracy a player’s likelihood of injury or a performance slump based on:

  • Historical data
  • The player’s current physical condition
  • Psychological stressors
  • Training intensity
  • Training discipline
  • The player’s diet

In doing so, the technology can help coaches make well-informed decisions when selecting players. This information will also help the training staff to optimize training regimens and diets, and schedule proper recovery days without compromising the team’s overall performance.

Team managers and coaches can also leverage ML algorithms to forecast breakout seasons for their star players. That way, they can use this data to budget for new signings and trade players who don’t align with their team’s evolving strategies and seasonal goals.

3. Injury prevention

Another use of AI in sports is anticipating injuries before they occur. Professional athletes experience an average of 62.49 injuries for every 100 players per season [3]. Predicting these injuries early on can help reduce the severity of these injuries or sidestep them altogether.

AI technology typically uses machine learning models to identify indicators like exhaustion, in-game collisions, historical health data, and others to determine the likelihood of an injury. These models can predict spikes in player workload using parameters like how much distance they traveled, the frequency of their training, and total game time. They can also identify decreased sprint speed and reduced movement as signs of muscle fatigue.

Some teams use artificial intelligence to monitor players’ sleep patterns to help schedule recovery and rest periods. Players who’ve not had enough sleep may have to sit out the next match or will be prescribed medication and therapies to help them sleep better. Players perform better when well-rested, and are less likely to play recklessly, thus decreasing the risk of injuries.

Thanks to AI technology in sports, coaches can isolate Injury-prone players so that the medical team can begin early intervention to address the issue. The coach can also change the teams’ strategies accordingly to accommodate changes in the lineup. By lowering the risk of injury, players can enjoy longer and more rewarding careers before physical limitations force them into retirement. Injury prevention also means reduced medical costs and fewer missed games.

4. Breaking down game footage and identifying subtle patterns

Coaches can utilize artificial intelligence to scrutinize game footage comprehensively and identify patterns and movements that would otherwise slip under the radar. Machine learning algorithms analyze gameplay footage frame by frame, tracking players, certain objects, and even how the team moves as a unit. The coaches can then use these fresh insights to make prudent strategic decisions mid-game on the team’s formation and overall technique.

Coaches and team management can also use artificial intelligence to analyze players’ performance. Using this technology, they can pinpoint strengths and weaknesses among players and work closely with them to capitalize on their strengths and address their weaknesses. Smarter decisions translate into improved gameplay and team success.

5. Creating custom training regiments

Consistent training builds strength and endurance, but there’s no one-size-fits-all training regimen for every athlete. Athletes can use artificial intelligence to create tailored training regimens based on their goals, anatomies, and injury backgrounds. What’s more, with AI’s monitoring capabilities, they can receive real-time feedback on their progress and get suggestions on improving their form for optimal results.

That said, tailored workout programs and training routines are beneficial for athletes in the following ways:

  • Better performance: Proper training strengthens muscles and builds endurance while improving technique, resulting in better player performance.
  • Accelerates recovery: Athletes can use AI to set the optimal recovery and rest periods for quick recovery and peak fitness before the next event.
  • Reduced risk of injury: Inadequate training may increase the risk of injury in sports [4], but AI helps tailor your training routine to ensure enough training, thus reducing the risk of injury. AI can also alert you when you push your body beyond your limits.

6. Officiating assistance

Match officials get a lot of heat for wrong calls. Thankfully, AI can reduce these errors, ensuring fairness and precision. Foul action detection technology, for example, can accurately detect and call basketball fouls in real-time. There’s also been talk of using artificial intelligence in the MLB to pinpoint strike locations and trackball trajectories. In soccer, stadiums use AI-powered cameras and other technologies to deliver real-time verdicts on goal validity, offsides, fouls, and other events that human referees may fail to catch.

These are just a few examples of how sports facilitators can use artificial intelligence in officiating, but its effect is far-reaching. Combining AI-powered technology and human skill keeps bias and error at a minimum, ensuring fairness and strict adherence to the rules.

The future outlook of AI in the sports industry

AI is set to revolutionize the sports industry in profound ways. For starters, improvements in on-field analysis and improved insights into players will transform gameplay strategies. Teams that openly embrace AI are likely to have the upper hand over their rivals and stay on top of the game. However, it also means that sports will get more competitive as competing teams pull out all the stops and take full advantage of AI for optimal performance.

The physical health of athletes is also poised for a major boost as personalized diets, treatment plans, and training regimens are likely to be the norm. ML technologies will personalize athletes’ health, ensuring they get tailored care that not only addresses underlying issues but also reduces the risk of injuries. This way, athletes will have lengthy careers and stay healthy and energetic throughout their sporting careers.

Sports fans will also be the biggest beneficiaries of AI in the sports industry. Ai-powered VR technologies can immerse fans in the thick of the action, making them feel like they’re part of the game. AI can also curate personalized experiences, connecting fans to their favorite teams and keeping them on top of all the latest developments. Biased and unfair calls will also be minimal as AI-powered cameras, with the help of officials, ensure precise officiating.

Final thoughts

It’s hard to overlook AI’s contribution to and growing influence on the sports industry. As AI technology continues to evolve, it will not only enhance player performance and fan engagement but also streamline operations across the board. From predictive analytics to injury prevention and even officiating assistance, AI is transforming every aspect of the game.

While there are challenges of AI in the sports industry, such as balancing human intuition with machine insights, one thing is clear: AI is here to stay, and its role in sports will only grow stronger in the years to come.

AI in Sports – Frequently asked questions

Will the rise of AI in sports replace coaches, fitness trainers, match officials, and other key roles?

No, AI-powered devices won’t take over key roles and responsibilities in the sports industry. Instead, the technologies will act more like digital assistants, helping to ensure accuracy and guide decisions with data-driven insights. Coaches, trainers, and others form an integral part of sports and athletics, so it’s highly unlikely that AI will replace them in their respective capacities.

How does AI reduce injuries in different sports?

AI can help reduce sports injuries by analyzing player-specific data from medical reports and wearable devices. Machine learning can identify patterns in the data that show fatigue or imminent muscle failure. Medical personnel can then act quickly to address these issues before they spiral into full-blown injuries.

How can coaches use AI to optimize team performance in the middle of matches?

Coaches can make use of AI mid-game to analyze game footage and identify loopholes in the opponent’s formation or gameplay. These tools can identify tactics based on player movements and gameplay pace. AI-powered dashboards can also provide insights into player performance so coaches can make more informed decisions on substitutions and conjure the best formations to counter opponents’ tactics.


[1]sportspromedia.com, Global Sports Industry Revenues to Reach US$260bn by 2033, https://www.sportspromedia.com/news/global-sports-industry-revenue-projection-2033-two-circles/, Accessed on September 19, 2024
[2]alliedmarketresearch.com, Artificial Intelligence in Sports Market Expected to Reach $29.7 Billion by 2032, https://www.alliedmarketresearch.com/press-release/artificial-intelligence-in-sports-market.html#:~:text=The%20artificial%20intelligence%20in%20sports%20market%20size%20was%20valued%20at,the%20help%20of%20data%20analysis., Accessed on September 19, 2024
[3]nature.com, Temporal trends in incidence of time-loss injuries in four male professional North American sports over 13 seasons, https://www.nature.com/articles/s41598-021-87920-6#:~:text=A%20mean%20of%2062.49%20injuries,highest%20injury%20incidence%20in%20basketball., Accessed on September 19, 2024
[4]https://www.ncbi.nlm.nih.gov/, The training—injury prevention paradox: should athletes be training smarter and harder?, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4789704/#:~:text=Clearly%2C%20for%20athletes%20to%20develop,training%20may%20increase%20injury%20risk., Accessed on September 19, 2024



Category:


Artificial Intelligence