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Score with AI in sports

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The global sports analytics market will reach a valuation of $59.47 billion by 2034, expanding at an impressive Compound Annual Growth Rate of 29% from 2024 onwards

Artificial intelligence, machine learning and data analytics are all over the news in this 21st century. Name any sphere of the formal economy, you will find these elements shaping up the core industrial operations there. ‘Informed Decision Making’ has become a key buzzword, often heard during board meetings, but technology is ruling the roost here as well.

As a business, you want to launch a new product, but at the same point in time are you apprehensive about how the market will react to this? Data analytics will help you to understand the consumers’ mood, when it comes to product preference, thus helping you to fine-tune and tailor your goods and services further. This is the 21st century ‘Informed Decision Making’, aided by technology.

Sports is also something where informed decision-making plays a key role and technology is dominating the proceedings there too. In this article, we will talk about the ‘Global Sports Analytics Market’.

What the numbers suggest

As per the Fact.MR, the global sports analytics market will reach a valuation of $59.47 billion by 2034, expanding at an impressive CAGR (Compound Annual Growth Rate) of 29% from 2024 onwards.

Sports will become more engaging, competitive, and informed due to the marriage of cutting-edge technology and brilliant human minds. Data-driven insights are increasingly being used by teams and athletes to improve performances and make informed decisions. AI, machine learning, and IoT (Internet of Things) advancements have changed the way sports are evaluated and played.

Fact.MR study found out that while North America accounted for 29.1% of the global sports analytics market share in 2023, Asia-Pacific will become the second most lucrative zone for the industry, with a CAGR of 24.6% till 2034. In fact, sports analytics software accounted for 62.2% revenue share of the global sports analytics market in 2023.

If you are a sports analyst working in a 21st century interactive TV studio, a touch screen LED is your best ally to break down the game’s technical aspects in an engaging way. Audiences’ watching experiences are becoming more fulfilling and informative. They can easily get access to player statistics and their performance measurements, before forming their opinion on the game scenario.

The graphics and visual components in sports broadcasts have become more interactive, helping the viewers to connect with the live event in a more immersive way. From mere spectators, fans have become the jury, taking an informed call on which direction the game is going.

Best case studies

As per Appinventiv, there is an increased demand for AI solutions that can aid player monitoring and tracking, real-time sports data analytics, sports predictions, virtual assistants and chatbots for interacting with fans and sports enthusiasts.

AI-backed data collection and analysis is making the sports industry fiercer on and off the field. Tech-assisted player tracking, performance statistics, and predictive modelling are helping managerial professionals in fields like player workload management, apart from improving strategy and training.

Talent identification and acquisition is a multifaceted process encompassing various aspects such as biomechanics, player performance measurement, and player recruitment. Biomechanics plays a crucial role in assessing athletes’ physical capabilities and movement patterns, helping to identify potential talent.

Player performance measurement involves systematically evaluating players’ skills, abilities, and overall performance to gauge their suitability for recruitment.

The best example of AI in sports analytics is umpire assistance, where match officials use technology to make accurate decisions during matches. We have ball tracking systems in cricket which monitor the movement and trajectory of the ball in real-time. Then in football, we have the Video Assistant Referee (VAR), which aids the match official by reviewing decisions using video footage and providing advice based on those reviews.

As part of the tactical planning, player injury modelling is a crucial job, followed by the team formation assessment, where the think tank evaluates the strengths and weaknesses of individual players to create a cohesive and balanced unit. Here, AI is helping professionals through predictive modelling, by considering biometrics, external factors, simulating game scenarios and analysing historical data, before forecasting player injuries and suggesting prevention techniques.

Artificial intelligence is even assisting teams in creating game plans by analysing data on opponents’ playing patterns and their current form (including their key players). Appinventiv’s research also found out about tech recommending the best lineup combinations during games and making real-time tactical adjustments.

“Real-time player biometric monitoring is a crucial component. This makes identifying indicators of exhaustion, stress, or harm risk possible. Coaches and medical personnel are notified, which enables prompt interventions and eventually lowers the risk of injury. One popular use of AI in sports is determining the swimmer’s performance below water filters using human pose estimation. This method takes over the ancient quantitative evaluation method by manually annotating the swimmer’s body,” the study noted further.

The report also used the NBA example, where from 2015 to 2018, the professional basketball league reviewed over 25,000 games through the tech and found over 2,000 missed/incorrect actions from the officials. This amounted to 1.49% wrong decisions in the finals of each close game. AI has been deployed now, where referees, armed with probability and visual data, are cutting down the judging errors significantly.

Using machine learning, AI is also suggesting diet plans for players. AI-based fitness apps are flooding the markets further. Some of these tools and techniques are using key point skeleton models to identify human joints for online yoga and pilates.

Meet the inspirational force

Valeriy Lobanovskyi, who is often recognised as the greatest football manager of the Soviet era and then, later, Ukraine, became the manager of the Dynamo Kyiv in 1973 and within a year, guided the team to its first Soviet Top League title. In fact, under his watch, the team won the title for another seven times. In the post-Soviet era, Lobanovskyi is credited with five Ukrainian National League titles from 1997 to 2001.

Lobanovskyi, apart from being a professional footballer during his young days, was also an engineering student. In 1957, the USSR opened the first cybernetic institute in Kyiv and it became a world leader in automated control systems, artificial intelligence, and mathematical modelling. In fact, the early prototype of the modern personal computer was developed in that institute in 1963.

In fact, Lobanovskyi along with statistician Anatoliy Zelentsov, authored the book titled “The Methodological Basis of the Development of Training Models”, which offered a science-based breakdown of the game.

Lobanovskyi pioneered methods like video analysis, field research and tracking players’ fitness levels, to provide a more comprehensive approach towards helping the athletes maintain peak physical condition. He, as a coach, was known for following this approach to ensure that Dynamo Kyiv maintained their peak form across different playing conditions, while maximising the team’s overall flexibility to adapt to the changing game patterns.

Both Zelentsov and Lobanovskyi used to conduct advanced pre-and-post-match analysis with individual player stats and elements of the game recorded. Their strategies are used to even include factors like the exact measurement of the football pitches.

Lobanovskyi’s approach towards the game was method-oriented, bringing variables into the play, while making strategies. He and Zelentsov can be credited as football’s original scientists, who used to collect data in a Kyivian Soviet Laboratory and test their hypotheses out on the field.

These legends were ahead of their time. Their book came out in 2003 and 20 years later, coaches and athletes have made technology their ally, exactly how Zelentsov and Lobanovskyi envisioned.

Gamified training app Actiquest’s latest solution revolves around providing personalised sports coaching through AI digital twins of human mentors. These digital coaches will train athletes remotely, providing live recommendations, allowing real-time interaction, and offering rewards based on training performance.

Sports teams are adding artificial intelligence to the scouting and recruitment aspects too. Machine learning algorithms aggregate data and evaluate players’ skills and overall potential in various game categories, thereby helping the teams to make informed decisions on which new faces they can add to their side.

Be it ticketing, making live predictions or revolutionising sports advertising, the tech-assisted global sports analytics market has gone much beyond its envisioned role of assisting coaches and athletes.

As data-driven insights reshape fan engagement, personalised experiences, and sponsorship strategies, the sports analytics market’s influence is pervasive. From enhancing fan interactions to shaping marketing campaigns, it proves integral to the entire sports ecosystem, signalling a transformative era.

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