AI in Sports: How is AI Used in Sports Management

The global sports industry is navigating through a period of massive transformation. Deloitte reports that the overall economics of the sports industry is expected to continue to be strong in 2024 with a changing commercial model. One that is transforming the traditional revenue streams. Powered by emerging technologies like Artificial Intelligence.

In a comprehensive report titled 2024 Sports Industry Outlook, Deloitte shares that Generative AI is quickly entering many facets of the sports industry. There are significant investment shifts towards innovative AI applications. Ones that report mentions will be empowered by generative AI for ‘content generation and management, live sports coverage, player evaluation, sports betting, fan engagement, and back-office operations.’

What is AI in sports management?

AI in sports management simply means the use of AI-powered solutions across the many aspects of sports management. Like team management, marketing, partnerships, facility management, data analysis, fan engagement, athlete performance management, and more.

AI-powered systems are empowering the sports sector with rapid transformation. Enhancing athlete performance and building new capabilities. AI algorithms are processing large data sets from sports tournaments, events, games, and online engagement. To generate real-time insights to improve decision-making during games. Leading to increased chances of success in the game, via marketing efforts and an overall increase in ROI.

AI in sports management Global statistics

Dev Technosys reports the following stats that directly share the relevance and significant role of AI in transforming the sports sector:

a. The global AI in the sports industry is projected to grow from 518.8 million in 2022 to 4.3 billion dollars by 2028 at a CAGR of 42.3% over the forecast period. By 2030, the global impact of AI is expected to reach $19.9 Billion.

b. Global sports analytics is expected to grow at a rate of 27.3 percent per year between 2021 and 3031.

c. By 2026, it is estimated that 400 million sports-related wearable devices will be shipped.

What does this mean?

It means:

a. Emergence and increasing use of intelligent smart sports-related devices across sports professionals, professional academics, tournaments and facilities, fitness enthusiasts, yoga professionals, and more.

b. A surge in global sports career opportunities across sports management, operations, and strategy.

c. The number also reflects the rising opportunities for sports entrepreneurs, sports journalists, AI sports analysts, etc.

d. They also reflect the rising influence of data-driven decision-making across sports operations like sports marketing, advertising, facility management, fan engagement, etc.

Application of AI in the sports industry

1. Performance optimizations and analysis

AI offers sports managers with athletic performance data of a player on the team. It can help coaches to transform game strategy by designing new training programmes that suit the strengths and weaknesses of an athlete. Resulting in building more effective workout plans.

AI-powered solutions and tools allow managers, coaches, and athletes themselves to access valuable data about their performance.

For instance: AI tools can build Biomechanical analysis. This is when AI can identify and correct flaws in an athlete’s performance by studying their movements. Say an AI tool studies Tennis ace player Novak Djokovic’s performance through the last four grand slams to share critical data on his performance during his serve, in the first set vs the last set, during match set points, and more.

Further offering significant insights into the exact technique essential for the game.

2. Player performance, Injury prevention and rehabilitation

With the use of wearable sports devices like smart clothes or as simple as a Fitbit, sports managers can analyse vast amounts of player performance data, including video footage. Offering real-time insights into player positioning, tactics, and game strategy. In the sports sector where injuries are common, AI is helping to prevent injury with proper training and technique suggestions. Here’s how it’s helping in injury prevention:

i. Predictive Analysis: AI models study an athlete’s biomechanics and physical fitness to predict injury risk. Offering proactive steps to follow to reduce the likelihood of an injury.

ii. Load and stress management: AI tools offer training and game details to prevent overtraining, and thereby reduce the risk of extra stress on a muscle leading to injury.

iii. Customize rehabilitation and injury tracking: AI tools analyse a sports athlete’s medical history, past injuries, and performance data to build customized rehab plans for fast recovery. It helps to accelerate and track the injury in real time, allowing medical staff to make informed decisions. Make real-time adjustments to the recovery plan as necessary.

3. Fan engagement and community experience

Emerging technologies are rapidly shaping brand-new experiences to engage fans with their favourite player or sports teams. Think of online sports applications like Dream 11, MPL, LeagueX, etc. that offer fantasy league experiences to users. Here is how AI is offering transformative fan engagement and community experiences:

i. Personalized content: With data analytics and AI-powered tools, sports managers utilize user interaction analysis to build personalized content. Analysing a user’s viewed history, social media activity, community comments, engagement, etc aid in developing personalized content for various user segments.

ii. Offering fans real-time updates: With AI-powered chatbots and mobile application pop-up updates, sports managers offer fans real-time updates on game scores, player stats, tournament highlights, and more.

iii. Fantasy sports leagues: A key element of community experience powered by AI is the fantasy league sector. AI algorithms help to create and manage fantasy sports teams.

4. Assisting referee

To allow referees to make accurate decisions, AI is being utilized in more than one way. Avoiding any chance of conflict or debate over human error in decision-making. Here is how AI assists referees to make the right decisions:

i. Video assistance referee (VAR): It is a system that makes use of video images from various high-speed VAR cameras around the field for instant replays of the play.

ii. Goal-line technology: This is powered by AI to determine if the ball has crossed over the line. Eliminating any human-error-based debate or controversy about disputes goals in Football.

Use case examples:

– In 2018/19 Laws of the Game, football introduced VAR.

– In the game of Tennis, balls are equipped with sensors and tracked from different angles to represent the ball’s trajectory. Allowing umpire to verify their calls during the match.

5. Game Analysis and Strategy

AI tools and software help to build effective game strategies. Such as

i. Player recruitment: AI tools help in scouting and identifying the best talent basis their statistics and performance information.

ii. Performance Metrics: AI-generated metrics offer sports managers, coaches, and players a comprehensive learning performance. Allowing teams to build training programmes to improve their performance.

iii. Tactical Analysis: AI tools help to break down large video content into smaller data sets. Allows managers to analyse tactical decisions up close and design game strategy adjustments as necessary.

By assessing player movement, pitch conditions, weather forecasts, player launch angles, ball exit speed, and more – AI is building predictive analytics models for various games. These models are packed with performance data transforming the sports sector. AI is revolutionizing how coaches, players, sports managers, and fans interact, train, and compete. State-of-the-art AI-driven training simulations, personalized content, and generative AI’s automated sports journalism are fine examples of the role of AI in sports management.

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Author: Mankiran