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Digitally Transform the Process of Officiating in Sports

Use AI and ML to innovate on-field processes.

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  • Using data to the organization’s advantage. The sports entertainment industry captures an enormous amount of data - as organizations continue to be more digital its important that they use this data to their advantage.
  • Improving processes. Implementing AI and ML to improve processes within the business is essential to drive efficiencies and improve the overall game.
  • Mitigating risks with technology. AI and ML can be used within many areas of the business, such as officiating where the risk of gambling scandals are increasing due to the rising popularity of sports betting in North America.

Our Advice

Critical Insight

Digitally transforming different processes through technological advancements such as officiating is critical to improve the integrity and fairness of sports, where strategically combining people and technology processes will enhance the lives of officials.

Impact and Result

  • Learn how AI and ML work, their algorithms, capabilities, and how they affect the entire business and officiating.
  • Review the considerations, potentials, and limitations any organization should be aware of when implementing AI and ML for on-field decision-making.
  • Consider the type of architecture, implementation model, vendor, and strategy needed to successfully transform officiating.
  • Visit Info-Tech's AI Research Center to kick start an AI and ML implementation process.

Digitally Transform the Process of Officiating in Sports Research & Tools

1. Digitally Transform the Process of Officiating in Sports Deck – This report will guide you through understanding how AI and ML can be used to innovate the process of officiating and next steps to get started.

Read our digital transformation report to find out how you can innovate officiating through artificial intelligence (AI) and machine learning (ML) technologies.

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Digitally Transform the Process of Officiating in Sports

Utilize AI and ML to Innovate On-Field Processes

Analyst Perspective

Transform sports through digital and data driven processes

This is a picture of Elizabeth Silva

Elizabeth Silva
Research Analyst, Sports Entertainment Industry
Info-Tech Research Group

Artificial intelligence (AI) and machine learning (ML) are quickly changing the landscape of the sports industry all the way from media and fan experience to management and operations, as $1.6 billion has been invested in AI and ML within the sports industry to date (Neoteric, 2022).

AI and ML are both effective changes for the future; they will have an influential impact on digital transformation and innovation within many industries, including sports entertainment. As AI and ML have many uses within sports, its important to understand each use case individually to determine if it is a fit for the specific organization.

Officiating in sports has always been controversial; fans and spectators can be skeptical of some of the decisions officials make during a game. Unfortunately, there is a history of gambling scandals and other bad decisions made by referees that set a precedent for skepticism.

This poses a great challenge for technology to overcome by using digital, data, AI, and ML to drive more efficient and trustworthy processes. By combining people and technology processes, the integrity and fairness of sports will improve, while enhancing the quality of the game.

Executive Summary

Your Challenge

Using data to the organization's advantage. The sports entertainment industry captures an enormous amount of data. As organizations continue to digitize it's important that they use this data to their advantage.

Improving processes. Implementing AI and ML to improve processes within the business is essential to drive efficiencies and improve the overall game.

Mitigating risks with technology. AI and ML can be used in many areas of the business, such as officiating where the risk of gambling scandals are increasing due to the rising popularity of sports betting in North America.

Common Obstacles

AI and ML are not a low-cost investment. This creates an intimidating investment for a business to decide on before fully investigating its current state and potential capabilities for the organization.

It is difficult to understand how AI and ML work. Due to their advancements over the years it can be challenging to comprehend.

AI and ML are not broadly used for officiating. This can make it challenging to determine how it could or would be used to assist officials in making decisions.

Info-Tech's Approach

Review the considerations, potentials, and limitations any organization should be aware of when implementing AI and ML for on-field decision-making.

Consider the type of architecture, implementation model, vendor, and strategy needed to successfully transform officiating.

Visit Info-Tech's AI Research Center to kick start an AI and ML implementation process.

Info-Tech Insight

Digitally transforming different processes through technological advancements such as officiating is critical to improve the integrity and fairness of sports, where strategically combining people and technology processes will enhance the quality of the game.

The future will be driven by AI and ML

Digital transformation is an at-scale change program – planned and executed over a finite time period – with the aspiration of creating material, sustainable improvement in the performance of an organization. This is done by deploying a programmatic approach to innovation, along with enabling technologies, capabilities and practices that drive efficiency and create new products, markets and business models.

Artificial intelligence (AI) and machine learning (ML) will drive the future due to the incredible impact they will have on digital transformation and innovation within the sports industry.

When considering the future of innovation for the sports market, there are various digital potentials that can improve the overall industry to drive efficiency and create new products.

This is an image of the main areas of application for AI and ML in sports

A study within the United States revealed that 65.5 million people are sports viewers.

It is expected that by 2025, 90.7 million people will be considered sports viewers (Statista, 2021).

Problem solve with data-driven AI

The success of any sports league or team is determined by its financial strength. The outcome of each game is important to the overall business.
This creates significance on how fair each game is, but there are always random factors that play into the outcome of a game.

Some factors are:

  • Incorrect decisions made by officials (referees, umpires, governing officials)
  • Weather-related influences
  • Unevenness of the pitch
  • Absence of players

With all these factors, there is only so much that can be controlled. However, those factors that can be improved through the use of digital transformation, such as assistance in decision making for officials, should not be ignored. Wrong decisions by officials put every sport at a disadvantage to varying degrees. The minimization of wrong decisions is essential.

Officials may make incorrect decisions based on a variety of components, such as the following:

Match manipulation (intentional)

Social pressures, leading to psychological stress and mental illness (unintentional)

Genuine miscall from human error (unintentional)

The use of more technology can assist with these problems by improving the integrity and fairness of sports games while making the lives of officials easier.

a circle graph is depicted with 64% of the graph colored in dark green, and the number 64% in the center.

…of fans vote for the continued use of VAR (video assistant referees) in soccer (football), despite the criticism it receives due to interruptions it causes, as VAR was created to reduce the amount of clearly wrong decisions referees make.

International Journal of Innovation and Economic Development, 2020.

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Author

Elizabeth Silva

Contributors

Eman SMadi, Sports Data Scientist - Own the Podium

Anonymous Contributor, Business Executive - AI solution provider

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