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12:07, 14 January 2026
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The KHL Is Looking to AI to Make Officiating More Objective

Russia’s Kontinental Hockey League (KHL) is exploring how artificial intelligence could support the sport’s development. In an interview, KHL Vice President Valery Kamensky outlined key areas where AI could be applied effectively.

A New Chapter

The KHL vice president believes AI is well suited for reviewing game episodes, including offside calls and goal decisions. Automating these checks could speed up the process and improve the accuracy of contentious rulings during matches. AI could also support the league’s disciplinary committee by identifying serious violations on the ice. Another potential application lies in marketing and league promotion, where AI could strengthen existing digital tools.

For the KHL, artificial intelligence remains a “new and largely unexplored chapter,” and its rollout would require adaptation and practical testing. Even so, representatives of sports organizations are already acknowledging the technology’s potential and the advantages it could bring.

Earlier, Andrey Razin, head coach of Metallurg Magnitogorsk, also highlighted the possibilities of using AI in officiating and even suggested handing some of these functions over to algorithms. He argues that in the future, cameras will be able to register infractions flawlessly, helping eliminate subjectivity in refereeing.

Lessons From Football

AI is already being used successfully by football scouts. Major clubs rely on technology to evaluate players and forecast the return on transfer investments. Working with large datasets, AI systems can identify players based on specific parameters and automatically generate shortlists of candidates who match predefined criteria. These parameters can include technical skills, transfer value, and age.

Experts caution that full reliance on AI is still premature. However, it can remove the need for manual searches and generate selections automatically in a very short time. Looking ahead, AI could take into account a far broader range of characteristics, not only on-field performance. With sufficiently accurate data, decision-makers may eventually be able to trust machine-driven choices.

Sport, and hockey in particular, is getting faster. Sometimes it is impossible for referees to determine a rules violation. I am convinced that in the near future offside calls, icing, and too-many-men violations will be determined by cameras, not ‘at the referee’s discretion.’ Tripping, holding, and other technical fouls must always be identified, regardless of the score or the roar of the crowd. There should be no such term as ‘at the referee’s discretion.’ A violation either exists, or it does not
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Digital tools have not only made broadcasts more engaging but have also opened access to advanced analytics. Neural networks analyze live footage in real time, increasing interactivity and the precision of statistics. Video compilations of mistakes and successful actions are created automatically, while AI proposes alternative attacking scenarios and evaluates a team’s physical condition using GPS tracking data. Thanks to computer vision and deep learning algorithms, sports clubs are gaining access to data that was previously unavailable.

AI Analytics as a Competitive Edge

Efforts to integrate advanced digital technologies into the organizational, regulatory, and commercial framework of a major sports league represent a strategically important step toward the digital transformation of sport. AI has the potential to make officiating more objective, disciplinary procedures more efficient, and the overall sports product more competitive.

For now, these remain intentions rather than fully implemented systems. Still, they signal that organizations are seeking to leverage AI’s advantages across virtually all industries. It will be essential for such initiatives to be accompanied by pilot projects, clear assessments of economic impact, and the involvement of IT experts with experience in sports analytics.

If the use of AI by sports organizations moves from isolated cases to widespread adoption, Russian IT companies specializing in computer vision and sports analytics will gain valuable opportunities to test their products. With successful results, these solutions could later be offered to foreign sports leagues.

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