AI-powered referees are changing soccer with faster, more accurate calls, but can they beat human referees? Yes, AI shines in objective decisions like offsides, thanks to its speed and precision. However, soccer’s complexity and need for personal opinion keep human refs vital. As tech improves, AI could take on more, blending with human skills to enhance officiating.
Current Use of AI in Soccer Officiating
AI is already part of soccer through tools like VAR (Video Assistant Referee) and goal-line technology. According to سایت شرط بندی an Iranian football betting site, VAR uses cameras and smart systems to track players and the ball, helping refs decide on offsides, fouls, and goals.
So, this will affect betting styles and patterns. Likewise, these tools make calls more precise, but human referees still review the data and make the final say. Here is how AI in soccer works:
Cameras and Sensors
Multiple high-resolution cameras, often 10 or more, are mounted above the pitch. For example, the Video Assistant Referee (VAR) system in UEFA Euro tournaments uses 10 cameras to track 29 points on each player’s body (e.g., shoulders, knees, feet).
These cameras operate at frame rates up to 500 frames per second, ensuring no movement is missed. The soccer ball itself contains an embedded sensor that updates its position and movement 500 times per second.
The combination of cameras and sensors creates a 3D map of the field, tracking players and the ball with millimeter accuracy. For instance, in the FIFA World Cup 2022, semi-automated offside technology relied on 12 tracking cameras and a ball sensor to instantly detect offside violations, reducing decision times significantly.
Algorithms and Machine Learning
The raw data from cameras and sensors is fed into advanced software that processes it using computer vision and machine learning algorithms.
Computer Vision: This technology analyzes video feeds to identify key elements, like players, the ball, and events like tackles or passes. It uses techniques like object detection and segmentation to isolate and track objects in real-time.
Machine Learning Models: These use massive datasets of soccer matches to recognize patterns. For instance, they learn to detect offside positions by analyzing thousands of scenarios where the ball is played and players are positioned relative to defenders. Common models include deep neural networks, which excel at processing visual data.
Training Process: The models are fed historical match footage, labeled with correct decisions (for example, “offside” or “no foul”), allowing them to refine their predictions over time.
The Hawk-Eye system, originally developed for tennis and cricket, has been adapted for soccer. It uses computer vision to track the ball trajectories and player movements with pinpoint accuracy, supporting decisions like goal-line calls.
Decision-Making Process
AI systems follow strict rules to make decisions tailored to soccer’s laws. Here is how they handle two important scenarios:
Offsides
- The AI pinpoints the exact moment the ball is kicked using ball sensor data.
- It then maps the positions of all players (based on camera tracking) relative to the last defender and the halfway line.
- Within milliseconds, it determines if any attacking player is in an offside position when they play a ball.
- Output: A visual overlay is generated for review.
Fouls
- The AI analyzes player movements and contact points to flag potential fouls.
- This is trickier because fouls often involve subjective factors like intent or severity, so the AI typically flags incidents for human review rather than making a final call.
Pros and Cons of AI-Powered Refs
AI-powered refs bring big benefits to soccer. They process tons of info instantly, making quick, spot-on calls about ball positions or offsides. Unlike humans, AI never gets tired or loses focus, so it stays sharp all game long. It can also check many camera angles at once, cutting down on mistakes. These strengths make AI a powerful tool for cleaner, fairer soccer matches.
AI has its downsides in soccer too. The game has tricky moments, like judging fouls or player intent, that need human-like thinking, which AI can’t fully handle yet. Tech glitches, like broken cameras or slow data, can mess up calls. Plus, setting up AI costs a lot, so only big leagues can afford it, leaving smaller ones stuck with human refs for now.
The Importance of Human Judgment in Refereeing
Human refs have a special edge AI lacks. They understand the game’s flow, read player behavior, and keep things fair with personal judgment. They decide tricky calls, like whether a foul was intentional, which tech struggles to figure out. Thus, this human touch keeps soccer’s spirit alive, making refs key for balancing rules with the heart of the game.
Final Words
AI-powered refs can boost soccer with precise, fast calls, but they are not ready to top humans yet. The game’s need for personal judgment keeps human refs essential. As AI grows, it will likely assist more, creating a combo that could make soccer fairer and more exciting in the years ahead.