How AI Is Redefining the Tennis Experience

Over the past decade, tennis has fundamentally changed—the very mechanism we use to understand, analyze, or even just follow the game has transformed. Where coaches once relied on a keen eye and a notebook, and spectators depended on commentators to explain why a particular shot was brilliant, impartial algorithms now do the work. Artificial intelligence is quietly but rapidly rewriting the rules of tennis analytics.

Why AI Became Necessary

I remember what tennis used to be like: a coach with a notebook in the stands, a couple of general tips after the match, and if you were really lucky, a video recording to review your game after the fact. Decisions were made based on "court feel," an intuitive "technical indicator" that couldn't be measured, as well as personal experience reconstructed from memories of successful or failed rallies.

Today, I coach young players and professionals in California. Every day, I see tennis transforming into an exact science: every shot, every step, every tactical scheme can now be decoded, measured, and analyzed down to the smallest details.

The reason is simple: modern tennis has become too fast and complex for human perception. Serves reach speeds over 137 mph, topspin is generated at fantastic rates, and the tactical depth of top-level matches is such that the human brain physically cannot track all the nuances in real time. This is where AI enters the scene.

Technologies That Changed the Game

For several years now, automatic tracking systems have been in use—such as the famous Hawk-Eye, the ubiquitous Playsight, or the accessible SwingVision—they became the true "digital eye" of the sport's kitchen, effortlessly seeing what's invisible to humans.

Hawk-Eye is a network of 10–12 high-speed cameras tracking ball trajectory in three-dimensional space with millimeter precision. Artificial intelligence algorithms process image streams from all cameras in real time, fully reproducing a 3D model of the ball's flight. Thanks to this, the system can authoritatively show the bounce with millimeter accuracy, putting an end to officiating disputes.

Playsight Smart Court represents the democratization of technology. A system of cameras and sensors on a stationary court automatically tracks the ball and players, providing detailed reports: serve speeds, shot heat maps, movement statistics. The system allows you to compare metrics from different training sessions, track progress, and identify patterns.

SwingVision is a revolution for tennis amateurs. The sports "genius" of SwingVision lies in using neural network capabilities to process video without expensive equipment. The mobile app uses AI and an ordinary smartphone camera to analyze play: automatic shot classification, point counting, ball speed, and spin. Professional analytics becomes accessible to every amateur.

Today, AI in professional tennis goes far beyond analyzing serves and shots—it:

• automates officiating—now machines make decisions, not humans, with their potential errors
• analyzes player movements and shot technique—showing exactly where you're losing power or speed
• suggests tactical decisions to coaches and players based on data
• makes broadcasts interactive—fans can receive explanations and analytics in real time
• predicts results and personalizes training—both on and off the court

Seven Tools of the New Era

1. Electronic Line Calling (ELC)

Since 2025, tournaments like Wimbledon have abandoned human line judges and fully transitioned to an automated line-calling system. This evolution of ELC technology minimizes human errors and ensures consistency in officiating across all courts.

2. SkeleTRACK (Advanced Player Tracking and Real-Time Biomechanics)

Modern extensions of the Hawk-Eye system now track not only the ball but also the player's body movements in 3D, capturing up to 29 key skeletal points. This data helps analyze biomechanics, positioning, and movement technique, which is important for both coaches and tactical match analysis.

3. AI Analytics and Match Insights

Some major tournaments use AI-based analytics tools (for example, developed in collaboration with Microsoft and Azure) that process Hawk-Eye data and other sources in real time, analyze tactics, serves, drop shots, and other game patterns, and provide insights to players and coaches right at courtside.

4. Generative AI and Interactive Assistants for Fans

At the 2025 US Open, AI assistants appeared that answer viewer questions in real time, explain key match moments, and create 3D replays of rallies.

5. AI Analytics for Training (SportAI and Similar Platforms)

New platforms use computer vision to analyze techniques from regular video. You upload a clip from your smartphone and get a breakdown of shot biomechanics, swing speed, and recommendations for correcting technique.

6. Advanced Data and Visualizations

AI algorithms are also used to create:

• movement heat maps
• statistical patterns (serve effectiveness, positional play)
• tactical forecasts based on big data

7. Wearables and Biometrics

Although not always officially allowed during matches, wearable devices (such as Whoop) are increasingly used in training to track recovery, sleep, workload, and the body's stress responses. These technologies help predict injury risk and optimize the training process, giving coaches and athletes a clear understanding of physical condition. What's particularly significant is that advanced analytics, once available only to elite players at enormous cost, are now accessible to fans and amateur players—democratizing insights that were previously reserved for the professional level.

The Boundaries of Technology

It's important to understand: despite all its power, AI remains a tool, not a replacement for a coach or player. It doesn't make decisions—it provides data for choice.

A smart model can give a player and coach a report: "At 40–15, when your opponent serves to the right corner, your probability of winning the point with a down-the-line return is 68%, cross-court—53%." Sounds like a direct recommendation, right? But this isn't a command to "hit down the line"—it's merely an impartial mirror reflecting the effectiveness of past actions.

The final decision—choosing the shot at this specific moment, taking into account fatigue, psychological state, time of day, weather conditions, and other influencing factors—remains with the human. AI simply provides the most complete picture possible for this choice.

The main strength of AI is eliminating cognitive biases. A player might think their backhand "isn't working." The data will show: effectiveness hasn't changed, the opponent is simply deliberately attacking that side. AI translates the conversation from the realm of emotions into the space of facts.

What AI Cannot Do

No algorithm can measure the flash of anger after a missed set point, the cold determination on a tiebreak, or the loss of concentration from crowd noise. It's in these moments that the drama is born that makes us love tennis.

As a coach, I use AI system data to prepare a player's body and tactical mind. But preparing their will to win, their character, their ability not to break in a critical moment—that's a human task. And here we work on stress resilience, the ability to manage emotions, and the capacity to find inner reserves.

The Future of Tennis

The tennis of the future will be even faster, more powerful, more spectacular. But most importantly—it will be smarter. A champion's intuition will be backed by the analytical power of machines. The beauty of the human spirit will shine brighter against the backdrop of a clear data structure. Emotions will remain, but understanding will be added to them. AI will make victories more honest and understandable. It will open access to knowledge.

I'm convinced this is the best of all possible evolutions. Because here, technology doesn't displace personality—it serves its potential, which, as any coach will confirm, is truly limitless.

Author: Savriyan Danilov – Professional Tennis Player, Coach, and Leadership Mentor for Athletes