Data-driven coaching – tennis, we are ready
How does it sound to receive real-time, data-based feedback during your training session? It’s already possible, and only accelerating in the future.
At every skill level, and more broadly in many areas of life, the use of technology has become everyday practice. Tennis coaches have always been able to explain things verbally and demonstrate them visually.
However, for a long time, tennis has relied solely on these two methods. While video recording has become more common and added a new dimension to training, there’s still room to improve in data usage.
The Key to Successful Data-Driven Coaching: Relatability
Tennis viewers have followed technological advancements in professional matches for years. We've become accustomed to reading and hearing from the broadcast about serve percentages and directions, rally lengths and win rates, court positioning and how it changes during matches, or the depth of groundstrokes.
We are ready. We can relate to the technology. Data-driven coaching is moving the sport forward.
Your game, reimagined. Zenniz enhances every practice and match with real-time performance tracking, electronic line calling, and immersive video. All in one system. Get in touch.
The First Steps Towards Data-Based Coaching
As a coach, how can you take your first steps towards more data-driven training? First, your training environment needs to support smart tennis technology. After that, it’s largely about shifting your coaching habits.
Think about which data is useful and how to obtain it. Ultimately, put yourself in the shoes of your players: what information is truly helpful?
It’s important to remember that we all, coaches and players, resist change to some extent. In our experience, information and new methods are more readily accepted when presented in a relatable and easy-to-understand way.
What Data-Driven Coaching Looks Like
Firstly, tennis and playing the game will stay the same. Tennis is a game. Let’s not forget that.
"Also, it's good to understand that players have many different learning styles. A coach needs to take that into account", highlights coach Julius Kaverinen from the Finland´s biggest club HVS-Tennis.
But with the help of AI, development can be supported through:
Measurability: No more guessing, every shot tracked, in both practice and matches.
Real-Time Feedback: Analyze and provide feedback instantly during training, not just afterward.
Recognition: Identify development patterns in different shots and scenarios - shot maps visualize progress.
Learning: Coaches and players can return to the data repeatedly. No need to rely on memory alone.
With the help of Zenniz Premium, the revolutionary tennis app, players can make a deep dive into three sections:
Performance Rating - A detailed breakdown of your game, rating your performance across serves, returns, backhands, and forehands. Track progress over time with personalised insights powered by Zenniz AI.
Playstyle IQ - Discover your unique court identity with visual AI-insights into five key areas of your game. Earn badges like Risk Taker or Tactical Mastermind to recognize your strenghts and chart your evolution against different kinds of players.
SmartView Player - Relive every match moment with intuitive AI video tools. Filter footage to focus on key plays, rallies, or match-defining shots. Whether you're reviewing for fun or fine-tuning your skills, SmartView Player makes it easy to see the game your way.
"Generally speaking, many players don’t really understand what their own game looks like, so video is extremely useful for everyone. On top of that, raw data helps and deepens the understanding. It's good for a coach to say something, but being able to support that message visually significantly improves learning", continues Kaverinen.
"I use net clearance and depth of the shot the most. Often hobby players think in terms of power, fantasizing about those cannon shots that just skim the net. But the fact is, even professionals have shape and depth in their shots, which brings both consistency and power", ends Kaverinen.
In the end, when done right, data supports learning and playing - it doesn’t distract from it.