Smartphones may now outperform sensor-based rackets in helping athletes refine their technique. A Norwegian startup, SportAI, has introduced software that offers real-time, objective analysis for players of racket sports without relying on specialized equipment. Leveraging AI tools such as computer vision and machine learning, the platform delivers biomechanical insights from regular video footage. This approach could lower the cost barriers traditionally linked to performance coaching and analysis in sports like tennis, paddle, and pickleball. The company aims to make high-quality feedback more accessible to everyday players, broadcasters, and manufacturers alike.
Earlier solutions such as sensor-embedded rackets with companion apps failed to gain widespread traction due to hardware costs and user limitations. SportAI’s strategy, which requires no special hardware beyond a video capture device, offers broader scalability and ease of use. While other companies had focused on integrating sensors into rackets, SportAI’s software-based model enables instant feedback with minimal infrastructure, eliminating the need for manual tagging or specialized coaching tools.
Who benefits from SportAI’s platform?
How does the technology work across different user groups?
SportAI offers its platform to various stakeholders including professional federations, broadcasters, sports academies, and equipment brands. It delivers AI-driven analysis by comparing an athlete’s movements with a large database of player data, including that of professionals. Feedback includes visual overlays and written summaries, enabling scalable coaching and performance tracking. These features provide an alternative to expensive one-on-one coaching, which often varies by instructor and lacks consistent metrics.
The system’s real-time processing stands out as a key feature. Instead of manually tagging video, users receive automatic analysis seconds after footage is captured. This is particularly useful for organizations that manage large player bases, allowing them to evaluate and monitor thousands of players simultaneously.
“One of the most exciting things is how instant the analysis is,”
explained co-founder Lauren Pedersen, who has a background in both competitive tennis and the tech industry.
Because SportAI’s platform is hardware-agnostic, it can analyze videos sourced from mobile phones, fixed court cameras, or television broadcasts. This flexibility expands its utility to consumers, coaches, and content creators. The company is also partnering with racket manufacturers to align player data with equipment recommendations.
“Player-level detection via a short video clip allows us to match a player’s actual technique and ability to the right equipment,”
said Pedersen, adding that this may improve customer satisfaction and support product development.
By avoiding dependence on proprietary hardware, SportAI aims to reach wider markets.
“Not everyone has access to smart rackets or sensors. But almost everyone has a phone,”
noted Pedersen. The platform offers equipment brands a way to collect user data and offer personalized recommendations without managing physical tech infrastructure. This method also reduces concerns around device maintenance, battery life, and adoption rates.
The company is targeting racket sports first but sees potential in extending its technology to other sports where technique and biomechanics are critical. SportAI has already partnered with Matchi, a fast-growing racket sports platform. Through this collaboration, automated analysis and statistics are being delivered across thousands of courts equipped with cameras.
“Players love highlights and data and are willing to pay for it,”
said Pedersen, highlighting how the service can become a revenue stream for sports clubs and federations.
SportAI’s software-based analysis enters a space that has long been dominated by expensive, hardware-reliant systems and subjective coaching methods. By using AI to process video data from common devices like smartphones, the company offers a scalable and more affordable alternative. For consumers, this means improved access to personalized feedback and better gear recommendations. For coaches and organizations, it provides a tool to track performance across large groups. As the company expands its offerings beyond racket sports, the same principles could apply to any activity where biomechanics influence results. SportAI’s model shows how software can replicate services that once required high-end equipment, offering potential for both mass adoption and targeted insights.
