From Hawk-Eye Live to smart racket sensors and AI coaching with Andy Murray, Eastbourne 2026 showcases how technology is transforming tennis for players and fans.
Hawk-Eye Live has been fully operational at Eastbourne since 2024, addressing a longstanding problem on grass courts: ball marks that disappear almost instantly after impact. The system eliminates the need for human line judges, providing near-instantaneous calls accurate to within millimeters. For players, this means fewer distractions and a sharper focus on strategy rather than disputing calls.
“On grass, you lose the mark immediately, so Hawk-Eye Live is a massive upgrade. It gives you confidence that every call is correct,” said Jack Draper, who benefited from the system during his first-round match.
The technology also enhances the fan experience. Screens around the stadium and the tournament app display real-time 3D visualizations of ball trajectories and bounce points, allowing spectators to see exactly where a ball landed. This is especially valuable during tie-breaks and close calls, as seen in Draper's tense 7-6(7-5) second set against Marcos Giron. Such real-time data integration mirrors advances in other sports, such as AI-driven predictions in football.
The data from Hawk-Eye is also fed into player analytics, giving coaches a detailed record of every shot's location and spin. This seamless flow from court to tablet is a cornerstone of modern grass-court preparation.
At Eastbourne 2026, several top players are using rackets embedded with sensors that measure swing speed, spin rate, and impact location. These sensors, located in the handle, transmit data wirelessly to coaches' tablets within seconds of each shot. For the first time, fans can see these metrics on broadcast overlays, adding a new dimension to the viewing experience.
During Draper's match, broadcasters showed live spin rates exceeding 3,200 rpm on his forehand, while first-serve speeds averaged 129 mph. Such granular data helps explain the “why” behind winners and errors.
Coaches like Sir Andy Murray, who recently joined Draper's team, use this data to make micro-adjustments between games. “We saw a pattern in the second set – Marcos was attacking Draper's backhand when he moved left. The data confirmed what we suspected, so Jack adjusted his positioning,” Murray explained. This blend of human intuition and real-time data is reminiscent of how athletes in other sports integrate technology to refine their skills.
The combination of Hawk-Eye and smart racket data creates a comprehensive picture of every point, from ball flight to racket head speed. This is transforming both player performance and how fans understand the game.
Jack Draper's victory at Eastbourne on Monday was his first competitive match in over two months, following a knee injury that had sidelined him since April. His training block with newly knighted coach Sir Andy Murray relied heavily on AI analysis of opponent patterns. Draper credited the approach: “We looked at hours of footage with AI tagging key trends. It allowed us to build a game plan that exploited Giron's weaknesses on serve return.”
“I haven't called him 'Sir' yet – that's not going to happen,” Draper joked about Murray's knighthood. “But I'm really grateful that he's chosen to help me. Today was a performance a bit like what he used to do – winning ugly.”
The match itself was a showcase of data-informed tactics. Draper dropped just one point behind his first serve in the opening set, winning it 6-4 in 35 minutes. In the second set, he went up a break but lost concentration, allowing Giron to force a tie-break. Draper held his nerve, winning 7-5 in the breaker. This was his first win since beating Novak Djokovic at Indian Wells in March, a victory that showed the promise of combining Murray's competitive instincts with modern AI tools. The use of AI in sports strategy is part of a broader trend, as seen in AI shaping football predictions and other sport analytics.
The synergy between human coaching expertise and machine learning is not just for elite players. Apps that offer similar AI analysis are becoming available to amateur players, democratizing access to insights that were once the domain of top pros.