The evolution of player tracking and performance data in professional tennis
How Hawk-Eye tracking turned tennis into one of the most data-driven sports – and why performance metrics now shape every set-winner and game-handicap market
Novak Djokovic, 2025 | © Tennis Majors
Tennis is one of the simplest sports to watch. Two players, one court, a ball that goes back and forth until someone misses. No lineup rotations, no roster depth charts, no weather delays that last three hours. You can explain the rules to a stranger in two minutes flat.
But when it comes to serious bettors, tennis is always said to be one of the toughest sports to bet on. The difference between how simple the sport looks and how complex its markets are is bigger than in almost any other major sport. It’s a good idea to think about this contradiction, because once you understand why it exists, you understand how the whole market is priced.
We tracked this question using ATP and WTA data from the 2025 and 2026 seasons. Most people who bet on the sport don’t realise that the odds are actually driven by something else.
How Hawk-Eye and Performance Data Changed Tennis Betting
For most of the history of tennis, bookies priced matches the way a knowledgeable fan would: head-to-head records, surface, current form, ranking. That info was public, and the market reflected it pretty quickly. The edge was narrow.
Then Hawk-Eye came into Grand Slam matches and eventually spread across the ATP and WTA tours. What started out as a line-call review system has turned into something else entirely: a granular data feed. Every match now generates serve speed, first-serve percentage, break point conversion rate, return points won, and net approach success rate. The ATP tracks more than 60 different performance metrics for each player in each match. SAP processes ATP data through its partnership with the tour, and publishes aggregated player statistics that anyone can access at atptour.com.
The change in the markets was pretty fundamental. Bookies aren’t just relying on reputation when it comes to tennis anymore. They price it based on how well it actually performs, updating it as it’s being used. That’s why in-play odds on a tennis match can change faster than pretty much any other live market: a single break of serve, or a visible drop in first-serve percentage from 68% to 51%, can shift a set-winner price significantly within two games.
This is the bit that casual bettors often miss. They look at the pre-match odds and think they reflect how the match will go. They usually show the results of the last three matches more than anything else.
What Markets Actually Matter, and What Drives Each One
Most of the action in the market for match-winners happens there. But it’s also where you’ll find the most sophisticated pricing. If you’re a regular with player tracking data, you’ll know that the edges, when they exist, tend to be in the secondary markets.
We checked out five market types across a sample of 200 matches from the 2025 and 2026 clay and hard-court seasons to see what data inputs are most linked to correct pricing.
| Market | Key Data Driver | Why It Matters |
|---|---|---|
| Match winner | H2H on surface, current serve %, ranking | Most efficiently priced; least edge |
| Set betting (exact score) | Break point conversion, tiebreak record | Prices vary more between books |
| First set winner | First-set break conversion, serve under pressure | Volatile; useful after checking recent form |
| Game handicap | Average games per set won, variance | Depends heavily on surface and player style |
| Player performance (aces, double faults) | Serve speed, first-serve %, wind conditions | Often mispriced when surface recently changed |
