Tie-Break Performance: Who Thrives or Struggles Under Pressure?
Which ATP players overperform in tie-breaks relative to their level? Comparing tie-break win % against games won % reveals some surprising names — including Nadal.
Tennis Lab
9In Tennis Lab, I analyse tennis betting using data and interactive charts, focusing on how favourites and underdogs behave across different tournaments, surfaces and contexts. The goal is to understand long-term patterns that help build a real betting edge.
The "Giant Killer" Effect: What Happens After You Beat Djokovic, Nadal, Federer, Sinner or Alcaraz?
What happens if you bet on the player who just beat Djokovic, Nadal, Federer, Alcaraz or Sinner? How does he do in his next match? Results inside.
Underdogs vs Favorites in Masters 1000 Hard Courts: What 16 Years of Data Show
6,000+ bets. 16 years. Underdogs have clearly outperformed Favorites at Pinnacle closing odds in Masters 1000 hard courts. Full analysis here.
Indian Wells: Where Underdogs Consistently Outperform Favorites
Indian Wells has historically been one of the worst tournaments for betting favorites. We break down the numbers — and ask whether this reflects a systematic market inefficiency.
Rio's ATP 500 Heat Burns Favorites
Favorites have been a losing bet in Rio since 2010. The data shows a statistically significant gap with underdogs — and the brutal playing conditions might explain why.
Grand Slam Betting: How Often Do Matches Go to 5 Sets?
A data-driven analysis of how Grand Slam matches are decided, from straight-sets wins to five-set battles and retirements.
Australian Open Betting: Underdogs Yield –9.8% (Women)
Betting on underdogs at the Australian Open (Women) is a losing game, but less negative than in the men, due to the best-of-3 format.
Australian Open Betting: Underdogs Lose –20.1% (Men's Data)
Discover why betting on underdogs at the Australian Open is a financial disaster. An analysis of 2,008 matches reveals a brutal -20.1% yield.
The Favorite–Longshot Bias in Tennis: Evidence from 40,000 Matches
Data analysis of 40,000 ATP matches proves the Favorite-Longshot Bias in betting. Underdogs yield -5.6% vs -2.0% on favorites. See the evidence.