Models for predicting tennis matches

Last updated on December 27th, 2021

Predicting tennis tournaments can cause headaches for bettors, but it’s also a fairly profitable industry. It’s worth considering bookmakers with competitive betting lines to increase your chances of high profits. 



Many bettors have chosen VOdds to create a betting account and have been loyal to the sportsbook aggregator platform since then. Here you can have a multi-purpose dashboard displaying pre-match and live tennis odds and enjoy prompt technical support anytime. 


Now that your account is set, here are a few tennis prediction models you can use to analyze and forecast the game result. 


Tennis Betting Models You Can Use For Your Next Bets


Head-to-Head Model


In studying the history of head-to-head matches between tennis players, it’s recommended to look for matches where the maximum advantage is observed instead of simply looking at the number of victories between them. 


Let’s take an example: Roger Federer won 25 of his 28 games against Stan Wawrinka. There’s more weight in paying attention to the context of their matches. Wawrinka won all three games on clay court, while Federer did not give any opportunity for his opponent to win on grass courts.



Keep in mind that we are talking about more than a decade of confrontation history. This only confirms that the individual qualities of athletes and their skills have greater impacts than simple statistics of the game.


Serve Percentage


This is one example of the Point-based tennis models. Serves are considered extremely important in predicting tennis. 


Tennis players who perform a good serve, especially the first serve, have a huge advantage over their opponents. A single point involves several shots, but the serve is the only action conducted without the opponent’s interference.


If unfulfilled, the athlete will have great difficulty during the match. It will likely cause them to be at disadvantage if the opponent has the head start. Consider some of the factors that can affect whether or not a player hits the first serve so that you can include them in your tennis predictions and betting models. 


  • Weather conditions (like wind, snow, or rain)
  • Court surface
  • Athlete’s tournament preparations


Regression-based Models


When you have data that could predict outcomes but their connections with each other are unclear, Regression-based models are helpful.


This model works by studying correlation and gives you an estimate on how impactful each factor is. One well-known example of this model is the analysis done by Del Corra and Prieto-Rodriguez in 2010.


They studied 20 factors ranging from court conditions to physical differences among professional tennis athletes. They discovered that for Association of Tennis Professionals (ATP), world ranking is the most important predictor of which player to win. Age and past performance are also good indicators, except for height, which is insignificant. 


As seen in all three models mentioned above, all of them heavily rely on data to predict outcomes of tennis odds matches. You can use readily available datasets from other projects in Github or you can collect your own using sports betting API


We also recommend reading our article “Tennis Betting: Features and Nuances”. After reading, your tennis bets will be more accurate!

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