Tennis Data Analytics and Statistics

Tennis Data Analytics and Statistics

Baseball and Premier League football have seen the use of statistics flourish over time, while tennis was initially latecomer to this trend. It is slowly catching on however; world-class players such as Craig O’Shannessy hire strategy coaches like him to interpret their data for them.

Analytics have become more prevalent thanks to smart equipment like Hawk-Eye optical tracking cameras used at top tournaments with latency of less than 400 milliseconds on one camera angle.

How it works

Tennis, like other sports, features one-on-one interactions between players. Yet despite this uniqueness, its analytics development has lagged behind other sports. This could be attributable to structural changes within the sport itself as well as efforts taken by its governing bodies to protect data.

That may be changing thanks to improved technology and an emergence of startups and academic projects dedicated to analytics. With their help, national governing bodies now provide shot-level data while new metrics such as “red steps” have entered tennis’ vocabulary – quantifying how often a player moves forward during a point.

Alongside these advances, the ability to index footage and produce detailed analyses with just a single camera angle has unlocked new opportunities. Foxtenn has developed a system that accurately tracks and analyses ball paths during practice or matches; that information can help coaches pinpoint ideal training practices or assess player execution of strategies effectively during matches.

These new metrics are helping both tennis coaches and players understand how they can improve their games and win more matches, while making it easier for fans to connect with the sport in ways previously unavailable.

Tennis analytics alone cannot guarantee improved player performance; other intrinsic factors — like mental approach, physical conditioning and endurance over five-set matches — still have a profound effect on any match’s outcome.

However, all players would do well to jump on board with analytics – its benefits can even extend to high levels of play.

Discovering that a rival has a powerful crosscourt forehand but struggles to maintain consistency over long rallies can help you formulate an effective plan against them, while knowing their wide deuce-side serve is more successful against certain players can give you an advantage when selecting your service order.

What it can tell you

Data analysts working with top American tennis players find the United States Open qualifying season their most hectic time of the year. Their 15-hour days consist of creating and curating quantitative data and video clips to provide players and coaches with a competitive edge by assessing the effectiveness of specific shots against their opponents.

Hawk-Eye optical tracking cameras have become an indispensable piece of smart equipment in top prize tournaments for over a decade, providing superior tracking analysis with less than 400 millisecond latency on one camera angle – surpassing previous efforts in sports analytics.

Advanced tracking technology not only aids refereeing decisions such as line calls, but it can also assist coaches in analyzing player movements on the court to identify strengths and weaknesses – information which they then pass onto players to enhance training regimens or focus on specific skill sets during practice sessions.

Data collected during a tennis match provides us with insight into not only how fast players serve but where on the court it lands and what type of spin it has. Such insights are beneficial not only to coaches and players preparing for competitive matches but also provide fans with unique content to make watching an event even more exciting and immersive.

Tennis will soon join the Moneyball era of sports if it can remove structural barriers that have kept high-quality data away from players and coaches who most need it – Novak Djokovic may have set an example in this regard by leading an initiative among professional tennis players that may help overcome some of these hurdles.

As the ATP and WTA collaborate with analytics companies, incentives can be aligned for data collection of performance-related points to benefit both players and fans alike. But ultimately, only demand from players themselves will unlock its full potential.

How it can help you

Data analytics is an effective way to gain a competitive edge. It enables you to assess the strengths and weaknesses of your opponents and tailor your game around them; whether that means finding out that an opponent struggles running down crosscourt forehands or tends to serve wide in ad court, data can provide direction in these regards.

Tennis has begun to catch up to other sports in terms of data analytics. Top tournaments use sophisticated equipment, including Hawk-Eye optical tracking cameras that can detect players and the ball with less than 400 milliseconds latency from just one camera angle – this allows spectators to gain an overall perspective.

This technology can also identify player tendencies and assist them in improving their game by pinpointing areas they should focus on improving, such as first serve percentage and ace count. Analyzing service statistics may highlight this need. For example, looking at first serve percentage and ace count will highlight where improvements need to be made.

Shot analysis can offer players and coaches invaluable insights. Analyzing the percentages of shot length in a match, for example, can reveal which types of shots are more successful than others and pinpoint a player’s most effective volleys.

Big data in tennis can also assist players in developing their fitness and endurance by giving them a clearer idea of their energy levels and helping to avoid over-training while simultaneously making sure they work efficiently and effectively.

Data analytics have proven their worth in tennis by helping many young players hone and perfect their games, so it is likely that more and more people take advantage of data-analytics opportunities available to them. Tennis will likely continue to flourish as more people make use of available data-analytics solutions.

But in order to truly realize the potential of data in tennis, you must alter the structures that prevent its reach reaching those players and coaches who could most benefit. While this might prove challenging, Moneyball provides a model of actionable steps you can take as a way forward.

How it can hurt you

Even though analytics have the power to revolutionize tennis, its adoption has been slow. Even today, advanced analysis tools like Hawk-Eye used for reviewing line calls at top tour events remain out of reach of players and coaches who could benefit. One reason could be economic incentives at play here, with tournaments seeking to keep analytical data out of analysts’ hands in order to maximize sponsorship revenue and broadcast rights values.

Top players could benefit greatly from being able to monitor the details of both their own and opponents’ games, for example by being able to access data about crosscourt forehands or slice backhands down the line that were most effective during long rallies, who is losing concentration during these exchanges, who has difficulty switching direction quickly or changing directions quickly, etc. To develop such a database it would require viewing hundreds of matches by dedicated analysts like Montrealer Sebastien Lavoie, who contributes at Australian firm DDSA providing tennis analytics services for top players, juniors and coaches alike.

Lavoie’s work involves tagging video of tennis matches using software such as Dartfish to assess players and their performances. This type of data analysis enables coaches to uncover patterns in returns, player positioning, hot and cold plays and other factors which might alter game play; players can use this knowledge to identify areas for improvement and identify ways they may need to change their approach to match play.

Analytics have the potential to produce dramatic effects for players. A study by Dr Reid and La Trobe’s Associate Professor Stuart Morgan of three years of Australian Open Hawk-Eye data demonstrated that most shots that win points occurred from similar distances from baseline. This indicated that players who tend to play deeper and closer to the line than their opponents preferred enjoyed an advantage over those who played further away from it.

Some top players such as Novak Djokovic and Roger Federer have hired strategy coaches to help them take advantage of data analysis, but an analytics revolution for tennis may only really occur once structural barriers have been removed to allow greater access to data and an abundance of analytic skills in players and coaches alike.