Outsiders have often played a pivotal role in driving statistical innovations in sports. Their dabbling helped transform an English cricket reporter from 19th-century into Baseball’s father; while another worker on night shift at a pork and beans factory came up with texts for sabermetric societies.
Tennis analytics have taken time to gain ground, yet have seen impressive strides over recent years. Data-centric companies now exist that offer services for players, coaches and broadcasters.
Ball Trajectory
Players and coaches looking to maximize their tennis game must consider various variables that could alter ball trajectory. These variables include the type of racquet used by each player, their biomechanics, dwell time on racquet, tension of the racquet stringing system, environmental conditions (such as altitude density) as well as ball weight; these will all come into play when formulating how the ball will travel forward or backward from its point of contact.
These factors all play an integral role in how the ball travels and, consequently, your chances of winning a shot. For instance, higher ball velocity at impact with the racquet increases its probability of traveling upwards as it leaves the racket; however, having such high ball speeds also creates more drag as they pass through the air, making horizontal movement across court more challenging.
Talent and fitness remain key components of tennis success, yet data analytics have opened up a whole new sphere in the sport. Players and coaches can now leverage data to better understand opponents’ games – for instance knowing whether a rival might serve well in the fifth set or rush to the net more frequently than anticipated.
As opposed to baseball, where Michael Lewis’ book and Brad Pitt’s film Moneyball popularized sabermetrics with mainstream audiences, tennis’ adoption of advanced statistics has been more of an evolutionary process. Yet recently new technologies have seen increased adoption due to advances that allow more efficient data capture and processing capabilities; companies like GIG, TennisViz, Hawk-Eye and Dartfish are offering various Big Data Analytics-related innovations for use by tennis players, coaches and broadcasters alike.
Player Movement
Tennis’ push for more granular analysis of players and points has been an effort to increase engagement with the sport and appeal to younger fans, similar to its efforts with baseball. Unfortunately, like its counterpart, dismantling barriers preventing an analytics revolution may prove challenging; as is often the case when dealing with institutionalized barriers. Outsiders will likely play an integral part in ushering tennis into its Moneyball era–this same kind of dabbling which propelled 19th-century English cricket reporter into being known as America’s Father; night guard at pork & beans factory night guard turned into a foundation text of an emerging sabermetric society (Schiff 2008).
Top tennis players already pay six-figure retainers to analyst teams, yet it was only in 2013 when Djokovic started using detailed statistics, followed by Federer in 2017. This delay can be explained by the nature of tennis being an individual sport rather than team competition.
Hawkeye, a camera system using up to 10 cameras positioned around a court to map out the position of the ball in 3D, has begun collecting player movement data as well. This will give coaches new insight into when their players transition between defensive and attacking positions and how best to prepare their players for changing dynamics of each point.
Lvision uses computer vision technology to convert “single vantage point video feed into metrics.” Their goal is to help players better understand where their shots are landing by tracking trajectories of shots as well as steps taken by each player, and using this data to identify effective ways of improving player performances and make more intelligent coaching decisions.
Shot Type
While tennis may not be as advanced in its use of data analytics as other sports, it has seen steady advancement in recent years. Technology makes collecting and evaluating more data points simpler; video tagging services like DDSA and Tennis Analytics also provide useful metrics that coaches and players can use, such as percentage won on first serves as well as how a point will unfold depending on player positioning over time.
At the forefront of data analysis in tennis are specialized tools available for professional players. This technology allows them to scout opponents before matches, identify patterns in returns, and gain insight into how court surfaces or weather conditions impact play. While these tools can aid performance improvement, they cannot replace intrinsic factors like physical readiness and mental approach that impact on overall game strategy.
Tennis still has the opportunity to join the Moneyball era of sports, but this will require structural reform that ensures high-quality data can reach athletes and coaches who would most benefit from it. One solution could come from within: when players organize to demand access to information they need in order to compete at their highest level.
No matter if it be game film breakdown, events indexing, or match reports; our aim at DDSA is to assist tennis players and coaches alike with developing their game through data. So join today and see how DDSA can take your tennis to new levels; annual contracts include current season content as well as up to three past season content!
Shot Quality
Shot quality is another metric used to assess the efficacy of tennis player’s play. According to the ATP’s website, “Shot Quality is a score between 0-10 that evaluates shots’ speed, spin, depth and angle – providing players with useful data regarding what shots work against particular opponents or which patterns appear in their play.
As more data points become available, coaches are turning increasingly to analytics as a means of improving player performance. This trend can especially be found within top-tier professional tennis where enormous sums of money are at stake and every edge counts.
Data offers coaches and players many advantages, yet it must be remembered that data cannot replace intrinsic factors when it comes to predicting match outcomes. No matter how great a player’s shot selection or tactical strategy may be; match outcomes ultimately depend on factors like their fitness level, mental attitude and stamina.
Even with these caveats in mind, analytics in tennis have proven beneficial to fans and players alike. More data has allowed analysts to examine individual player styles more in depth and make more accurate forecasts about future performance.
“Tennis Fingerprinting,” an innovative method for analyzing tennis performance, utilizes video analysis and Hawk-Eye optical tracking cameras to measure ball and player movement with very little latency – helping coaches and players understand which strategies and styles of play work most efficiently against opponents.
Scoring
Scorekeeping is one of the key elements to consider when analyzing sports and improving tennis play, scoring being of particular significance. Analysing data about player rallies won, errors committed and energy expended per match provides invaluable insight that allows both players and coaches to make smarter strategic choices during a match.
Lvision, a newly developed sports data analytics technology, is being employed by multiple specialized sports data analysis companies to transform match video into big data. This allows tennis players at junior levels of the sport to tag their own match videos and analyze them for performance metrics such as winning percentages on first and second serves, likelihood of taking points from opponent second serves or shots’ anthrometric characteristics.
However, there remain obstacles preventing an all-out tennis analytics revolution. With structural changes to professional competition having taken effect since 2000 and keeping data away from players and coaches who could most benefit from it; tennis will likely never experience its own Moneyball era of sport unless these structural hurdles are eliminated.
Though these challenges exist, those interested in applying a more sophisticated approach to tennis do have opportunities. Numerous tech-focused companies are keen to assist players, coaches, broadcasters and fans by providing new insights into its development using various technologies like advanced camera systems like Hawk-Eye as well as crowdsourcing platforms – these technologies will likely increase the richness of tracking data as their development unfolds.