This article is co-written with Johnny Parkes and supplements a previous report published on Sport Performance Reports.
Introduction
How was Steve Jobs able to buy Pixar for $10 million and sell it for $1 billion?
It wasn’t due to an above-average business acumen. It wasn’t blood, sweat, and tears.
It was through crossing domains and utilizing a network.
In an 8-year collaborative research study, Dyer, Gregersen, and Christensen (1) sought to gain a deeper understanding of ‘disruptive innovators’. In their book, ‘The Innovator’s DNA’ they highlight 5 commonalities that transcend disciplines and help lead to success – one of which is networking. The author’s found that innovators ‘actively search for new ideas by talking to people who may offer a radically different view of things’.
Crossing over domains can yield brilliant results in creativity.
In a similar manner, when coaches from different backgrounds and experiences engage one another in regular and open dialogue, they can combine approaches and connect more dots within athletic performance.
In this article, we show how a decades-old concept in track & field can be combined with common game style categorizations in tennis to gain a deeper understanding of individual athletes and create a more collaborative environment amongst coaching staffs.
Profiling Middle Distance Runners using the Anaerobic Speed Reserve Concept
The middle-distance running events in track and field have long been a point of contention – in large part due to the difficulty in narrowing down what we actually mean by ‘middle-distance’. Historically, this grouping has covered competitive distances from 800m to 5,000m, or events lasting in duration from approximately 1.5 minutes to 13 minutes.
Within this range of events lies a broad range of effective training methodologies. If we simply look at those who compete over the 800m distance, we will come across athletes who find success training as a 400-800m hybrid (sprint-based), an 800m specialist, or an 800-1500m hybrid (endurance-based).
With this variance, profiling athletes to better understand them on an individual level is imperative when looking to fine-tune performance at all levels of the sport. The method of choice in this regard utilizes a concept known as Anaerobic Speed Reserve (ASR).
The ASR is the speed range from an athlete’s velocity at maximal oxygen uptake (vV̇O2max), also known as maximal aerobic speed (MAS), to their maximal sprint speed (MSS) (2,3). These metrics allow us to consider the aerobic/metabolic role through MAS and the neuromuscular/mechanical input through MSS.
Both MAS and MSS can be obtained relatively easily. Briefly, MAS can be obtained from simple field tests such as the 2 kilometer or 6-min run test (e.g., 1600m covered in 360 seconds equals MAS of 4.4m/s). Maximal sprint speed (MSS) can be tested over distances of 30-40 meters using timing gates placed every 5-10m (i.e. 20-25m, 25-30m, etc.).
Fig 1. Adapted from [4].
As the floor (MAS) and ceiling (MSS) of ASR may shift throughout the off-season training and competition season, assessments should be done periodically throughout the calendar year. This provides insights into an athlete’s strengths and weaknesses at various time points, which can subsequently help guide decision-making in the training process. Further, it affords us the opportunity to profile an athlete. This profiling can be a critical step in managing large groups when trying to incorporate some level of individualization to the training program.
In addition to the ASR, the Speed Reserve Ratio (SRR) can also be easily calculated by dividing the MSS by the MAS. For instance, if an athlete has a MSS of 8.8 m/s and a MAS of 4.4 m/s the SRR equals 2.0 (8.4 / 4.8) . This provides a single number which can be used to determine whether the athlete is endurance-based, speed-based, or a hybrid.
Fig 2. Sample speed reserve ratio data with shaded areas highlighting, from left to right, endurance-, hybrid, and speed-based profiles.
Coming back to the 800m example in track and field, the graph below highlights three individual athletes, all with similar 800m times (2:03.36 – 2:04.65).
Fig 3. Adapted/recreated from Sandford GN, Stellingwerff T. “ Question your categories”: the misunderstood complexity of middle-distance running profiles with implications for research methods and application. Front Sport Act Living. 2019;1:1–8.
While the outcome is similar, the manner in which each athlete gets there is quite unique. For instance, Athlete A’s strength lies in their MSS, which is the weakness for Athlete C. Athlete B presents a well-rounded profile for the specific demands of the 800m.
It’s important to note that one particular profile is not necessarily ‘better’ than another. We are simply trying to better understand the individual athlete in order to make informed decisions on the training program.
From the Track to the Pitch to the Court
Similar to the middle-distance events of track and field, the ASR, with its adaptable determinants (MAS and MSS), also reflects the complexity of the speed and metabolic demands involved in other sports. Sandford and Buchheit (2021) explained,
“Varying locomotor profiles can be found across team sport players, which can… logically predispose players to certain playing positions in the team that fit with tactical models” (4).
In tennis, we often ‘zoom out’ and look at the entire sport to make generalizations on the demands of the sport, or its determinants of performance. This ignores the unique and intricate characteristics of the game, and more specifically, of the individual differences in tactical strategies between players with varying game styles.
Starting with the game, Fernandez et.al (2014) described the demands of tennis as, “intermittent whole body efforts, alternating short (2–10 s) bouts of high-intensity exercise and short (10–20 s) recovery bouts interrupted by several resting periods of longer duration (60–90 s), with a typical average match time of 1.5 h, although in some cases it can last for more than 5 h. After serving around 200 km/h, a tennis player runs an average of 3 m per shot and a total of 8–15 m with 3–4 changes of direction in the pursuit of one point, hitting the ball an average of 4–5 times and completing 1300 to 3600 m per hour of play, depending on the player’s level (amateur or advanced) and court surface (slow or fast)” (5).
Due to these varying demands of match play, it is important to consider an athlete’s game style in relation to their physical strengths and weaknesses. This is no different from soccer, where positional demands can alter the training programs employed.
“Playing style is important to understand in order to effectively train tennis players. It is essential to understand the player’s style that is being trained, as many differences do exist and the training programs will depend on the style.” – CTPS Workbook
The four main game styles as described by the United States Tennis Association (6) are described below in Table 1.
Table 1. Tennis game style characteristics; adapted from USTA Player Development Journal.
When examining individual differences in physical capacities, the game demands can vary not only according to game styles, but when different game styles are matched up against one another. Common examples are:
1. Smaller body types with a counter-attacker game style generally have slower serves and may have higher average shots per point.
2. A taller body type may have lower average shots per point due to having a faster serve that allows them to serve and volley or serve and have an “easier” shot after the serve.
Data from Tennis Analytics, a company that provides match and technical analysis services to top professionals on the ATP and WTA tours, USTA Pro and Player Development, Tennis Canada, and over 45 NCAA collegiate teams, suggests an increasing percent contribution in match play of 1-4 strokes per point with age (U12 through college). This is probably in part due to normal growth and maturation (body size, lean mass) of an athlete which in turn enhances athletic characteristics (e.g. speed and power) and skills.
The percent stroke count contributions can be further broken down by game style, especially in the older age groups (U16, U18, NCAA, and professional).
The significance of stroke count gives you an idea of the average proportion of points played with certain time demands, and how this can be linked to individual game style demands. One logical assumption is that the Counter-Attacker and Aggressive Baseliner would have a slightly higher contribution percent in the longer stroke count ranges (9-12 and 13+). The reverse can be assumed for the All-Court player and Serve and Volleyer (i.e. the percentages would be higher in the shorter stroke count ranges).
Further analysis is needed to understand the averages for each game style and to understand the impact of one game style vs. another. Environmental constraints can also play a factor with different surfaces and court speeds.
Special Considerations
In the younger age groups (U12 and U14), defining players by a game style could prove difficult as we wouldn’t want to pigeonhole a player into a particular game style if they end up having physical and athletic characteristics that are more suited to another game style following the adolescent growth spurt (i.e. post peak height velocity (PHV)).
Instead, the emphasis in the younger age groups should be on developing holistic and well-rounded athletes with skill sets that are rooted in the fundamental components of sport. Teaching the youth tennis athlete as many technical, tactical, physical and mental skills as possible in the pre and circa-PHV years can make a player more diverse and adaptable in the long term.
As players develop a well-rounded skill set and start to understand their physical strengths attributed to their body type and genetic make-up, they can start to form their on-court game style.
Connecting ASR Profile To Tennis Game Style
An athlete with a Serve & Volley game style must move quickly and explosively, placing an emphasis on MSS. In contrast, an athlete who plays with a Counter-Punch game style prefers to prolong a match and fatigue the opponent, utilizing more of their aerobic capacity and MAS.
With this in mind, we assigned a SRR value to each game style. We started by placing values to both ends of the spectrum. Counter-Attacker characteristics require them to be consistent, play longer points, and move exceptionally well. This would require them to rely more on aerobic capacity and align with a SRR less than 1.65.
At the other end of the spectrum, Serve and Volley players put instant pressure on their opponents by playing at the net, reacting and returning the ball quickly. This game style requires a greater speed profile to play shorter points explosively. Given these characteristics, we assigned this game style a SRR value of greater than 1.89.
The Aggressive Baseliner and All-Court Player would therefore sit in the middle as a hybrid profile with a SRR between 1.66 -1.89. However, an Aggressive Baseliner may lean closer towards the endurance side and an All-Court player may lean towards the speed side.
Table 1. Tennis game style characteristics. Adapted from USTA Player Development Journal
This information proves useful when making training decisions. Once we understand an athlete’s ASR profile, we can better determine how much time and energy to spend on the various components. At times, we may want to push the ceiling (MSS) by reinforcing their strengths. Equally, there may be times we choose to raise the floor (MAS) by challenging their weaknesses.
Closing the Loop
The act of categorizing provides two main benefits – it reduces complexity and adds meaning. The process we undertook was as follows…
1. Test the athlete’s to identify their locomotor profile, this “reflects their individual propensity for dominance in speed versus endurance aptitude” (4).
2. Discuss results with the tennis coaches and identify the individual game style of each tennis athlete.
3. Select the training priorities / group for each athlete based on a desire to target strengths or weaknesses.
4. Individualize programs for athlete’s in each sub-group.
Coaches are constantly making many micro and macro decisions around the athlete’s training duration, intensity, frequency and load. As tennis is a complex sport that trains and competes year round, the daily training decisions are centered around what phase the athlete is in, which is often looked at as, “How long until the next competition?”.
Table 2. Variation in programming based on duration of time before next competition.
Whether it be event demands in track and field, positional demands in soccer, or game style and match demands in tennis, accurately identifying said demands can highlight a potential endpoint for our physical development plan. It adds meaning through providing a destination. But where do we start?
For this, we need to better understand the individual. Through testing an athlete on their neuromuscular and metabolic capacities we can identify their strengths and weaknesses, subsequently reducing the complexity that is inherently involved in working with humans. We have found our starting point.
In the space between the starting point and the destination, with the complexity reduced and heightened purpose added, our philosophy, knowledge and experience as coaches can shine. This enhances the trust, connection and relationship with the athlete to continue to develop long-term.
In Part 2, we will dive into training methods, individual considerations of each athlete, and results in the physical testing and on-court.
References
1. Dyer J, Gregersen HB, & Christensen C M (2011). The innovator’s DNA: mastering the five skills of disruptive innovators. Boston, Mass., Harvard Business Press.
2. Blondel N, Berthoin S, Billat V, Lensel G. (2001) Relationship between run times to exhaustion at 90, 100, 120, and 140% of vVO2max and velocity expressed relatively to critical velocity and maximal velocity. Int J Sports Med.; Jan;22(1):27-33.
3. Buchheit M, Laursen PB. (2013) High-intensity interval training, solutions to the programming puzzle Part II: anaerobic energy, neuromuscular load and practical applications. Sports Med.; 43:927–954
4. Sandford GN, Laursen PB, Buchheit M. (2021) Anaerobic Speed/Power Reserve and Sport Performance: Scientific Basis, Current Applications and Future Directions. Sports Med.; Oct;51(10):2017-2028.
5. Fernandez-Fernandez J, Ulbricht A, Ferrauti A. (2014) Fitness testing of tennis players: How valuable is it? British Journal of Sports Med.;48:i22–i31
6. United States Tennis Association Player Development Journal (2020); Access: http://assets.usta.com/assets/1/15/8086_Player_Development_Journal.pdf