The TennCom Model: A New Approach to Reviewing Tennis Racquets
The Context for My Frustrations, Hence… My Genius
You have no idea how many times I’ve been asked the question “what is the best racquet?” On the surface, the question is quite reasonable. You are about to spend a few hundred dollars, you want the best. But take a second to analyze the question and you will realize it is fucking stupid. If there was one “best racquet,” we would only sell one type of racquet. So long as the racquets are made of the similar material type and quality, with the same generic “tennis racquet” design, no racquet is strictly “better” than another. It’s all preference.
Having worked in the tennis industry for years, as a customer service rep, master racquet technician and YouTube sensation (haha), I have spent many eye-wateringly boring minutes trying to explain how racquets feel and what they play like. The differences between “good” racquets and “bad” racquet is entirely subjective. Yet I can understand why a consumer would think there is a “best racquet.” Those subjective differences are defined by objective, physical properties. These are headsize, static weight, stiffness, beam width… the list goes on. These physical properties are objectives means for manufacturers to develop certain playing characteristics into a racquet. These playing characteristics are then interpreted by the player. Since every player is different, we have subjective views on what playing characteristics are desirable and which are not. Interestingly, these playing characteristics are often mutually exclusive. Despite the conventional marketing wisdom, one cannot really have both more power and more control.
My previous scoring system, implemented with in my Courtside Reviews, was a relatively “objective,” or “empirical,” way to describe these playing characteristics. The magnitudes of 5 key playing characteristics, Power, Spin, Stability, Control and Feel, were scored out of 10, as a means to compare the relative playability of different racquets. This scoring system did not account for a few crucial items.
The first shortfall was the mutual exclusivity of playing characteristics. It was possible for me to score both power and control as a 10, even though it is, in my opinion, a theoretical impossibility.
The second shortfall was the lack of consideration for different classes of racquets. I made a conscious effort to base my scores for racquets in comparison to other racquets in their class, but this was never explicitly stated, nor were the classes ever defined. The reason for this is vagueness between racquet classes. I’m not sure how I would have split things up. By weight? Swingweight? Target demographic? It was all too vague and would be too imperfect in the ultra saturated tennis racquet market. For example, the Blade 104 CV. It is a weird racquet. If it for beginners because it’s oversized? Intermediates because of the weight? Advanced because of the thin beam and tight pattern?
The third shortfall was the entirety of the feel category. Feel is outrageously complex. Boiling it down to single number does not adequately describe its intricacies, from comfort to level of feedback and more. Not to mention the fact the feel is the single most subjective category in tennis.
A 3-Dimensional Model for Scoring Racquets
A 3-D graph plotting weight distribution, string-bed performance and potential energy. Beckett Chung. TennCom Media, 2021.
I studied economics in university so I am a sucker for a good model. Something that over simplifies and complex system in just the right ways. To help with visualization, I felt it best to limit the dimensions of playing characteristics to 3. These dimensions will address the 3 shortfalls as listed above.
First, mutual exclusivity, by using a sliding scale we can assign higher numbers to one playing characteristic and lower numbers to its opposite characteristic. We must now completely reject the idea of better. A higher number isn’t better. A lower number isn’t better. It’s just different. Our three dimensions will be:
Potential Energy: Control (lower number) -> Power (higher number)
Stringbed Performance: Lower launch angle (lower number) -> Higher launch angle (higher number)
Weight Distribution: Maneuverability (lower number) -> Stability (higher number)
Second, consideration of different classes, this is why it was imperative to limit the dimensions to 3. Comparable racquets should lie near to each other on the 3D plane. Lack of specific class definition should help reduce bias among the consumer, while reflecting the ability of manufacturers to produce “segment disturbers,” like the previously mentioned Blade 104 CV.
Third, feel. Ok this is a cop out, but I’m completely removing feel from the “playing characteristics” umbrella. From now one, “playing characteristics” will be exclusively racquet qualities that affect the physical properties of the ball after it leaves your stringbed. These being, the acceleration of the racquet face, the spin imparted on the ball and the direction the ball is launched off the strings. Feel should have no affect on how the play is put into play, but rather feel describes the sensations felt by the user which then inform the user of which physical properties were imparted on the ball. We will discuss feel later on.
Potential Energy
So potential energy refers to how much potential a racquet has to impart MPH and RPM onto the ball. Basically we have power vs. control and spin vs. control. The following is a list of physical properties that will increase “power.”
Mass. The heavier the racquet, the more force can be transferred to the ball. Think: heavier fighter punches harder.
Head-Heavier Balance. The more weight behind the ball, the more efficiently the force is transferred.
Swingweight. Basically the most important number in any racquet. It is a culmination of the weight and balance, but also takes into account polarization, or weight distribution. As the distribution of weight nears the poles (hence, polarization), the swingweight will increase exponentially.
Stiffness. The stiffer the racquet the more efficiently it returns energy to the ball.
Beam thickness. This is often a commentary on stiffness, as from a manufacturing perspective, its the most efficient way to increase stiffness.
While all of these factors increase power, they also increase spin potential. Spin potential is basically the same as power in the way that the more efficiently that the racquet can transferring force onto the ball, the more spin there will be.
It this case, we will describe the absence of power and spin as control. This comes from the modern interpretation of control racquets as those being thin beamed, soft racquets with tight string patterns.
Stringbed Performance
String-bed performance is primary based off the string-bed’s density. As the strings are (supposed to be) the only things that actually contact the ball, their relatively orientations define the angle at which the ball leaves the string-bed. It is pretty much impossible to actually calculate a racquet’s exact launch angle because we cannot isolate the variables on a string job. The stringer’s technique, the machine used, the quality variance among different string batches, even within the same type of string, as well as racquet manufacturing differences and ball manufacturing differences are just some of the variables that we cannot control for when attempting to test a racquet’s launch angle. This means we are stuck with using human experience to measure launch angle.
Denser string-bed’s will launch the ball at a lower angle. If you tend to over hit and the ball often flies long, consider a denser stringbed.
A more open string-bed will launch the ball higher. If you hit the het more often than miss long, consider a more open bed.
More open string-beds are open perceived as more powerful due to the easier access to depth, however, there is little evidence to support that a more open string-bed leads to more ball speed/
More open string-beds are also often related to spin potential. The idea is that a larger gap between the strings leads to less friction between the strings, promoting snapback. In general, from my personal experience, I would agree with this notion.
Weight Distribution
This describes the general weight distribution in a racquet, both from tip to tail, and from 3 to 9 o’clock. Once, again, the consumer does not typically possess the tools to measure the weight distribution, so one must rely on their playing experience for deductions. There are a few key factors we need to consider to understand how weight distribution affects a racquet.
Swingweight: Another fairly common measure, swingweight is a key dynamic measurement that explains how racquets exert force. Holding everything constant, increasing mass and the balance point will always increase the swingweight. There is a a common misconception that adding weight to the handle will lower the swingweight. This is mathematically impossible. Swingweight is measured in kgcm^2, meaning you multiply mass by distance (more detail on this in a further article). The third factor that determines swingweight is the polarization of the racquet. Polarization describes how the weight is balanced on the racquet. For example, consider a racquet with an even balance. If you have all the weight concentrated around the balance point, you will have the lower swingweight possible for your given specs. If you have half the weight at the tip and the other half in the handle, you will maximize your swingweight. Polarization is rarely, if ever, described by the manufacturers.
Twistweight: Twistweight is the most important number in any racquet that is never talked about. It describes how vulnerable the racquet is to twisting on off-centre shot. More weight you have distributed at 3 and 9, the higher your twistweight, and the more stable your racquet feels. The more concentrated the weight is the the centre axis of the racquet, the more maneuverable it will feel.
In general, the higher the swingweight, the greater the stability, and the highest the twistweight, the higher the stability. Likewise, the lower each is, the greater the maneuverability.
Feel
Ok so finally we will discuss feel. In my opinion, feel is a pretty two dimensional subject. On one hand, we have racquets that are very muted, like the Babolat Pure Drive, and racquets that are very responsive, like Wilson 6.1 95’s. Once again, these qualities are mutually exclusive, and exist on a sliding scale. The second dimension of feel describes ball pocketing, or dwelling time. Racquets like the Head Prestige MP Graphene 360+ hold the ball on the strings for a very longtime, meaning they have strong ball-pocketing characteristics. Racquets like the Babolat Pure Strike 98 feel like the shoot the ball off the strings very quickly. Chris Edwards, the famous Tennis Warehouse reviewer, refers to this characteristic as “point-and-shoot.”
Responsiveness: One way we can think of this is in-terms of the magnitude of vibration. Vibration is typically described as a wave on a graph. The higher the peaks and the lower the valleys on the graph, the greater the magnitude. Responsive racquets will have a greater magnitude of vibration. Muted racquets hide the vibration, lowering the magnitude of vibration. Technologies like Babolat’s Cortex, WIlson’s Countervail (CV) and Yonex’s Vibration Dampening Mesh (VDM) aim to reduce vibrations. It is unclear if they are targeting magnitude, frequency, or both, but to me, they make racquets feel more muted, and less responsive.
Dwell-Time: While string-bed stiffness is the the most important factor when considering dwell time, the racquet has an impact as well. Racquet stiffness is quite important, however simple RA ratings rarely tell the full story. The main issue is RA stiffness describes and average flex across the whole racquet, rather than showing specific soft/stiff points which surely have an impact on dwell time. Typically, softer sticks will have longer dwell times, or better ball-pocketing.
Visualizing Feel on our 3-D Playing Characteristics Model
It was crucial for me to develop a highly visual model that makes it easy for consumers to make buying decisions, even if they don’t have access to racquet demos. This means we are limits to 3-D graphs, but I had to find a way to add the two dimensions of feel to the graph. I believe that the most elegant solution to this is by colour coding each plot. Every racquet will occupy a point on the graph. Each point will be coloured according the a colour wheel.
The more red the point is on the graph, the more responsive it is, the more cyan, the more muted. The more purple the dot is, the longer is pockets the ball and the more lime it is, the faster it shoots the ball off the strings. The more saturated a colour is, the more intensely the given playing characteristic is experienced. The less saturated, the moderate the racquet feels.
Once again, there is no such thing as “best feel,” only different feel.
Measuring
By definition, there is no scientific way to measure scores of racquets, so I’m going to transfer the racquet I’ve tested with Courtside Sports. Below is a master-sheet showing every racquet I tested.
Aspirations
I hope to build a 3-D interactive model accessible on the web so people can easily view and compare racquets. This would be a very easy way to visualize similar racquets according to player preference. One could sort by feel and then isolate certain values. For example, say you like long dwell-time and low launch angles. Just look for purple dots in a specific area of the map to find similar racquets.
