Authors: Jennifer A. Kurtz* (1), Jake Grazer (2), Bradley Alban (3), Mike Martino (4)
Jennifer A. Kurtz, MS
120 Coventry Court
Fayetteville, GA 30215
Jennifer Kurtz is a doctoral student at The University of
Georgia studying exercise physiology. She is also an assistant strength and
conditioning coach at Elite Performance Institute.
Jake Grazer is an Assistant Professor of Exercise Science at
Georgia College & State University.
Bradley Alban is an Assistant Professor of Exercise Science
at Georgia College & State University.
Mike Martino is an Assistant Professor of Exercise Science at
Georgia College & State University.
Ability for tennis specific variables and agility for determining the Universal Tennis Ranking (UTR): A Review and Recommendations
Our purpose was to investigate tennis
specific measures to predict a player’s Universal Tennis Ranking (UTR) value
and to see what percentage of the variables most influence the ranking. Methods:
15 male and 14 female athletes volunteered to participate in this study. Each
volunteer performed no more than 16 total serves or eight from the add and
deuce side down the “T”, no more than 16 total forehands and backhands down-the-line,
three spider tests, and two trials of footwork taps in 30 seconds. Only the top
two hits were analyzed. Results: A multiple linear regression was calculated
predicting a player’s UTR based on serve, forehand, backhand, agility, and
footwork taps. The regression equation was significant (F (5,23) = 29.66,
p<.05) with an R squared value of 0.866. Coefficient of variation (CV) and
intra-class correlation coefficients (ICC) were calculated to assess
reliability between player serve (r=0.902), forehand (r=0.843) and backhand
velocity (r=0.858), agility (r=-0.817), and footwork (r=0.472). More noticeable
was the significant predictive value of serve (r=0.902) and backhand velocity
(r=0.858) to the player’s UTR. Conclusion: These results underline the important
relationship between the player’s UTR and tennis-specific characteristics
(serve and backhand velocity) as assessed by the player’s stroke velocity. The
ability of training regimens to improve tennis-specific metrics would improve
performance qualities and the player’s UTR.
Key words: tennis,
UTR, ranking prediction, sport-specific tests, sport performance
Tennis involves intermittent
high-intensity efforts interspersed with periods of low-intensity activity in
which active and passive recovery periods take place (6). Tennis matches are
characterized by intermittent periods of whole-body effort, alternating short
bouts (2-10 seconds) of high-intensity exercise, and short recovery periods
(10- 20 seconds) interrupted by several resting periods of longer duration
(60-90 seconds) and a typical match can last about 1.5 hours, and in some
cases, it can last for more than five hours (29). In each point, on average, players
run a total of 8-15 m (with 3-4 changes of direction) and an average distance
of 1300 to 3600m per hour during a match and hit the ball an average of 4-5
times per point depending on the player’s level (amateur or advanced) and court
surface (slow or fast) (20, 29). Knowledge of the contribution of physical and
performance characteristics and ranking measures could assist in determining
the relative importance of such variables to provide optimal training programs.
The role of physical variables in
tennis is gradually increasing due to the physical demand of the sport. The relationship
between the physical capabilities and competition performance of tennis players
creates the possibility of forming optimal conditioning training programs (10).
Previous research indicated agility was the only significant fitness variable
in prepubescent tennis players (ages 8-12) to predict competitive rankings (2,
20, 26, 41). In preadolescence and adolescent junior tennis players (ages
11-16), correlations were found with speed (14, 16, 23, 33, 41), agility and
quickness (14, 23, 33, 41), explosive power of the trunk and upper body (15,
16, 28, 47), explosive strength of the lower limbs (squat jump,
counter-movement jump, and drop jump, core strength of the trunk, hand-eye
coordination (10, 14, 16, 23), aerobic endurance (10, 14, 28, 33), flexibility (33),
and maximal strength of the dominant arm (14, 16, 33) correlated with the
player’s competition performance and ranking. Furthermore, the more a tennis
player matures, their results in physical characteristics showed better
performance levels and stronger correlations than preadolescences and
Successful tennis performance cannot
be defined by one predominating physical attribute; the specifics of these
variables have yet to be determined but correlation studies have been
undertaken to determine which physical components have a strong relation with
match results and ranking. Since it is primarily a tactical and technical sport
that requires open skills, competitive tennis demands a complex interaction of
the major physiological and physical variables (29, 47).
Tennis is a sport with uncertainty
and an unknown degree of transitivity with numerous variables that can affect
the outcome of the match (9). Tennis agility (20, 29, 47), footwork (11),
forehand velocity (13, 22, 27, 37, 44), backhand velocity (5, 11, 13, 23, 26,
43), and serve velocity (14, 17, 22, 25, 26, 27, 48) are predominant factors
that influence performance and ranking. To possess a high ranking, a player
must encompass strong technical skills such as the ability to produce high
amounts of force through serves and ground strokes, have efficient footwork,
and high levels of agility (13, 29). Furthermore, stroke rating was a vital
predictor for tournament performance and national rankings (r=0.94) (26, 39, 41).
The athlete has to master many aspects of their game, such as the serve, a
mixture of strokes, footwork, ball placement, strength, endurance and strategy
in order to exemplify high performance levels (48). Since sport specific
technical skills are predominant factors in tennis, it is unknown to what
extent these variables influence performance and ranking. There have been no studies to date analyzing the extent of
those variables and how they are linked to overall tennis skill and ranking (2).
Thus, much of the available research is based on our knowledge of the physical
demands of tennis.
The rankings of the world’s top
tennis players provide a fast and simple method for predicting match winners
and comparing players. The notion of an overall ranking might seem simplistic
in a sport like tennis which features an unknown degree of transitivity.
However, the plethora of variables in tennis might potentially affect the
outcome of any individual match (9). Previous ranking systems such as the ATP
(Association of Tennis Professionals) (40); the WTA (Women’s Tennis
Professionals) (46); the Page Rank System (6, 9, 46); the Parametric Page Rank
System (1); the Prestige Score (40); SortRank (45); Sports Ladder System (44);
Common Opponent Model (24, 44) and the Network-Based System (34) do not provide
a fair basis of comparison and future prediction of performance since they lack
evaluating tennis specific variables. Official ranking systems do not precisely
and accurately rank players according to their abilities but rather they measure
their cumulative progress throughout various tournament rounds. Previous
research has used rankings from a wide array of systems, but the Universal
Tennis Ranking (UTR) has yet to be investigated.
The UTR is the most newly created
system based on a 16-point scale that has been utilized to calculate a player’s
ranking based on their results from their most recent 30 matches across all
competitive systems in the last 12 months (19, 35, 38). The UTR is the official
rating of The Tennis Channel, Intercollegiate Tennis Association, World Team
Tennis, Professional Tennis Registry, United States Professional
Tennis Association, International Tennis Hall of Fame, and Orange Coach (19,
46, 38). This non-discriminant ranking system was designed to implement a new
algorithm to increase the accuracy and reliability of ratings to standardize
them to a uniform measurement for all tennis players. It categorizes every
competitive player regardless of age, gender, and nationality, considers the
opposing opponent and the score of the match and accounts for player’s current
relative abilities and competitiveness (36-38). It calculates the player’s
ranking value based off percentage of games won by the player, match outcome
factor for the players for their most recent matches, and opponent’s player
rating number. However, the UTR does not directly consider a tennis
player’s physical metrics (agility, footwork, forehand velocity, backhand
velocity, and serve velocity).
Since the UTR is the highest tennis
ranking worldwide, it would be beneficial to predict a player’s UTR ranking based off of sport specific movements; to date, no
study has investigated collegiate tennis players and the extent of tennis
specific variables that influence the UTR. If coaches predict a player’s
UTR value based off tennis specific variables besides percentage of matches
won, they can be more accurate in programming and optimize training efficiency
to help improve an athlete’s ranking and performance. We hypothesized that
tennis ranking performance would be enhanced by improving a player’s stroke
skills (serve, backhand, and forehand) and footwork. The purpose of this study is
to investigate tennis specific measures (serve, backhand, forehand velocity,
agility, and footwork) to predict a player’s UTR value and to see what
percentage of the variables most influence the ranking.
At the beginning of the study, 31
male and female tennis players agreed to participate with a mix of right and
left-handed hitters. Twenty-nine male (N=15) and female (N = 14) players with
an UTR ranging from levels 5.29 to 12.99 (intermediate- advanced) (Figure 1) (35)
participated in this study, which was performed in their off-season. Inclusion
criteria included Division II and Division III male and female tennis players
ranging from ages 18-25, a validated UTR score within the past six months, at
least four years of competitive tennis prior to entering college, and no
current or previous injuries in the past six months. An injury was defined by
anything that will prevent the athlete from practices or matches. Exclusion
criteria for the study included if the
athletes did not have a validated UTR score or if they have had an injury in
the past six months. The UTR rankings were pulled from within a month of when testing
occurred. The players were familiar with the tennis specific tests and were involved
in tennis training and competitive matches for at least four years prior to
entering college with no documented injuries that hindered performance in the
past six months. The players were informed of the research requirements,
procedures, risks, and benefits before signing the informed consent form. They
all provided a written consent for participation. This study was approved by
the Institutional Research Ethics Committee.
Figure 1: UTR 16-Level Chart (45)
Experimental Set Up
On the day of testing, after a
seven-minute warm up which consisted of two minutes of a self-selected jog
around the court, three minutes of ground strokes hits fed by the principle investigator
(PI) who is a proficient tennis player to the athletes incorporated forehand
and backhand shots, and then the athlete practiced the flat serve down the ‘T’
for two minutes, so they were familiarized with the tests (48). Every other
player received a brand-new set of Wilson tennis balls prior to warm-up.
After warm-up, athletes were allowed
a two-minute break to drink water if needed before the assessments.
Instructions were explained to participants which included: six flat serves
down the “T” in the add and deuce side, six forehands and backhands down the
line in the target area, Spider test following the diagram (Figure 1), and
performing as many foot taps as they could in 30 seconds. All data was recorded
from the fastest three trials on the serve, forehand, and backhand velocity,
Spider drill test, and two trials for the footwork test to ensure reliability.
The highest of the three (serve, forehand, backhand velocity, and agility) or
two (footwork test) trials were recorded. The test followed this order: serve,
forehand, and backhand velocity, agility, and footwork taps for every athlete
to ensure validity. All data was recorded on an individual player data sheet.
Two radar guns (Model PR1000-BC;
Stalker Professional Sports Radar; Plymouth, MN, USA) were used to measure
serve velocity. The radar was positioned at the center of the baseline, 4 m
behind the server, aligned with the approximate height of ball contact pointing
down the center of the court (47). The serves for subjects who were
right-handed first served to the left serve box (from the right) and the ones
who were left-handed served to the right serve box (from the left). The player
was then instructed to serve six flat serves down the ‘T’ on the add and deuce
side. The athletes were instructed to serve into the service box, not hit the
net, nor commit a foot-fault, in order for the serve to count. The velocity of
the highest three serves that made it into the service box was recorded from
the average of the two radar gun measurements (41 m). Athletes were instructed
to perform six maximal serves down the “T” (center line). A target area (6.40 X
1.03m) was placed in the serve box. They were allotted no more than 16 total
serves or eight from each side to minimize fatigue and injury. If the athlete
only hit one serve in the box, that score was recorded. Athletes were given a
minimum rest period of no less than three minutes and no more than five minutes
before the next test to ensure reliability. If the athlete went over the
five-minute time frame, their data was excluded.
Forehand and Backhand Velocity.
Two radar guns (Stalker Professional
Sports Radar; Radar Sales, Plymouth, MN, USA) were used to measure forehand and
backhand velocity. The radar guns were positioned at the service line, 4 m to
the right of forehand and backhand, aligned with the approximate height of ball
contact pointing at the of the court. A strength coach manually fed the player
underhand balls to the player standing in between the baseline and service
line. The player was then instructed to hit six forehands and then six
backhands down the line with maximum effort. Each effort was performed
independently due to a maximum 30-second pause between strokes. The athletes
were instructed to hit the ball over the net in the opponent’s part of the
court, in the target area (5.50 X 2.06 m) and must not be a sliced hit for the
stroke to count (43). The highest velocity of the top three forehand and
backhand strokes that made it down the line and in the coned-off region were
recorded. The players were allotted no more than 16 total serves or eight from
each side to minimize fatigue and injury. If the athlete only hit one forehand
or backhand down the line, that score was recorded. Athletes were given a minimum
rest period of three minutes and no more than five minutes before the next test
to ensure reliability. If the athlete went over the five-minute time frame,
their data was excluded.
The footwork assessment was completed
on the athlete’s respective tennis court. The GoPro (Hero5) was set up at the
height of 6” to video all footwork taps. The assessment started off with the
player standing in athletic position, greater than parallel and between 115-135◦. The PI
supervisor measured their knee flexion using the Coaches Eye App (8) to verify
the athlete’s knee flexion was in the appropriate range. While maintaining
athletic position, the researcher then commanded the athlete to perform as many
foot taps as they could in 30 seconds. If the athlete’s feet did not leave the
ground, the taps did not count. The participant was given a minimum rest period
of one minute and maximum of three minutes before the next attempt to ensure
reliability. If the athlete went over the three-minute time frame, their data
was excluded. The highest amount of footwork taps was recorded. After the
completion of the footwork test, the athlete was given a minimum rest period of
three minutes and no more than five minutes to ensure reliability.
For the agility test, certified
strength and conditioning coaches set up electronic timing gates using the
Brower Timing System and placed the timing gates at an appropriate height of 1
m for all participants and 3 m behind the baseline, to avoid any collisions
when returning to the center point after each sprint (Figure 2) (20). Athletes
started with a practice trial at 75% effort to ensure familiarization of the
test. After the trial, they were given a minimum rest period of one minute and
a maximum of five minutes before the actual test. All participants were
required to complete a total of three trials to ensure reliability.
Participants were instructed to break the beam of the timing gates, officially
starting the assessment. Participants started with the sprint to the right
first (number 1) and then working in a counterclockwise direction after. Sprint
numbers 1 and 5 represent a distance of 4.11m while numbers 2, 3, and 4 each
measure 5.49 m. Each sprint required athletes to return to the center point on
the baseline before starting the next. Once the final sprint was completed
(returning from sprint 5) athletes were required to turn right 90◦ to complete
the three-meter sprint through the timing gates completing the test (Figure 1) (20).
Athletes were given a minimum rest period of one minute and a maximum of three
minutes before the next trial to ensure reliability. If the athlete went over the
three-minute time frame, their data was excluded. Total time for the Spider
test was recorded to the nearest hundredth of a second and the highest of the
three trials was recorded. If athletes breached the methodological guidelines
for the test (by failing to reach the line for a change of direction step), the
trial was voided, and an additional trial was conducted following three minutes
of rest. Athletes were given a minimum rest period of three minutes and no more
than five minutes before the next test to ensure reliability. If the athlete
went over the five-minute time frame, their data was excluded. Previous
research has shown spider test to be a valid and
reliable measurement for change of direction movements in tennis (20).
Figure 2: Schematic of the Spider Drill (20)
Coefficient of variation
(CV) and intra-class correlation coefficients (ICC) were calculated to assess
reliability for the serve, backhand, and forehand velocity, agility, and
footwork (Table 5). Pearson-product moment correlations were run to determine
the relationships of the variables (serve, forehand and backhand velocity,
agility, and foot taps) to a UTR ranking (Table 2). An alpha level of p≤0.05
was used to determine statistically significant correlations. A multiple linear regression was calculated
predicting a player’s UTR based on serve, forehand, and backhand velocity,
agility, and foot taps. Multiple regression analysis
was used to examine the amount of variance explained by the variables for UTR. The relative contribution of each variables to predict
the variance of UTR was used to determine contribution of each dependent
variable to the overall multiple regression model (32). Dependent
variables that did not produce a statistically significant correlation
coefficient (p≥0.05) were removed from the model. The multiple regression model
was performed successive times with remaining variables until all dependent
variables produced a statistically significant correlation coefficient
(p≤0.05). Variables that did not produce a statistically
significant prediction coefficient (P>0.05) were removed from the prediction
model. Intra-class correlations and coefficient of variations were assessed for
all variables (serve, forehand and backhand velocity, agility, and foot taps). Cohen’s f2 effect size was calculated to assess
the magnitude of the model (8). The following scale was used: small
effect f=0.02, medium effect f=0.15 and large effect f=0.35 (8).
statistics comparing males and females for UTR and the specific assessments can
be found in Table 1. A significant regression equation was found (F (5,23)
=29.66, p<.05) with an R2of 0.866. Model 4 produced a statistically
significant prediction model (F (2,26) =79.63, p<0.01) with an R2of
0.860 which included only serve and backhand velocity (Table 3). The
correlations between UTR and a player’s physical performance parameters are
presented in Table 2. Foot taps showed a moderate correlation (r=.472,
P<0.05) to UTR. The highest correlations were observed in serve velocity
(r=.902), forehand velocity (.843), backhand velocity (r=.858) and agility
(-.817) to UTR. Based on the results of Model 4, only serve velocity (P<0.001)
and backhand velocity (P=0.007) were statistically significant predictors of
Table 1. Descriptive Statistics Comparing Male and Female Athletes
|Sex||UTR||Serve Velocity (mph)||Forehand Velocity (mph)|
|Male (N=15)||11.35 ± 1.03 (9.55-12.99)||107.37 ± 9.39 (86.0-122.0)||88.73 ± 6.34 (79.0-102.0)|
|Female (N=14)||7.97 ± 1.60 (5.29-10.01)||83.18 ± 8.29 (69.5-94.0)||70.14 ± 9.22 (56.0-89.0)|
|Note. Values are expressed as mean ± standard deviation, (minimum-maximum value)|
Table 2. Correlation Coefficients of tennis-specific characteristics with player performance (UTR ranking).
|Variables||UTR||Serve Velocity||Forehand Velocity||Backhand Velocity||Spider Test||Foot Taps|
|Serve Velocity (mph)||0.902||1||0.894||0.813||-0.827||0.541|
|Forehand Velocity (mph)||0.843||0.894||1||0.805||-0.844||0.576|
|Backhand Velocity (mph)||0.858||0.813||0.805||1||-0.777||0.458|
Table 3. Multiple Regression Models
|Model||R||R2||Significant F Change|
|1. Predictors: (Constant), Foot Taps, Backhand Velocity, Spider Test, Serve Velocity, Forehand Velocity
2. Predictors: (Constant), Backhand Velocity, Spider Test, Serve Velocity, Forehand Velocity
3. Predictors: (Constant), Backhand Velocity, Spider Test, Serve Velocity
4. Predictors: (Constant), Backhand Velocity, Serve Velocity
As the results indicate from Model 4,
serve velocity contributes 54.5% of the explained variance and backhand velocity
contributes 45.5% of the explained variance for prediction of UTR. All
variables showed acceptable levels of reliability within subjects (Table 5).
Cohen’s f2 effect sizes demonstrated a very large effect for all
Table 4. Relative Contribution to Multiple Regression Models
|Model||Serve Velocity (mph)||Forehand Velocity (mph)||Backhand Velocity (mph)||Spider Test (s)||Foot Taps|
Table 5. Intraclass Correlations and Coefficient of Variations Between Variables
To date, this is the only study that
has been done to examine the effects of tennis specific measurements on
collegiate athletes to predict a player’s UTR. The aim of the present study was
to detect whether tennis specific characteristics (serve, forehand and backhand
velocity, agility, and foot taps) are related to player’s performance (UTR). In
total, 29 collegiate tennis players were examined in this study, including 19
Division II players and 10 Division III players. Thus, a player’s agility,
endurance, and stroke capabilities may be influential in performance ranking
measures. A previous study demonstrated that agility was the physical ability
that most influenced the competitive level of young tennis players (2, 20, 26,
29, 41). It was also suggested that skills related to tennis strokes can be
used to maximize and predict competitive success (5, 11, 14, 22, 25, 26, 27,
40, 43, 48). Consistent with these findings, the researchers found a
significant correlation between players’ ranking and serve velocity (r=0.902).
It is recommended, therefore, that power training to target the serve be
included in the training programs of tennis players in order to improve their
performance (26). These findings of this study displayed significant
correlations between certain tennis characteristics and tennis ranking.
Comparisons are difficult because previous studies analyzing tennis-specific
variables typically involve small sample sizes and non-collegiate athletes. In
this regard, the results of this research are contrary to previous studies of
advanced prepubescent and youth tennis players, which suggested that specific
qualities such as agility (13, 20, 29), speed (14, 29), vertical jumping (11,
15, 16, 47), and serve (13, 29) correlated most strongly with tennis
performance. However, findings indicated that physical performance tests do not
predict the ability to play tennis at a competitive level (12, 41).
In this present research assessing
collegiate athletes, the results regarding correlations between tennis specific
measurements and performance (Table 2) showed that serve, forehand and backhand
velocity, and agility presented the largest correlations with the player’s
ranking in all divisions, followed by tennis-specific endurance (foot taps)
with moderate correlation values of a player’s UTR. Our hypothesis tennis
ranking performance would be enhanced by improving a player’s stroke skills was
correct. We were, however, somewhat surprised by the magnitude of that
difference between foot taps and ranking.
The results with this study align
with previous literature explaining that tennis-specific technical measurements
and change of direction ability have been found when comparing higher levels of
play to lower level players (13, 29). Based on results from the multiple
regression, serve and backhand velocity appear to contribute the strongest
predictors for an individual’s UTR. A player’s serve velocity aligns with
previous literature stating the serve was the strongest predictor of a player’s
ranking due to relying on the multiple body segments and complex coordination
of muscular activation to produce power to the ball (14, 25). This could be due
to male subjects having a higher UTR and previous research has shown that males
have higher UTR rankings due to higher strength levels compared to female
counterparts (3, 18, 31). In contrast to previous research when looking at
youth athletes, the forehand was more strongly related to ranking (26, 41).
This could be due to the fact that the forehand is easier to learn since the
backhand is generally harder to master than the forehand stroke (26). However,
at partly strengthening the existing research, which claims that the serve is
the most powerful, potentially dominant shot (12, 17, 27). Furthermore, when
comparing female and male athletes, we found all descriptive statistics to be
higher in males (Table 2). These differences could have an influence in terms
of playing style because being taller and heavier offers an advantage when
producing power in the serve, forehand, or backhand. Hence, the results of the
present study emphasize the importance of sport-specific technical tests and
demonstrate their value and contribution to athlete’s performance.
Although there were aspects of this
study that had never been done before, there are limitations to our study. Even
though there was a variety of athletes, the different levels of competitive
play between athletes could have affected the results of the study. We also
only tested tennis-specific movements and agility to ranking performance, so
whether similar results would be found for other intermittent tests (i.e.
30-15) or other types of measures of performance such as lower or upper body
power, remains to be seen. Furthermore, the PI underhand fed each ball to the
athletes. This may have caused inconsistency in the spin and could have
affected the velocities of the strokes. With the help of a ball machine, this
would have provided greater accuracy and precision with ball feeding.
This study has shown a player’s serve
and backhand velocity can be used to determine a UTR value. Strong correlations
were found between the backhand and serve velocity corresponding to UTR.
However, future research should aim at investigating a larger sample size of
higher division ranked players (Division I or professional), specifically separating
males and females, intermittent endurance capacity, or lower body power to
further identify specific variables that may influence UTR. These results
highlight the importance that tennis specific stroke skills (backhand and serve
velocity) can be used as a practical performance test to precisely and
individually prescribe training regimens.
APPLICATIONS IN SPORT
tennis has progressed from a sport in which skill was the primary prerequisite
for successful performance, into a sport that requires the complex interaction
of several tennis-specific components, it is vital to identify the most
influential factors on performance and ranking measures. Since the UTR is the
highest tennis ranking worldwide, analysis shows it would be beneficial to
predict a UTR ranking based off a tennis player’s sport specific metrics
(serve, backhand, forehand velocity, agility, and footwork). The results of
this present study underline the importance of tennis-specific characteristics.
According to our findings, a player’s power (serve and backhand velocity) seem
to be the most important components in collegiate athletes to predict a
player’s UTR. Therefore, we would recommend using these tests in the framework
of physical testing and training regimens. Additionally, the present results
could be useful to compare the development of players and to create individual
fitness programs. This would enable the identification of weaknesses in
different parameters and facilitate the design of more efficient and optimize
training programs. To date, no study has investigated the specific tennis
variables that influence the UTR and to what extent.
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