Article
DOI: 10.30827/ijrss.33202


The Relationships Between the Functional Movement Screening Test (FMS) Scores and Technical and Physical Performance Parameters in Female Tennis Players


Relación entre las puntuaciones de la prueba de evaluación del movimiento funcional (FMS) y los parámetros técnicos y físicos del rendimiento en jugadoras de tenis


International Journal of Racket Sports Science, vol. 7(2) (July - Dec, 2025), 22-29. eISSN: 2695-4508


Received: 06-05-2025
Acepted: 10-11-2025

AUTHORS

Mustafa Söğüt * 1 ORCID

Koray Biber 1 ORCID

Hasan Ödemiş 1 ORCID

İsmet Tarık Ulusoy 1,2 ORCID



1 Department of Physical Education and Sports, Faculty of Education, Middle East Technical University, Ankara, Türkiye

2 Department of Physical Education and Sports Teaching, Faculty of Sports Sciences, İstanbul Aydın University, İstanbul, Türkiye


Corresponding Author: Mustafa Söğüt, msogut@metu.edu.tr

Cite this article as: Söğüt, M., Biber, K., Ödemiş, H., & Ulusoy, İ. T. (2025). The relationships between the functional movement screening test (FMS) scores and technical and physical performance parameters in female tennis players. International Journal of Racket Sports Science, 7(2), 22-29. https://doi.org/10.30827/ijrss.33202



ABSTRACT

Abstract

Functional Movement Screening (FMS) test is a frequently used assessment tool that evaluates the fundamental movement patterns of athletes. However, there is a paucity of information on the relationship of FMS with the performance determinants in racket sports players. The purpose of this study was to examine the associations between FMS test scores and technical and physical performance parameters in recreational female tennis players, providing initial insight into this relationship. Twelve participants (age = 24.2 ± 3.8 years) were measured for various parameters. The collected data included anthropometrics, FMS scores, serve speed and accuracy, countermovement jump, grip strength, agility, and linear speed. The results revealed a positive and significant (p = 0.042) correlation between FMS score and serve accuracy performance. On the other hand, the FMS scores were not significantly associated with countermovement jump (p = 0.115), grip strength (p = 0.165), agility (p = 0.093), 10m sprint (p = 0.121), and serve speed (p = 0.514) performances. The findings highlighted that the movement quality scores evaluated through the FMS may not be associated with physical performance indicators in female tennis players

Keywords: Racket sports, athletic performance, screening tests, physical fitness, female athletes.

Resumen

La prueba de evaluación del movimiento funcional (FMS) es una herramienta muy utilizada que evalúa los patrones de movimiento fundamentales de deportistas. Sin embargo, hay poca información sobre la relación entre la FMS y los determinantes del rendimiento en jugadores de deportes de raqueta. El objetivo de este estudio fue analizar las asociaciones entre las puntuaciones de la prueba FMS y los parámetros de rendimiento técnico y físico en jugadoras de tenis recreativas, proporcionando una visión inicial de esta relación. Se midieron diversos parámetros a doce participantes (edad = 24,2 ± 3,8 años). Los datos recopilados incluyeron antropometría, puntuaciones de FMS, velocidad y precisión del saque, salto con contramovimiento, fuerza de agarre, agilidad y velocidad lineal. Los resultados revelaron una correlación positiva y significativa (p = 0,042) entre la puntuación de la FMS y la precisión del saque. Por otro lado, las puntuaciones de la FMS no se asociaron significativamente con el salto con contramovimiento (p = 0,115), la fuerza del agarre (p = 0,165), la agilidad (p = 0,093), el sprint de 10 m (p = 0,121) y la velocidad del saque (p = 0,514). Los resultados resaltaron que las puntuaciones de calidad del movimiento evaluadas mediante la FMS pueden no estar asociadas con los indicadores de rendimiento físico en las tenistas.

Palabras clave: deportes de raqueta, rendimiento deportivo, pruebas de detección, aptitud física, atletas mujeres.



Introduction

INTRODUCTION


Many athletes undergo regular evaluations using various physiological and performance screening methods to determine training intensity, identify signs of overtraining, and enable coaches to adapt training programs to the specific demands of their sports (Kiely et al., 2019). These evaluations are crucial for identifying and reducing prospective injury risks (Dennis et al., 2008; Gabbe et al., 2004). Among the commonly used screening tools to assess movement quality are the star excursion balance test (SEBT), Y balance test (YBT), and Functional Movement Screening (FMS) test (Chang et al., 2020; Engquist et al., 2015). FMS is a frequently used assessment tool that evaluates fundamental movement patterns in individuals, consisting of seven patterns requiring a balance of mobility and stability (Cook et al., 2006; Teyhen et al., 2012). It is designed to identify movement limitations and asymmetries that might increase the risk of injury (Cook et al., 2006). To enhance movement quality and lower the risk of injury, customized exercise programs can be developed with the help of FMS (Alexe et al., 2024; Dorrel et al., 2015; Kiesel et al., 2007; Maleki et al., 2025; Zhitao et al., 2024). FMS can assist athletes in avoiding injuries and improving performance by detecting movement dysfunctions beforehand (Chimera et al., 2015). Additionally, FMS has shown strong inter-rater reliability (Shultz et al., 2013) and is practical to use in a number of circumstances due to its ease of use in a brief time with minimum equipment (Cook et al., 2006; Kiesel et al., 2007). It is also more affordable when compared to more sophisticated movement assessment tools (Cook et al., 2006).

Racket sports involve high-intensity exercise and are comparable in terms of task demands, match performances, and talent parameters (Faber et al.,2016) however, swinging movements, field dimensions, and ball velocity are very different (Ak & Kocak, 2010; Akpinar et al., 2012).. For instance, in comparison to table tennis players, tennis players have a longer time to anticipate and react to strokes (Ak & Kocak, 2010). Tennis matches, which may take more than an hour and occasionally more than five hours, demand players to alternate between high-intensity and low-intensity activity, with active recovery between points and passive recovery between (Christmass et al., 1998; Davey et al., 2003; Fernandez-Fernandez et al., 2009; Kovacs, 2007; Mero et al., 1991; Smekal et al., 2001).. Therefore, in order to cope with the challenging physiological requirements of the game, which requires executing powerful shots and quick movements repeatedly for a long period of time, professional tennis players need a combination of physical qualities, including power, speed, agility, and aerobic fitness (Ferrauti et al., 2018; Girard & Durussel, 2015; Girard & Millet, 2009; Kovacs, 2007; Mero et al., 1991; Roetert et al., 1992; Ulbricht et al., 2016). Thus, it is crucial to periodically evaluate these physical performance components, and assessing the FMS would be a practical way to monitor physical qualities.

Benz (2010) implemented four (countermovement jump, forty-yard sprint, t-test, and overhead medicine ball toss) athletic performance tests on 50 young male high school football players to analyze the relationship between FMS scores and athletic performance. It was observed in the study that there was a significant correlation between FMS scores and countermovement jump but no correlation with the other three tests. Parchmann & McBride (2011) investigated if there is a relationship between FMS scores and athletic performance of 25 (female = 10, male = 15) golfers. The results of the study showed no significant correlations between FMS scores and athletic performance. Supporting that, in a study that Lockie et al. (2015) conducted on 22 male recreational team sport athletes, FMS did not show any significant correlations with athletic performance. Moreover, Lockie et al. (2015) also reported no significant correlations between FMS scores and athletic performance of 32 male recreational team sports athletes. Okada et al. (2011) observed the core stability of 28 healthy individuals and found significant correlations between left in-line lunge and right shoulder mobility components of FMS with the t-run time. They also reported a significant correlation between right rotary stability and backward overhead medicine ball throw. Yet, they observed that core stability and FMS have no significant correlation.

To the best of the authors' knowledge, there is no study investigating the relationship between the FMS and the technical and physical parameters of young adult female tennis players. Therefore, this study aimed to determine these associations. Findings of the study may provide better understanding of the relationship between movement quality and technical and physical performance in recreational female tennis players.


Methods

Methods


Participants

A group of 12 recreational female tennis players (age = 24.2 ± 3.8 years, height = 164.2 ± 3.6 cm, body mass = 55.2 ± 6.5 kg, body fat percentage = 22.3 ± 5.7) who have been playing tennis regularly for at least 4 years was recruited to participate in the study. All participants were informed of the purpose and measurements of the study and gave their informed consent. The ethical approval was obtained from the Human Subjects Ethics Committee of Middle East Technical University.

Experimental Design

Each player participated in two testing sessions. During the first session their demographic information, anthropometric characteristics, and FMS scores were obtained in the Performance Laboratory of the University. The second testing session took place on an indoor tennis court. After a standard warm-up protocol, including light jogging and stretching exercises, their technical parameters were measured through service accuracy and service speed tests. The physical performances of the players were determined by vertical jump, hand grip strength, agility, and linear speed tests respectively. All players were instructed to maintain their usual sleep and dietary habits and not to engage in intense physical activity throughout the data collection process.

Measures
Anthropometrics

A wall-mounted stadiometer (Holtain, United Kingdom) was used to measure the height of the players (Sørensen et al., 2020). The body mass and body fat percentage of the players were measured using a body composition analyzer (TANITA MC-780MA, Japan), which was previously validated (Verney et al.., 2015).

Serve Accuracy and Speed

Serve speed and serve accuracy tests were conducted in an indoor tennis court. Players performed the tests with their own rackets. Tennis balls approved by the International Tennis Federation were used in the tests. In the serve accuracy test, players were asked to deliver 16 serves to the predetermined targets. If the player hit the small target (0.5 x 0.5 meters), they received 5 points, hitting the medium-sized target earned them 3 points, and serving directly into the correct service box yielded 1 point. The total score obtained from the sixteen serve attempts (8 serves from both deuce and advantage courts) was recorded as the serve accuracy performance score (Englert & Bertrams, 2014). All participants were informed on the scoring system before the tests. To determine the serve speed of the players, a validated (Hernández-Belmonte & Sánchez-Pay, 2021) sports radar device (PR1000-BC; Ball Coach, Santa Rosa, Calif., USA) was used. Each player served at their highest speed from the service line at 30-second intervals. Five successful serves were recorded, and their average was used for analysis.

Countermovement Jump

The countermovement jump performance of the players was measured using an electronic device (Microgate, OptoJump, Italy) with a digital timer that recorded the players' time in the air. They were instructed to stand, keep their hands on their hips during the test, and jump to their maximum height after a downward bending motion. The resting period was 30 seconds between three trials, and the highest value was recorded.

Grip Strength

A hand dynamometer (Baseline, Smedley, Germany) was used to measure the grip strength. During the measurement, players were asked to sit on a platform, keep their arms by their sides, and squeeze the dynamometer with their dominant hand as forcefully as possible for five seconds. The measurement was applied twice, and the highest score was recorded.

Agility

Agility performance was measured using the T-agility test. Before the test, cone markers were placed in a T-shaped pattern. Players were asked to run forward, touch the front cone, then touch the cones on the left and right sides in sequence, and finally touch the front cone again before running backward to the starting line. Electronic timing gates (Witty Photocell gates, Microgate, Italy) were used in the test, and it was repeated twice, with the fastest time recorded.

10m Sprint

Ten-meter sprint performance was measured using electronic timing gates (Witty Photocell gates, Microgate, Italy) positioned at 0m and 10m. The test was repeated twice, and the fastest time was recorded.

Functional Movement Screen (FMS)

FMS protocol is comprised of seven components, including deep overhead squat, in-line lunge, hurdle step, active straight leg-raise, trunk stability push-up, shoulder mobility, and rotary stability. A description of the FMS tests was followed during the assessment (Cook et al., 2006). Each part of the assessment was videotaped from the lateral and anterior views. The participants had three trials for each test and the best score of the three was recorded. The scoring system for FMS has four options (Cook et al., 2006). The participant is given a score of zero if she feels pain anywhere in her body during the testing. The painful area is noted additionally. A score of one is given if the participant is incapable of performing the movement pattern. A score of two is given if the participant can complete the movement pattern with compensating movements. A score of three is given if the participant can perform the movement correctly without any compensation. The majority of the FMS assess the right and left sides separately. Thus, both sides were scored. The lower scores of the two sides were recorded. Three of seven tests including trunk stability push-up, shoulder mobility, and rotary stability have additional clearing assessments which were graded as positive or negative. The only consideration of these clearing movements was whether the participant had pain or not. A grade of positive was given if the participant had pain and a grade of negative was given vice versa.

Statistical Analysis

Descriptive statistics (mean and standard deviation) were calculated for all variables. The Shapiro-Wilk test was computed to check the normality assumption. The Pearson correlation coefficient was used to analyze the associations between FMS scores and performance parameters. The strength of the correlations was classified following Hopkins et al. (2009) as small (r < 0.1), moderate (0.1-0.3), large (0.3-0.5), very large (0.5-0.7), and extremely large (0.7-0.9). The SPSS software package (v.28.0) was used for statistical analysis, and a significance level of 0.05 was considered.


Results

Results


The descriptive statistics of the players are presented in Table 1.


Table 1 Descriptive statistics of the players

Variables Mean SD
Countermovement jump (cm) 24.1 5.2
Grip strength (kg) 30.1 5.6
Agility (s) 11.8 1.1
10m (s) 2.1 0.1
Serve accuracy (score) 13.0 4.2
Serve velocity (km/h) 106.3 26.4
FMS (score) 18.0 1.7


The associations between FMS scores and performance variables are illustrated in Figure 1. The results showed a very large, positive and significant (r = 0.593, p = 0.042) correlation between FMS score and serve accuracy performance (r = 0.593, p = 0.042). On the other hand, the FMS scores were not significantly associated with countermovement jump (r = 0.479, p = 0.115), grip strength (r = 0.428, p = 0.165), agility (r = -0.507, p = 0.093), 10m sprint (r = -0.473, p = 0.121), and serve speed (r = 0.209, p = 0.514) performances.


Figure 1 Correlation results between FMS scores and performance variables

v7n2a3image001.png

CMJ: Countermovement jump, * p<0.05



DISCUSSION

DISCUSSION


The purpose of this study was to investigate the association between FMS scores and technical and physical performance parameters in young adult female tennis players. The results indicated that the serve accuracy performance is significantly correlated with FMS scores while serve speed was not related. Additionally, the physical parameters, including countermovement jump, grip strength, agility, and linear speed tests, were not correlated with FMS. This study was the first investigation into the association between FMS scores and technical and physical performance parameters in young adult female tennis players.

The results from this study were partly consistent with the findings of the previous studies indicating that FMS was not correlated with athletic performance (e.g., T-test agility, 20 m sprint, vertical jump) among female golfers (Parchmann & McBride, 2011) and female team sport athletes (Alexe et al., 2024; Lockie et al., 2015). This suggests that while FMS may offer useful information on movement quality, it might not comprehensively capture the multifaceted nature of athletic performance in female tennis players, which involves specific physical skills such as speed, agility, and explosive power.

The correlation between FMS and serve accuracy may be explained by the biomechanical demands of the serve. Serving is a complex, full-body action that relies on mobility (shoulder, hip, thoracic spine), stability (core, balance), and coordination across the kinetic chain (Reid et al., 2012; Whiteside et al., 2014). Limitations in these areas can disrupt timing and reduce accuracy, which aligns with what the FMS is designed to assess (Cook et al., 2006). In contrast, measures such as jump height, sprint speed, or grip strength depend more on strength and power capacities rather than integrated movement quality, which may explain their lack of association with FMS (Parchmann & McBride, 2011; Lockie et al., 2015).

The present study found a correlation between serve accuracy and the FMS, which contrasts with the findings of Parchmann and McBride (2011), reporting a non-significant relationship in sport-specific technical performance among golfers. This can be explained by serve as a very complex movement that requires higher flexibility, mobility, balance, and motor ability; however, this study does not provide a cause-and-effect. The serve has been described as the most important stroke in tennis (Whiteside et al., 2013). Thus, the serve accuracy should always be considered and the results from this study suggested that the FMS test can be utilized prior to designing a program to improve serve accuracy performance and to evaluate the progress regularly. Another study (Okada et al., 2011) reported contrasting findings to this study that there is a significant relationship between FMS and T-agility as well as full body power. In fact, Okada et al. (2011) presented data indicating where higher FMS scores were associated with lower athletic performance. Future studies are needed to explore conflicts to reach a consensus in literature.

This study has limitations. Firstly, the sample size was limited to 12, which reduced the ability to generalize the results. Future studies should consider investigating a larger sample size. Also, this study was conducted cross-sectional. The fluctuations during the season could demonstrate a correlation between FMS and athletic performance. Thus, longitudinal studies are needed to explore this potential relationship.


Concluding

CONCLUSIONS


The findings indicate that the movement quality scores evaluated through the FMS show only a limited correlation with physical performance indicators in female tennis players. Therefore, the findings of the study highlight that improved movement quality may contribute to better serve accuracy in female tennis players. While FMS should not be the sole method for evaluating tennis athletes, it remains useful as a pre-season or periodic screen for movement limitations, guiding corrective exercises that may support broader training adaptations. Coaches and practitioners are encouraged to combine FMS with sport-specific performance tests (e.g., tennis-specific agility or repeated sprint tests) for a more comprehensive athlete profile.


Notas

Notas


[2] Financial disclosure This study is funded by the Scientific Research Projects Coordination Unit at Middle East Technical University [project number AGEP-504-2023-11328].

[3] Conceptualization: Mustafa Söğüt. Funding acquisition: Mustafa Söğüt. Investigation: Mustafa Söğüt, Koray Biber, Hasan Ödemiş, İsmet Tarık Ulusoy. Methodology: Mustafa Söğüt. Supervision: Mustafa Söğüt. Writing-original draft: Mustafa Söğüt, Koray Biber, Hasan Ödemiş, İsmet Tarık Ulusoy. Writing-review & editing: Mustafa Söğüt

[4] In this article, the authors did not use generative Artificial Intelligence tools.


Acknowledgments


The authors would like to thank all players for their support and cooperation.


References

REFERENCES


Ak, E., & Koçak, S. (2010). Coincidence-Anticipation Timing and Reaction Time in Youth Tennis and Table Tennis Players. Perceptual and Motor Skills, 110(3), 879-887. https://doi.org/10.2466/pms.110.3.879-887

Akpinar, S., Devrilmez, E., & Kirazci, S. (2012). Coincidence-Anticipation Timing Requirements are Different in Racket Sports. Perceptual and Motor Skills, 115(2), 581-593. https://doi.org/10.2466/30.25.27.pms.115.5.581-593

Alexe, D. I., Čaušević, D., Čović, N., Rani, B., Tohănean, D. I., Abazović, E., ... & Alexe, C. I. (2024). The relationship between functional movement quality and speed, agility, and jump performance in elite female youth football players. Sports, 12(8), 214.

Benz, J. (2010). Functional Movement Screen to predict athletic performance. Kean University.

Chang, W. D., Chou, L., Chang, N., & Chen, S. (2020). Comparison of Functional Movement Screen, Star Excursion Balance Test, and Physical Fitness in Junior Athletes with Different Sports Injury Risk. BioMed Research International, 2020, 1-8. https://doi.org/10.1155/2020/8690540

Chimera, N. J., Smith, C. A., & Warren, M. (2015). Injury history, sex, and performance on the Functional Movement screen and Y Balance test. Journal of Athletic Training, 50(5), 475-485. https://doi.org/10.4085/1062-6050-49.6.02

Christmass, M., Richmond, S. E., Cable, N. T., Arthur, P. G., & Hartmann, P. (1998). Exercise intensity and metabolic response in singles tennis. Journal of Sports Sciences, 16(8), 739-747. https://doi.org/10.1080/026404198366371

Cook, G., Burton, L., & Hoogenboom, B. (2006). Pre-participation screening: the use of fundamental movements as an assessment of function - part 2. North American journal of sports physical therapy: NAJSPT, 1(3), 132-139.

Davey, P. R., Thorpe, R. D., & Williams, C. (2003). Simulated tennis matchplay in a controlled environment. Journal of Sports Sciences, 21(6), 459-467. https://doi.org/10.1080/0264041031000101926

Dennis, R. J., Finch, C. F., Elliott, B., & Farhart, P. (2008). The reliability of musculoskeletal screening tests used in cricket. Physical Therapy in Sport, 9(1), 25-33. https://doi.org/10.1016/j.ptsp.2007.09.004

Dorrel, B. S., Long, T., Shaffer, S. W., & Myer, G. D. (2015). Evaluation of the functional movement screen as an injury prediction tool among active adult populations. Sports Health, 7(6), 532-537. https://doi.org/10.1177/1941738115607445

Englert, C., & Bertrams, A. (2014). Autonomy as a protective factor against the detrimental effects of ego depletion on tennis serve accuracy under pressure. International Journal of Sport and Exercise Psychology, 13(2), 121-131. https://doi.org/10.1080/1612197x.2014.932828

Engquist, K. D., Smith, C. A., Chimera, N. J., & Warren, M. (2015). Performance comparison of Student-Athletes and General College students on the Functional Movement Screen and the Y Balance Test. The Journal of Strength and Conditioning Research, 29(8), 2296-2303. https://doi.org/10.1519/jsc.0000000000000906

Faber, I. R., Bustin, P. M. J., Oosterveld, F. G. J., Elferink‐Gemser, M. T., & Sanden, M. W. G. N. D. (2015). Assessing personal talent determinants in young racquet sport players: a systematic review. Journal of Sports Sciences, 34(5), 395-410. https://doi.org/10.1080/02640414.2015.1061201

Faber, I. R., Bustin, P. M., Oosterveld, F. G., Elferink-Gemser, M. T., & Nijhuis-Van der Sanden, M. W. (2016). Assessing personal talent determinants in young racquet sport players: a systematic review. Journal of sports sciences, 34(5), 395-410. https://doi.org/10.1080/02640414.2015.1061201

Fernández-Fernández, J., Rivas, D. S., & Méndez-Villanueva, A. (2009). A review of the activity profile and physiological demands of tennis match play. Strength and Conditioning Journal, 31(4), 15-26. https://doi.org/10.1519/ssc.0b013e3181ada1cb

Ferrauti, A., Ulbricht, A., & Fernandez-Fernandez, J. (2018). Assessment of physical performance for individualized training prescription in tennis. In G. Di Giacomo, T. S. Ellenbecker & W. B. Kibler (Eds.), Tennis medicine: a complete guide to evaluation, treatment, and rehabilitation (pp. 167-188). Springer.

Gabbe, B. (2004). Reliability of common lower extremity musculoskeletal screening tests. Physical Therapy in Sport, 5(2), 90-97. https://doi.org/10.1016/s1466-853x(04)00022-7

Girard, O., & Durussel, A. (2015). Improving physical determinants of tennis performance in teenage players with repeated sprint training: Are directional changes adding value? Medicine & Science in Tennis, 20(3).

Girard, O., & Millet, G. P. (2009). Physical determinants of tennis performance in competitive teenage players. The Journal of Strength and Conditioning Research, 23(6), 1867-1872. https://doi.org/10.1519/jsc.0b013e3181b3df89

Hernández-Belmonte, A., & Sánchez-Pay, A. (2021). Concurrent validity, inter-unit reliability and biological variability of a low-cost pocket radar for ball velocity measurement in soccer and tennis. Journal of sports sciences, 39(12), 1312-1319.

Hopkins, W., Marshall, S., Batterham, A., & Hanin, J. (2009). Progressive statistics for studies in sports medicine and exercise science. Medicine+ Science in Sports+ Exercise, 41(1), 3-12.

Kiely, M., Warrington, G. D., McGoldrick, A., & Cullen, S. (2019). Physiological and Performance monitoring in competitive sporting environments: A review for Elite Individual sports. Strength and Conditioning Journal , 41(6), 62-74. https://doi.org/10.1519/ssc.0000000000000493

Kiesel, K., Plisky, P. J., & Butler, R. J. (2011). Functional movement test scores improve following a standardized off‐season intervention program in professional football players. Scandinavian Journal of Medicine & Science in Sports, 21(2), 287-292. https://doi.org/10.1111/j.1600-0838.2009.01038.x

Kiesel, K., Plisky, P. J., & Voight, M. L. (2007). Can serious injury in professional football be predicted by a preseason functional movement screen?. North American journal of sports physical therapy: NAJSPT, 2(3), 147. https://pmc.ncbi.nlm.nih.gov/articles/PMC2953296/

Kovacs, M. S. (2007). Tennis physiology. Sports Medicine, 37(3), 189-198. https://doi.org/10.2165/00007256-200737030-00001

Lockie, R. G., Jalilvand, F., Jordan, C. A., Jeffriess, M. D., & Luczo, T. M. (2015). Research-Grade Scoring for the Functional Movement Screen and Relationships with Athletic Performance Tests in Team Sport Athletes. Journal of Athletic Enhancement, 4(1). https://doi.org/10.4172/2324-9080.1000188

Lockie, R. G., Schultz, A. B., Callaghan, S. J., Jeffriess, M. D., & Berry, S. P. (2013). Reliability and Validity of a New Test of Change-of-Direction Speed for Field-Based Sports: the Change-of-Direction and Acceleration Test (CODAT). Journal of sports science & medicine, 12(1), 88-96.

Lockie, R. G., Schultz, A., Jordan, C. A., Callaghan, S. J., Jeffriess, M. D., & Luczo, T. M. (2015). Can selected functional movement screen assessments be used to identify movement deficiencies that could affect multidirectional speed and jump performance? The Journal of Strength and Conditioning Research, 29(1), 195-205. https://doi.org/10.1519/jsc.0000000000000613

Maleki, A. A., Mousavi, S. H., Biabangard, M. A., & Minoonejad, H. (2025). Influence of exercise interventions on functional movement screen scores in athletes: a systematic review and meta-analysis. Scientific Reports, 15(1), 26335.

Mero, A., Jaakkola, L., & Komi, P. V. (1991). Relationships between muscle fibre characteristics and physical performance capacity in trained athletic boys. Journal of Sports Sciences, 9(2), 161-171. https://doi.org/10.1080/02640419108729877

Okada, T., Huxel, K. C., & Nesser, T. W. (2011). Relationship between core stability, functional movement, and performance. The Journal of Strength and Conditioning Research, 25(1), 252-261. https://doi.org/10.1519/jsc.0b013e3181b22b3e

Parchmann, C. J., & McBride, J. M. (2011). Relationship between functional movement screen and athletic performance. The Journal of Strength and Conditioning Research, 25(12), 3378-3384. https://doi.org/10.1519/jsc.0b013e318238e916

Pluim, B. (2004). Physiological demands and injury in racket sports: differences and similarities. In A. Lees, J. F. Kahn, & I. W. Maynard (Eds), Science and Racket Sports III (pp. 61-69). Routledge.

Reid, M., Whiteside, D., Gilbin, G., & Elliott, B. (2012). Effect of a common task constraint on the body, racket, and ball kinematics of the elite junior tennis serve. Sports Biomechanics, 12(1), 15-22. https://doi.org/10.1080/14763141.2012.724702

Roetert, E. P., Garrett, G. E., Brown, S. W., & Camaione, D. N. (1992). Performance profiles of nationally ranked junior tennis players. The Journal of Strength and Conditioning Research , 6(4), 225-231. https://doi.org/10.1519/00124278-199211000-00006

Shultz, R., Anderson, S., Matheson, G. O., Marcello, B., & Besier, T. F. (2013). Test-Retest and interrater reliability of the functional movement screen. Journal of Athletic Training, 48(3), 331-336. https://doi.org/10.4085/1062-6050-48.2.11

Smekal, G., Von Duvillard, S. P., Rihacek, C., Pokan, R., Hofmann, P., Baron, R., Tschan, H., & Bachl, N. (2001). A physiological profile of tennis match play. Medicine and Science in Sports and Exercise, 33(6), 999-1005. https://doi.org/10.1097/00005768-200106000-00020

Sørensen, G. V. B., Riis, J., Danielsen, M. B., Ryg, J., Masud, T., Andersen, S., & Jorgensen, M. G. (2020). Reliability and agreement of a novel portable laser height metre. PloS one, 15(4), e0231449. https://doi.org/10.1371/journal.pone.0231449

Teyhen, D. S., Shaffer, S. W., Lorenson, C. L., Halfpap, J. P., Donofry, D. F., Walker, M. J., Dugan, J. L., & Childs, J. D. (2012). The Functional Movement Screen: A Reliability Study. Journal of Orthopaedic & Sports Physical Therapy, 42(6), 530-540. https://doi.org/10.2519/jospt.2012.3838

Ulbricht, A., Fernández-Fernández, J., Méndez-Villanueva, A., & Ferrauti, A. (2016). Impact of fitness characteristics on tennis performance in elite junior tennis players. The Journal of Strength and Conditioning Research , 30(4), 989-998. https://doi.org/10.1519/jsc.0000000000001267

Verney, J., Schwartz, C., Amiche, S., Pereira, B., & Thivel, D. (2015). Comparisons of a multi-frequency bioelectrical impedance analysis to the dual-energy X-ray absorptiometry scan in healthy young adults depending on their physical activity level. Journal of human kinetics, 47, 73.

Whiteside, D., Elliott, B. C., Lay, B., & Reid, M. (2014). Coordination and variability in the elite female tennis serve. Journal of Sports Sciences, 33(7), 675-686. https://doi.org/10.1080/02640414.2014.962569

Whiteside, D., Elliott, B., Lay, B., & Reid, M. (2013). The effect of age on discrete kinematics of the elite female tennis serve. Journal of Applied Biomechanics, 29(5), 573-582. https://doi.org/10.1123/jab.29.5.573

Zhitao, L., Junlong, D., Rui, Y., Leijiao, Y., Cheng, G., & Jun, Y. (2024). Relationships Between Functional Movement Quality and Sports Performance in Elite Figure Skating Athletes of China. The Journal of Strength & Conditioning Research, 38(11), e678-e685.