Original Article Identifying a Connection Between Mobility Degree

Original Article
Identifying a Connection Between Mobility Degree, Balance, Strength, and Tennis Serve: a Pilot Study
Prodan Rodica 1
Grosu Emilia Florina 2
Popovici Cornelia 3
Grosu Vlad Teodor 4
1,2UBB, FEFS, Str. Pandurilor nr. 7, Cluj-Napoca, 400376, Romania
3UMF “Iuliu Ha?ieganu”, Faculty of Medicine, Str. Louis Pasteur nr. 6,
Cluj-Napoca, 400349, Romania
4UTCN, Dep. of Mechatronics and Machine Dynamics, Blvd. Muncii nr.103-105,
Cluj-Napoca, 400671,Romania
DOI: xxxxxxxxxxxxxx
Keywords: tennis, strength, speed, tennis serve
Abstract
Tennis serve is the only hit that depends exclusively on the hitter. This aspect leads to the necessity of identification and understanding of the importance of all the elements.
The hypothesis is that serve speed is predictable by force of upper and lower limbs.

A group of 24 amateur young tennis players, (age of 14 ±2) was subjected to a series of mobility, balance, strength and serve speed testing. The Pearson correlation coefficient was used to identify connections between serve speed, considered as a dependent variable, and mobility, balance, and strength, as independent variables.

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Hip external rotation angle of the non-dominant arm, one-leg jumps and one arm ball throws have shown strong positive associations with serve speed (p < 0.05). The anticipation of serve speed had an 81% variance of precision. A combination of body mobility and force may lead to the reasonable anticipation the serve speed individual capacity.

1. Introduction
The tennis serve is the only stroke in tennis without influence from the opposition, allowing the player a larger locus of control across the movement pattern. Precise coordination across the kinetic chain is necessary to reach the greatest serve speed potential (Girard, Micallef, & Millet, 2005; Reid, Elliott & Alderson, 2008; Martin, Bideau, Bideau, Nicolas, Delamarche, & Kulpa, 2014). Given the desire for optimization of serve speed, understanding the variables that contribute to increased serve speed are of particular interest. Biomechanical analysis of the tennis serve shows that kinetic energy is produced almost equally between the upper extremity (UE) and lower extremity (LE) throughout the motion (Martin et al., 2014).

However, many servers lose the potential to produce higher serve speeds because of a lack of energy flow from their LE to their UE, and hence develop an over-reliance on UE force production to generate serve speed (Martin et al., 2014). LE electromyogram and ground-reaction profiles support that professionally ranked players demonstrate more refined neuromuscular coordination patterns during their movement pattern compared with less elite or even amateur players. Greater muscle forces created by the LE drive during the loading stage of a serve correlate with increased serve speed (Girard et al., 2005; Reid et al., 2008; Martin et al., 2014).
Numerous studies have shown potential correlations with tennis serve speed, including anthropometric traits, player skill, flexibility, and strength measurements through isokinetic and isometric testing (Bonato, Maggioni, Rossi, Rampichini, La Torre, & Merati, 2015; Baiget, Corbi, Pedro Fuentes, & Fernandez-Fernandez, 2016; Sögüt, 2017). Advanced player skill has a positive association with increased serve speed in junior competitive tennis players (Sögüt, 2017). Increased wrist flexion, shoulder flexion, and shoulder internal rotation (IR) range of motion (ROM) have significant correlations to increased serve speed in tournament-level players (Cohen, Mont, Campbell, Vogelstein, & Loewy, 1994; Sawle, Freeman, & Marsden, 2017).
Current research does not provide a consensus as to what performance – related objective variables are correlative to a tennis player’s serve speed (Ulbricht, Fernandez-Fernandez, Mendez-Villanueva, ; Ferrauti, 2016). Because of the nature of a comprehensive movement pattern, increased serve speed is likely a combination of several factors, including player attributes of skill, anthropometrics, and physical performance measures. The purpose of this study was to investigate the correlations between tennis serve speed, player skill, UE and LE ROM, strength, balance, and power.

2. Material and methods
The hypothesis is that serve speed is predictable by the force of upper and lower extremities.

A group of 24 amateur young tennis players, boys, and girls (age of 14 ±2) was subjected to a series of mobility, balance, strength and serve speed testing performed outdoor during 6 months.

The mobility degrees of shoulder and hip were established by measuring the internal and external rotating angles. Also, palm ankle dorsiflexion were measured. The balance was evaluated by one leg standing on the dominant and non-dominant leg with eyes open, standing on both legs with the eyes shut. The strength of the arms was measured by a sitting one arm ball throw of a 2kg ball. Legs strength evaluations implied measuring broad jumps and counting one-leg jumps on the dominant and non-dominant leg.

Serve speed was observed directly by using a sensor attached to the racket handle.
All data analysis was accomplished using SPSS statistical software (v 24; IBM Corp). Descriptive statistics were calculated for all variables (Table 1).

The Pearson correlation coefficient was used to identify connections between serve speed, considered as a dependent variable, and mobility, balance, and strength, as independent variables.

Significance for all analyses was set at P ; 0.05. Variables are listed in relation to the player’s dominant serving arm, with LE variables written as either ipsilateral or contralateral to the player’s dominant serving arm. Significant correlations were used in a stepwise linear regression model while removing outliers outside of 2 SDs. Serve speed was listed as the dependent variable, and all significant variables from the Pearson correlation were listed as independent variables.
3. Results and Discussions
There were not any significant correlations found for participant age (r = 0.04, P = 0.31) or racket string tension (r = ?0.08, P = 0.27).
Range of motion variables portrayed a significant positive correlation for hip external rotation angle of the non-dominant arm to serve speed (r = 0.36, P = 0.01). No other ROM variables demonstrated significant correlations to serve speed (P ; 0.05) in this pilot study sample.
Shoulder external rotation to internal rotation strength ratio was calculated and did not show significance to serve speed for the dominant (r = 0.18, P = 0.13) or non-dominant UE (r = ?0.03, P = 0.44).
No strength variables tested demonstrated significant correlations to serve speed for the UE or LE (P ; 0.05). Shoulder ER to IR strength ratio was calculated and did not show significance to serve speed for the non-dominant (r = 0.20, P = 0.11) or dominant UE (r = ?0.03, P = 0.42). Strength correlations were also assessed for UE strength variables grouped together and for each LE hip strength variable grouped together. These groupings demonstrated correlations as follows:
dominant UE (r = 0.13, P = 0.21), non-dominant UE (r = 0.02, P = 0.46), ipsilateral LE (r = ?0.01, P = 0.47), and contralateral LE (r = 0.02, P = 0.46).

Even though these values could be biased due to a small sample size of only 24 participants, authors consider that it is an entitled need for future studies to look after precise differences between levels of performance, genders and age groups.

This pilot study has limitations that should be considered when interpreting the data. First, no power analysis was performed, and the sample size was relatively small due to the amount of amateur players available.This reduces the power of the results when portraying significant correlations, as they may have been too small to accurately detect relationships.
Also, because of participant availability, testing was conducted over an 6-month period, which may have led to discrepancies in the amount of training and practice among players.

Table 1. Descriptive statistics and correlation coefficients between serve speed and all variables

false
Scaled score was obtained using the equation:
(distance thrown cm / weight kg)
Although this study was intended to capture a gross kinetic chain approach to understanding physical traits that may affect serve speed, the study design included objective testing commonly performed from a rehabilitation perspective while trying to ease each participant’s time commitment. As a result, not all measurements were made to fully capture the complex movement pattern of the tennis serve. Also, to promote feasibility of testing, a single-examiner approach was used for all objective measures. Even included variables have shown fair to good intrarater reliability, there are inherent flaws with the stated methods. A single-examiner approach for stabilization and the range of motion measurement, a make test with a hand-held goniometer for a single repetition, may have all led to measurement error.

Finally, it is important to note that no true bio-mechanical analysis using video motion capture was incorporated in this pilot study.

Discussions
This pilot study has limitations that should be considered when interpreting the data. First, no power analysis was performed, and the sample size was relatively small due to the amount of amateur players available.This reduces the power of the results when portraying significant correlations, as they may have been too small to accurately detect relationships.
Also, because of participant availability, testing was conducted over an 6-month period, which may have led to discrepancies in the amount of training and practice among players.

Although this study was intended to capture a gross kinetic chain approach to understanding physical traits that may affect serve speed, the study design included objective testing commonly performed from a rehabilitation perspective while trying to ease each participant’s time commitment. As a result, not all measurements were made to fully capture the complex movement pattern of the tennis serve. Also, to promote feasibility of testing, a single-examiner approach was used for all objective measures. Even included variables have shown fair to good intrarater reliability, there are inherent flaws with the stated methods. A single-examiner approach for stabilization and the range of motion measurement, a make test with a hand-held goniometer for a single repetition, may have all led to measurement error.

Finally, it is important to note that no true bio-mechanical analysis using video motion capture was incorporated in this pilot study.

4. Conclusions
This pilot study offers an analysis of the correlations across player skill, range of motion, strength, balance, and power variables with tennis serve speed among amateur tennis players. The combination of player skill, unilateral upper extremity and lower extremity power, and hip range of motion may be predictive in determining tennis serve speed.

References
BAIGET, E., CORBI, F., PEDRO FUENTES, J., FERNANDEZ-FERNANDEZ, J. (2016). The relationship between maximum isometric strength and ball velocity in the tennis serve. J Hum Kinet. 53:63-71;
BONATO, M., MAGGIONI, M.A., ROSSI, C., RAMPICHINI, S., LA TORRE, A., MERATI, G. (2015). Relationship between anthropometric or functional characteristics and maximal serve velocity in professional tennis players. J Sports Med Phys Fitness. 55:1157-1165;
COHEN, D.B., MONT, M.A., CAMPBELL, K.R., VOGELSTEIN, B.N., LOEWY, J.W. (1994). Upper extremity physical factors affecting tennis serve velocity. Am J Sports Med. 22:746-750;
FERNANDEZ-FERNANDEZ, J., ULBRICHT, A., FERRAUTI, A. (2014). Fitness testing of tennis players: how valuable is it? Br J Sports Med. 48(suppl 1):i22-i31;
GIRARD, O., MICALLEF, J.-P., MILLET, GP. ( 2005). Lower-limb activity during the power serve in tennis: effects of performance level. Med Sci Sports Exerc. 37:1021-1029;
MARTIN, C., BIDEAU, B., BIDEAU, N., NICOLAS, G., DELAMARCHE, P., KULPA, R. (2014). Energy flow analysis during the tennis serve: comparison between injured and noninjured tennis players. Am J Sports Med. 42:2751-2760;
REID, M., ELLIOTT, B., ALDERSON, J. (2008). Lower-limb coordination and shoulder joint mechanics in the tennis serve. Med Sci Sports Exerc. 40:308-315;
SAWLE L, FREEMAN J, MARSDEN J. (2017). Intra-rater reliability of the multiple single-leg hop-stabilization test and relationships with age, leg dominance, and training. Int J Sports Phys Ther. 12:190-198;
SÖGÜT, M. (2017). A comparison of serve speed and motor coordination between elite and club level tennis players. J Hum Kinet. 55:171-176;
ULBRICHT A, FERNANDEZ-FERNANDEZ J, MENDEZ-VILLANUEVA A, FERRAUTI A. (2016). Impact of fitness characteristics on tennis performance in elite junior tennis players. J Strength Cond Res. 30:989-998.

Original Article
Identifying a Connection Between Mobility Degree, Balance, Strength, and Tennis Serve: a Pilot Study
Prodan Rodica 1
Grosu Emilia Florina 2
Popovici Cornelia 3
Grosu Vlad Teodor 4
1,2UBB, FEFS, Str. Pandurilor nr. 7, Cluj-Napoca, 400376, Romania
3UMF “Iuliu Ha?ieganu”, Faculty of Medicine, Str. Louis Pasteur nr. 6,
Cluj-Napoca, 400349, Romania
4UTCN, Dep. of Mechatronics and Machine Dynamics, Blvd. Muncii nr.103-105,
Cluj-Napoca, 400671,Romania
DOI: xxxxxxxxxxxxxx
Keywords: tennis, strength, speed, tennis serve
Abstract
Tennis serve is the only hit that depends exclusively on the hitter. This aspect leads to the necessity of identification and understanding of the importance of all the elements.
The hypothesis is that serve speed is predictable by force of upper and lower limbs.

A group of 24 amateur young tennis players, (age of 14 ±2) was subjected to a series of mobility, balance, strength and serve speed testing. The Pearson correlation coefficient was used to identify connections between serve speed, considered as a dependent variable, and mobility, balance, and strength, as independent variables.

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For You For Only $13.90/page!


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Hip external rotation angle of the non-dominant arm, one-leg jumps and one arm ball throws have shown strong positive associations with serve speed (p < 0.05). The anticipation of serve speed had an 81% variance of precision. A combination of body mobility and force may lead to the reasonable anticipation the serve speed individual capacity.

1. Introduction
The tennis serve is the only stroke in tennis without influence from the opposition, allowing the player a larger locus of control across the movement pattern. Precise coordination across the kinetic chain is necessary to reach the greatest serve speed potential (Girard, Micallef, & Millet, 2005; Reid, Elliott & Alderson, 2008; Martin, Bideau, Bideau, Nicolas, Delamarche, & Kulpa, 2014). Given the desire for optimization of serve speed, understanding the variables that contribute to increased serve speed are of particular interest. Biomechanical analysis of the tennis serve shows that kinetic energy is produced almost equally between the upper extremity (UE) and lower extremity (LE) throughout the motion (Martin et al., 2014).

However, many servers lose the potential to produce higher serve speeds because of a lack of energy flow from their LE to their UE, and hence develop an over-reliance on UE force production to generate serve speed (Martin et al., 2014). LE electromyogram and ground-reaction profiles support that professionally ranked players demonstrate more refined neuromuscular coordination patterns during their movement pattern compared with less elite or even amateur players. Greater muscle forces created by the LE drive during the loading stage of a serve correlate with increased serve speed (Girard et al., 2005; Reid et al., 2008; Martin et al., 2014).
Numerous studies have shown potential correlations with tennis serve speed, including anthropometric traits, player skill, flexibility, and strength measurements through isokinetic and isometric testing (Bonato, Maggioni, Rossi, Rampichini, La Torre, & Merati, 2015; Baiget, Corbi, Pedro Fuentes, & Fernandez-Fernandez, 2016; Sögüt, 2017). Advanced player skill has a positive association with increased serve speed in junior competitive tennis players (Sögüt, 2017). Increased wrist flexion, shoulder flexion, and shoulder internal rotation (IR) range of motion (ROM) have significant correlations to increased serve speed in tournament-level players (Cohen, Mont, Campbell, Vogelstein, & Loewy, 1994; Sawle, Freeman, & Marsden, 2017).
Current research does not provide a consensus as to what performance – related objective variables are correlative to a tennis player’s serve speed (Ulbricht, Fernandez-Fernandez, Mendez-Villanueva, ; Ferrauti, 2016). Because of the nature of a comprehensive movement pattern, increased serve speed is likely a combination of several factors, including player attributes of skill, anthropometrics, and physical performance measures. The purpose of this study was to investigate the correlations between tennis serve speed, player skill, UE and LE ROM, strength, balance, and power.

2. Material and methods
The hypothesis is that serve speed is predictable by the force of upper and lower extremities.

A group of 24 amateur young tennis players, boys, and girls (age of 14 ±2) was subjected to a series of mobility, balance, strength and serve speed testing performed outdoor during 6 months.

The mobility degrees of shoulder and hip were established by measuring the internal and external rotating angles. Also, palm ankle dorsiflexion were measured. The balance was evaluated by one leg standing on the dominant and non-dominant leg with eyes open, standing on both legs with the eyes shut. The strength of the arms was measured by a sitting one arm ball throw of a 2kg ball. Legs strength evaluations implied measuring broad jumps and counting one-leg jumps on the dominant and non-dominant leg.

Serve speed was observed directly by using a sensor attached to the racket handle.
All data analysis was accomplished using SPSS statistical software (v 24; IBM Corp). Descriptive statistics were calculated for all variables (Table 1).

The Pearson correlation coefficient was used to identify connections between serve speed, considered as a dependent variable, and mobility, balance, and strength, as independent variables.

Significance for all analyses was set at P ; 0.05. Variables are listed in relation to the player’s dominant serving arm, with LE variables written as either ipsilateral or contralateral to the player’s dominant serving arm. Significant correlations were used in a stepwise linear regression model while removing outliers outside of 2 SDs. Serve speed was listed as the dependent variable, and all significant variables from the Pearson correlation were listed as independent variables.
3. Results and Discussions
There were not any significant correlations found for participant age (r = 0.04, P = 0.31) or racket string tension (r = ?0.08, P = 0.27).
Range of motion variables portrayed a significant positive correlation for hip external rotation angle of the non-dominant arm to serve speed (r = 0.36, P = 0.01). No other ROM variables demonstrated significant correlations to serve speed (P ; 0.05) in this pilot study sample.
Shoulder external rotation to internal rotation strength ratio was calculated and did not show significance to serve speed for the dominant (r = 0.18, P = 0.13) or non-dominant UE (r = ?0.03, P = 0.44).
No strength variables tested demonstrated significant correlations to serve speed for the UE or LE (P ; 0.05). Shoulder ER to IR strength ratio was calculated and did not show significance to serve speed for the non-dominant (r = 0.20, P = 0.11) or dominant UE (r = ?0.03, P = 0.42). Strength correlations were also assessed for UE strength variables grouped together and for each LE hip strength variable grouped together. These groupings demonstrated correlations as follows:
dominant UE (r = 0.13, P = 0.21), non-dominant UE (r = 0.02, P = 0.46), ipsilateral LE (r = ?0.01, P = 0.47), and contralateral LE (r = 0.02, P = 0.46).

Even though these values could be biased due to a small sample size of only 24 participants, authors consider that it is an entitled need for future studies to look after precise differences between levels of performance, genders and age groups.

This pilot study has limitations that should be considered when interpreting the data. First, no power analysis was performed, and the sample size was relatively small due to the amount of amateur players available.This reduces the power of the results when portraying significant correlations, as they may have been too small to accurately detect relationships.
Also, because of participant availability, testing was conducted over an 6-month period, which may have led to discrepancies in the amount of training and practice among players.

Table 1. Descriptive statistics and correlation coefficients between serve speed and all variables

false
Scaled score was obtained using the equation:
(distance thrown cm / weight kg)
Although this study was intended to capture a gross kinetic chain approach to understanding physical traits that may affect serve speed, the study design included objective testing commonly performed from a rehabilitation perspective while trying to ease each participant’s time commitment. As a result, not all measurements were made to fully capture the complex movement pattern of the tennis serve. Also, to promote feasibility of testing, a single-examiner approach was used for all objective measures. Even included variables have shown fair to good intrarater reliability, there are inherent flaws with the stated methods. A single-examiner approach for stabilization and the range of motion measurement, a make test with a hand-held goniometer for a single repetition, may have all led to measurement error.

Finally, it is important to note that no true bio-mechanical analysis using video motion capture was incorporated in this pilot study.

Discussions
This pilot study has limitations that should be considered when interpreting the data. First, no power analysis was performed, and the sample size was relatively small due to the amount of amateur players available.This reduces the power of the results when portraying significant correlations, as they may have been too small to accurately detect relationships.
Also, because of participant availability, testing was conducted over an 6-month period, which may have led to discrepancies in the amount of training and practice among players.

Although this study was intended to capture a gross kinetic chain approach to understanding physical traits that may affect serve speed, the study design included objective testing commonly performed from a rehabilitation perspective while trying to ease each participant’s time commitment. As a result, not all measurements were made to fully capture the complex movement pattern of the tennis serve. Also, to promote feasibility of testing, a single-examiner approach was used for all objective measures. Even included variables have shown fair to good intrarater reliability, there are inherent flaws with the stated methods. A single-examiner approach for stabilization and the range of motion measurement, a make test with a hand-held goniometer for a single repetition, may have all led to measurement error.

Finally, it is important to note that no true bio-mechanical analysis using video motion capture was incorporated in this pilot study.

4. Conclusions
This pilot study offers an analysis of the correlations across player skill, range of motion, strength, balance, and power variables with tennis serve speed among amateur tennis players. The combination of player skill, unilateral upper extremity and lower extremity power, and hip range of motion may be predictive in determining tennis serve speed.

References
BAIGET, E., CORBI, F., PEDRO FUENTES, J., FERNANDEZ-FERNANDEZ, J. (2016). The relationship between maximum isometric strength and ball velocity in the tennis serve. J Hum Kinet. 53:63-71;
BONATO, M., MAGGIONI, M.A., ROSSI, C., RAMPICHINI, S., LA TORRE, A., MERATI, G. (2015). Relationship between anthropometric or functional characteristics and maximal serve velocity in professional tennis players. J Sports Med Phys Fitness. 55:1157-1165;
COHEN, D.B., MONT, M.A., CAMPBELL, K.R., VOGELSTEIN, B.N., LOEWY, J.W. (1994). Upper extremity physical factors affecting tennis serve velocity. Am J Sports Med. 22:746-750;
FERNANDEZ-FERNANDEZ, J., ULBRICHT, A., FERRAUTI, A. (2014). Fitness testing of tennis players: how valuable is it? Br J Sports Med. 48(suppl 1):i22-i31;
GIRARD, O., MICALLEF, J.-P., MILLET, GP. ( 2005). Lower-limb activity during the power serve in tennis: effects of performance level. Med Sci Sports Exerc. 37:1021-1029;
MARTIN, C., BIDEAU, B., BIDEAU, N., NICOLAS, G., DELAMARCHE, P., KULPA, R. (2014). Energy flow analysis during the tennis serve: comparison between injured and noninjured tennis players. Am J Sports Med. 42:2751-2760;
REID, M., ELLIOTT, B., ALDERSON, J. (2008). Lower-limb coordination and shoulder joint mechanics in the tennis serve. Med Sci Sports Exerc. 40:308-315;
SAWLE L, FREEMAN J, MARSDEN J. (2017). Intra-rater reliability of the multiple single-leg hop-stabilization test and relationships with age, leg dominance, and training. Int J Sports Phys Ther. 12:190-198;
SÖGÜT, M. (2017). A comparison of serve speed and motor coordination between elite and club level tennis players. J Hum Kinet. 55:171-176;
ULBRICHT A, FERNANDEZ-FERNANDEZ J, MENDEZ-VILLANUEVA A, FERRAUTI A. (2016). Impact of fitness characteristics on tennis performance in elite junior tennis players. J Strength Cond Res. 30:989-998.

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