**Core Stability and Symmetry of Youth Female Volleyball Players: A Pilot Study on Anthropometric and Physiological Correlates**

**Sophia D. Papadopoulou 1, Amalia Zorzou 2, Sotirios Drikos 3, Nikolaos Stavropoulos 1, Beat Knechtle <sup>4</sup> and Pantelis T. Nikolaidis 2,\***


Received: 28 January 2020; Accepted: 4 February 2020; Published: 6 February 2020

**Abstract:** The aim of the present study was to examine the variation in core stability and symmetry of youth female volleyball players by age, and its relationship with anthropometric characteristics, the 30 s Wingate anaerobic test (WAnT), and the 30 s Bosco test. Female volleyball players (*n* = 24, age 13.9 ± 1.9 years, mean ± standard deviation) performed a series of anthropometric, core stability tests (isometric muscle endurance of torso flexors, extensors, and right and left lateral bridge), WAnT (peak power, mean power, Pmean, and fatigue index, FI) and Bosco test (Pmean). Flexors-to-extensors ratio and right-to-left lateral bridge ratio were also calculated. Participants were grouped into younger (*n* = 12, 12.3 ± 1.2 years) or older than 14 years (*n* = 12, 15.4 ± 1.0 years), and into normal (flexors-to-extensors ratio < 1; *n* = 17) or abnormal flexors-to-extensors ratio (≥1; *n* = 7). The older age group was heavier (+11.3 kg, mean difference; 95% CI, 2.0, 20.6) and with higher body mass index (+2.8 kg m<sup>−</sup>2; 95% CI, 0.4, 5.1) than the younger age group. The group with abnormal flexors/extensors had larger flexors muscle endurance (+77.4 s; 95% CI, 41.8, 113.0) and higher flexors/extensors ratio (+0.85; 95% CI, 0.61, 1.10) than the normal group. Body fat percentage (BF) correlated moderately-to-largely with flexors (*r* = −0.44, *p* = 0.033), extensors (*r* = −0.51, *p* = 0.011), and left lateral bridge (*r* = −0.45, *p* = 0.027); WAnT Pmean moderately-to-largely with right (*r* = 0.46, *p* = 0.027) and left lateral bridge (*r* = 0.55, *p* = 0.006); FI moderately-to-largely with right (*r* = −0.45, *p* = 0.031) and left lateral bridge (*r* = −0.67, *p* < 0.001), and right/left ratio (*r* = 0.42, *p* = 0.046); Bosco Pmean correlated moderately-to-largely with right (*r* = 0.48, *p* = 0.020) and left lateral bridge (*r* = 0.67, *p* = 0.001). A stepwise regression analysis indicated FI and BF as the most frequent predictors of core stability. The findings of the present study suggested that increased core stability was related to decreased BF and increased anaerobic capacity. A potential misbalance between torso flexors and extensors might be attributed to bidirectional variations (either high or low scores) of flexors muscle endurance rather than decreased extensors muscle endurance.

**Keywords:** human performance; muscle endurance; team sport; torso extensors; torso flexors

#### **1. Introduction**

Female volleyball has been one of the most popular team sports worldwide [1]. Performance in this sport has been associated with a series of physical, physiological, psychological and technique and tactical characteristics [2,3]. With regards to physiological characteristics, most studies have focused on jumping ability and anaerobic power so far showing that female volleyball players jumped high and were characterized by high levels of anaerobic power [4,5]. Both jumping ability and anaerobic power might vary by age with adults scoring higher than adolescents [6]. Moreover, they might vary by in-game role of the players, e.g., higher jump height in hitters than libero players [6]. On the other hand, muscle endurance, i.e., the ability maintain muscle power output over time, in female volleyball—despite being a major component of health-related physical fitness—has received less scientific attention [7]. Muscle endurance has been considered not only in terms of absolute values, but also with regards to symmetry between different muscle groups (e.g., agonists versus antagonists) [7].

Core stability, i.e., the ability to optimize the placement and movement of the torso over the pelvis, has been recognized as a major component of muscle endurance. It was observed that core stability was beneficial for human performance, e.g., being stable reference would allow upper and lower limbs developing force [8], and health, e.g., maintenance of low back and knee health [9]. A low level of core stability increased the risk of low back and knee injuries [10]. In volleyball, those with core instability had high scapular malposition, inferior medial border prominence, coracoid pain, and dyskinesis of scapular movement [11]. Furthermore, the inclusion of core stability exercises was considered in preventive training programs [12,13]. With regards to the symmetry of the muscle endurance of torso muscles, e.g., flexors-to-extensors or right-to-left lateral flexors, few studies were conducted in sports [14,15] including volleyball [7]. It has been proposed that a ratio of torso flexors-to-extensors muscle endurance larger than one might indicate misbalance in the torso muscle groups [16], and consequently, this ratio could be used in volleyball to monitor muscle imbalances and identify potential injury risk. Volleyball included overhead tasks relied on shoulder movements, which in turn needed core stability to be efficient [7], and it has been shown that core stability might influence muscle strength of shoulders [17].

Although the abovementioned studies improved our understanding about the role of core stability and symmetry on health, little information existed about its role on performance in volleyball. The knowledge of the relationship of core stability and symmetry with anthropometric and physiological characteristics would be of practical value for professionals working with female volleyball players. In addition to the symmetry of core muscle endurance, it would be also interesting to examine the metabolic aspect, where it might be assumed that it would rely on the anaerobic energy transfer system considering its duration (several seconds) and exercise intensity (increased muscle activity) [18]. In exercise testing, the Wingate anaerobic test (WAnT) has been considered as a "golden" standard of anaerobic power and capacity despite its specific mode of exercise (cycling) [19]. A continuous 30 s Bosco jumping test has been developed as more sport-specific than WAnT to monitor performance, especially in sports involving many jumps [20,21]. Therefore, information on the relationship of core stability and symmetry with WAnT and Bosco test would provide insight into the metabolic demands of exercise testing of the former variables. In turn, anaerobic capacity has been shown to be inversely related with body fat percentage (BF) [22], i.e., the higher the BF, the lower the anaerobic capacity, and, consequently, it might be expected that BF would be related with core stability indices too.

With regards to correlates of core stability with physiological measures, research on female soccer players reported no correlation of core stability with sprint and muscle strength; however, this finding might be due to the sample size of this study [23]. In addition, information about the variation of core stability and symmetry by age in female volleyball would also be interesting in terms of training and testing. It has been shown that the prevalence of back pain was higher in 14–17 than 11–13 year-old athletes [24]. Moreover, anaerobic capacity assessed by the WAnT and Bosco test was larger in 14–18 than in under 14 year-old female volleyball players [25], whereas no difference was observed in sit-ups test between under and over 14 years female volleyball players [26]. However, no information on age related differences in volleyball has been examined previously with regard to core stability and symmetry. Therefore, the aim of the present study was to examine the variation in core stability and symmetry of female volleyball players by age and its relationship with anthropometric characteristics, WAnT, and the Bosco test. A secondary aim was to compare examine differences between groups varying for torso flexors-to-extensors ratio as it was suggested that a ratio ≥ 1 would indicate misbalance [16]. The research hypothesis was that increased core stability indices would be associated with high scores of WAnT and Bosco test indices, and low BF. Since anaerobic capacity and body composition were related to performance [4,5], a potential association of core stability indices with these variables would highlight the relevance of core stability with performance.

#### **2. Materials and Methods**

#### *2.1. Study Design and Participants*

Female volleyball players (*n* = 24, age 13.9 ± 1.9 years) performed a series of anthropometric, core stability (isometric muscle endurance of torso flexors, extensors, and right and left lateral bridge) and WAnT (peak power, mean power, Pmean, and fatigue index, FI, were estimated). Since there was no information about minimal level of effect size in the differences between groups that would be of scientific interest, the sample size was selected considering previous studies [7,23]. Flexors-to-extensors ratio and right-to-left lateral bridge ratio were also calculated to evaluate the symmetry of the core stability variables. Participants were volleyball players of a sport club in Athens and volunteered for this study. They had sport experience 2.9 ± 1.9 years, practiced volleyball 3.7 ± 1.0 days per week with each training session lasting 93 ± 10 min, a total weekly training volume 348 ± 124 min and participated in one official game per week. After being informed with details about all procedures, participants and their guardians provided their consent to participate. The exercise testing was performed in a single session. The study was approved by the local Committee of Ethics (EPL 2019/12). Participants were grouped into younger (*n* = 12, age 12.3 ± 1.2 years, sport experience 2.5 ± 1.6 years, 3.6 ± 0.6 weekly training units, and volume 321 ± 54 min) or older than 14 years (*n* = 12, 15.4 ± 1.0 years, 3.4 ± 2.1 years, 3.8 ± 1.2 and 374 ± 166 min, respectively), and into normal (flexors-to-extensors ratio < 1; *n* = 17) or abnormal flexors-to-extensors ratio (≥1; *n* = 7) according to the classification of McGill [16]. An age of 14 years has been suggested to categorize pubertal status in girls [27] and classified adolescent female volleyball players into age groups [25,26]. Considering the sample size and their small sport experience, the participants were not grouped by playing position.

#### *2.2. Equipment and Procedures*

Participants were evaluated for stature (SECA, Leicester, UK) and body mass (HD-351 Tanita, City, IL, USA) to the nearest 0.1 cm and 0.1 kg, respectively. The thickness of ten skinfolds (cheek, chin, pectoral, triceps, subscapular, abdomen, chest II, iliac crest, patella and proximal calf) was measured on the right side of the body to the nearest 0.1 mm (Harpenden, West Sussex, UK) and was used to estimate BF according to a Parizkova equation described by Eston and Reilly [28]. After a standardized warm-up including 9 min submaximal cycling and 6 min stretching exercises, participants performed the 30 s Wingate anaerobic test (WAnT) on a cycle ergometer (874 Ergomedic, Monark, City, Sweden) against braking force 0.075 <sup>×</sup> body mass providing peak power (Ppeak, W kg<sup>−</sup>1), mean power (Pmean, W kg−1), and fatigue index (FI, %). Participants were informed that WAnT was an all-out test not allowing the adoption of a pacing strategy, and were encouraged continuously during the test to exert maximal effort. In addition, a continuous 30 s jumping Bosco test was performed, where the participants were instructed to jump continuously throughout this period aiming to achieve maximal jump height in each jump, minimal time spent at the ground between consecutive jumps and maintaining their hands on the hips [20]. The mean power (Ppeak, W kg<sup>−</sup>1) was the outcome measure of the Bosco test.

To assess core stability, four primary (torso flexors, extensors, right and left lateral bridge test) and two secondary measures (flexors to extensors ratio and right to left lateral ratio) following the recommendations of Hoogenboom and Bennett [29] were performed. Participants were familiarized with these measures, since they were included in their training routine. In the torso flexors test, the participant adopted a sit-up position at angle 60◦ from the floor, whereas, in the torso extensors test, the participant was with her upper body unsupported out of a table and an ankle 180◦ at hips. In the lateral bridge test, the participant was lying using a side-bridge position. A few seconds practice was provided prior to testing to explain the correct position. A single trial was performed for each test and a 5-min break was provided between tests to allow sufficient recovery [18]. In each test of core stability, participants were asked to maintain the correct position as much as possible. Each primary measure was evaluated in the nearest 0.1 s; thereafter, the secondary measures were calculated to the nearest 0.1. The timing of each test started when participants adopted the instructed position and stopped when a deviation from the position was observed. This protocol evaluated core stability and symmetry previously in female and male soccer players [14,15]. Reliability coefficients ranged from 0.93 (flexors), and 0.96 (right later bridge) to 0.99 (extensors and left lateral bridge) [18].

#### *2.3. Statistical and Data Analyses*

IBM SPSS v.23.0 (SPSS, Chicago, USA) and Graphpad v.7.0 (GraphPad Prism, San Francisco, CA, USA) were used for statistical analyses. Although the data did not present normal distribution according to visual inspection of Q–Q plots and Shapiro–Wilk test (since *n* was lower than 50), parametric statistics were used to provide comparable methods and analysis with previous studies on core stability [16,18,23,29]. A non-parametric statistics (median, inter-quartile range, Mann–Whitney U test for differences between groups and Spearman rho for correlations among variables) were also presented in Tables 1–3 to maintain the statistical integrity of this paper. Data were expressed as mean and standard deviation. A preliminary examination of potential relationship of training characteristics with the variables of interest did not reveal any significant correlation; thus, training characteristics were not considered as covariate. An independent student *t*-test examined differences between age groups (under 14 years versus over 14 years) and torso flexors-to-extensors ratio groups (normal versus abnormal). The magnitude of these differences was evaluated by Cohen's d, classified as trivial (*d* ≤ 0.2), small (0.2 < *d* ≤ 0.6), moderate (0.6 < *d* ≤ 1.2), large (1.2 < *d* ≤ 2.0), or very large (*d* > 2.0) [30]. The relationship of core stability and symmetry (torso flexors, extensors, right and left lateral bridge test, flexors to extensors ratio, and right to left lateral ratio) with anthropometric characteristics (age, height, weight, body mass index and BF), WAnT (Ppeak, Pmean and FI), and Bosco test (Pmean) was examined using Pearson correlation r. A step-wise regression analysis examined predictors of core stability and symmetry. Statistical significance was set at alpha 0.05.


**Table 1.** Descriptive statistics by age group.


**Table 1.** *Cont*.

SD = standard deviation, IQR = inter-quartile range, BMI = body mass index, BF = body fat percentage, flexors-to-extensors ratio, right-to-left lateral bridge ratio, WAnT = Wingate anaerobic test, Ppeak = peak power, Pmean = mean power, FI = fatigue index; \* *p* < 0.05, \*\* *p* < 0.001.

**Table 2.** Descriptive statistics by flexors-to-extensors ratio group.


IQR = inter-quartile range, BMI = body mass index, BF = body fat percentage, flexors-to-extensors ratio, right-to-left lateral bridge ratio, WAnT = Wingate anaerobic test, Ppeak = peak power, Pmean = mean power, FI = fatigue index; \* *p* < 0.001, \*\* *p* < 0.01.

**Table 3.** Correlations r (Spearman rho in brackets) of core stability and symmetry indices with anthropometric characteristics and Wingate anaerobic test.



**Table 3.** *Cont*.

BMI = body mass index, BF = body fat percentage, flexors-to-extensors ratio, right-to-left lateral bridge ratio, Ppeak = peak power, WAnT = Wingate anaerobic test, Pmean = mean power, FI = fatigue index; \* *p* < 0.05, \*\* *p* < 0.01, \*\*\* *p* < 0.001.

#### **3. Results**

The older age group differed in age from the younger one by 3.1 years (95% confidence intervals, CI, 2.2, 4.0; Cohen's *d* = 2.8), was heavier (+11.3 kg, mean difference; 95% CI, 2.0, 20.6; *d* = 1.0) and had a higher body mass index (+2.8 kg m−2; 95% CI, 0.4, 5.1; *d* = 1.0) (Table 1). No other difference was observed between age groups (*p* > 0.05). The group with abnormal flexors/extensors had larger flexors muscle endurance (+77.4 s; 95% CI, 41.8, 113.0; *d* = 1.6) and lower flexors/extensors (+0.85; 95% CI, 0.61, 1.10; *d* = 2.8) than the normal group (Table 2). No other difference was shown between flexors/extensors groups (*p* > 0.05).

The correlations of core stability and symmetry indices with anthropometric characteristics, WAnT and Bosco test were presented in Table 3. BF correlated moderately-to-largely with flexors, extensors and left lateral bridge, WAnT and Bosco Pmean moderately-to-largely with right and left lateral bridge, and FI moderately-to-largely with right and left lateral bridge, and right/left ratio. Representative correlations were depicted in Figure 1. The findings of the stepwise regression analysis were presented in Table 4. FI and BF were the most frequent predictors of core stability and symmetry.

**Figure 1.** Relationship of core stability with body fat percentage (**BF**; **a**), mean power (**Pmean**; **b**), and fatigue index (**FI**; **c**) of the Wingate anaerobic test.

**Table 4.** Stepwise regression analysis.


BF = body fat percentage, flexors-to-extensors ratio, right-to-left lateral bridge ratio, Ppeak = peak power, Pmean = mean power, FI = fatigue index, WAnT = Wingate anaerobic test; SEE = standard error of the estimate.

#### **4. Discussion**

The main findings of the present study were that (a) no difference in core stability and symmetry was observed between age groups; (b) participants with abnormal flexors-to-extensors ratio had more

muscle endurance in flexors than those with normal ratio; (c) flexors and extensors muscle endurance correlated with BF, i.e., the larger the muscle endurance, the lower the BF; (d) lateral muscle endurance correlated with indices of WAnT and Bosco test; and (e) FI and BF were the most frequent predictor of core stability and symmetry.

Considering the role of age, the comparison between age groups (~12 versus ~15 years) did not show any difference in core stability and symmetry, which was in agreement with a study on adolescent non-athletes [31]. It might be assumed that the intermittent nature of volleyball did not facilitate the development of muscle endurance. The relationship of core stability with BF might be attributed to the negative role of BF in exercise performance related to muscle endurance and anaerobic capacity [22,32]. Previously, it was observed that BF correlated with WAnT Pmean in both adolescent and adult female volleyball players [22], where high BF was related to low WAnT Pmean. It has been also shown that a higher BF was related to a lower number of sit-ups in 1 min in female police officers [32]. This negative role of BF for core stability and muscle endurance might be that fat was an extra load that should be sustained without contributing to muscle contraction.

Core stability indices (lateral bridge) correlated either with WAnT Pmean, i.e., mean cycling performance over 30s, or FI, i.e., percentage decrease of cycling performance over 30 s. Particularly, a high score of lateral bridge was related to high score of Pmean and low score of FI. It should be highlighted that a low score of FI in WAnT-combined with adequate Pmean-indicated high anaerobic capacity, since a participant was able to maintain performance during prolonged exercise [33]. On the other hand, no correlation was observed between core stability and Ppeak, i.e., performance in the first 5 s of WAnT. This finding was in agreement with a study in female and male soccer players, where core stability did not correlate with isometric muscle strength [15]. From a physiological point of view, core stability tests lasting from 6 s to 230 s had closer affinity with anaerobic capacity (WAnT Pmean and FI) rather than muscle power (Ppeak) and muscle strength. Moreover, it has been observed that exercise duration might partially explain the similar results of two different modes (cycling versus jumping) of exercise tests [21]. With regard to the correlations of the Bosco test, it was observed that the performance on this test correlated moderately-to-largely with torso lateral flexors muscle endurance. This observation was in agreement with research showing that torso lateral flexors had substantial potentials as stabilizers and energy generators during jumps [34] and played an important role in single-leg jumps independently of vertical or horizontal direction [35].

With regard to torso flexors-to-extensors ratio, it was found that an increased ratio in the abnormal group was due to an increased score of flexors. A ratio of 1.15 was observed in workers with a history of back disorders compared to 0.71 in their healthy counterparts [16], where the 1.15 ratio was attributed more to weak extensors rather than to strong flexors. These findings implied that, although the abnormal group of volleyball players had increased flexors-to-extensors ratio–observed also in a group with history of back disorders [16]—a different aetiology might be assumed (increased muscle endurance of flexors in the former group versus decreased muscle endurance of torso extensors in the latter group). The overall torso flexors-to-extensors ratio in the present study (0.74) was similar to that of healthy adults (0.71) [16] and adult female volleyball players (0.73) [7]. It should be highlighted that, although our results about torso flexors-to-extensors ratio were similar to their adult counterparts [7], the absolute scores of torso flexors and extensors muscle endurance were quite lower in our sample. Thus, the higher values of torso flexors and extensors in adult female volleyball players [7] might be attributed to a long-term training effect. Moreover, low back pain was associated with torso extensors and flexors weakness [36]. With regard to the normal group, i.e., the group with torso flexors-to-extensors ratio lower than one, it was observed that this ratio (0.49) was lower than that reported by literature on healthy adults and adult female volleyball players (~0.72) [7,16]. It was also shown that this decreased ratio was attributed more to decreased flexors muscle endurance rather than to the score of extensors. Thus, a training aim should be to prevent torso flexor-to-extensors misbalance in both directions (i.e., low or high scores of flexors muscle endurance.

The mean score of right-to-left lateral bridge (≥0.90) indicated a relative symmetry between right and left side of the torso; however, the large variation of scores of the right-to-left lateral bridge ratio shown by SD 0.28–0.41 suggested a lack of symmetry between the two sides, i.e., there were participants with large differences in muscle endurance between right and left torso flexors. On the other hand, SD as a measure of inter-individual variation should be interpreted with caution considering the lack of normal distribution of the data as indicated by non-parametric statistics (Tables 1 and 2). These findings highlighted the need for a balanced training load between torso flexors and extensors as well as between right and left lateral muscle groups.

A limitation of the present study was that the exercise tests of core stability relied on isometric muscle contraction; thus, caution would be needed to generalize the findings to exercise tests using other modes of muscle contraction (isotonic or isokinetic). Furthermore, special attention would be necessary when performing exercise tests of core stability such as torso flexors, since even a minimal deviation from the correct position would result in altered muscle activation influencing the outcome [37]. It was also acknowledged that other assessment methods of muscle symmetry (e.g., surface electromyography and isokinetic dynamometry) should be selected in future studies to verify our findings by using laboratory methods. On the other hand, the strength of this study was its novelty as it provided evidence about the relationship of core stability indices with BF, WAnT, and the Bosco test. In addition, the findings had practical applications for physicians, exercise physiologists, and fitness trainers to monitor the training of volleyball players. Performance in volleyball relied on the effectiveness of the dynamic movements of the shoulder, which in turn performed movements taking advantage of a stable torso; in this sense, although the core did not participate directly in dynamic movements, its optimal muscle function was necessary to stabilize the shoulder zone and pelvis in order for upper and lower limbs to perform efficiently [7]. Since data on core stability of adolescent female volleyball players were not available in the existed literature, practitioners might use our findings as reference to evaluate core stability and symmetry of their athletes. Although a correlation would not indicate causation, the knowledge of the relationship of core stability with BF, WAnT, and the Bosco test would aid practitioners in the interpretation of core stability measurements, e.g., a low score of core stability of an athlete with high BF might be attributed to an excess BF in addition to a likely muscle weakness.

#### **5. Conclusions**

The findings of the present study suggested that increased core stability was related to decreased BF and increased anaerobic capacity. A potential misbalance between torso flexors and extensors might be attributed to bidirectional variations (either high or low scores) of flexors rather than decreased extensors muscle endurance. Considering the lack of available data on core stability and symmetry in adolescent female volleyball players, our findings could be used by practitioners in the context of testing and training.

**Author Contributions:** Conceptualization, S.D.P. and P.T.N.; methodology, S.D.P. and P.T.N.; software, P.T.N.; validation, S.D.P. and P.T.N.; formal analysis, S.D.P. and P.T.N.; investigation, S.D.P. and P.T.N.; resources, S.D.P. and P.T.N.; data curation, S.D.P. and P.T.N.; writing—original draft preparation, S.D.P., A.Z., S.D., N.S., B.K., and P.T.N.; writing—review and editing, S.D.P., A.Z., S.D., N.S., B.K., and P.T.N.; visualization, S.D.P. and P.T.N.; supervision, S.D.P., B.K., and P.T.N.; project administration, S.D.P., B.K., and P.T.N. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Acknowledgments:** The voluntary participation of volleyball players in this research and the collaboration with the technical staff were gratefully acknowledged.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## *Article* **Agreement between Dribble and Change of Direction Deficits to Assess Directional Asymmetry in Young Elite Football Players**

#### **Athos Trecroci 1, Tindaro Bongiovanni 2, Luca Cavaggioni 1,3, Giulio Pasta 4, Damiano Formenti 5,\* and Giampietro Alberti <sup>1</sup>**


Received: 1 April 2020; Accepted: 5 May 2020; Published: 8 May 2020

**Abstract:** This study aimed to examine the agreement between asymmetries of dribble and change of direction (COD) deficits and to determine their potential difference to each other. Sixteen young elite football players were recruited and tested for sprint (over 10 m), dribbling (90◦CODdribbling) and COD (90◦CODrunning) performance in dominant (fastest) and non-dominant (slowest) directions. Dribble and COD deficits were computed to express dribbling and COD ability without the influence of acceleration. The asymmetric index (AI%) of both dribble and COD deficits were obtained for both directions. The level of agreement between dribble and COD deficits was assessed by Cohen's kappa statistic (κ). Results showed that AI% measured by dribble and COD deficits presented a poor level of agreement (κ = −0.159), indicating their imbalance did not favor the same direction. Moreover, AI% of the dribble deficit was significantly higher than those of the COD deficit. This study demonstrated that asymmetries in dribbling and change of direction performance (measured by dribble and COD deficit) were not in agreement to favor the same direction, also displaying a significant difference to each other. Practitioners should consider the task-specificity of asymmetry to reduce the imbalance in dribbling and COD performance.

**Keywords:** agreement; imbalance; football skills; football performance

#### **1. Introduction**

The combined asymmetrical and unpredictable nature of football prompts each player dribbling or changing direction in multiple directions (chaotically) within the pitch, which is unlikely to be equally distributed during a match [1]. Moreover, additional inherent factors (e.g., playing position, tactical constraints and players' leg or directional preference) may also contribute to influencing the players' movements within the pitch favoring predominantly their dominant side or direction to the detriment of the non-dominant one [2]. Although it would be advantageous for team sport athletes to express similar dribbling and change of direction (COD) performance toward different directions (right versus left) [3], they often manifest a certain degree of asymmetry, even throughout the season [1,4], that should be opportunely quantified.

Despite the apparent relevance of assessing dribbling and change of direction (COD) asymmetries, the available literature is scarce. Most of the studies used the completion time (the total time to cover a

specific course) to detect the dribbling [5] and COD performance [2,6] for imbalance purposes. It has been previously observed that completion time might be biased by an individual's sprint capacity either via dribbling [7,8] or changing direction assessment [9,10]. To overcome this issue, dribble and COD deficits have been proposed to provide practitioners with a more valid and isolated measure within a field-based context, limiting the impact of acceleration [7–10].

A recent study quantified the directional asymmetry in the 505 COD test by deficit and total time between groups of different team-sport athletes (e.g., football, basketball and cricket). It was found that all athletes manifested a certain degree of asymmetry between the dominant and non-dominant side for both COD deficit and total time [11]. The authors also concluded that, being COD deficit unbiased toward individuals with higher acceleration capacity, its use should be preferred to compare asymmetry in respect of total time [11]. Moreover, in the studies of Dos'Santos et al. [3,12], the asymmetry of COD deficit reported higher percentages compared with total time with 35% of the subjects exhibiting values greater than the asymmetric threshold (14.5%) and 49% showing asymmetries greater than 10% [3], which has been previously used as a limit for an acceptable imbalance [12–14]. Although a dearth of research exists on COD deficit asymmetries, no information is available on the use of dribble deficit to quantify directional asymmetry.

Following the available literature, different assessments of asymmetry over a certain task may detect diverse levels of imbalances rarely favoring the same side or direction [15]. Madruga et al. [16] investigated whether the asymmetry was consistent between three unilateral jump-based tests in team sport athletes. The authors reported a low level of agreement suggesting that the asymmetries rarely favored the same dominant side. Similarly, Bishop et al. [17] reported slight to a fair agreement in the asymmetry within unilateral strength and jumping-based tests. Taken all together, these findings highlight the task-specificity of asymmetry, which should be considered when interpreting any performance influenced by leg or directional dominance in team sports. This may have important implications on the assessment of dribbling and COD asymmetries in football players. Dribbling and changing direction is pivotal to successfully compete in football. Quick and accurate change of directions while dribbling a ball allows a player to pass her or his opponent more easily, to invade a specific field area and to create a numerical superiority for increasing any chance of scoring a goal. In this context, besides quantifying the asymmetry using dribble and COD deficits, knowing whether there is consistency across them would be of practical importance. Of note, this may provide practitioners with useful information to target additional exercises for each individual's dominant (faster or preferred) and non-dominant (slower or non-preferred) side [17], which might differ between dribbling and CODs.

Therefore, the aim of the study was twofold: i) to examine the degree of agreement between dribble and COD deficit asymmetries in favoring the same direction; ii) to determine the extent of each dribble and COD deficit asymmetry and the possible difference to each other. Dribbling and COD are different movement tasks with the former more complex and technically demanding, especially concerning dominant and non-dominant sides [5]. Given the supposed task-specificity of asymmetry, we hypothesized that asymmetries of dribble and COD deficit would not favor the same direction, with the former displaying greater values than the latter.

#### **2. Materials and Methods**

#### *2.1. Experimental Approach*

In this cross-sectional study, 16 young football players from a professional club were tested for their dribbling and change of direction ability via a 90◦COD test (for both dominant and non-dominant directions) over 10 m (with 5-m entry and exit). Dribble and COD deficits were employed to offer an actual ability to dribble or change direction without the influence of acceleration capacity. Then, the asymmetry index of dribble and COD deficit was computed to establish their level of agreement

through the kappa coefficient. The derived asymmetries were also compared to each other to detect whether a potential difference would exist between dribbling and changing direction.

#### *2.2. Subjects*

Sixteen young elite football players from the same professional club (age 14.5 ± 0.8 years, body weight 64.3 ± 6.2 kg, height 177.1 ± 4.9 cm, maturity offset 1.05 ± 0.30 years) voluntarily participated in the study. The selected sample size was above the minimum value requested for conducting a Cohen's kappa agreement study [18]. All participants and their parents or guardians were informed about the purpose and potential experimental risks. After a deep description of the study, written consent was obtained from subjects and their parents or guardians to participate in the investigation. The study was approved by the Ethical Committee of the local Institution, in accordance with the Helsinki's declaration.

#### *2.3. Testing Procedures*

The subjects took part in the experimental procedure in June and were tested on an outdoor artificial turf at the same time of the day (i.e., from 3 p.m. to 5 p.m.). The subjects participated in two sessions. The first session involved a familiarization procedure in which all subjects gained confidence with the testing battery. Additionally, height, sitting height and body mass were taken by a stadiometer (SECA 213, Germany) and a portable scale (813, Germany) to the nearest of 1.0 cm and 0.1 kg, respectively. In the second session, a testing battery including 10-m sprint and 90◦COD test (executed with and without a ball) was randomly arranged. A 5-min standardized warm-up based on forward and backward jogging, acceleration, deceleration and skipping movements up to 5 m, was employed before undertaking the first test [19]. An electronic timing gates system (Witty, Microgate, Bolzano, Italia) was used to record the total time for 10-m sprint, dribbling and COD performance with the gates set at 0.7 m above the ground. The foremost foot was placed 0.3 m behind the starting line.

#### 2.3.1. Sprint Assessment

Each subject, when ready, sprinted over a 10 m from a two-point staggered stance. The subjects performed three maximal efforts interspersed by 2 minutes of passive recovery. The best performance time was considered in the analysis.

#### 2.3.2. Dribbling and Change of Direction Assessment

A 90◦ change of direction test for dribbling (90◦CODdribbling) and running (90◦CODrunning) was employed. The layout of the test is shown in Figure 1. All players were instructed to perform three bouts with the ball and three bouts without the ball for each direction (right and left) with 2 minutes of passive recovery in between. The best performance of the three bouts (in each direction) was considered for subsequent analysis. The distance between the starting line to the cone and between the cone and the finish line was 5 m each. For 90◦CODdribbling, the players were requested to dribble the ball around the cone with a minimum of two touches (with the same foot) along each 5-m path. For 90◦CODrunning, they were instructed to change direction around the cone using the same side-step technique in each bout, to avoid any influence due to different COD execution technique. In case of hitting or touching the cone (even with the ball) at the turning point, the player was stopped and invited to repeat the bout after 2 minutes of recovery. The 90◦CODdribbling and 90◦CODrunning performance were initially measured by the total running time to complete the 5-m + 5-m course. Based on the recommendations of previous studies [3,9], we decided to employ a COD deficit for inferential analysis on asymmetry while using total running time for descriptive purposes. The dribble deficit was calculated by subtracting the 90◦CODrunning total time from the 90◦CODdribbling total time. The COD deficit was calculated by subtracting the 10-m sprint time from the 90◦CODrunning total time. The fastest mean value between right and left directions was deemed as dominant (D) and the slowest mean value was considered as non-dominant (ND) [3].

**Figure 1.** The layout of the 90◦ change of direction (COD) test. The black silhouettes with and without the ball identify the dribbling and COD performance, respectively.

#### 2.3.3. Asymmetric Index Calculation

For both dribble and COD deficits the asymmetry index (AI%) was computed with the following formula:

$$\text{AI\%} = ((\text{D} - \text{ND})/\text{D}) \times 100$$

Likewise, as previously proposed by Dos'Santos et al. [3], an asymmetry threshold (AT%) was also obtained to determine whether an individual can be considered as asymmetrical with the formula [3]:

$$\text{AT\%} = \text{AI\%} \text{ пева} + (0.2 \times \text{SD})$$

where SD is the standard deviation of the AI% mean.

#### *2.4. Statistical Analysis*

The Shapiro–Wilk's test was conducted to verify if all data were normally distributed. The AI% resulted in non-normal distribution. Relative and absolute reliability was assessed for all tests using the intra-class correlation coefficient (ICC), standard error of the measurement (SEM) and the coefficient of variation (CV), respectively. Paired t-tests or Wilcoxon signed-rank test were used to detect differences between D and ND directions in 90◦CODrunning (for total running time and COD deficit) and 90◦CODdribbling (for total dribbling time and dribble deficit) tests, and between the AI% of dribble and COD deficit, respectively. The effect size of each difference was detected by Cohen's d (*d*) computation. The corresponding *d* was classified as *trivial* (*d* < 0.2), *small* (0.2 < *d* < 0.6), (0.6 < *d* < 1.2) *moderate*, (1.2 < *d* < 2.0) *large*, (2.0 < *d* < 4.0) *very large* and (*d* > 0.8) *near perfect*.

The degree of agreement between the AI% of dribble and COD deficit was assessed by Cohen's kappa statistic (κ). We used κ coefficient as an appropriate tool for assessing the agreement of directional asymmetry (between the two tests) involving right and left dichotomous variables. The κ coefficient described the chance-corrected proportional agreement determining how consistently an asymmetry in dribble and COD deficit agreed on the same direction [20,21]. Specifically, κ was given by the formula:

κ = (Observed Agreement − Chance agreement)/(Maximum agreement − Chance agreement)

where the observed agreement defines the percentage proportion of the directions (right and left) for which dribble and COD deficit agree, and the chance agreement defines the overall random agreement probability that they agree on the same direction. According to Viera and Garrett [20], the following levels of agreement were considered: κ < 0.00 (*poor*), 0.01 < κ < 0.20 (*slight*), 0.21 < κ < 0.400 (*fair*), 0.41 < κ < 0.60 (*moderate*), 0.61 < κ < 0.80 (*substantial*) and 0.81 < κ < 0.99 (*almost perfect*). Statistical analysis was performed using IBM Statistical Package for the Social Science version 21.0 (IBM Corp.; Armonk, NY, USA). An α-value of 0.05 was set as a criterion level of significance. Ninety-five percent confidence intervals (95% CI) are shown in squared brackets. Data are reported as mean ± standard deviation (SD).

#### **3. Results**

ICC values showed excellent reliability in 10m sprint (ICC = 0.95, 95% CI [0.86 to 0.98]; SEM = 0.02 s, CV = 1.8%), 90◦CODrunning test for D (ICC = 0.93, 95% CI [0.88-0.96]; SEM = 0.03, CV = 2.3%) and ND directions (ICC = 0.94, 95% CI [0.86-0.95]; SEM = 0.03, CV = 2.5%), 90◦CODdribbling test for D (ICC = 0.88, 95% CI [0.61 to 0.96]; SEM = 0.097 s, CV = 3.3%) and ND directions (ICC = 0.88, 95% CI [0.66 to 0.96]; SEM = 0.105, CV = 3.5%). The descriptive statistics of each performance outcome with the inclusion of asymmetry are shown in Table 1. In 90◦CODrunning test, significant differences were observed between D and ND for total running time and COD deficit with *large* and *moderate* effects, respectively (p < 0.0001, *d* = −1.07, 95% CI [−1.84 to −0.30] and *p* < 0.0001, *d* = −0.73, 95% CI [−1.47 to 0.00], respectively). Likewise, in 90◦CODdribbling test, significant differences were observed between D and ND for total dribbling time and dribble deficit with *small* effects (*p* < 0.0001, *d* = −0.55, 95% CI [−1.28 to 0.17] and *p* < 0.0001, *d* = −0.57, 95% CI [-1.30 to 0.15], respectively). The Wilcoxon signed-rank test revealed a significant difference between AI% of dribble deficit and AI% of COD deficit (Z = −2.275, *p* = 0.021). The AT% of dribble and COD deficits were 17.22% and 41.62%, respectively.


**Table 1.** Descriptive statistics of performance outcomes.

\*\*\* Significant (*p* < 0.0001) difference from ND, \* Significant (*p* < 0.05) difference from AI COD deficit (%). <sup>a</sup> *Large* effect size *d* versus ND, <sup>b</sup> *moderate* effect size *d* versus ND, <sup>c</sup> *small* effect size *d* versus ND. Note: D = dominant, ND = non-dominant, COD = change of direction speed, AI = asymmetry index, SD = standard deviation, CI = confidence interval.

Figure 2 shows the individual data for dribble and COD deficit asymmetries. In 6 out of 16 players, the two AIs% favored the same direction with a resultant observed agreement of 0.38 (38%). The random probability agreement that dribble and COD deficit favored the right and left directions were ~39% and ~10%, respectively, with a chance-corrected proportional agreement of 0.46 (46%). The resultant κ score indicated a *poor* agreement of −0.159 (standard error = 0.187, 95% CI [−0.526 to 0.208]) between AIs% of dribble and COD deficits in favoring the same direction.

**Figure 2.** Individual asymmetry data (AI%) for dribble and change of direction (COD) deficits. Bars above the 0 line shows the asymmetry favoring the right direction, and bars below the 0 line shows the asymmetry favoring the left direction. The dotted lines indicate the asymmetry threshold of dribble deficit while the solid lines indicate the asymmetry threshold of COD deficit, respectively.

#### **4. Discussion**

The main finding of this study was that the asymmetry measured by dribble and COD deficits presented a *poor* level of agreement, indicating they did not favor the same direction. Moreover, it has been shown that, on average, AIs% of dribble and COD deficits were significantly different from each other, with the former presenting the highest values. These findings are in line with our hypothesis that dribble and COD deficits would not exhibit asymmetries favoring the same direction, with the former displaying the highest value.

Demonstrating whether (or not) the level of asymmetry (i.e., right versus left) is consistent across dribbling and COD performance provides practitioners with practical information that can be helpful to design targeted training strategies. According to the present results, while a player exhibited a fast change direction with the ball on a given side (right), she or he tended to display a fast change direction without the ball toward an opposite one (left). For example, Figure 2 shows only 6 out of 16 (~ 38%) players presenting an AI% favoring the same side, whereas most of the AIs% were not consistent across dribble and COD deficits. Indeed, the probability that asymmetries of both dribble and COD deficits would favor the same direction by chance was 46%, which is higher than the observed agreement. As such, the resultant level of κ score, which has the peculiarity of removing any agreement by chance, indicated that they did not produce similar results on a given side or direction. Taken all together, these findings also suggest that the asymmetry for 90◦CODdribbling and 90◦CODrunning tests over young subjects and using a common metric (e.g., deficit) is task-specific. This is supported by the study of Bishop et al. [17] in which the authors examined whether asymmetries were consistent across unilateral strength and common jumping-based tests (e.g., single-leg countermovement jump and single-leg broad jump) for peak force and impulse (eccentric and concentric). Most of the agreement for peak force (κ = 0.05) and impulse (−0.25 < κ < 0.32) ranged from *slight* to *fair* even across common tests, except

for the *substantial* (κ = 0.79) agreement between single-leg countermovement jump and single-leg broad jump tests for concentric impulse. This provides evidence for the notion that asymmetry is task-specific. In fact, given the current results, practitioners should consider the task-specificity of asymmetry when interpreting dribbling and change of direction performance to implement targeted training strategies for an individual's dominant (faster or preferred) and non-dominant (slower or non-preferred) side [17]. For instance, it has been demonstrated that practicing with an emphasis on the non-preferred side (e.g., ND direction) by increasing accuracy and force in the kicks, ball control and speed may be a good practice to reduce asymmetry in dribbling [5]. Of note, the nature of these two motor actions (dribbling and COD) presents some peculiarities that differ from each other. Indeed, compared with COD, dribbling fast in multiple directions requires players a high technical (bilateral) proficiency to maintain the ball under control, which in turn slows their performance time.

To our knowledge, the present study is the first quantifying and comparing the dribbling and COD performance in young elite football players. Dribbling and COD are pivotal to successfully compete in youth football [22–24] with the former considered a field-based predictor of a player's success in one-to-one duels [25]. Unfortunately, some evidence exists on COD deficit in the current literature [3,9,26–28], there is a dearth of information on dribble deficit [7,8] and no data are available on its asymmetry. The unpredictability of game scenarios, together with inherent factors such as playing position, tactical constraints and players' leg or directional preference, may prompt players choosing predominantly their dominant side (at the expense of the non-dominant one) to address any football-specific maneuver [5]. The current results showed that the mean AI% of dribble deficit roughly doubled that of COD. The use of the ball requires players being able to perform complex movements depending on additional factors [29] (e.g., force, accuracy and precision kicking of dominant and non-dominant legs) that are likely to enhance the expected directional asymmetry among individuals [5]. Of note, in Figure 2, 6 (~ 38%) and 5 (~ 31%) out of 16 players were asymmetrical, presenting an AI% higher than the corresponding AT% for dribble and COD deficits, respectively. It is worth noticing that their values exceeded the common threshold of 10%, which has been previously used as a limit for an acceptable bilateral imbalance [12–14].

As regards COD deficit asymmetries, the present results appear in line with the study of Dos'Santos et al. [3], in which 35% of the subjects reported a significantly higher bilateral imbalance in COD deficit (by the 505 COD test) than the corresponding asymmetry threshold. However, according to recent studies, the relevance of any discussion about the thresholds and their capability to detect asymmetry has been questioned [4,15]. Bishop et al. [4,17] reported individual data for unilateral strength and jumping-based tests showing that asymmetries can sometimes be as large as 20%–40% with no bearing on a performance outcome (e.g., during CODs) [4]. Additionally, interpreting mean data without devoting attention to an individual approach would not depict a clear portrait of a player's asymmetry, and her or his training needs to reduce it. The current results appear to be in line with such consideration. Regarding dribble deficit, some individuals (e.g., player n◦ 1 in Figure 2) exhibited an imbalance higher than 50%, which is one and a half times larger than mean SD, while others were about on average (e.g., player n◦ 6 in Figure 2). Thus, it is evident how designing targeted training programs to the player n◦ 6 (with an AI% barely below the mean) would not likely contemplate the required additional exercises for the player n◦ 1 in an attempt to reduce the highest asymmetry. This information can be of practical relevance as practitioners are helped to plan any additional exercise on a more individual level to reduce asymmetry [17] in both dribbling and change of direction ability. It is notable that while COD asymmetries are detectable among team-sport athletes [11], within a homogeneous group as the present elite players, the inter-variability of dribbling and COD tests would limit the interpretation of the mean values. Bishop et al. [17] suggested to report and compare asymmetries to testing variability (e.g., CV%). In support of this, the inter-individual variability should be taken into account when attempting to screening young football players [30]. As such, it can be provided relevant information underpinning the monitoring and development of individualized or small-groups program routines [30].

This study presents limitations that should be acknowledged. The 90◦COD test currently selected may be limited to represent the variety of dribbling techniques (close dribbling skills or a combination of long kicks and fast acceleration to run past an opponent) performed in matches [25]. Taking into account the task-specificity of asymmetry, further studies are warranted to examine how the evidence of no agreement with COD would be confirmed within a wider spectrum of dribbling skills. We also put in evidence that our findings cannot be surely extended also to other team sports. For instance, dribbling and COD abilities are determinants component in basketball. Thus, further studies are warranted to examine whether the current disagreement between dribble and COD deficit asymmetries in football would be found also in basketball players who dribble with upper limbs instead of lower limbs. Finally, we put in evidence that the present findings should be interpreted according to maturity status. Indeed, although the current players' maturity offset was fairly homogeneous, it might be possible that different results would come from heterogeneous maturity-related profiles, and consequently leading to different dribbling and COD deficit results.

#### **5. Conclusions**

This study demonstrated that asymmetries in dribbling and change of direction were not in agreement to favor the same direction, probably reflecting the different nature of these motor actions. As such, practitioners should consider the task-specificity of asymmetry to reduce the imbalance between dominant and non-dominant directions. For example, additional dribbling exercises placing the emphasis on the ND direction may represent a good strategy to improve the ND itself, without affecting the D direction. Of note, practitioners are encouraged to interpret asymmetry data with an individual approach to contemplate the required additional exercises for a given player to reduce her or his imbalance on a more individual level. In young elite players, assessing the direction of asymmetry during dribbling and changing direction appears pivotal to guarantee informative data on their potential individual imbalance. Finally, coaches and practitioners may benefit from data on players' directional imbalances to ameliorate both individual monitoring and training processes across the youth athletic development.

**Author Contributions:** Conceptualization, A.T. and D.F.; methodology, A.T., L.C. and T.B.; formal analysis, A.T. and D.F.; investigation, A.T., L.C., T.B., G.P. and G.A.; data curation, A.T.; writing—original draft preparation, A.T. and D.F.; writing—review and editing, A.T., T.B., L.C., G.P., D.F. and G.A.; supervision, G.A.; All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


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