Gender-Specific Influences of Balance, Speed, and Power on Agility Performance : The Journal of Strength & Conditioning Research

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Gender-Specific Influences of Balance, Speed, and Power on Agility Performance

Sekulic, Damir1; Spasic, Miodrag1; Mirkov, Dragan2; Cavar, Mile3; Sattler, Tine4

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Journal of Strength and Conditioning Research 27(3):p 802-811, March 2013. | DOI: 10.1519/JSC.0b013e31825c2cb0
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Agility is often recognized as the ability to quickly change directions and to start and to stop quickly (14). Some authors have identified agility as the ability to maintain and control correct body positions while quickly changing direction through a series of movements (36). This ability is a determinant of sport performance in field and court sports, evidenced by time-motion analysis, validation of testing batteries for elite and nonelite performers, and coaching analyses for various team sports (33). Because of the diverse agility manifestations (e.g., forward-backward; rotational, lateral, etc.), the agility is hard to be generally developed throughout strength and conditioning training. Therefore, studies repeatedly tried to find the background of agility in different athletic abilities like power and speed, with the idea that the improvement in such capacities will lead to agility improvement (8,14,17,22). Although the morphological and biochemical determinants of maximal speed and agility (i.e., fiber types) have led to the assumption that these qualities are highly related (14), studies of the relationships among speed and agility have provided inconsistent findings. Relationships between speed and standard agility range from low values (0.27–0.32) (25) to moderate correlation coefficients (0.52–0.73) (23). In a study of rugby league players (8), the authors noted correlations of 0.52–0.58 for a standard and 0.61 and 0.62 for a modified 505 reactive agility test [for more details on reactive agility, see Sheppard et al. (33)]. Based on the presumed dependence on the same morphological origin (e.g., fiber types) and the results of several studies that have established a positive relationship between muscle power and sprinting abilities (2,5,10,11,34,35), it was expected that power would also be positively related to agility. However, there are limited data supporting this assumption. In their recent article, Markovic et al. (17) found a low multiple correlation between leg extensor strength qualities and agility performance, and their findings were similar to those of Young et al. (38), who found low to moderate coefficients. In contrast, Nimphius et al. (22) found a strong correlation between relative strength and the ability to change direction (agility performance) measured using 505 test variations in female softball players.

Authors already suggested that apart from speed and explosive strength, an improvement of balance should be considered as one of the key features of agility improvement (36). Miller et al. (18) stated that enhancing balance and control of body positions during complex movements should result in an improvement of agility. This hypothesis seems logical because all agility performances include a stop-and-go movement pattern, where balance is likely to significantly influence the efficacy of the directional change. In other words, because of inertia, body segments tend to maintain the direction of the movement, whereas balance ability ensures stability for positioning and a subsequent change of direction. However, studies on the influence of balance on different agility performances are scarce.

As evident from previous short literature overviews, studies conducted so far noted differential influence of the speed and power on different agility manifestations in men and women. More precisely, power and speed are not evidenced as strong predictors of the agility in trained men (17,25,38), but investigators noted higher correlations between speed and power in relation to agility among women (22,23).

The aim of this study was to evaluate the gender-specific influence of running speed, power, and balance on different agility manifestations in physically active young adults (college-aged athletes). Apart from the fact that systematic investigations of the influence of balance qualities on agility are rare, there is also an evident lack of studies on the relationships between different possible predictors (e.g., power, speed, and balance) on agility manifestations among male and female subjects of advanced fitness status (e.g., collegiate-level athletes).


Experimental Approach to the Problem

Speed, power, and balance are suggested to be important predictors of agility. However, most of the studies performed so far have either considered the relationship between only one of the mentioned predictors and agility or sampled highly diverse subjects (from low fitness to highly trained examinees). Additionally, we have found no study that investigated the gender-specific influence of balance on agility performance. Therefore, we tested college-aged athletes of both sexes for speed, power, and balance measures (predictors—independent variables), tested their agility performance (criteria—dependent variables), defined the reliability of the agility tests, and related their achievement of the predictors to their agility performance using linear correlation and multiple regression analysis. We deemed as particularly important to study such relationships because of the eventual possible transfer of the changes in predictor variables on agility performance.

Although previous studies used simple correlation analysis to identify relationships between speed and power as predictors of agility, in this investigation, we additionally calculated multiple regression analysis between anthropometric variables, speed, balance, and power qualities (predictors) and agility measures (criteria). We thought that multiple regression will allow ranking the predictors of agility among studied independent variables, and therefore to explain the relations more specifically.


A total of 32 college-aged male (age 21.6 ± 2.1 years) and 31 college-aged female athletes (age 20.6 ± 2.1 years) participated in this study. Inclusion criteria for participation in this study were (a) no pending medical problems and (b) no ankle, knee, or back pathology within the preceding 2 months. All subjects were in good physical condition during the time of testing. All the participants had sufficient experience in the testing procedures performed in this study and were involved in soccer (40% men; 10% women), basketball (20% men and women), handball (15% men; 25% women), volleyball (5% men; 20% women), martial arts (5% men; 7% women), gymnastics and dance (2% men; 6% women), or other sports (13% men; 12% women). Although there are some differences in sports in which the subjects were involved, we believe that such discrepancies should not be judged as a possible confounding factor of the results. For example, men are more involved in soccer than women, but the possible influence of the sport-specific performance of soccer as agility sport (36) is most probably diminished by the fact that women are more involved in other sports, like volleyball and handball, where agility is considered as significant factor of performance also (7,33).

All the measurement procedures and potential risks were verbally explained to each participant before obtaining their written informed consent. The institutional ethical board was introduced to the testing methods and the complete experiment and gave written consent for the investigation.

Training History

All the subjects were involved in systematic sport training for at least 5 years. Before study, as a part of the regular training regime, subjects regularly participated in 6–10 training sessions per week, including strength training (20–30%) and endurance exercise (20–50%), and sport-specific exercise sessions (40–60% of all sessions performed weekly). In general, their strength training included free-weight and machine-based exercises that lasted 30–45 minutes on average, Most of the subjects (70%) participated in the endurance-based exercise, which lasted 30–60 minutes. Average training frequency for all subjects ranged from 6 to 10 training sessions per week, with an average of 7–8 sessions weekly.


Anthropometric variables were composed of body height (BH), body weight (BW), and the body mass index (BMI). Five agility tests were conducted, namely a t-test (T-TEST), zig-zag test (ZIG-ZAG), 20-yard shuttle test (20YARD), agility test with a 180-degree turn (T180), and a forward-backward running agility test (FWDBWD). Other tests included 1 jumping ability power test (squat jump, SQJ), 2 balance tests, including a measurement of the overall stability index (OSI) and the overall limit of stability score (LOS), and 2 running speed tests of a straight sprint for 10 and 20 m (S10 and S20, respectively). All the tests were performed indoors on a synthetic pitch in a volleyball gymnasium. The subjects performed the tests wearing their choice of running shoes (excluding the balance testing, which was completed barefoot). Subjects were asked to be properly hydrated and to have a proper prior sleep. Before the testing, the subjects completed a 15-minute warm-up, including jogging, lateral displacements, dynamic stretching, and light jumping. The first day of testing consisted of anthropometrics and the power and speed measurements. The second day was used for 2 of the agility tests (T-TEST and 20YARD), and the third day was used for balance and the other 3 agility tests. During the course of the testing, the subjects were asked to maintain their normal diet and to stop exercising. To account for diurnal variation in fitness abilities, all the tests were performed at the same time of the day (9–11 AM), and the testing was done during November.


The BH and BW were assessed using a Seca stadiometer and weighing scales (Seca Instruments Ltd., Hamburg, Germany). The BMI was calculated as a ratio of the BW (kg) and squared BH (m). The agility and running speed were measured using a Brower timing system (Brower Timing System, Salt Lake City, UT, USA). The SQJ was measured using the Optojump system, a dual-beam optical device that measures ground contact and flight time during a jump or series of jumps (Microgate, Bolzano, Italy) (26,27). Balance was measured using a Biodex Balance System,(BBS) (Biodex Medical Systems, Shirley, NY, USA).

Agility Tests

For the T-TEST, 4 cones were arranged in a T shape, with a cone placed 9.14 m from the starting cone and 2 additional cones placed 4.57 m from either side of the second cone. All of the times were recorded using an electronic timing gate (Brower timing system), with a height of 0.75 m and a width of 3 m, in line with the marked starting point. The subjects were asked to sprint forward 9.14 m from the start line to the first cone and touch the tip with their right hand, shuffle 4.57 m left to the second cone and touch the tip with their left hand, shuffle 9.14 m to the right to the third cone and touch the tip with their right hand, and shuffle 4.57 m back left to the middle cone and touch the tip with their left hand, before finally back pedaling to the start line. The timing began on a sound signal and stopped when the subject passed through timing gate on their return. The trials were deemed unsuccessful if the participants failed to touch a designated cone, crossed their legs while shuffling, or failed to face forward at all times. The time was measured in hundreds of seconds.

During the ZIG-ZAG test, the test course consisted of four 5-m sections set at 100° angles. The ZIG-ZAG test was chosen because it requires the acceleration, deceleration, and balance control facets of agility, and the familiarity of the subjects with the test and its relative simplicity also minimized learning effects. The timing began on a sound signal and stopped when the subject passed through timing gate. The time was measured in hundreds of seconds.

In the 20YARD test, the examinee started in a 3-point stance and ran 5 yards in one direction, 10 yards in the opposite direction, and then sprinted back to the starting point. This exercise tests lateral speed and coordination. The timing began on a sound signal and stopped when the subject passed through timing gate on their return. The time was measured in hundreds of seconds.

The T180 test required five 1-m lines. The first line was the starting line. At 6, 9, and 12 m from the starting line were turning lines, and the finish line was 18 m from the starting line. The subject started on a sound signal from a stationary standing start, ran toward the 9 m line, stepped on the line and made a 180° turn, ran in the opposite direction to the 6 m line, stepped on the line and made a 180° turn, ran in the opposite direction to the 12 m line, stepped on the line and made a 180° turn, ran in the opposite direction to the 9 m line, stepped on the line and made a 180° turn, and ran in the opposite direction to the finish (18 m) line. The timing began on a sound signal and stopped when the subject passed through timing gate on their return. The time was measured in hundreds of seconds.

The performance and measurement of the FWDBWD test was the same as in the T180 but without the 180° turns, meaning that the subject ran with their chest turned toward the finish line during the whole trial. The subjects ran from the start line to the 9 m line, ran backward to the 6 m line, forward to the 12 m line, backward to the 9 m line, and forward to the finish line. The subjects were not permitted to turn their heads or trunks during the trial.


The SQJ test began with the subject in a stance with 90° knee flexion, with the feet hip-width apart. The subject's hands remained on their hips throughout. From this static position (with no pre-stretching), the subject performed a quick upward vertical jump as high as possible.


The OSI is an index of the average tilt in degrees from the center of a platform. The higher the OSI numeric value, the greater the variability from horizontal positioning, that is, the greater the instability while balancing on the platform. Conversely, lower scores indicate greater stability. The stability testing was performed without footwear. The subjects were instructed to establish a foot position and a comfortable stance width that allowed them to maintain the most stable (leveled horizontally) position possible on the platform. The positions of the feet were recorded and marked with tape using coordinates on the platform's grid to ensure the same stance and, therefore, consistency during test items, as previously suggested (4). The subjects were instructed to maintain the most level position possible on the platform for the duration of the test. The subjects were required to maintain an upright posture while keeping their arms to their sides and looking straight ahead at a wall approximately 0.5 m away. The subjects were allowed 1 practice trial before the 3 test trials. Each testing trial lasted 20 seconds. The resistance level was set at number 2 on a scale ranging from 1 (least stable) to 8 (most stable).

The LOS is defined as the maximum angle that a person can incline from the upright position in any direction without falling or altering his or her base of support (13). The BBS facilitates a dynamic balance assessment by having subjects view a moving cursor and move their center of mass while on a moveable platform within their LOS. In other words, dynamic LOS testing using the BBS assesses how accurately and quickly subjects move their center of mass and regain their balance at a new point. The dynamic LOS was measured by requiring the subjects to move their center of gravity, while standing on a movable platform, to 8 targets indicated on the front screen in any direction, under their own control. Overall, the LOS score and the time required to complete the test were obtained using the BBS. The subjects were required to hit each target with a cursor and hold the cursor inside the flashing box for 0.25 seconds.

Running Speed

Two electronic timing gates were positioned 10 and 20 m from a predetermined starting line for the S10 and S20 tests. The subjects were instructed to begin with their preferred foot forward, placed on a line marked on the floor, and to run as quickly as possible along the 20-m distance from a stationary standing start. The times were recorded at 10 m (the first electronic timing gate) and 20 m (the second electronic timing gate). For all tests, subjects performed 3 trials with 3–4 minutes of pause between the trials (1 minute for balance tests), and the best trial was used for further analysis.

Statistical Analyses

Descriptive statistical parameters (mean and SD) were calculated for all the applied tests.

The average interitem correlation coefficients and Cronbach's alpha reliability coefficients were used to determine the intersubject reliability of the agility tests. The within-subject variation for each of the tests was determined by calculating the coefficient of variation. The reliability was calculated for the overall sample and separately for men and women. An analysis of variance (ANOVA) analysis for repeated measures and a Tukey post hoc test were used to detect any systematic bias between the individual trials (items) for each test.

The differences between men and women in all the applied tests were calculated using Student's t-test for independent samples.

Linear correlation analyses were applied to evidence (a) the intercorrelations among the agility tests and (b) the influence of power, speed, and balance (predictors) on the agility manifestations. Multiple regression analysis was done to determine the multivariate influence of the BH, BW, balance, speed, and power as predictors of agility. These analyses were conducted separately for men and women.

All the coefficients were considered significant at a 95% confidence level (p < 0.05). Statsoft's Statistica version 10.0 (Statsoft, Tulsa, OK, USA) was used for all analysis.


The reliability analysis demonstrated that all the agility tests were reliable. The Cronbach's alpha coefficients ranged from 0.83 to 0.96, the interitem correlation coefficients ranged from 0.66 to 0.90, and the coefficient of variation ranged from 0.05 to 0.09. The lowest reliability was found for the T180 test in women. Based on our results, the ZIG-ZAG test should be considered as the most reliable test of all the tests used in this study. Analysis of variance found significant systematic bias between trials for ZIG-ZAG (for men), T180, and T-TEST (for men and women). However, post hoc analysis found significant differences only between the first trial and the other 2 trials, whereas there was no significant difference between second and third trial in any of the agility tests.

Men performed better than women in all applied agility tests (Table 1), and differences were significant at p < 0.05.

Table 1:
Descriptive statistics, reliability coefficients, and t-test differences between men and women for the agility tests.*

All the agility tests were significantly intercorrelated when examined in the sample as a whole and when examined separately among men and women. According to the sum of the correlation coefficients, the FWDBWD should be considered as the most general, and therefore the most valid, agility test for both the genders (Table 2).

Table 2:
Intercorrelations of the agility tests.*

Men are significantly taller and heavier and performed better than women in sprinting and in SQJ (all at p < 0.05). Oppositely, women performed better (p < 0.05) in both balance tests (Table 3).

Table 3:
Descriptive statistics and t-test gender differences for anthropometrics, balance, power, and sprinting variables.*

Because the analysis of the differences using the t-test indicated significant differences (at p < 0.05) in all the measured variables between the genders (Table 3), we have calculated the correlations between the speed, power, and stability tests (predictors) and agility measures independently for women and men. The highest shared variance between speed and agility in both of the genders was found between the FWDBWD and S10 (60 and 66% of the common variance for men and women, respectively). The SQJ was significantly correlated to the FWDBWD and T-TEST only for women, with the small portion of the common variance explained (16 and 20%, respectively). In contrast, the balance measures were more significantly related to the agility performance among men (Table 4).

Table 4:
Pearson's correlation coefficients between balance, power, running speed, and agility performance among men (M) and women (F).*

Multiple regression analysis (Table 5) found significant multivariate relationships between selected predictors and several agility performances (note that BMI as an index calculated on a basis of BH and BW was not included in this analysis). The significant multiple correlations are found for FWDBWD (44 and 58% of the common variance for men and women, respectively), 20YARD (44 and 46% for men and women, respectively) and T-TEST (men exclusively; 45% of the common variance). Among women, speed and power are found to be significant predictors of the FWDBWD and 20YARD (β coefficients are significant at p < 0.05). Among men, speed contributes partially to FWDBWD achievement, LOS is partially related to performance in ZIG-ZAG, whereas partial relationship of both balance measures (LOS and OSI) reached statistical significance in the prediction of T-TEST.

Table 5:
Multiple regression results between anthropometric, running speed, power, and balance predictors, and agility criteria.*


The purpose of this study was to evaluate the relationship between speed, power, and balance to different agility manifestations in male and female collegiate athletes. A novel aspect of this investigation was the influence of balance on agility measures. Apart from the fact which we have that found agility tests as reliable and relatively stable, the results of this study demonstrate that (a) power and running speed are more significantly related to agility manifestations among female collegiate athletes than among their male peers, whereas (b) balance is found to be important predictor of the agility measures among men but not among women. Each of these findings is discussed in more details in the following texts.

The reliability of agility tests is regularly studied using a number of diverse methodological and statistical procedures. Most of the studies used a form of test-retest reliability analysis (1,9,21,31), whereas in others, the authors examine the interrater (trained vs. untrained rater) reliability (37), and therefore, their results are not comparable to ours. The authors who studied the reliability of agility tests using similar procedures as those presented here (e.g., multiple-trial measurements with calculations of the between- and within-subject variations in the test results) found somewhat higher (23) or similar (19,36) reliability parameters to those we have reported. Compared with the subjects tested in the current study (college athletes), soccer players (19,36) achieved on average 10–20% better scores in agility performance.

Although limited, previous studies are relatively consistent regarding the findings of the influence of power (explosive strength) on agility, and power is rarely found to be an important predictor of the capacity for quick changes of direction in trained men (17). Even studies in which the authors sampled only athletes who competed in sports involving sprints with changes of direction (i.e., the subjects had similar running techniques) (38) support the findings of the relatively low influence of power on agility measures. Those findings are in concordance with our results (note that the SQJ is not a significant predictor for any of the studied agility measures in men). Even multiple regression results support such discussion. In short, beta ponder of the SQJ did not reach the appropriate level of significance in any of the 5 calculated multiple regressions for men. A reasonable explanation for poor relationship between power and agility could be that the majority of the investigations (including this study) analyzed power using relatively rigid jumping forms (the squat jump and counter-movement jump, e.g.). In contrast, most of the agility measurement tests are rather complex and require a coordinated expression of the force of various lower limb muscles (3), which is often accompanied by synergistic muscular function of the torso and upper limbs.

The results we have found are supportive of the idea that speed should be considered as an important predictor of agility performance, which should be explained by the equal morphological and biochemical determinants of these 2 qualities (14). However, clear relationships between running speed and agility manifestations are not consistently found among trained men, and correlation coefficients ranged from low (0.27–0.32) (25) to moderate (0.52–0.58) (8,23). We believe that such differences in the obtained results may be partially explained by the differences in testing procedures. Most specifically, in the recent investigation where low correlation coefficients were reported (25), the authors used running speed tests that incorporated a track-and-field starting position (from the start block). This starting position almost certainly negatively influenced the running results and achievement of some of the subjects (e.g., soccer, handball, or basketball players), who were not familiar with such a specific testing technique. At the same time, those examinees likely performed well in the agility tests (see second paragraph of Discussion section where we compared our results on agility tests with those observed in soccer players), which altogether led to the low correlation between the speed and agility measures.

Balance is rarely studied in relation to agility, although authors have noted the necessity for an improvement in balance to improve agility performance (18,36) or recognized balance control as a facet of agility (14). The reason for an evident lack of studies addressing this problem may be because of the challenge of balance measurement. In short, balance testing requires relatively sophisticated, robust, and expensive equipment. Consequently, we consider the presented relationships between balance and agility here to be somewhat pioneering. The background of the balance influence on the agility performance should be found in the ability to accurately coordinate the timing and action strength of skeletal muscles (i.e., coordination), which is essential for both balance and agility (15). While both are modified by the physical structure of an athlete and may be affected by technique, balance, and agility, both rely heavily on the development of neuromuscular control. Of all the tests studied here, the influence of balance on agility in men was most pronounced in the T-TEST, followed by the ZIG-ZAG test. When analyzing those results, we have found one explanation to be potentially interesting. Briefly, of all the sampled agility tests, only during the ZIG-ZAG and T-TEST, the subjects perform lateral and semilateral movements and place their feet laterally (or semilaterally) during the pivot point(s). In these moments, the feet rotate, and because of the limited ankle and minimal knee lateral flexibility, stability is disrupted. Therefore, during such a performance, the influence of the balance ability is much more pronounced than in those tests where the examinee is able to compensate for disrupted stability by knee flexion (e.g., tests that primarily involve forward-backward running). In particular, it has been shown that higher stability can be achieved by leaning forward and lowering the center of gravity, thus allowing for more rapid changes in direction (32). As a consequence, the ability to make frequent changes in direction is related to the ability to maintain appropriate postural adjustments and, therefore, an appropriate ability to maintain balance. Therefore, it seems logical that the ability to adequately control both static and dynamic balance could be of profound importance for the successful execution of “agile” movements. This hypothesis could be illustrated by the motion pattern in the T-TEST. For success in this test, the ability to perform rapid accelerations and decelerations while moving forward and quick changes of movement from side to side are crucial. Because these actions cause frequent perturbations of the center of gravity, which require efficient neuromuscular control adaptations, one's ability to efficiently maintain static and dynamic balance may positively affect success in agility performance. These claims have been indirectly proven in some recent studies (6,12). Davlin (6) demonstrated that soccer players were superior to nonathletes in balance performance. Considering the recent findings of Mirkov et al. (20) that the most prominent advantage of soccer players over control subjects during the entire tested age (from 11 to 14 years) period appeared to be movement agility and coordination, one could conclude that this advantage could be related to their ability to more efficiently maintain balance.

In addition to discussed linear correlation results, the multiple regression shows additional findings regarding the hierarchy of the influence of different predictors on agility performance. Among men, selected predictors defined the smallest portion of the criteria variance when related to ZIG-ZAG and T180, although beta ponders' values evidenced significant partial influence of the LOS to ZIG-ZAG achievement in men. Therefore, and supportive to previous discussion of the linear correlation results, it seems that balance should be judged as the most important predictor of the agility performances when athletes perform lateral (T-TEST) or semilateral (ZIG-ZAG) quick changes of direction. At the same time, linear running speed is found to be only significant predictor of the FWDBWD performance, which directly supports previous considerations of strong influence of the speed on linear agility performance (14). Contrary to linear correlation analysis, where S10 and S20 were significantly related to 20YARD, in the multiple regression of the same variable, none of the studied variables was found to be significantly partially related to 20YARD among men, although multiple regression revealed significant multiple correlation. It seems reasonable to conclude that the influence of the studied predictors on such performance (20YARD is a test which requires linear running and crossover cutting) should be discussed in a more complex (i.e., latent) manner. Evidently, optimal motor structure for such agility manifestation in trained men includes running speed and advanced balance.

Contrary to men, where correlation coefficients between power and agility did not reach statistical significance, the relationship between SQJ as a predictor and 2 agility tests (T-TEST and FWDBWD) for women reached statistical significance. It is also evident throughout multiple regressions, where SQJ was found to be a significant predictor in 3 of 5 calculated analysis. Interestingly, similar findings of a significant relationship between power and agility are noted in one of the rare investigations of this issue among women (23). The slightly higher coefficient of the correlation found in that study (23) is most likely because the authors sampled highly diverse subjects who ranged from “low sport” to “college athletes.” Because calculations of the correlation coefficients rely on variance, both among the individuals within the sample and between the 2 variables (24,28,29), a higher numerical value of the correlation coefficient between power and agility should be expected from a more diverse sample population.

The correlations found previously when authors have studied relationships between running speed and agility among women showed a strong influence of running speed on agility performance (22,23). Significant correlations between speed and agility we have found herein support such findings.

Although linear correlation showed the highest correlations between speed and agility achievement on FWDBWD and 20YARD, on the basis of the multiple regression results, it is evident that both power and speed should be judged as equally important predictors of the FWDBWD and 20YARD agility among women. Consequently, for these tests, the optimal combination of motor qualities will include (a) running speed (which is logical since both tests comprised repeated linear running) and (b) high level of muscular power (most probably because of the necessity of repeated start in the turning points of the test). The influence of the power on agility manifestations in women is additionally supported in the multiple regression calculation where T-TEST was observed as a criterion variable. In short, in this particular case, SQJ was found to be a significant predictor of the agility, but the multiple correlation did not reach the appropriate level of significance most probably because of the low influence of other studied tests on this agility variable.

In this study, the relationship between balance and agility measures was higher in men than in women. Apparently, the women we have studied here had sufficient balance ability (i.e., their balance was better than that of the tested males, see Results), and their agility performance was primarily related to their power and speed capacities. Similarly to women and their power and speed capacities, those men who were more advanced in balance directly used that balance in agility manifestations. Although not studied systematically here, there is certainly a possibility that superior flexibility (i.e., ankle flexibility) in women (30) is one of the key elements for their dominance in balance performance, which has already been suggested (4). In short, gait balance is maintained by regulating the interactions between the center of mass and the base of support (16). Superior ankle flexibility (primarily in the sagittal plane) assures a wider base of support in all situations when balance is challenged (i.e., the feet do not rotate but are planted stably on the surface), assuring better stability.

Practical Applications

Despite the fact that the relationships we have calculated allow insights into associations but not into the causes and possible training effects, based on the results studied and discussed, we may emphasize some important findings and related practical considerations.

The most complex influence of the different athletic abilities is found for agility manifestations where combination of different movement patterns is evident (i.e., tests which comprise linear running, crossover cutting, side stepping, etc.). In those maneuvers, balance and speed seem to be equally important predictors of agility achievement.

Power should be observed as a better agility predictor in women than in men. This finding means that strength and conditioning specialists should be aware of the fact that improvements of power qualities could probably influence the agility performance of women of advanced fitness status (e.g., collegiate athletes). At the same time, the eventual positive transfer of power improvement to agility is questionable among their male peers

Our results showed a systematic influence of the running speed on the agility measures both in men and women. Therefore, improvements in running speed should be observed as potentially beneficial to agility. Because the running technique and physical capacities are equally important determinants of the sprinting results, both of these factors should be emphasized in strength and conditioning programs aimed at agility improvement.

As far as the authors are aware, this study is one of the first studies to investigate balance as a gender-specific predictor of different agility measures. The results support the previously reported hypothesis, which noted the potential importance of balance qualities for agility. Balance is found to be the most important predictor of lateral and semilateral (i.e., zig-zag) movements, especially among men. Although further analysis of the problem is necessary, it seems logical to conclude that balance training should be incorporated in training programs aimed at agility improvement, especially for male athletes of advanced speed and power status. In short, for those male subjects, further improvements in speed and power are unlikely, and balance training may be beneficial for agility improvement.


Support of the Ministry of Science, Education and Sport of Republic of Croatia (project No 315-1773397-3407) is gratefully acknowledged. The authors declare that they have no conflicts of interest relevant to the content of this manuscript. The results of this study do not constitute endorsement of the product by the authors or the National Strength and Conditioning Association.


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reliability; agility prediction; field-testing; performance

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