Effects of Arm Dominance and Decision Demands on Change of Direction Performance in Handball Players

There are diverse physiological, psychological, and cognitive skills which are necessary to fulfil the demands of a complex team sport. In this regard, some of the major skills required are the ability to accelerate, decelerate, and to change one’s direction swiftly and efficiently (e.g., David et al., 2018; Taylor et al., 2017). Such unilateral high-intensity movements have a crucial impact on the outcome of competitions (e.g., Nimphius et al., 2018). In team handball, fast change of direction movements are one of the most frequently observed individual actions during a game (Karcher and Buchheit, 2014; Pereira et al., 2018). Some previous studies have focused on such change of direction movements in handball (Massuça et al., 2014; Pereira et al., 2018; Wagner et al., 2019). However, it is unclear how the unilateral dominance in handball, i.e., use of mainly one arm for throwing and passing (Weber and Wegener, 2019), influences the ability of players to change the direction. We conducted a field study to investigate if there are any differences in speed during an orthogonal change of direction action between left and right independent of the arm dominance. With this assumption, we examined whether this is influenced by the reaction to a visual stimulus.

Change of direction is simply defined as the ability to alter the direction, speed, and the type of a movement. When such change of direction is due to a reaction to a specific stimulus, it is termed as agility (Haff and Tripplet, 2016). This distinction between a simple change of direction and agility is crucial, particularly in the context of team sports, because in team sports, agility is the foremost requirement for players (Young et al., 2021). In general, every change of direction is due to tactical reasons and is affected by cognitive variables (e.g., perception, anticipation, decision making). Young and Farrow (2006) described agility in their deterministic model as a multifactorial ability which is based on cognitive factors (visual scanning, anticipation, pattern recognition, knowledge) and the basic change of direction speed (technique aspects, sprinting speed, muscle qualities).

Change of direction is mainly accompanied by high force impact and thus, injuries are common (e.g., rupture of the anterior cruciate ligament, David et al., 2017). Therefore, a large body of research has focused on injury prevention while changing direction in cutting manoeuvres in the past (David et al., 2017; Kadlec and Gröger, 2020; Nimphius et al., 2018; Taylor et al., 2017). While there is some general research on health considerations, particularly in performance sports, it lacks in specificities. The evaluation of agility or simply the change of direction speed should be done under precise conditions because of the movement dimensions (e.g., forward, backward, lateral) which differ according to the sport being analysed (Sekulic et al., 2014). For instance, in rugby the change of direction is mainly done in y-shape-courses, while in handball, basketball or tennis, more stop-and-go movements occur. These stop-and-go movements often occur at zero velocity in the deceleration phase in which athletes stop completely (Sekulic et al., 2014). If we assume that these differences are only at the motoric level, it becomes clear that the different specific cognitive requirements of different sports influence agility. A study by Nimphius et al. (2018) further elaborates that the results of testing the agility or the ability to change direction are influenced by a variety of test dimensions like the length of the test, the number of direction changes or the run-up direction.

Previous research has described general position-specific demands in handball (Büchel et al., 2019; Manchado et al., 2013; Taylor et al., 2017), without considering individual technical-tactical skills. While agility is necessary in all phases of the game (defence, offense, transition, goalkeeping), high speed and tactical effective change of direction behaviours like cutting manoeuvres with the ball, particularly in attack, seem to be advantageous against the opponent. Despite the overall importance of successful change of direction on the outcome of the game (Nimphius et al., 2018), Pereira et al. (2018) have indicated that with regard to handball, this crucial topic remains unexplored with the role of functional unilateral dominance in handball conspicuously missing.

In practice, it seems useful for an attacking player to be unpredictable for the defender. This means that having the same abilities (speed) in all movement vectors (in handball in particular from left to right and right to left) is an asset for offensive players. However, we assume that due to the tactical demands, the handedness of players influences the change of direction speed. Therefore, cutting manoeuvres with the final movement in the direction of the throwing arm are made faster than manoeuvres with the final movement direction against the throwing arm.

Accordingly, we conducted a field study to, firstly, investigate the impact of the throwing arm dominance on the change of direction speed in two different movement vectors (right, left). Secondly, we investigated the impact of the reaction to a visual stimulus on the change of direction speed by comparing a simple change of direction with an agility task. We assumed that an additional cognitive demand (perceiving a visual direction stimulus) in a simple change of direction task (cutting manoeuvre with the ball after a run up on the left or the right back position) leads to a loss in the speed of the change of direction. This assumption was based on several existing results (Spasic et al., 2015). The aim of evaluating this again was to validate the previously-used experimental paradigms, and to evaluate if the assumed effect of the hand dominance of players can be found in planned and unplanned situations.

The three way interaction of the factors, gender, direction and decision shows no effect F(1, 38) = 0.63, p = 0.43, η²_partial = 0.01. Furthermore, no statistically significant interaction effect of gender and direction F(1, 38) = 0.30, p = 0.59, η²_partial= 0.01, gender and decision F(1, 38) = 0.89, p = 0.35, η²_partial = 0.02, and direction and decision, F(1, 38) = 1.03, p = 0.31, η²_partial= 0.02, could be found. The missing interactions and the significant main effect of the covariate gender, F(1, 38) = 7.66, p > 0.001, η²_partial = 0.16, confirms that men performed faster under all conditions (Table 1).

The factor decision showed a significant main effect, F(1, 38) = 7.92, p < 0.01, η²_partial = 0.17. In the planned action, participants reached a higher change of direction speed than in the unplanned action (Figure 3). Also, there was a significant main effect in the factor direction. The velocity to the throwing arm side was higher than against the throwing arm side, F(1, 38) = 33.93, p < 0.001, η²_partial = 0.47 (Figure 3).

Figure 3

The results of the current study confirm our assumption that a reaction to a visual stimulus (signal detection + decision) leads to a significant decrease in the change of direction speed. Primarily, we measured the direction differences between a cutting manoeuvre to the left and a cutting manoeuvre to the right, and found a significantly lower speed in movements against the direction of the throwing arm of participants (Figure 3).

The gender effect as a secondary result of our study was not surprising. The results of the faster changes of direction of male participants than female athletes could simply be explained by greater muscle mass of male compared to female participants (Karcher and Buchheit, 2014; Manchado et al., 2013). Interestingly, no interaction was found between the factor gender and the other experimental factors, thus, the effect of factor direction and the decision is also independent of the gender.

Independent of this covariate, in our study, we could replicate the finding that additional cognitive requirements reduce the speed in the change of direction. With these findings, we verified the results of different experimental approaches (Nimphius et al., 2018; Spasic et al., 2015). Thus, our results are not novel, but are now validated in a new experimental setting. This could be due to the time limitation for spatial perceptions for positioning the body parts in the movement in a way that a deceleration with subsequent acceleration cannot be performed in a biomechanically optimal way. Also, the action of vision could affect the focus for movement execution. This could make movement execution more challenging based on the coordinative abilities. Additionally, it is possible that participants were uncertain about the correctness of their decision and therefore, unconsciously performed the action at a slower speed. This could result in a longer contact time during the stop-and-go phase of the movements or shorter distances during the change of direction due to lower force development. Nevertheless, we think that the speed differences between planned and unplanned cutting manoeuvres could be seen as a potential for the development of playing performances. We expect that the influence of additional cognitive demand, which is always a part of the game, cannot completely be removed, but players should be trained in a way that they could handle the visual and decision-making demands of the game to improve their performance in unplanned and open game situations. Several studies have indicated that agility abilities (change of direction in response to a stimulus) could be trained and developed (Paul et al., 2016). In particular, smallsided games seem to be effective to develop specific agility performances and are superior in just training change of directions without decision-making components (Paul et al., 2016). It should be further investigated in line with a cognitive-perceptual expertise approach (Williams and Ericsson, 2005) if experts could better handle the additional visual and decision demands than less experienced players.

The result of the higher change of direction speed on the side of the throwing arm could be based on several reasons. First, we expected a technical-coordinative aspect. Getting in an optimal throwing position which allows a rotation of the body-segments to get an optimal acceleration of the ball (Wagner et al., 2012), after the change of direction in the direction of the throwing arm is easier than in another one. If the cutting manoeuvre is performed against the direction of the throwing arm additional to the step combination (due to the rules a maximum of three steps are allowed) a (opposite) body rotation after the throwing movement is necessary to get in an optimal throwing position. We expected that this additional demand could lead to a slower execution of the preparation movement of the throw, the cutting manoeuvre. Furthermore, we expected that simple reasons of athleticism could affect the differences between the two movement directions. If the cutting manoeuvre in the direction of the throwing arm is easier, it is more likely to be used. Thus, we expected that frequency effects had an impact on the power development in a way that experienced handball athletes could have higher deceleration and acceleration abilities in the direction of their throwing arm. If cutting manoeuvres in one direction are more likely, we would expect that motivation could also influence the speed.

Thus, it would be useful for further research to examine if the determined pattern of results is affected by firstly, expertise, secondly, athleticism (e.g., power, coordination), and thirdly, motivation. Independent of the reason for the direction effect on movement speed, coaches could focus on technical or athletic exercises to develop balanced agility abilities. Athletes who could perform the specific cuttings in both directions with nearly similar speed, might be superior because they can act more unpredictably. Nevertheless, it has to be evaluated in further intervention studies if complete balancing of the vector depending movement speed is possible or restricted by the sport specific unliteral dominance (in team handball the handedness).

The main aim of this study was to test the change of direction movement in a specific situation with utilisation focused measures. Therefore, we suggest further adaptations of the experimental setting with a test environment being as realistic as possible (Nimphius et al., 2018). For example, the air body could be replaced by a (passive) defender, the direction stimuli could be modified (e.g., defender steps to the left or the right side), and speed measurement could be simplified via local positioning systems, a radar or light barriers.

Our study shows that in cutting manoeuvres, the movement to the direction of the throwing arm could be performed with higher speed than the movement in the direction against the throwing arm. This could be based on expertise, athleticism or motivation. The additional cognitive task (reaction to a stimuli) could affect the time needed for orienting and positioning the limbs and thus, could have lower velocities as a result. Against the general criticism on measuring the change of direction speed under unspecific conditions (Nimphius et al., 2018), our study represents results in specific spatially executed cutting manoeuvres. While our study lacks in specificity due to the visual-perceptual stimuli (signal detection of a light) and further research is needed, we expect that our experimental design can help coaches test and develop the potential of their athletes. In cutting manoeuvres, the fluid transition between deceleration and subsequent acceleration in the new direction should be trained at the cognitive and motoric levels. Especially, from a technical point of view, there still seems to be a potential for development in the movement in the direction against the throwing arm side.