It is crucial for athletes to be able to anticipate an opponent’s next move in a game setting (Loffing, & Cañal-Bruland, 2017; Smeeton et al., 2019; Williams, & Jackson, 2019). In order to anticipate the intention of a movement, collection of information is vital (Smeeton et al., 2019). In team sports, athletes receive such information from their opponents’ body language, which allows them to thereby draw conclusions about the opponent’s intention (Frith & Frith, 2006). Several studies have investigated the gaze behavior of athletes in basketball in laboratory settings (e.g., Klostermann et al., 2018; van Maarseveen & Oudejans, 2018), however, so far, little is known about the on-field gaze behavior of the defensive players. In fact, it is unclear whether coaching instructions are given on a defender’s gaze strategy or not, and if so, to what extent are they implemented. Thus, this study was conducted to evaluate the on-field gaze behavior of basketball players on two levels of expertise of defending in a one-on-one play in basketball and compare the results with coaching instructions from expert coaches.
Studies across the spectrum of sports have demonstrated that watching movements in opponents which are known and practiced during training, can lead to the observer becoming more active and ready for the given task (Aglioti et al., 2008; Cross et al., 2006; Fadiga et al., 2005). It has, therefore, been argued that experienced players are able to focus on information relevant to the task in a much better way than novices. This process is described as the information-reduction hypothesis (Haider & Frensch, 1996). The underlying principle here is that people are able to learn to differentiate between task-relevant and task-redundant information, a point that has also been evidenced by various studies on anticipation (e.g., Loffing, & Cañal-Bruland, 2017; Ward & Williams, 2003; Williams et al., 2004, 2009). An explanation of how information reduction works while watching well-known movements, could be a higher level of confidence (Nodine et al., 2002). According to Powers (2005), human actions are enabled by perceived differences between the desired outcome of a situation (e.g., correctly anticipating an opponent’s movement) and the final decision (execution of action). While approaching the decision to take action, novices tend to show lower levels of confidence, therefore, allocating more temporal resources for re-examining the task procedure. Consequently, novices tend to have shorter fixations as the eye is constantly moving and thus, they are unable to process the relevant cues for the task (Mann et al., 2007). In contrast, experts are able to not only extract more information from each fixation, but also condense the amount of information they need to process because they are more confident in the information collected. As a result, the speed of information processing increases and time for task completion is reduced (Mann et al., 2007).
The greater ability of experts to anticipate actions in sports (Cross et al., 2006; Fadiga et al., 2005) is, therefore, not only based on motor expertise in specific movements (Aglioti et al., 2008; Cañal-Bruland et al., 2010), but also on perceptual expertise (Brault et al., 2012; Dicks et al., 2010; Henry et al., 2012; Wright & Jackson, 2014). Both, visual and motor experience, and expertise contribute to the visual analysis of human movement (Loula et al., 2005).
Researchers have observed intra- and interindividual differences with regard to visual information collection along with variations in gaze behavior depending on the function of the demands of the task (e.g., Hüttermann, Helsen, et al., 2018; Williams et al., 2004). However, previous studies generally agree that efficient information collection requires athletes’ visual attention, by directing their gaze to the task-relevant areas (Loffing & Cañal-Bruland, 2017). In basketball, Sebanz and Shiffrar (2009) have exhibited the superiority of experts over novices in detecting pass fakes in a video-based study. Findings from other empirical studies show that expert basketball players identify key points better (Mann et al., 2007; Sebanz & Shiffrar, 2009). Based on this finding, conclusions about the location of the relevant areas could be drawn from the experts’ gaze fixations.
Studies across various sports have been carried out with the aim of finding the body areas which could provide relevant information for anticipating an opponent’s actions (e.g., Huys et al., 2008; Williams et al., 2009). Even though this research area remains practically unexplored for the defensive plays in basketball, general work in the field of perceptual anticipation have indicated various results on how information is gathered (for review see, Müller & Abernethy, 2012). The first indications can be found in tennis studies which suggest that the relative motions of the trunk to the hip may be used to anticipate the subsequent movement (Fukuhara et al., 2017; Hodges et al., 2005). More distal information could then be used to confirm the anticipation based on proximal cues (Fukuhara et al., 2017; Hayes et al., 2007; Hodges et al., 2005; Ward et al., 2002). Causer et al. (2017) suggest that experts might not necessarily need relative movement between body parts to accurately predict the resulting action. Deriving from these studies in tennis, and in accordance with the information reduction hypothesis, specific predictions for gaze strategies might suggest looking at motion-specific task-relevant partial movements.
The use of eye-tracking systems has been the commonly used method to evaluate gaze behavior in sports in the last few decades (for reviews see, Hüttermann, Noël, & Memmert, 2018; Kredel et al., 2017). In field studies, participants usually wear mobile eye-tracking devices to measure their gaze behavior while in action. Most eye-tracking studies in basketball have been conducted in free throw situations (Klostermann et al., 2018; Rienhoff et al., 2015; Wilson & Vine, 2009; Zwierko et al., 2018) or investigate the different gaze behaviors of the shooter without the influence of a defender (de Oliveira et al., 2008; Klostermann et al., 2018; van Maarseveen & Oudejans, 2018; Vickers, 2016). Movement-specific differences occur in the results based on how long or where the final fixation onset needs to be. A common verdict of studies on shooting actions indicates that the crucial predictor for subsequent performance is the final fixation of the shooter (Vickers, 2016). Quiet eye is seen as a possible explanation in the gaze analysis literature for the improved performance (Hüttermann, Noël, & Memmert, 2018; Vickers, 2007, 2016). Quiet eye is defined as the final fixation within 3° (or less) of the visual angle for at least 100 ms on a specific location in the context of the task. The onset occurs prior to the critical movement initiation and the offset occurs when the gaze deviates from the location or target by more than 3° for more than 100 ms (Vickers, 2007, 2016). It has been shown that a long quiet eye can be a reliable distinction between elite and nonelite performers, and between successful and unsuccessful motor performances (Vickers, 2016). Quiet eye is well investigated in standardized game situations, like soccer penalty kicks (e.g., Piras & Vickers, 2011), gun shooting (e.g., Causer et al., 2010), or basketball free throw (e.g., Vickers, 1996). However, it has remained largely neglected in free, highly dynamic actions in the field. According to the review by Hüttermann, Noël, and Memmert (2018), only 8% of eye-tracking analyses were conducted in the field, which included none from the defensive perspective, suggesting that the expert gaze strategies remain largely unclear in many sports.
Only a few studies have investigated the influence of a defender on the general gaze strategy of the attacker (Klostermann et al., 2018; van Maarseveen & Oudejans, 2018). The findings of these studies have shown that the defender is a relevant restricting factor for an attacker in basketball shooting situations, as it negatively influences shooting accuracy compared with a situation without a defender. The presence of the defender causes a shortened final fixation and subsequently, an impairing of the gaze strategy of the attacker. Broadly speaking, existing research concludes that different gaze strategies of attackers (e.g., quiet eye) have a significant impact on performance. In effect, the current state of research neglects the defender’s gaze strategy and thus, creates the need to examine defensive gaze behavior in basketball.
According to Dicks et al. (2009), a drawback of many research studies has been the inaccurate reconstruction of the performance environments which the athletes experience in real game situations. Existing literature using experimental paradigms of video simulation indicates that athletes’ perceptual and decision-making strategies vary depending on the task (for reviews see, Gegenfurtner et al., 2011; Mann et al., 2007). In line with kinematic specification of dynamics principle, this seems to be based on the differences in location and sequence of the relevant kinematic information within the observed movement (Runeson & Frykholm, 1983). The task used to study perception and action should, therefore, accurately reflect the specific performance contexts of the sport. Johnston et al. (2018) stated that representative study designs increase the chances of finding variables that have a predictive value for top athletes. Our study was, therefore, carried out with a field experiment to ensure the representativeness and practical application. In the process, applicable indicators of the perceptual strategies underlying defensive behavior in real games were identified.
In summary, the existing research has delivered insights on experts’ gaze strategy and eye tracking in basketball; however, any specific findings about the defender’s gaze behavior in basketball is still missing. For this reason, we carried out an initial exploratory study on this subject. First, expert coaches provided input for the methodology, information on the current coaching doctrine on gaze strategy in practice, and the horizon of expectation. In a field experiment, we then examined the gaze behavior of a defender in a one-on-one situation in basketball. The aim was to highlight the differences between experts and novices in order to gain insights on their respective gaze strategies. Thus, the distribution of gaze fixation areas for different phases of the one-on-one play were evaluated.
The research questions of whether and how the gaze behavior of experts differs from coaching instructions and less skilled players are investigated in this study. We assumed that the coaches have a common guideline for the gaze behavior of a defender which is largely based on the hypothesis that the visual attention should be directed to the areas with the relevant kinematic information (e.g., Loffing & Cañal-Bruland, 2017). In line with the literature, it is assumed that participants’ gaze strategies vary in the different phases of the one-on-one action (e.g., Gegenfurtner et al., 2011, Hüttermann, Helsen, et al., 2018). Furthermore, differences in gaze behavior are expected between experts and novices; although, it is unclear to what extent with regard to gaze zone and sequence phase (e.g., Mann et al., 2007; Wright & Jackson, 2014).
Study
The study was structured in two stages. Qualitative practical input from the expert coaches, supplemented by a quantitative analysis of gaze behavior provided a valuable methodological evaluation. First, the expert coaches were interviewed through a written questionnaire to provide reference values from practice. In line with their answers, the potential gaze areas as well as trial sequences were subdivided for later analysis. In the second part, a field experiment was conducted to generate data on the gaze behavior of a defender in basketball. Thereafter, the data were examined based on the parameters defined by the expert coaches and the final results were compared with the statements by the expert coaches.
Method
Sample Size Estimation
Based on previous research examining the on-field gaze behavior in basketball (van Maarseveen & Oudejans, 2018 [n = 13 females]; Klostermann et al., 2018 [n = 15 males and eight females]), a total sample size of 18 (nine per expertise group) was calculated using G*Power (Heinrich-Heine-Universität, Düsseldorf; Faul et al., 2009). This calculation was based on the main effect of expertise on the gaze behavior in these previous studies to achieve a power of 0.95, having a mean effect size (η2) of .453, and an α value of .05.
Participants and Design
Qualitative Interview
Four expert basketball coaches (Mage = 48.75, SD = 10.00 years, male, experience: M = 20.00, SD = 8.72 years) were interviewed using a written questionnaire prior to the experiment. Because the coaches were included in the development and analysis of a scientific study design, all the interviewed coaches had a sports science degree (Diploma or PhD) and were the highest licensed coaches working on the national level in Germany (ProB, BBL, and national/federation coach).
Field Experiment
A total of 32 subjects were evenly split in two groups (experts vs. novices). All participating subjects in the expert group were members of a German Bundesliga team (Mage = 24.44, SD = 2.48 years, four females, experience: M = 9.12 years, SD = 2.63 years). Furthermore, all the expert subjects confirmed that they had received visual guidelines from coaches during their training. The expert coaches did not coach or advise any of the participants beforehand at all.
The novice group were less-skilled, inexperienced players who had a general understanding of the game, but never had any professional basketball training or club-level playing experience (Mage = 20.25, SD = 1.24 years, four females). In order to offset anomalies among the novice players due to discrepancies in fitness level, sports science students were selected.
The study was carried out in accordance with the Declaration of Helsinki, 1975 and written informed consent was obtained from each participant prior to testing. Approval was obtained from the German Sport University’s Ethics Commission (no. 041/2017).
Materials and Procedure
Qualitative Interview
In compliance with the qualitative research literature, the written interviews (see Table 1 for full questionnaire and responses) of the four expert coaches followed the same open question protocol (e.g., Alcaraz-Rodríguez et al., 2018). The interviewees were asked whether they instruct gaze behavior strategies in practice to the players or not and if so, which specific strategies did they usually recommend. Moreover, they were asked where, in their opinion, the main gaze fixation point should be located overall and specifically, in relation to potential different phases of the observation. Finally, the coaches were asked if they thought that there might be differences in gaze behavior between experts and novices and if so, what might those differences be.
Full Answers From the Four Expert Coaches to the Questions of the Written Interviews on the Topics Coaching Instructions (Q1), Fixation Expectation Overall (Q2) and per One-on-One Phase (Q3), and Expectation Differences in Fixation Between Expertise Groups (Q4)
| Responder | Q1: | Q2: | Q3: | Q4: |
|---|---|---|---|---|
| Do you give instructions in the training regarding gaze behavior and if so which ones? | In your opinion, what is the main fixation point in the gaze behavior of the test persons (group of experts), taking into account the test setup described? | Divide the one-on-one game into different phases. What is your prognosis with regard to eye behavior for the individual phases (group of experts)? | Do you think that there are differences in gaze behavior between novices and experts? | |
| Coach 1 | - Yes, focus on shoulder axis and peripheral motion perception | - Floor - Ball | - Receiving the ball: Ball - Dribbling: Ball/torso - Shooting: Ball | - Differences yes. - Novices are more focused on the ball and maybe the feet.a |
| Coach 2 | - Yes, to ignore feints (shot fake get closer and jab step back) while training peripheral perception and fixating hip/torso | - Ball and torso/navel | - Ball receiving: Upper body/ball - Dribbling: Ball - Shooting: Ball | - Yes, strong but I cannot say anything about the exact differences. |
| Coach 3 | - Yes, navel | - Ball | - Receiving the ball: Ball - Dribbling: Ball - Shooting: Ball/shoulder girdle to sternum | - Yes, novices will be more ball oriented and let the gaze wander, experts will have more of a soft look resting with the eye and take actions peripheral.a |
| Coach 4 | - Yes, but only if the athlete has obvious difficulties to anticipate. Then recommendation navel to avoid feints | - Rather soft look - Very peripheral perception | - Receiving the ball: Ball - Dribbling: Body - Shooting: Ball | - Yes, but not clear where to go. |
aInitial discrepancy between the two independent experts/raters, resolved unanimously.
Field Experiment
To determine the gaze behavior of the defender, the test setup was developed similar to the one in a study by van Maarseveen and Oudejans (2018). An eye tracker from Senso Motorik Instruments was used in line with previously conducted field experiments in basketball (van Maarseveen & Oudejans, 2018). Prior to the experiment, a three-point calibration was carried out, ensuring reliability by uniformly using the same dimensions for all the subjects. While standing at the free throw line, the subjects had to look sequentially at the top left corner of the backboard, the center of the front ring and the top right corner of the backboard. Two external cameras were positioned to capture both the attacker and the defender along with the complete playing field. The first camera (Camera 1) was placed in the center circle and covered the area from the attacker’s point of view. The second camera (Camera 2) was positioned under the basket with a distance of 2 m to the baseline to avoid injuries. Here, the entire width of the playing field was recorded from the defender’s point of view (Figure 1).
—Graphic display of the field experiment setup. Note. The defender (D) started each trial with a bounce pass to the attacker (A).
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Graphic display of the field experiment setup. Note. The defender (D) started each trial with a bounce pass to the attacker (A).
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Graphic display of the field experiment setup. Note. The defender (D) started each trial with a bounce pass to the attacker (A).
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
Consistent with the approach detailed by Carter et al. (2005) and Ramos Campo et al. (2014), the positions in male and female basketball are not only differentiated by their current positioning on the field, but also by the players’ heights, technical abilities, and trained position. Therefore, in the experiment, the subjects were only defending against players with similar parameters including the same gender, handedness, playing level, trained playing position (for experts), and a maximum height difference of 5 cm (Carter et al., 2005; Ramos Campo et al., 2014). Following the experiment setup by van Maarseveen and Oudejans (2018), the attacker always started at the same position, from the top of the three-point line (top of the key) on the midline (the imaginary line that divides the basketball court in half from rim to rim), facing the basket. The subjects were tested in 15 trials, defending in a one-on-one play with the same initial positions. The defender started at the free throw line and played a fast and precise bounce pass into the hands of the attacker, followed by a close out. This ensured that the defender was in a frontal defensive position without predefining any side in the beginning. In each trial, the attacker was free to move in any direction, but was limited to three allowed dribbles. The trial ended with the first shot attempt.
Data Analysis
Qualitative Interview
A sports scientist (independent expert/Rater 1: 28-year-old, male, M.Sc. Sports Science) conducted a qualitative content analysis (QCA) of the transcripts from the written interviews using the inductive category development (Mayring, 2014). The procedure was further validated by an independent basketball expert with a scientific expertise, who was not involved further in this study (independent expert/Rater 2: 35-year-old, female, official licensed Basketball Coach, with coaching experience of 20 years, PhD Sports Science). The QCA identified the following categories: fixation description, further gaze specifications, justification, condition, open answer, and decision. Table 2 shows the results of the QCA for the four questions (Q1–Q4) analyzed according to the six general categories as mentioned above. Subsequently, the four expert coaches defined and divided the gaze fixation location of the defender into four zones—ball, head, feet, and torso (Figure 2). These gaze zones were consistent with Ward et al. (2002) and Causer et al. (2017). In addition, the coaches subdivided the one-on-one play sequence into three phases in the third question (Q3): receiving phase (Q3.1), dribbling phase (Q3.2), and shooting phase (Q3.3).
Results of the Qualitative Content Analysis of Written Interviews With Four Expert Coaches on the Topics Coaching Instructions (Q1), Fixation Expectation Overall (Q2), Fixation Expectation for Different One-on-One Phases (Q3), and Expectation Differences in Fixation Between Expertise Groups (Q4)
| Total entries,a n = 46 | Average entries per expert coach,b M (SD) | Relative occurrence of the code | |
|---|---|---|---|
| Question: Topic | |||
| Q1: Coaching instructions | 13 | 3.25 (0.40) | 28.26% |
| Fixation description | 4 | 1.00 (0.00) | 30.77% |
| Other gaze specifications | 2 | 0.50 (0.58) | 15.39% |
| Justification | 2 | 0.50 (0.58) | 15.39% |
| Condition | 1 | 0.25 (0.50) | 7.69% |
| Decision | 4 | 1.00 (0.00) | 30.77% |
| Q2: Fixation expectation overall | 6 | 1.50 (0.50) | 13.04% |
| Fixation description | 5 | 1.25 (0.50) | 83.33% |
| Other gaze specifications | 1 | 0.25 (0.50) | 16.67% |
| Q3.1: Fixation expectation receiving phase | 5 | 1.25 (0.51) | 10.87% |
| Fixation description | 5 | 1.25 (0.50) | 100% |
| Q3.2: Fixation expectation dribbling phase | 5 | 1.25 (0.51) | 10.87% |
| Fixation description | 5 | 1.25 (0.50) | 100% |
| Q3.3: Fixation expectation shooting phase | 5 | 1.25 (0.51) | 10.87% |
| Fixation description | 5 | 1.25 (0.50) | 100% |
| Q4: Expectations expertise differences | 12 | 3.00 (1.41) | 26.09% |
| Fixation description | 3c | 0.75 (0.50) | 25.00% |
| Other gaze specifications | 2 | 0.50 (0.58) | 16.67% |
| Justification | 1d | 0.25 (0.50) | 8.33% |
| Open answer | 2 | 0.50 (0.58) | 16.67% |
| Decision | 4 | 1.00 (0.00) | 33.33% |
aThe individual entries refer to the total quantity of coded segments. Multiple entries per coach were possible within a category. bThe average values referred to the sample size of four expert coaches. cInitial discrepancy to expert/Rater 2, who assigned two answers to this category. dInitial discrepancy to expert/Rater 2, who assigned no answer to this category.
—Graphic display of the gaze zones used for analysis.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Graphic display of the gaze zones used for analysis.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Graphic display of the gaze zones used for analysis.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
Cohen’s κ was calculated to assess interrater reliability (Cohen, 1960). Calculated for the two independent experts/raters on 36 cases (six questions with six categories each), Cohen’s κ revealed a high degree of compliance with a ratio of 90.8% (κ = .908, z = 9.57, p < .001) compliant with Altman (1990). Aspects that were rated differently associated exclusively to the last question and were discussed between the two independent experts/raters, resolved unanimously, and were eventually rated the same as Rater 1 in both the disputed cases (Table 2). Disagreements in the initial rating were marked in Tables 1 and 2.
Field Experiment
A German licensed basketball coach (30-year-old, male, with coaching experience of 7 years) evaluated the gaze behavior in a post hoc frame-by-frame analysis based on the Senso Motorik Instruments output file using video analysis software Kinovea (version 0.8.15; Kinovea, Bordeaux, France). The post hoc frame-by-frame analysis in highly dynamic situations has been applied widely in recent research (Fasold et al., 2018, 2021; Klatt, Noël, Nicklas, et al., 2021; Klatt, Noël, Schwarting, et al., 2021). Following the approach by Mavridis et al. (2006), the time stamps of the camera captures were used for post hoc evaluation of the time length of the three individual phases during the one-on-one play. The evaluation was further validated by a second basketball expert with a scientific expertise (53-year-old, male, official licensed basketball coach, with coaching experience of more than 20 years, PhD sports science). In conformity with van Maarseveen and Oudejans (2018), the video recording showed projected fixation areas with a minimum of 100 ms (Figure 3). Cohen’s κ was calculated to assess intraobserver reliability (Cohen, 1960). Calculated for two examination runs on 128 cases (32 subjects with four gaze zones each), Cohen’s κ revealed a high degree of compliance with a ratio of 83.1% (κ = .831, z = 37.9, p < .001), in line with Altman (1990).
—Example Senso Motorik Instruments output file: A defender’s field of vision with fixation point (white circle) while looking at the attacker (player with ball) during the experiment.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Example Senso Motorik Instruments output file: A defender’s field of vision with fixation point (white circle) while looking at the attacker (player with ball) during the experiment.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Example Senso Motorik Instruments output file: A defender’s field of vision with fixation point (white circle) while looking at the attacker (player with ball) during the experiment.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
Relative fixation times (RFT) were used with reference to the total time of a sequence phase, congruent with previous eye-tracking research (Beitlich et al., 2014; Pinhas et al., 2014). The RFT were calculated by dividing the fixation times by the total sequence time and included only fixations >100 ms, compatible with existing studies conducted with eye tracking (for a review see, Lebeau et al., 2016). This ensured comparability for the individual one-on-one play sequences since the sequence lengths could have deviated greatly depending on the playing level and attacker behavior. The RFTs were not in relation to a movement or decision task, as would be the case in a quiet eye study. To eliminate erroneous eye-tracker recordings based on a drift in the calibration, which could have been caused by greater contact, the eye tracker was recalibrated. An observation sheet was developed to record the relative distribution of the fixation areas and assign the respective gaze zones (ball, head, feet, and torso), and sequence phases (reception, dribbling, and shooting).
For statistical analysis, the effects of the independent variables, gaze zone (head, ball, feet, and torso) and sequence phase (receiving phase, dribbling phase, and shooting phase) on the dependent variable, fixations (RFT) were calculated in a repeated-measures analysis of variance with the between-subject factor expertise (experts vs. novices). Post hoc analyses (independent t test, Bonferroni corrected) were used to evaluate potential differences. The standard error was, as usual, accounted for in this work, because our interest was in comparisons between expertise groups (Lyden et al., 2012). The precision of the mean distribution of gaze behavior from each individual subject was, thereby, evaluated. Effect sizes of the interaction and main effects were calculated in η2 and evaluated according to Cohen (1988). Effect sizes of the post hoc tests were calculated in Cohen’s d and evaluated according to Cohen (1988).
Results
Qualitative Interview
The empirical gaze data collected in the field experiment was preceded by the qualitative interviews. The QCA results are presented here. All four expert coaches explicitly confirmed that they were giving instructions for the gaze behavior of a defender as part of their training program. All the coaches confirmed that the focus of the gaze should be on the gaze zone—torso, with different intrazone locations being indicated. Here, the overall “torso,” the “sternum,” the “belly button,” and the “hip” were each mentioned once in total. Two coaches stated that in addition to the fixation point, the peripheral perception is important for defending. The reasons for the taught gaze strategy were given twice, unanimously stating that the aim of such input would be to “avoid falling for fakes.” One coach noted a condition for giving gaze instruction, stating that coaching instructions were given if the athlete had “obvious problems anticipating.”
Furthermore, all the coaches indicated that they were not expecting the overall gaze strategy of the experts to always correspond to their coaching instructions; however, they did not elaborate further to why this might be the case. Next to fixations on the “torso” (one entry), the locations “ball” (three entries), and “floor” (one entry) were named.
With regard to the ball receiving phase, all experts agreed that the “ball” would be fixated on the most, while the “torso” was mentioned once. Assessing the main point of fixation during the dribbling phase, the expert coaches mentioned the “torso” twice and the “ball” three times. For the final shooting phase of the sequences, the “ball” was unanimously named to be the main fixation point. In addition, the “torso” was mentioned once. Interestingly, the “torso” was referred to once per phase as the expected fixation point, each time, by a different coach.
All the coaches unanimously expected differences between experts and novices regarding their gaze behavior. No statement on the exact differences was given twice, while three fixation differences were mentioned. According to the expert coaches, novices would tend to look more at the “ball” (two entries) and to the “feet” (one entry). Furthermore, two differences regarding other gaze characteristics were found. “More eye movement of the novices” and a “resting eye movement of the experts” were both mentioned once. A reason for the prediction was given once as: “peripheral perception is more often used by the experts.”
Field Experiment
The evaluation of the fixations revealed a significant three-way interaction for the factors gaze zone, sequence, and expertise with a moderate effect size, F(6, 180) = 2.020, p = .033, η2 = .063. For the receiving phase (Figure 4), post hoc analyses revealed that the novices fixated on the ball significantly (p = .014, d = 0.950) more often than experts (Mexp = 17.50%, SE = 7.71%; Mnov = 45.83%, SE = 7.71%). For the dribbling phase (Figure 5), post hoc analyses revealed that the experts fixated on the head significantly (p = .020, d = 0.900) more often than novices (Mexp = 56.03%, SE = 6.72%; Mnov = 32.61%, SE = 6.72%). Furthermore, novices fixated on the ball significantly (p = .001, d = 1.284) more often than experts (Mexp = 14.82%, SE = 6.12%; Mnov = 45.22%, SE = 6.12%). No significant differences were found with regard to the shooting phase (Figure 6).
—Comparison of average relative fixation percentage of the expertise groups (experts vs. novices) in the receiving phase for each gaze zone (head, ball, feet, and torso). *Significant difference between expertise groups (≤.05). +Significant differences between the gaze zones (≤.05). Error bars in SE.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Comparison of average relative fixation percentage of the expertise groups (experts vs. novices) in the receiving phase for each gaze zone (head, ball, feet, and torso). *Significant difference between expertise groups (≤.05). +Significant differences between the gaze zones (≤.05). Error bars in SE.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Comparison of average relative fixation percentage of the expertise groups (experts vs. novices) in the receiving phase for each gaze zone (head, ball, feet, and torso). *Significant difference between expertise groups (≤.05). +Significant differences between the gaze zones (≤.05). Error bars in SE.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Comparison of average relative fixation percentage of the expertise groups (experts vs. novices) in the dribbling phase for each gaze zone (head, ball, feet, and torso). *Significant difference between expertise groups (≤.05). +Significant differences between the gaze zones (≤.05). Error bars in SE.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Comparison of average relative fixation percentage of the expertise groups (experts vs. novices) in the dribbling phase for each gaze zone (head, ball, feet, and torso). *Significant difference between expertise groups (≤.05). +Significant differences between the gaze zones (≤.05). Error bars in SE.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Comparison of average relative fixation percentage of the expertise groups (experts vs. novices) in the dribbling phase for each gaze zone (head, ball, feet, and torso). *Significant difference between expertise groups (≤.05). +Significant differences between the gaze zones (≤.05). Error bars in SE.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Comparison of average relative fixation percentage of the expertise groups (experts vs. novices) in the shooting phase for each gaze zone (head, ball, feet, and torso). +Significant differences between the gaze zones (≤.05). Error bars in SE.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Comparison of average relative fixation percentage of the expertise groups (experts vs. novices) in the shooting phase for each gaze zone (head, ball, feet, and torso). +Significant differences between the gaze zones (≤.05). Error bars in SE.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Comparison of average relative fixation percentage of the expertise groups (experts vs. novices) in the shooting phase for each gaze zone (head, ball, feet, and torso). +Significant differences between the gaze zones (≤.05). Error bars in SE.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
A significant interaction effect of gaze zone and expertise was found (Figure 7), F(3, 90) = 7.848, p < .001, η2 = .207. Post hoc tests showed significantly (p = .018, d = 0.912) more fixations on the head by experts compared to novices (Mexp = 40.81%, SE = 5.11%; Mnov = 22.76%, SE = 5.11%). Furthermore, novices fixated significantly (p < .001, d = 1.436) more often on the ball than experts (Mexp = 41.41%, SE = 3.82%; Mnov = 62.63%, SE = 3.82%).
—Comparison of average relative fixation percentage of the expertise groups (experts vs. novices) in the entire sequence for each gaze zone (head, ball, feet, and torso). *Significant difference between expertise groups (≤.05). +Significant differences between the gaze zones (≤.05). Error bars in SE.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Comparison of average relative fixation percentage of the expertise groups (experts vs. novices) in the entire sequence for each gaze zone (head, ball, feet, and torso). *Significant difference between expertise groups (≤.05). +Significant differences between the gaze zones (≤.05). Error bars in SE.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
—Comparison of average relative fixation percentage of the expertise groups (experts vs. novices) in the entire sequence for each gaze zone (head, ball, feet, and torso). *Significant difference between expertise groups (≤.05). +Significant differences between the gaze zones (≤.05). Error bars in SE.
Citation: Journal of Sport & Exercise Psychology 44, 2; 10.1123/jsep.2021-0149
The interaction of sequence and gaze zone was also found to be significant, F(6, 180) = 47.578, p < .001, η2 = .613. The significant differences evaluated post hoc are illustrated for the receiving phase (Figure 4), the dribbling phase (Figure 5), and the shooting phase (Figure 6).
A significant main effect of the gaze zone was found with a large effect size, F(3, 90) = 59.118, p < .001, η2 = .663. The mean values and the post hoc evaluated significant differences between the gaze zones are presented in Figure 7.
Discussion
The results of this study reveal important findings with regard to the areas fixated on while defending in basketball. Broadly, the expert players mainly fixated on the head while the novices’ primary fixation focus was on the ball. The fixation frequency on the feet was very low (<1%) and therefore, negligible, while fixation frequency on the trunk was similar for both groups—around 20%. These findings were in great contrast to the coaching advice to look at the trunk of the opponent and not at the head or the ball. While the literature suggests that gaze behavior is trainable at least to a certain extent (Ryu et al., 2018; Wilson & Vine, 2018), the role of explicit and implicit learning sources in the development of expertise needs to be explored in greater detail in the future. The deviation of the test results from coaching instruction could, therefore, be due to a lack of appropriate coaching tools and time expenditure on developing the defender’s gaze behavior. A further reason could be a false narrative among coaches due to a lack of research on defenders’ gaze strategies. An investigation on the influence of the different gaze strategies on defensive performance, especially in anticipation tasks, should be conducted to provide evidence for future coaching doctrines on defensive gaze behavior.
Another aspect of the gaze behavior differences between the experts and the novices were the way their eyes moved. While the novices mainly focused their gaze on the ball, the experts concentrated their eyes mainly on the head of the opponent. However, since the head of the opponent was approximately at eye level due to the test setup, the eyes of the expert defender were much steadier. This explanation is in conformity with the findings of previously conducted studies, which found significantly calmer eye behavior, meaning longer and fewer fixations, and much earlier gaze fixation by the professional players in contrast to the novices (Lee, 2010; Millslagle et al., 2013).
Based on the statements by the expert coaches, experience could be the basis for the development of this strategy, while direct feedback could help players who subjectively have problems in anticipating their opponent’s movements. Interestingly, peripheral vision was mentioned multiple times by the coaches and, therefore, seems to be a factor in defense. According to the evaluation of the fixation behavior of the experts, the coaches assumed that the fixation on the opponent’s head functions as a visual center point allowing good peripheral vision of the entire action area of the attacker (e.g., Vater et al., 2020). Furthermore, these findings might also be a reflection of the gaze oriented toward the perception or relative motion information mentioned earlier (Fukuhara et al., 2017; Hodges et al., 2005).
Due to the setup of this study, the question which gaze areas were perceivable well in the peripheral vision while the defenders focused on the opponent’s head, could not be answered. Future research is necessary analyzing the maximum extension of the visual focus of attention in the visual periphery (cf. Hüttermann et al., 2013; Hüttermann, Memmert, & Liesner, 2014; Hüttermann & Memmert, 2017). These athletes’ statements within the current study, were in contrast to the existing assumption that efficient information gathering requires athletes’ visual attention by directing the gaze to the task-relevant areas (Gegenfurtner et al., 2011; Loffing & Cañal-Bruland, 2017). An explanation for the contradiction might be based on the different task objectives. While previous research indicated that anticipation of a single movement was improved by increased visual attention, generally defending in a multidirectional sport like basketball may require a broader attentional focus (Hüttermann et al., 2019; Petway et al., 2020; Taylor et al., 2017). In a game, an attacker has multiple options to proceed along with other attackers who may also intervene. Although the setup of this study did not include any additional attackers or defenders, the individually trained, and commonly used gaze strategy may have been utilized.
Regarding the different phases, the evidence provided by this study showed that experts kept their focus on the head during receiving and dribbling phase. During these phases, the attacking behavior was the most difficult to predict because the attacker had multiple options: immediately shoot the ball, or dribble, or perform a corresponding deception first. In a game, passing the ball would be an additional option. While the eyes and head orientation may provide relevant information about the offensive players’ intentions, it seems possible that the fixation location reflected a gaze “anchoring” strategy from which information for anticipation is extracted (Vater et al., 2020). In contrast to the receiving and dribbling phase, the focus shifted toward the ball when the attacker shot the ball. As mentioned earlier, differences in visual information collection and gaze strategy might be based on the task presented (e.g., Hüttermann, Memmert, & Simons, 2014; Hüttermann, Helsen, et al., 2018). In this case, the receiving and dribbling phases of the one-on-one situation may not have allowed for the participants to search for task-relevant areas; because, the defender had to anticipate the attacker’s intent with a variety of movement options given. Here, the gaze “anchoring” strategy with peripheral information gathering from different sources may have been the best option.
However, the shooting phase provided a single task with fewer range of motions by the attacker. Here, the visual attention may be directed to the task-relevant area in order to anticipate the movement based on specific kinematic sources of information (e.g., Ward & Williams, 2003). Interestingly, both experts and novices mainly fixated their gaze on the ball during the shooting phase, which provides no such information. In accordance with previous studies conducted on eye tracking in basketball, this last fixation may be most relevant for performance (e.g., Vickers, 2016).
Gaze strategies suggest that while information from foveal vision (e.g., the quiet eye) is important, visual information from the periphery also appears to be indispensable for decision making (Klostermann et al., 2020). The aim of this study, though, was to evaluate gaze behavior of elite players against the coaching instructions and of less skilled players’ in-game one-on-one defense in an open-play. How this gaze behavior affects the defensive anticipation performance cannot be answered by this study design, and needs to be further evaluated. However, our results can give an indication of the general gaze strategies and in-game information gathering (foveal vs. peripheral) of defenders.
Previous research indicates that the anticipation of the professional players in a game might be vulnerable to receiving information from false sources due to their visual gaze behavior (Jackson et al., 2006; Sebanz & Shiffrar, 2009). This is underlined by a recent game-analysis study by Meyer et al. (2022), which shows that shot fakes are an effective way to deceive the opponent and gain an advantage in basketball. While studies proved the positive influence of motor expertise on detecting fakes, fixating on the ball or the head, potentially leaves the defender vulnerable to deceptive movements (Jackson et al., 2006). Güldenpenning et al. (2020) showed that shifting attentional capabilities toward the head in basketball, decreases the reaction time of defenders in passing situations. How the examined focus on the ball affects performance in shooting situations, remains unknown. As the attackers commonly use their head and the ball for deception—to get the defender to wrongly anticipate a shot—there is a practical necessity for further investigation (Friehs et al., 2019; Wooden & Nater, 2006). Research on deception in sports indicates differences in anticipation behavior between the time window, where the players have already been deceived (Jackson & Cañal-Bruland, 2019) and where they are susceptible to deception (Warren-West & Jackson, 2020). The findings of this study, therefore, suggest that the differences in anticipation performance of the susceptible-to-deception time window may be based on the underlying gaze behavior of experts and novices in which they anticipate the intention of a movement.
In contrast to our study design, the abovementioned studies conducted video-based lab experiments. In line with Dicks et al. (2009) and Johnston et al. (2018), future studies testing similar hypotheses need to consider actual game situations in their experimental design or make it as close to the game setting as possible. These must include a realistic response time and game-like responses to ensure high ecological validity. This will complement the findings of this study and provide the basis for a recommendation toward practice when defending during a shooting situation.
Some limitations need to be considered when discussing and interpreting the results of this study. Using the RFT as the only dependent measure limits the depth of information as it combines informative raw visual data (number of fixations and fixation duration). While this data could increase comparability with previous work, it would potentially reduce the representativeness of the study task by equalizing the total duration.
Conclusion
In summary, the results of this study showed a discrepancy between the instructed gaze behavior of coaches and the actual gaze behavior of a player defending in one-on-one plays in basketball. While expert coaches advised players to look at the torso, expert players mainly fixated on the head in the receiving and dribbling phase, and the ball in the shooting phase. In contrast, novices mainly fixated on the ball in all the three phases. In contrast to existing literature, the expert coaches stated that peripheral vision is of great importance for the anticipation performance of defenders. This suggests that the head might be used as a visual pivot point by the experts. But video-based research shows that fixating on the ball or head potentially leaves the defender vulnerable to deceptive movements. Regarding the current state of research, the findings of our study point to insufficient research on the impact of gaze behavior on the anticipation performance of defenders in real games. To give quality coaching advice on gaze behavior, future studies need to consider actual game situations in their experimental design, or game-like responses and response times to ensure high ecological validity.
Acknowledgments
The study was approved by the Ethics Commission of the German Sport University Cologne (Ethics Proposal No. 041/2017). Raw data were generated at the lead institution. All the data supporting the findings of this study are available from the corresponding author (J. Meyer) on request.
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