Authors: Haneol Kim

Department of Exercise and Sport Science, University of Wisconsin-La Crosse, La Crosse, WI, 54601, USA

Haneol Kim
University of Wisconsin-La Crosse
124 Mitchell Hall, La Crosse, WI 54601
Cell: 765-586-5878

Haneol Kim is a faculty member in the Department of Exercise and Sport Science at University of Wisconsin-La Crosse. His areas of research interest include biomechanics, motor control and learning in sports.

Coincidence anticipation timing requirements across different stimulus speeds in various sports: A pilot study


The ability of coincidence anticipation timing is directly related to athletic performance in sports, and anticipation timing requirements vary according to the sports type. This case study aimed to investigate the coincidence anticipation timing of male university athletes in various sports across different stimulus speeds such as slow (3 mph), moderate (6 mph), and fast (9 mph). Nineteen university athletes from soccer (n = 5), tennis (n = 7), and volleyball (n = 7) participated voluntarily in this study and were compared to non-athletes (n = 6). All participants pressed the button when the light stimulus arrived at the target location of a Bassin anticipation timer to assess anticipation timing accuracy in terms of constant, absolute, and variable errors. A speed effect in constant error (p < 0.001) and a group by speed interaction in variable error (p = 0.044) were found. However, no significant difference was found in absolute error. In conclusion, coincidence anticipation timing requirements are different across sports types. Racket sports such as tennis might be more beneficial to improving anticipation timing skills than other sports or non-athletes.

Keywords: sports performance, anticipation timing accuracy, athletes, male


The importance of visual anticipation is emphasized in sports because it allows athletes to perform high-level skills with precise timing (1). Athletes make decisions through visual anticipation when they make movements, such as catching (e.g., baseball), hitting (e.g., baseball, badminton, tennis), kicking (e.g., soccer), or spiking (e.g., volleyball). They are required to perform competitive visual anticipation based on spatial (precise judgments on the location) and temporal accuracy (moment of interception) (2). Visual perception and information processing are involved in coincidence anticipation timing (CAT), and these two processes can develop up to 10 to 12 years of age (2).

Coincidence anticipation timing is the capability to track the motion of an object, estimate arrival at a specific location, and precisely coordinate movement with the stimulus when it arrives at that target position (3-5). The ability of CAT is fundamental in racket sports such as tennis, squash, table tennis, and badminton, as well as in open-field play sports such as baseball, soccer, and volleyball. More accurate anticipation timing is a decisive factor in a successful play. Thus, as a visual perception ability, CAT has been used to differentiate the experts’ performance from novices and investigate how well expert athletes anticipate precise timing compared to beginners (6-8).

Every sport is expected to have different CAT requirements due to the characteristics of sports. Many studies have measured anticipation timing using constant, absolute, or variable error in racket sports (5, 6, 8, 9) as an indicator of performance accuracy. Akpinar and colleagues (9) compared timing accuracy between racket sports, such as tennis, badminton, and table tennis players aged approximately 12 years. Specifically, tennis players had less absolute error at 1 m/s, badminton players at 3 m/s, and table tennis players at 5 m/s. In addition, a few studies have investigated the anticipation timing of open-field sports without rackets. Günay et al. (10) examined CAT and reaction time to compare volleyball players at different positions. Depending on the middle or outside position, speed conditions of 3 mph (slow) and 8 mph (fast) were applied to female adolescent players. A significant difference was found between the two groups at a fast speed, indicating the anticipation timing ability might differ. In contrast, Saygin et al. (11) found a significant difference among soccer players at 3 mph (not significantly different at 5 mph and 8 mph) between the players at other positions, including the goalkeeper and defense midfielder position and forward position. These results indicate that anticipation timing accuracy is affected by the stimulus speed, type of sports, and different positions.

Additionally, it might result from the use of different equipment, movements, reaction times, the different size of balls (e.g., tennis ball, birdie, also called shuttlecock, and ping-pong ball), and the constraints of the situation (e.g., score, playing surface, type of shot of the opponent, time available and distance to the ball) (12). The primary muscles that athletes use also differ regarding sports types. For example, in anticipation timing accuracy, the preferred hand is superior to the non-preferred hand (13). Moreover, other critical factors such as age, gender, and experience might affect the anticipation timing ability. Stimulus speed effect on CAT performance and gender differences were found (14). Male players generally had better timing accuracy and less variable at fast speeds than female players (8, 14, 15). In addition, Young (16) showed college players had shorter movement onset times than high school players. In this context, age as the maturational factor seems essential in anticipation timing ability (2). Anticipation timing is known to improve during childhood (5). Also, exercise intensity can affect the result since it did not differ at 3 mph but showed poor accuracy at 5 mph and 8 mph (4). In general, participants were not able to respond accurately at relatively faster stimulus speeds.

It is not fully understood how CAT differs between open-field sports such as soccer or volleyball compared to racket sports. An additional comparison between athletes and the control group of healthy male adults was performed. Moreover, some studies only partially provided the results of CAT accuracy as absolute errors, excluding constant and variable errors. Broadening knowledge of other error measurements can be an excellent guide to better understanding anticipation timing ability. Also, it might be necessary for coaches and athletes to plan the training or exercise schedule in order to improve anticipation timing skills for the specific type of sports.

Therefore, the purpose of this study is to examine CAT in various sports across different stimulus speeds, such as slow (3 mph), moderate (6 mph), and fast (9 mph), compared to non-athletes. We hypothesized that there would be a significant difference between the sports. And we also hypothesized that the athletes would significantly differ from the control regardless of sports type since expert players are generally more accurate in coincidence timing than novices (14, 17).



To observe anticipation timing performance accuracy with speed variations in various sports, nineteen male university athletes and six healthy non-athletes without known symptoms and disabilities participated voluntarily in this study (N = 25). Overall, the participants are composed of tennis players (n = 7), volleyball players (n = 7), soccer players (n = 5), and non-athletes (n = 6) as control. The mean age of tennis players was 24.4 (SD = 2.2), and the mean age was 22.6 (SD = 0.5) for volleyball players. And the mean age of soccer players was 23.2 (SD = 1.1) years and 25.3 (SD = 1.2) for controls, respectively. The experimental aim was explained to all participants, and they signed informed consent prior to data collection upon arrival at the lab.


After obtaining informed consent, a participant has positioned 1.5 meters away (18) from the target location on the Bassin Anticipation Timer (Model 50-575, Lafayette Instrument, Lafayette, USA), consisting of three sections of the runway (2.24 meters) with LED lights and a button to register the responses. Bassin Anticipation Timer (BAT) has been mostly used to measure anticipation timing tasks (19). Participants were asked to track the light stimulus as it traveled sequentially and horizontally to the target location and press the controller’s button when the stimulus was expected to arrive at the target location. After three practice trials to familiarize themself with the equipment, the participant performed ten trials for each speed condition, a total of 30 attempts. The anticipation timer displayed results (error) in thousandths of seconds. However, no feedback on CAT scores was given to the participants.

Data analysis

Coincidence anticipation timing was measured using the Bassin anticipation timer at different stimulus speeds such as slow, moderate, and fast, representing 3 mph (1.34 m/s), 6 mph (2.68 m/s), and 9 mph (4.02 m/s), respectively. The stimulus speed was presented to participants randomly to prevent a learning effect. The results of constant error (CE), absolute error (AE), and variable error (VE) were calculated and presented in Table 1 as the mean and standard deviation. The constant error provides information about the timing of early or late response on the arrival of the light stimulus, reflecting the directional bias in performance. A negative value of constant error means the participant responded before the stimulus reached the target location. A positive constant error means the participant responded after the stimulus reached the target location. The absolute error provides the distance information (absolute raw scores) from the target location without considering direction. The variable error measures the consistency of the responses in performance.

Statistical analysis

A series of two-way (4 group × 3 speed) mixed ANOVA with repeated measures on CE, AE, and VE was conducted using SAS 9.4 (Cary, NC, USA). Group (soccer, tennis, volleyball, and control) was a between-subjects factor, and speed (slow, moderate, and fast) was a within-subjects factor. Post hoc comparisons were completed when necessary. A significant level was set at α = 0.05 for all statistical tests.


Constant Error

The means and standard deviations for constant error are listed in Table 1, and the constant error profile of athletes in various sports and controls is presented in Figure 1a. All participants tended to respond to the stimulus earlier on average. Regardless of stimulus speed, tennis players showed the most accurate performance, while the control group showed the least accuracy. Every group of athletes performed better in the constant error in anticipation timing than controls. Specifically, tennis athletes showed the smallest value at 6 mph (2.68 m/s), which is close to zero (e.g., target), while the control group showed the best performance at 3 mph (1.34 m/s). Soccer and Volleyball athletes had the smallest constant error at 9 mph (4.02 m/s).

Figure 1a. Constant error as a function of sports classification and speed

There was a speed effect in constant error (F2,42 = 9.1, p < 0.001). Post hoc analysis revealed a significant difference between 3 mph and 6 mph (p < 0.001) and between 3 mph and 9 mph (p = 0.013) regardless of types of sports. More specifically, tennis players showed a significant difference between 3 mph and 6 mph (p = 0.006), and between 3 mph and 9 mph (p < 0.001). Volleyball players significantly differed between 3 mph and 6 mph (p = 0.044).

Absolute Error

The means and standard deviations for constant error are listed in Table 1, and the absolute error profile is shown in Figure 1b. Tennis players showed the least mean distance from the target, whereas volleyball players showed the farthest distance. At 3 mph, volleyball athletes performed the most accurate anticipation timing, whereas tennis and soccer players at 6 mph showed the most precise response. The control group also performed best at 6 mph. However, statistical results revealed no group effects, speed effects, or interaction in absolute error.

Figure 1b. Absolute error as a function of sports classification and speed

Variable Error

The means and standard deviations for constant error are listed in Table 1, and the variable error profiles for every group at different speeds are shown in Figure 1c. Tennis players demonstrated the best performance on average compared to the control group and other athletes. At 3 mph, tennis and volleyball players showed better accurate anticipation timing than the control. The control group had the smallest variable error score at 6 mph. At 9 mph, volleyball players showed the greatest anticipation timing accuracy.

Figure 1c. Variable error as a function of sports classification and speed

A group by speed interaction was found in variable error (F6,42 = 2.4, p = 0.044). Post hoc analysis showed a significant difference between 3 mph and 6 mph among the control group (p = 0.018) and between 6 mph and 9 mph (p = 0.024). Tennis players were significantly different from soccer players (p = 0.010), and the volleyball players were significantly different from soccer players (p = 0.028) at 3 mph. The control group differed significantly from tennis athletes at 3 mph (p = 0.043). There was a significant difference between the control and the volleyball group at 6 mph (p = 0.039).


The purpose of the present study was to investigate the effects of stimulus speed and various sports. Not only limited to tennis (e.g., racket sports), we also measured anticipation timing accuracy in volleyball, soccer, and non-athletes to compare. This study showed how anticipation timing varies across sports types (i.e., racket sports vs. open-field sports) and stimulus speed (i.e., low vs. moderate vs. fast). Our major finding is that tennis players demonstrated less error in constant, absolute, and variable error scores than volleyball and soccer players and controls.

More specifically, in constant error (Figure 1a), all participants tended to respond to the stimulus at a moderate speed earlier. Controls responded earlier at a low stimulus speed, but all athletes responded after the stimulus arrived at the target point. Controls and tennis players responded earlier at a fast speed, whereas volleyball and soccer players reacted later. Tennis players had the most accurate performance at 6 mph, whereas volleyball players and soccer players had at 9 mph. For the control group, the most accurate performance was at 3 mph. It appears racket sports and open-field sports may require different speeds.

The mean constant error mainly describes the direction of the timing performance. For example, negative values of constant error indicate the participant responded earlier before the stimulus arrived at the target, whereas positive values indicate the participant responded after the stimulus arrived at the target. A disadvantage of constant error is positive and negative values can be traded off and become zero. It is more reasonable to interpret the absolute and variable errors as representing the accuracy and consistency of the performance, respectively. Interestingly, there were no statistically significant differences in absolute error (Figure 1b), which shows the distance from the target point regardless of direction. Tennis players, soccer players, and controls showed the highest accuracy at 6 mph, whereas volleyball players showed the highest accuracy at 3 mph. The mean absolute values for volleyball players were approximately 47 ms, not similar to the results of Günay et al. (10). Volleyball players tended to decrease with increased speed, while the other groups showed the best performance at a moderate speed of 6 mph as a u-shape. The mean absolute values were approximately 46 ms for soccer players, similar to defense players and midfielders in Saygin et al. (11). In the variable error (Figure 1c), tennis players and controls were most consistent at 6 mph, volleyball players at 3 mph, and soccer players at 9 mph. Soccer players tended to increase consistency with increased stimulus speed. This result shows greater error values as stimulus speed increases and supports the idea that CAT ability differs in various sports. Tennis players showed better accuracy and consistency than controls and other athletes in absolute error and variable error in addition to constant error measurement.

Ak and Kocak (8) found a significantly better anticipation timing accuracy in tennis players compared to table tennis players in adolescents aged 10-14. In this study, university tennis players with a mean age of 24 showed better accuracy than the other sports. This consistent result indicates tennis players in different age ranges still showed better accuracy. Ak and Kocak (8) calculated the mean of 50.9 milliseconds at 2 m/s (approximately 4.5 mph), which is similar to the absolute error of this study for tennis players with the mean of 40.93 ms. Typically, it is known as coincidence anticipation timing performance develops until 12 years (2) and decreases in adults over 60 years (20). The age difference might induce different results, such that anticipation timing in young adults is more accurate than in children or adolescents. Söğüt et al. (21) reported a lower anticipation timing accuracy in eight-year-olds compared to 10-year-old players under the stimulus speed of 2 mph. In addition, Akpinar et al. (9) attempted to compare CAT in racket sports such as tennis, badminton, and table tennis using various stimulus speeds of 1 m/s (2.24 mph), 3 m/s (6.71 mph), and 5 m/s (11.18 mph) and tennis players had fewer absolute errors at the low stimulus speed (1 m/s). Similarly, our results showed that tennis players at 3 mph showed better accuracy in absolute error than soccer players and controls but not volleyball players. In variable error, tennis players showed better consistency than the other groups at 3 mph. Playing tennis might be more advantageous to improving and sustaining anticipation timing ability than other sports. Lobjois et al. (20) investigated the effect of tennis playing on CAT ability. Older adults who did not play tennis showed a visuomotor delay compared to older tennis players. This result supports that tennis might help maintain CAT ability, and this ability is positively correlated to specific sports-related experiences. Perceptual and motor skills appeared to be refined with practice and might be sensitive to age and gender (22).

This study has a few limitations. Participants were only male university athletes but did not consider the gender effect shown in visual perception tasks. Men had better anticipation timing accuracy than women due to the amount of sports-related experience or computer game experience (8, 15, 23). There might be different results if we had female participants. Anticipation timing ability is not fully understood across sports types and stimulus speed with gender, so future studies should consider gender effect. Moreover, it is recommended to conduct a study with a large sample size, including males and females, and include more racket sports (e.g., badminton, squash, and table tennis) and open-field sports (e.g., baseball and basketball) to generalize findings in this study.


In conclusion, coincidence anticipation timing requirements are different across sports types. Racket sports such as tennis might be more beneficial to improving anticipation timing skills than other sports or non-athletes.


I would like to thank Dr. Jianhua Wu and Dr. Robert Zeid for their comments and feedback on the manuscript. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.


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