ECSS Paris 2023: CP-BM03
INTRODUCTION: Volleyball players ability to observe the setters movements and predict the sets direction and tactics is critical for improving blocking success. This relies on players sensitivity to movement cues and is closely associated with specialized training. Studies have shown that experienced players detect movement cues earlier and over a broader range [1]. Using biological motion created by dynamic point-light displays, observers can focus on the relative movements of the setter’s body segments without viewing the ball’s trajectory. This approach enables the examination of observers’ visual discrimination sensitivity to setting movements. The purpose of this study was to investigate differences in recognizing various setting tactics among individuals with different levels of volleyball proficiency. METHODS: This study recruited 90 collegiate Division A, 84 Division B volleyball players, and 81 individuals without volleyball training. Using Simi Motion software, 17 markers were placed on specific body parts (toes, ankles, knees, hips, shoulders, elbows, wrists, fifth metacarpals, and head) of 6 Division A players (3 males) to record movements during 3 successful setting scenarios: A quick, an outside set (position 4), and a back-row attack (position 6). Wolfram Mathematica was used to create 18 dynamic point-light videos randomly ordered and embedded in Google Forms. Participants were briefed on the experiment and watched the videos on their phones in a quiet environment, completing the task within 10 minutes. A one-sample, one-tailed t-test determined whether the correct rates of each group exceeded the random guessing probability of 0.33. One-way analysis of variance (ANOVA) compared correct rates among the three groups. The significance level was set at 𝛼 = .05. RESULTS: The results showed that correct rates for all three groups were significantly higher than the random guessing probability of 0.33 (ps < .001). ANOVA indicated significant differences in correct rates among the three groups (p < .001). Post hoc comparisons revealed that Division A players significantly outperformed Division B and untrained individuals, while Division B players scored higher than untrained individuals (ps < .05). CONCLUSION: This study found significant differences in recognizing volleyball-setting tactics using dynamic point-light displays among individuals with different skill levels. Division A players excelled in identifying setting motion cues, likely due to their extensive volleyball experience and training. Division B players demonstrated higher visual discrimination abilities than untrained individuals, but their performance was still lower than that of Division A players, likely due to less exposure to standard setting skills. These findings suggest that professional sports skills are influenced by physical performance and perceptual abilities specific to sports scenarios. Reference [1] Allard F, Starkes JL. (1980). J Sport Psycho, 2(1), 22–33.
Read CV Chih-Hsuan CHANGECSS Paris 2023: CP-BM03
INTRODUCTION: Striking a ball off the tee-stand is commonly used as the batting practice in softball. When striking a ball off the tee, the visual focus is often on the ball; while hitting a ball from a pitch, the visual focus is on the coming ball. The batter needs to perceive the pitching event and swing at the ball when the ball enters the home plate based on the speed of the ball. Therefore, the visual focus should be on the direction of the incoming ball to perceive the distance that affords the swing time based on the ball speed. This study examined the performance of fast softball batters striking softballs off the tee under different visual focuses. METHODS: 4 active collegiate Division I female softball players performed the tee strikes under 4 visual focus conditions. The visual focus was on the ball for the regular tee strike (T); the other 3 visual focuses were at right (R), right-front (RF), and directly in front (F) of the player at a distance (4.5m) to simulate 70 km/h pitching speed and 0.23 s of swing time. Players performed 5 trials in each condition, and the order of conditions was randomly assigned. 3-D kinematics of the ball and the bat’s tip were captured using 2 high-speed cameras and the Simi Motion software. Based on the bat-ball speed change after the hit, the hitting results were classified into 3 groups: miss, decrease, and increase. A Chi-square test of independence was performed on the classification of batting results and the visual focus conditions. In addition, (T F) and (R RF) were further grouped, and the independent sample t-test was performed for each player. The significant level was set to α=.05. RESULTS: The chi-square test result was significant, p=.014. R and RF had a positive association with the number of misses, with a standardized residual of 3.184. There were individual differences in the t-test results: 2 batters at the T and F conditions performed significantly greater than that at the R and RF conditions, ps < .05, and one of the batters swing-and-missed all trials at the R and RF conditions; the other two batters did not reach significant difference between conditions, ps>.3. CONCLUSION: This study provides preliminary observations of the effect of visual focus on the softball tee strike performance. Overall, when the visual focus is not on the ball at the tee or in front of the simulated position of the ball, the probability of swing-and-miss increases. When focusing on the part unrelated to the hitting situation, half of the hitters’ performance was significantly affected. Striking the ball on the tee does not simulate the dynamic hitting situation, and the perception-and-action coupling is also different from the actual striking situation. In addition to increasing the sample size for future research, we suggest that if tee strikes are unavoidable due to equipment and resource issues, the visual focus should be placed at an appropriate distance in front to simulate the pitching situation.
Read CV Yun-Ting ChenECSS Paris 2023: CP-BM03
INTRODUCTION: In basketball, the presence of a defender forces shooters to adjust their movements, such as modifying shooting trajectories and shortening movement time. These adjustments are strategies to avoid blocking, but they often come at the cost of reduced stability and shooting success. Most prior research has focused on the impact of static defensive distances or the presence of defenders on jump shot performance, while the dynamic interaction between shooters and defenders remains underexplored. This study investigates how varying defensive starting distances and actions (hands-up or hands-down) dynamically influence shooters’ movements and performance. METHODS: Eight female division 1 collegiate basketball players made sixty 3-point jump shots at the 45-degree angle under 3 defensive starting distances (5.75m, 4.75m, 3.75m), each with hands-up or hands-down defensive actions. Video-based kinematics analysis was used with Simi Motion analysis software. 3-D data of the shooter’s right hip was used to determine the preparation and shooting phases as well as the air time. 3-D data of the ball was used to derive the ball release heights, angles, and velocity. In addition, 2-D data from the defender’s left hip was used to calculate the kinematics of the defender’s displacement. Shooting results were recorded manually. Shooters’ data were analyzed using two-way repeated measures ANOVA to examine the interactions between defensive distance and action. The relation between the shooter’s preparation time and defender displacement was examined using Pearson’s correlation analysis. RESULTS: The shorter defensive distance (3.75m) significantly reduced preparation and shooting times but increased air time and ball release angle, ultimately decreasing shooting accuracy (ps <.05). Defensive actions (hand-up or hand-down) and the interaction effect did not show any significant result. Six participants showed significantly positive correlations ranging from 0.78 to 0.92 between the preparation time and defender’s displacement (ps<.05). The other two shooters showed no significant correlation (ps>.1). CONCLUSION: The study shows that the shooting motion adjusts according to the defenders movement among different starting distances. The shooting movement time decreased as the initial defensive distance shortened. The shooter also increases the release angle and air time to avoid being blocked at the closest distance. These adaptations, however, reduced shooting accuracy. The results of correlation analysis indicate that most shooters spent more time in the preparation phase when defenders were further away. Future research should investigate defensive distances shorter than 3.75m and possibly the minimum shooting preparation time.
Read CV You-Xuan ChenECSS Paris 2023: CP-BM03