Examination of the Relationship Between Dribbling Footstrikes and Shots-on-Goal Scored in Soccer Field Tests Alisha K. Koxlien1, Elizabeth K. Manthey1,2, Kari E. Goranson1, David S. Senchina1 1Biology Department and 2Neuroscience Program, Drake University, Des Moines, IA, 50311 ABSTRACT: Team sports require coaches to determine which skills are most beneficial to scoring opportunities and how to divide practice time for maximum benefit for players. This experiment was designed to determine if a relationship existed in skills between 2 physical tests: 100 m sprint with ball dribble and shots-on-goal from 5 sites on the field. Foot contacts, time to completion, and heart rate at end of sprint were all measured. It was hypothesized that there would be a positive linear relationship between ball touches and goals scored. Subjects with soccer experience would use more touches to keep the ball close and in control, to prevent opponents from taking the ball. Pearson correlation was performed. No significant correlation was found between goals scored and ball touches, within all subjects or within soccer participants. A general positive correlation appeared, but in each case, these results were not significant. Participants with soccer experience on a turf field specifically could be used in further studies to have a better sample. Additionally, competitive players could be compared to amateur players to examine for a difference. Parameter All Subjects (n=15) Subjects Who Played Soccer in College (n=10) Subjects Who Didn’t Player Soccer in College (n=5) Time to Completion (sec) 22.3  4.2 22.7  4.6 21.5  3.5 Heart Rate at Completion (bpm) 180.2  16.7 174.9  14.6 190.8  16.7 Total Foot Contacts 15.6  6.1 16.7 6.4 13.4  5.5 Left Foot Contacts 4.2  4.2 4  4.2 4.6  4.5 Right Foot Contacts 11.4  4.4 12.7  4.7 8.8  1.8 Figure 1: shots-on-goal (left) and 100 m sprint with ball dribble (right). Table 2: Data from the 100 m sprint with ball dribble. RESULTS: Outcomes from the shots-on-goal test and the 100 m sprint with dribble are shown in Tables 1 and 2, respectively. Although there appeared to be some differences between subjects who played soccer in college and those that didn’t, the differences were not significant. We also tested all subjects in a 100 m sprint without dribble. There were no differences between those who played soccer in college and those that didn’t (average time to completion = 17.4  2.7 seconds; heart rate at completion 184.7  27.3 beats per minute). There was a significant difference in time to completion (p<0.001) such that time to complete the sprint without dribble was faster than sprint with dribble, as expected, and a trend towards significant differences in heart rate between the 2 sprints (p=0.6), both as would be expected. Total subjects’ goal-kicking successes were compared to their total number of foot strikes, and no correlation was found. The correlation coefficient was 0.195 and the calculated p-value was 0.487, which was much higher than the designated alpha value of 0.05 (Figure 3). When just the data from those subjects who played soccer in college was similarly considered, a poor correlation coefficient (0.349) and the p-value (0.323) were again found, both which exceeded the alpha level. Figure 3 portrays the correlation of foot strikes and goal-kicking successes for all of the subjects regardless of exercise history. The correlation coefficient (R) was 0.195, indicating a non-significant relationship. Figure 4 portrays the correlation between foot strikes and goal-kicking successes of subjects who have played soccer in college. The correlation coefficient (R) was 0.349, indicating a non-significant relationship. INTRODUCTION & HYPOTHESIS: Sports require many skills and talents. Coaches and players spend hundreds of hours determining which skills are most beneficial in a sport and how these skills can be fine-tuned through practice. Coaches have traditionally examined these abilities by watching and examining performance in competition (Bate, 1988). Soccer is no exception. Research in the past has focused on analyzing the performance of elite teams at world competitions to determine which skills are correlated to scoring opportunities. However, this method of research has not allowed for an unbiased analysis. By studying different abilities using field tests, coaches can determine how to divide practice time for different skills to gain the maximum benefit for the team (Mirkov, 2008). Current research suggests that dribbling may be the most important skill at creating scoring opportunities during a soccer game (Thomas, 2009). This experiment examined a variety of skills, including cognitive and physical skills of subjects. This poster focuses on two physical skills: the number of times the subject touched the ball during a 100 m sprint and the number of successful shots taken from a variety of positions around the goal box. It was hypothesized that an increased number of ball touches would be correlated with increased number of shots on goal. Dribbling requires that the player have both speed and control of the ball. If the ball is a great distance in front of the player during a sprint, the ball would easily be stolen by another player. However, if the subject had good control of the ball, due to an increased number of touches, then the ball would be less likely to be taken away in a game situation, signifying that that subject had some soccer experience and may also be more successful at shooting from different positions. Figure 3 (above): Correlation between footstrikes vs. goals scored for all subjects. Figure 4 (below): Correlation between footstrikes vs. goals scored for those subjects who reported playing soccer in college. MATERIALS & METHODS: The protocol was approved by the Drake University IRB (ID 09-10005). The subjects that took part in the experiment were college age males and females. Some subjects had soccer experience, while others did not. For the sprint with dribble, subjects were instructed to sprint the length of the soccer field (100m) while dribbling a soccer ball in front of them. Timing was started with the subject crossed the starting line and stopped with the subject crossed the ending line and brought the ball to a stop. This timing method was used to encourage the subjects to stay in control of the soccer ball. Two timers were used, one on each end of the field, and the recorded times were averaged. Along with being timed, each foot strike was recorded. Heart rate was recorded with a monitor worn by each subject (Polar Electro Oy, Kemple, Finland). The second skill that was tested was goal-kicking (see Figure 1.) Five spots were chosen to be the designated kicking spots (see Figure 2, from http://en.wikipedia.org/wiki/File:Football_pitch_metric.svg). Kicking positions are marked on Figure 2 with white circles. Each subject was allowed one practice kick and then three kicks were performed at each kicking spot, which equated to twenty total kicks with the outcome of fifteen being recorded. The successfulness of the kick and the foot used was recorded. The goal-kicking portion of the skills test was not timed. Both of the skills were performed on the Johnny Bright Field at Drake Stadium located on the Drake University campus. In addition to the skills tests that were performed, subjects were instructed to complete an exercise history questionnaire to determine if they had participated in soccer in college. The statistical analysis, Pearson Correlation, was done with the use of SigmaStat. Parameter All Participants (n=15) Subject Who Played Soccer in College (n=10) Subjects Who Didn’t Player Soccer in College (n=5) Point 1: Shots Made (out of 3) 0.2  0.4 Point 1: Left Foot/Right Foot Used L=9 / R=6 L=7 / R=3 L=2 / R=3 Point 2: Shots Made (out of 3) 1.8  0.8 1.8  0.4 2  1.4 Point 2: Left Foot/Right Foot Used L=1 / R=14 L=1 / R=9 L=0 / R=5 Point 3: Shots Made (out of 3) 2.8  0.6 3  0 2.4  0.9 Point 3: Left Foot/Right Foot Used L=0 / R=10 L=1 / R=4 Point 4: Shots Made (out of 3) 1.9  0.9 2.1  0.9 1.6  0.9 Point 4: Left Foot/Right Foot Used L=0 / R=15 Point 5: Shots Made (out of 3) 0.3  0.6 0.6  0.9 Point 5: Left Foot/Right Foot Used Total Shots Made (out of 15) 7.1  1.4 7.3  1.3 6.8  2.8 DISCUSSION & CONCLUSIONS: Notational analysis was used in this experiment to examine the relationship between ball touches during a 100m dribble and successful shots on goal made from five positions near the goal box. However, it was found that there is little, if any, correlation between these two traits and the relationship between the two was not significant (p= 0.195). Even when examining subjects who had soccer experience, it was found that the hypothesis must be rejected (p=. 323). This could signify that dribbling and shooting performances have little connection and one cannot be used as a predictor for the performance of the other. While this result was surprising, some considerations had not been factored into this hypothesis and experiment. Firstly, when considering this possible correlation, we did not consider the position that the subject may have played on the field. Midfielders may have better dribbling skills, while forwards may have better success of shots. Additionally, Anderson et al. (2008) suggested that turf soccer field playing and grass field playing result in drastically different performances for soccer players. The preference of the subject and their history on this subject was not asked. Further studies should include the elimination of the points on the end-line of the soccer field, as many shots are not taken from this position, and examination of elite or competitive soccer players. Table 1: Data from the shots-on-goal experiment. Positions 1-5 refer to the numbers described in the caption of Figure 2. Figure 2: Shot positions, numbered as “1” from the upper left and then numerically in a clockwise fashion, with the front dead center position denoted as “3.” REFERENCES: Andersson, H., Ekblom, B., & Krustrup, P. (2008). Elite football on artificial turf versus natural grass: Movement patterns, technical standards, and player impressions. Journal of Sports Sciences, 26(2), 113-122. Bate, R. (1988). Football chance: Tactics and strategy. Science and Football, , 293-301. Retrieved from SCOPUS database. Mirkov, D., Nedeljkovic, A., Kukolj, M., Ugarkovic, D., & Jaric, S. (2008). Evaluation of the reliability of soccer-specific field tests. Journal of Strength and Conditioning Research, 22(4), 1046-1050. Thomas, C., Fellingham, G., & Vehrs, P. (2009). Development of a notational analysis system for selected soccer skills of a women's college team. Measurement in Physical Education and Exercise Science, 13(2), 108-121 ACKNOWLEDGMENTS: Special thanks to Dr. Thomas Rosburg for his statistical expertise. We would also like to thank all of the subjects of this study, Mr. Michael Ball and Drake Athletic Facilities, and the Drake University Biology Department.