Examination of the Relationship Between Dribbling Footstrikes and
Shots-on-Goal Scored in Soccer Field Tests
Alisha K.
1Biology
1
Koxlien ,
Elizabeth K.
1,2
Manthey , Kari
E.
1
Goranson ,
David S.
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.
Figure 1: shots-on-goal (left) and 100 m sprint with ball dribble (right).
R = 0.195
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 soccerspecific 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
Subjects Who
Played Soccer in
College (n=10)
Subjects Who
Didn’t Player
Soccer in College
(n=5)
Time to Completion (sec)
Heart Rate at Completion (bpm)
Total Foot Contacts
Left Foot Contacts
Right Foot Contacts
22.3  4.2
180.2  16.7
15.6  6.1
4.2  4.2
11.4  4.4
22.7  4.6
174.9  14.6
16.7 6.4
4  4.2
12.7  4.7
21.5  3.5
190.8  16.7
13.4  5.5
4.6  4.5
8.8  1.8
Table 2: Data from the 100 m sprint with ball dribble.
6
4
2
0
0
5
10
15
20
25
30
Foot Strikes
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.
10
8
R = 0.349
Goals Scored
6
4
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 pvalue (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.
2
0
0
5
10
15
20
25
30
Foot Strikes
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
0.2  0.4
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
L=1 / R=14
L=1 / R=9
L=0 / R=5
2.8  0.6
30
2.4  0.9
L=1 / R=14
L=0 / R=10
L=1 / R=4
1.9  0.9
2.1  0.9
1.6  0.9
L=0 / R=15
L=0 / R=15
L=0 / R=15
0.3  0.6
0.2  0.4
0.6  0.9
L=0 / R=15
L=0 / R=15
L=0 / R=15
7.1  1.4
7.3  1.3
6.8  2.8
Point 2: Left Foot/Right Foot Used
Point 3: Shots Made (out of 3)
Point 3: Left Foot/Right Foot Used
Point 4: Shots Made (out of 3)
Point 4: Left Foot/Right Foot Used
Point 5: Shots Made (out of 3)
Point 5: Left Foot/Right Foot Used
Total Shots Made (out of 15)
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.”
All Subjects
(n=15)
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.
8
Goals Scored
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.
Parameter
12
10
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.
1
Senchina
Table 1: Data from the shots-on-goal experiment. Positions 1-5 refer to
the numbers described in the caption of Figure 2.
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.
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.
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.