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Kinesiologia Slovenica, 22, 2, 49– 63 (2016), ISSN 1318-2269 Original article
49
IZVLEČEK
Cilj raziskave je bil oceniti uspešnost igralcev pri
različnih protokolih testiranja ponavljajočih se šprintov
glede na njihov igralni položaj. V testiranje smo vključili
27 reprezentančnih nogometašev U19, in sicer testi
ponavljajočih se šprintov (repeated sprint test – RST)
7 × 34,2 m, 12 × 20 m in 6 × 40 m (20 + 20 m). Rezultati
so jasno pokazali, da so se napadalci najbolje odrezali
pri 7 × 34,2 m RST s skupnim časom 48,48 ± 3,12 s,
najhitrejšim časom 6,53 ± 0,36 s in indeksom utrujenosti
6,12 ± 4,14 %; branilci so se najbolj izkazali pri 12 × 20
m RST s skupnim časom 66,28 ± 2,62 s, najhitrejšim
časom 5,32 ± 0,22 s in indeksom utrujenosti 3,78 ± 1,92
%; vezni igralci pa so bili najboljši pri 6 × 40 m (20 + 20
m) RST s skupnim časom 35,77 ± 0,77 s, najhitrejšim
časom 5,80 ± 0,13 s in indeksom utrujenosti 2,87 ± 1,19
%. Poleg tega je povezava med rezultati različnih testov
med posameznimi igralci rahlo do zmerno pokazala, da
so imeli posamezni igralci pri različnih testih različne
rezultate. Čeprav so bili testi pripravljeni za merjenje
enakih značilnosti, ocena rezultatov podpira teorijo,
da različni testi pokažejo različne slabosti in prednosti
v uspešnosti. Ne glede na vse pa lahko individualno
prilagajanje oblike in izvedbe programa treninga
glede na igralni položaj igralca tudi v ekipnih športih
predstavlja ključni dejavnik za izboljšanje igralčeve
splošne uspešnosti.
Ključne besede: ocena, merjenje, ekipni šport, RSA (spo-
sobnost ponavljajočih se šprintov)
ABSTRACT
The aim of the present study was to evaluate players
performance on different repeated sprint test protocols
according to the players’ playing position. Twenty-seven U19
national team males’ field soccer players were tested on 7 ×
34.2 m repeated sprint test (RST), 12 × 20 m RST, and 6 × 40 m
(20 + 20 m) RST. Results clearly show that forwards scored best
on 7 × 34.2 m RST with 48.48 ± 3.12 s in total time, 6.53 ± 0.36
s in fastest time, and fatigue index of 6.12 ± 4.14%; Defenders
scored best on 12 × 20 m RST with 66.28 ± 2.62 s in total time,
5.32 ± 0.22 s in fastest time, and fatigue index of 3.78 ± 1.92%;
and midfielders scored best on 6 × 40 m (20 + 20 m) RST with
35.77 ± 0.77 s in total time, 5.80 ± 0.13 s in fastest time, and
fatigue index of 2.87 ± 1.19%. Furthermore, the relationship
detected between individual players results from test to test
were trivial to moderate indicating that individual players
score differently on different tests. Even though the tests
were designed to measure the same qualities, the evaluation
of the results supports the theory that different tests would
outline different performance weaknesses and strength.
However, even in team sports, individualizing the design and
the implementation of the training program according to the
player playing position could be a crucial factor in improving
the overall performance of the player.
Key words: Assessment; Measurement; Team sport; RSA
1University of Tunis
Depart ment of Functional Ne urophysiology and Path ology
2University of S tavanger
Depart ment of Education an d Sports Science
Corresponding author:
Shaher A. I. Shalfawi
Department of Education and Sports Science
University of Stavanger
2036-Stavanger
Norway
e-mail: shaher.shalfawi@uis.no
Tel: +47 45660660
THE EVALUATION OF SOCCER PLAYERS
PERFORMANCE ON DIFFERENT REPEATED
SPRINT TESTS: TRAINING AND TESTING
IMPLICATIONS
OCENA USPEŠNOSTI NOGOMETAŠEV PRI
RAZLIČNIH TESTIH PONAVLJAJOČIH
SE ŠPRINTOV: POMEN ZA TRENINGE IN
TESTIRANJA
Mehdi Ben Brahim1
Amri Mohamed1
Shaher A. I. Shalfawi2
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2, 49–63
(2016)
INTRODUCTION
Over the past years, research within soccer has been very successful in investigating the funda-
mental processes that contribute towards improving the game and players. Scientific research
shows that soccer players’ performance depends on a number of characteristics and skills, of
which the player's technical and tactical skills are the two major performance-determining fac-
tors for success (Turner & Stewart, 2014). Besides technical and tactical skills, the length of the
soccer game and the high-intensity actions observed during the game outline the importance of
both the aerobic and the anaerobic energy systems (Little & Williams, 2005; Vanderford, Meyers,
Skelly, Stewart, & Hamilton, 2004).
The results of match analyses showed that a field player covers an average distance of 9–12 km
during 90 min match (Bangsbo, 1994; Bradley et al., 2009; Vigne, Gaudino, Rogowski, Alloatti,
& Hautier, 2010) with 9–11% covered at high-intensity (Bradley et al., 2009). The high-intensity
actions were reported to have a duration of 2–3.8 s each (Bangsbo, Norregaard, & Thorso, 1991;
Mohr, Krustrup, & Bangsbo, 2003; Spencer, Bishop, Dawson, & Goodman, 2005) and take place
every 40–90 s (Spencer et al., 2005) with a total distance covered of 10–22.4 m per action (Reilly
& Thomas, 1976; Spencer et al., 2005). Spencer et al. (2005) summarised the total sprinting
bouts to be between 20–60 sprint per match, with a total sprinting distance of 700–1000 m.
Furthermore, forward players tend to perform more sprints than back players and midfielders,
and were reported to perform fastest on agility and repeated sprint tests (Bangsbo et al., 1991;
Kaplan, 2010; Kaplan, Erkmen, & Taskin, 2009; Reilly & Thomas, 1976). However, a recent study
showed that fullbacks conducted the highest number of high-intensity actions, followed by central
midfielders (Bradley et al., 2009; Carling, Le Gall, & Dupont, 2012). Research further indicate
that highly-trained soccer players performed 28% more high-intensity running compared to
moderately-trained soccer players (Mohr et al., 2003), and successful teams have been reported
to cover more distance at high-intensity than did less successful ones (Rampinini et al., 2009).
The repeated production of high-intensity sprints, with short recovery time, has been defined as
repeated sprint ability (Girard, Mendez-Villanueva, & Bishop, 2011; Spencer et al., 2005). These
repeated sprint actions during match play have been reported to cause a decline in performance
(Girard et al., 2011), indicating that repeated sprint ability in soccer is characterised by single
sprint speed and the ability to resist fatigue (Bishop, Girard, & Mendez-Villanueva, 2011). The
decline in the number of sprints observed towards the end of soccer matches linked fatigue to the
ability of repeatedly producing high-intensity sprints throughout the match (Mohr et al., 2003).
Therefore, it was suggested that the ability to repeat sprints could be a crucial factor that could
directly affect the match result toward the end of the match (Rampinini et al., 2009). Fatigue has
been defined as a “decline in maximal sprint speed over the number of sprint repetitions” (Girard
et al., 2011). Fatigue index has been calculated to measure the percentage decrement score of
sprints in a repeated sprint test (Glaister, Howatson, Pattison, & McInnes, 2008), results showed
a high relationship between the initial sprint speed (first sprint) and the occurrence of fatigue
in repeated sprint exercise (Mendez-Villanueva, Hamer, & Bishop, 2008). On the other hand,
players with higher aerobic capacity have been reported to have smaller decrements in repeated
sprint tests (Aziz, Mukherjee, Chia, & Teh, 2007), and performance on repeated sprint tests was
related to single sprint speed rather than aerobic capacity (Pyne, Saunders, Montgomery, Hewitt
& Sheehan, 2008). To explain this relationship, it was suggested that players higher initial sprint
speed have higher anaerobic metabolism contribution, which is highly related to performance
decrements (Girard et al., 2011; Mendez-Villanueva et al., 2008). The task of sprint (e.g., duration,
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Kinesiologia Slovenica, 22, 2, 49– 63 (2016)
surface, number of repetitions, and environment) would also have an effect on fatigue resistance
(Girard et al., 2011) and reported to be limited by neural factors (Mendez-Villanueva et al., 2008),
muscular factors (Bangsbo & Iaia, 2013), energy supplies and lactate acid accumulation (Reilly,
2007).
Since a soccer game is not predictable in nature, and repeated sprint efforts could occur in any
time during the match play, it was strongly advised to test and train this ability (Dawson, 2012;
Haugen, Tonnessen, Hisdal, & Seiler, 2014; Silvestre, West, Maresh, & Kraemer, 2006). As a result,
several repeated sprint test protocols were developed. However, the results of those tests have
so far contributed little to the effectiveness of training design as they overlook the individual
specific weaknesses according to the player playing position. Therefore, individual players may
not perform as well on different repeated sprint tests. This difference in performance has not been
well investigated in the literature of repeated sprint training for team sport and may have caused
researchers and the strength and conditioning specialists within team sports to overlook the
importance of such information. A question, however, needs to be answered: is it the right time
to individualize repeated sprint training in team sports to better improve players performance?
To be able to answer this question, soccer players were evaluated on three widely used repeated
sprint tests as a function of playing position and the rank order of scores from each player on
each test. We hypothesized that players would not perform differently on different repeated sprint
test according to their playing position.
MATERIALS AND METHODS
Subjects
Twenty-seven U19 national team males’ field soccer players volunteered to participate in our
study. These consisted of eleven defenders aged (± SD) (17.6 ± 0.5 years), with body mass (74.8
± 8.8 kg), height (182.9 ± 5.8 cm), and body fat (12.6 ± 2.1%); nine midfielders aged (17.6 ± 0.5
years), with body mass (70.4 ± 6.5 kg), height (178.0 ± 4.9 cm), and body fat (13.1 ± 1.6%); and
seven forwards aged (17.4 ± 0.5 years), body mass (71.5 ± 3.9 kg), height (179.9 ± 4.9 cm), and
body fat (13.4 ± 1.5%). In addition to the subjects’ physical education classes at school, their soccer
practice age was on average 9 years with training of 11 months a year, consisting of 5 sessions
per week plus a match. In general, soccer-training sessions lasted ~1.5 hours, including about
15–20 min of warming up, low-intensity games and stretching exercises, 15–25 min of techni-
cal soccer exercises (kicking actions, dribbling, jumping, and running with fast accelerations
and decelerations), 20-30 min of match practice, and 10 min of active recovery. None of the
participants reported any current or ongoing neuromuscular diseases or musculoskeletal injuries
specific to the ankle, knee, or hip joints, and none of them were taking any dietary or performance
supplements that could have affected performance during the study. Written informed consent
was received from all subjects after verbal and written explanation of the experimental design
and potential risks. The study was conducted according to the Declaration of Helsinki and the
study protocol was pre-approved by the local Ethics Committee of the Tunis University.
Procedures
We aimed to evaluate and compare soccer players’ performance reproducibility on repeated sprint
tests as a function of the individual player playing position and the rank order performance across
tests. All subjects were tested as a part of their training using three repeated sprint test protocols,
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namely, the 7 × 34.2 m repeated sprint test (Bangsbo, 1994), the 12 × 20 m repeated sprint test
(Cazorla, 2006), and the 6 × 40 m (20 + 20 m) repeated sprint test (Impellizzeri et al., 2008).
Unlike linear sprinting tests, the repeated sprint test protocols used in this study were designed
specifically for soccer players as they combine sprinting with changes of direction, stimulating
the type of high intensity actions observed during match play (Bangsbo, 1994; Cazorla, 2006;
Impellizzeri et al., 2008). Furthermore, to avoid the chronobiology bias on the subjects physical
performance during the tests, all tests were performed during a two weeks training camp on a
soccer field at 8 AM in the month of April under a temperature of 15°C−22°C. The subjects during
the training camp had their balanced morning meal every day at 6 AM. To be able to maximize
the reliability of the results, no more than one test was conducted on a given day, and each test
day followed two days of light intensity training.
T he s ub je ct s’ body ma ss wa s m ea su re d to t he n ea re st 0.1 kg us in g a n e le ct ro ni c sc a le (S ec a I ns tr u-
ments Ltd., Hamburg, Germany), height was measured to the nearest 0.5 cm using a stadiometer
(Holtain Ltd., Crymych, UK), and body fat was measured by skinfold thickness at four sites
(biceps, triceps, subscapular, and suprailiac) using Harpenden callipers (Lange, Cambridge,
MA, USA). All sprint tests were assessed using the Brower Speed Trap II timing system (Brower
Timing Systems, Utah, USA). The manufacturer of the Brower Speed Trap II timing system
stated that its radio frequency was 27.145 MHz and that accutacy of its timing system was 1/100
s. The reducibility of the system has been assessed and reported in a separate study (Shalfawi,
Tønnessen, Enoksen, & Ingebrigtsen, 2011).
7 × 34.2 m repeated sprint test:
Subjects started the test from a standing position 50 cm behind the starting photocell (time
zero) and sprinted a total distance of 34.2 m involving a right or left swing after the first 10 m,
then continued the sprint to the finish line where another photocell was placed (finish time).
Subjects were asked to perform a 25 s active recovery consisting of jogging back to the starting
line (Figure 1). Verbal feedback was provided to the subject during the recovery run every 10 and
20 s so the subject can be ready for the next run on time. The test leader said the word “ready” at
approximately the 23rd second of the recovery time, and at the 25th second the test leader said the
word “go”. The procedure continued until the subject completed seven sprints (Bangsbo, 1994).
Figure 1: The 7 x 34.2 m repeated sprint test (Bangsbo sprint test).
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Kinesiologia Slovenica, 22, 2, 49– 63 (2016)
12 × 20 m repeated sprint test:
Subjects started the test from a standing position 50 cm behind the starting photocell (time zero)
and sprinted a total distance of 20 m involving left, right, left and right swings after the first
4.30 m, 3.20 m, 5 m and 3.20 m, respectively, then continued the sprint to the finish line where
another photocell was placed (finish time). Subjects asked to perform a 40 s of passive recovery
consisting of walking back to the starting line (Figure 2). Verbal feedback was provided to the
subject during the recovery time at 20, 30, and 35 s so the subject could be ready for the next
run on time. The test leader said the word “ready” at approximately 37th second of the recovery
time, and at the 40th second the test leader said the word “go”. The procedure continued until the
subject completed twelve sprints (Cazorla, 2006).
Figure 2: The 12 x 20 m repeated sprint test (Cazorla sprint test).
6 x 40 m (20 + 20 m) repeated sprint test:
Subjects started the test from a standing position 50 cm behind the start/finish photocell (time
zero) and sprinted 20 m linearly, touched a line placed on the 20 m mark with a foot, turned and
sprinted back to the starting line crossing the start/finish photocell (finish time). After 20 s of
passive recovery, subjects were asked to start again. Verbal feedback was provided to the subject
during the recovery time at 10 and 15 s so the subject could be ready for the next run on time.
The test leader said the word “ready” at approximately 17th second of the recovery time, and at
the 20th second; the test leader said the word “go”. The procedure continued until the subject
completed six sprints (Impellizzeri et al., 2008).
Statistical Analyses
Deterioration in performance expressed as percentage of speed decrement (Dec%) was calculated
according to the approach used by Morin, Dupuy and Samozino (2011) for all the repeated sprint
tests in this study.
Equation 1
Dec% = 100 – (100 * [total sprint time ÷ (best time × number of sprints)])
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Then the data explored by histogram plot and the normality of distribution was tested using
Shapiro-Wilk’s test for each test results in this study. Next, descriptive statistics were calculated
and reported as mean ± standard deviations (SD) of the mean for all subjects on each of the
repeated sprint tests. For the data found to follow a normal distribution, the one-way ANOVA
assessed followed by the Tukey’s multiple comparisons test, with a single pooled variance. For
the data that found not to follow a normal distribution, the Kruskal-Wallis test assessed followed
by the Dunn’s multiple comparisons test. However, for a better understanding of the results, all
data were presented graphically using the mean difference and the 95% Confidence Interval with
the effect size (Cohen d) calculated and defined as small when d = 0.2 – 0.49, medium when d =
0.5 – 0.79 and large when d ≥ 0.8 (Cohen, 1988). Correlation matrix between all variables were
determined using Pearson’s r. Reliability assessed using a 2-way mixed intraclass correlation
(ICC) for all measures. The alpha level for significance was set to P # 0.05 for all statistical
examinations. The test re-test reliability for 7 × 34.2 m repeated sprint test was intra-class cor-
related (ICC) (ICC = 0.934, P < 0.01), for the 12 × 20 m repeated sprint test (ICC = 0.930, P <
0.01) and for the 6 x 40 m repeated sprint test (ICC = 0.886, P < 0.01).
RESULTS
Table 1. Mean ± standard deviations of the mean (SD) for all subjects on each of the repeated
sprint tests.
7 × 34.2 m RST 12 × 20 m RST 6 × 40 m (20 + 20) RST
Tot a l
Time Fastest time FI% To ta l
Time
Fastest
time FI% To ta l
Time
Fastest
time FI%
MF (n=9) 49.66
(1.9 7) 6.78 (0.26) 4.67 (4.00) 66.52
(2.4 6) 5.35 (0.22) 3.71 (2.97) 35.77
(0.77) 5.80 (0.13) 2.87 (1.19)
D (n=11) 49.9 0
(3.22) 6.93 (0.38) 2.86 (1.42) 66.28
(2.62) 5.32 (0.22) 3.78 (1.92) 36.18
(0.96) 5.90 (0.16) 2.32 (1.06)
F (n=7) 48.48
(3.12) 6.53 (0.36) 6.12 (4.14) 67.90
(0.60) 5.45 (0.13) 3.78 (2.20) 36.67
(1.32) 5.92 (0.14) 3.19 (1.89)
All (n=27) 49.45
(2.79) 6.78 (0.37) 4.31 (3.4) 66.78
(2.24) 5.37 (0.20) 3.76 (2.29) 36.17
(1.03) 5.87 (0.15) 2.73 (1.35)
RST = Repeated sprint test; FI% = Fatigue index in percent; MF = Midfielders; D = Defenders; F = Forwarders.
Within tests analyses:
Examining the results from the 7 × 34 .2 m r ep ea te d s pr int t es t revealed that there was no statistical
significant differences between players of the same playing positions. However, the effect size
of the difference revealed that differences exist between playing positions (Figure 3). When
examining the total time achieved, the results indicate that the differences between playing
positions performance was trivial. However, examining the results for fastest times indicate that
forwards had the fastest time with a large effect size difference compared to midfielders and
defenders. The results further showed that forwards had a large percentage of speed decrement
compared to defenders (Table 1 and Figure 3).
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Kinesiologia Slovenica, 22, 2, 49– 63 (2016)
Figure 3: The 95% Confidence Intervals and the effect size of the difference between group means
from the 7 × 34.2 m repeated sprint test.
While there was no statistical significant differences between players of the same positions in
the 12 × 20 m repeated sprint test, the results showed a large difference in total time between
forwards, midfielders and defenders, with defenders performing best (Figure 4). A medium
effect difference in fastest time performance was observed between forwards, midfielders and
defenders, with defenders performing best. Finally, a very trivial effect size in differences was
observed in percentage of speed decrement between playing positions (Table 1 and Figure 4)
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Figure 4: The 95% Confidence Intervals and the effect size of the difference between group means
from the 12 × 20 m repeated sprint test.
The results from 6 x 40 m repeated sprint test (20 + 20 m) did not show any statistical significant
differences between players’ positions. The results, however, showed a large effect size difference
in total time and fastest time between forwards and midfielders with midfielders scoring better
on both. A medium effect size difference was observed between defenders’ and midfielders’
fastest times with midfielders scoring best. Finally, a medium effect size difference was observed
between forwards and midfielders’ percentage of speed decrement, with forwards having a higher
percentage of speed decrement compared to midfielders (Table 1 and Figure 5).
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Figure 5: The 95% Confidence Intervals and the effect size of the difference between group means
from the 6 × 40 m (20 + 20) repeated sprint test.
Performance relationship between tests:
A moderate significant relationship was detected (r = 0.43, P = 0.0230) between total time per-
formance from the 6 × 40 m repeated sprint test and 7 × 34.2 m repeated sprint test (Figure 6).
Furthermore, a moderate significant relationship (r = 0.42, P = 0.0316) was observed between
percentage of speed decrement from the 7 × 34.2 m repeated sprint test and the 12 × 20 m repeated
sprint test (Figure 7). No other marked relationships were observed between repeated sprint tests
in the present study.
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Figure 6: The relationship between repeated
sprint total time performances across the
repeated sprint tests.
Figure 7: The relationship between groups’
fatigue index scores from the repeated sprint
tests.
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Kinesiologia Slovenica, 22, 2, 49– 63 (2016)
Figure 8: The relationship between groups fastest time from the repeated sprint tests.
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DISCUSSION AND CONCLUSIONS
The main findings from the present investigation indicate that soccer players from different play-
ing positions perform differently across repeated sprint tests. At the same time, they fail to show
a strong relationship between performances, indicating that repeated sprint tests investigated in
this study are specific and one test cannot entirely explain the results from the other tests (Figure
6, 7, 8). Examining the results further indicated no statistical differences in performance between
players playing position. However, investigation of the effect size of the difference revealed that
differences exist between players playing positions (Figure 3, 4, 5). Furthermore, the results
showed the following: In 7 × 34.2 m repeated sprint test, forwards scored the fastest sprint time,
the fastest total time and the highest fatigue index; in 12 × 20 m repeated sprint test, defenders
scored the fastest sprint time, the fastest total time and the highest fatigue index; in 6 x 40 m
repeated sprint test, midfielders scored the fastest sprint time, the fastest total time but not the
highest fatigue index (Table 1). Forwards have been reported to score best on repeated sprint
tests in studies that used distances of ~30 m (Kaplan, 2010) but not on distances ~40 m (Silvestre
et al., 2006). This could explain forwards scoring the highest fatigue index in both 7 × 34.2 m
and 6 x 40 m repeated sprint tests but not the best time either test. This explanation does not
contradict the results of other studies where forward players tend to perform more sprints than
back players and midfielders over a shorter distance compared to midfielders who conduct a
higher number of high intensity actions and sprints over a longer distance (Bangsbo et al., 1991;
Bradley et al., 2009; Carling et al., 2012; Reilly & Thomas, 1976). However, the results in this
study are in line with those of other studies, which indicate that players who scored the best total
time in one test score the best fastest time on the same test (Girard et al., 2011; Glaister et al.,
2008; Mendez-Villanueva et al., 2008; Pyne et al., 2008). Nevertheless, the differences observed
between performances across the repeated sprint tests could be attributed to the differences in
the tests design, which indicate that those tests assess other qualities besides repeated sprint
ability as the changes of direction differ from test to test. Furthermore, considering the different
profile of each playing position points out different physiological workload, which demonstrate
the importance of position-specific training programs (Kaplan et al., 2009).
To explain the differences better, one of the important purposes of assessing athletic performance
is to point out specific weaknesses in performance using various splits and test protocols to be
able to quantitatively determine athlete physical capacity, which in turns ref lect on training
program design to meet the desired outcome (Brown, Vescovi, & VanHeest, 2004). Repeated
sprint testing has been reported to be a useful tool for soccer players as it simulates the most
intensive game periods and gives an indication of the ability to sustain speed over time and resist
fatigue (Haugen et al., 2014). However, while testing is recommended in order to assess athletes
and point out their specific weaknesses in performance, it is important to consider the individual
player’s playing position, a factor which has been consistently overlooked by previous studies.
In contrast, the results from this investigation showed that forwards performed better on mixed
skill repeated sprint test where the path of the test is not entirely planned and the players had
the choice of choosing the change of direction during the test and the distance is shorter than
35 m (Figure 1), whereas, defenders scored better on closed skill repeated sprint test where they
have preplanned path (Figure 2), and midfielders scored better on mixed skill repeated sprint
test that involve a longer linear sprinting distance (6 x 40 m (20 + 20 m) repeated sprint test).
Despite the fact that the three repeated test protocols presented in this study were designed to
measure soccer player ability to repeatedly sprint, they point out weaknesses that correlate to the
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player’s playing position. It thus suggests that the same repeated sprint training program could
be of little relevant to some of the players of a certain playing position when considering the
type of skill to be developed (Kaplan et al., 2009). Research shows that after applying a physical
training program, the physiological adaptation that ref lects on performance transpires in the
tissues and movement pattern that were exposed to training (Reilly, 2007). In soccer, strength
and speed training could be seen as specific supplementary training, which is believed to provide
training advantages and reduce the risk of injury (Harman, 2008). Therefore, it is reasonable to
believe that the improvement of repeated sprint ability during match play could be achieved by
selecting exercises similar to the repeated sprint activities observed in a soccer game, in terms of
the specific skeleton region, muscle and joint movement, direction of movement, energy source
used, and other external factors such as playing ground, shoes (Baechle & Earl, 2008; Harman,
2008; Ratamess, 2008). Thus, individualization of training according to playing position is highly
recommended, and it is supported by the fact that this individualization promotes the highest
training adaptation to the pre-identified variables in need for improvement (Kraemer, 2002).
Research shows, for example, that agility and linear sprint are specific and independent qualities
(Little & Williams, 2005; Sporis, Jukic, Milanovic, & Vucetic, 2010), and suggests that improving
agility should be related to adaptations in the specific coordination of the neuromuscular system
(Ross & Leveritt, 2001; Ross, Leveritt, & Riek, 2001). Wojtys, Huston, Taylor and Bastian (1996)
reported a neuromuscular adaptation to agility training in the form of improved spinal reflex
and cortical response times in typical lower limb muscles. However, the differences observed in
performance from test to test and the relationship reported among repeated sprint tests (Figure
6, 7, & 8) highlights the importance of training the physical qualities in need of improvement,
which is based on the single player capacity and areas in need for improvements according to
playing position. Hence, different tests would outline different weaknesses and strengths, even
though all tests are designed to measure the same quality.
CONCLUSION
In line with other studies, the results from the present investigation indicate that players who
scored best on repeated sprint total time in one test has also scored best fastest time on the
same test. Nevertheless, players scored differently on the different tests with according to their
positions. These differences could be attributed to the differences in the tests design, which
indicate that those tests assess other qualities besides repeated sprint ability. Forwards performed
better on mixed skill repeated sprint test compared to defenders who scored best on closed skill
repeated sprint test and midfielders who scored best on mixed skill repeated sprint test that
involve a longer linear sprinting distance, which points out weaknesses relative to the player play-
ing position according to the type of repeated sprint skill being tested. These results highlights
the importance of training the physical qualities in need for improvement which is based on the
single player capacity and type of skill in need for improvement according to playing position.
The results suggest further that, even in team sports, strength and conditioning specialist should
pay attention to the specificity, individuality according to players position when designing the
strength and conditioning training program.
62
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2, 49–63
(2016)
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