Biochemical, physical and tactical analysis of a simulated game in young soccer players

Abstract

BACKGROUND: The objectives of this study were to describe and compare the displacement patterns and the tactical performance of the players in the first to the second game time and verify possible associations between indirect markers of muscle damage with displacement patterns in a simulated game played by young soccer players.
METHODS: Eighteen young soccer players were submitted to a simulated game and two blood collections, one before and another 30 minutes post-game to analyze the behavior of creatine kinase and lactate dehydrogenase enzymes. The patterns of displacement and tactics variables were obtained through functions developed in MATLAB environment (MathWorks, Inc., Natick, MA, USA).
RESULTS: It is observed a significant increase in average speed (P=0.05), number of sprints (P<0.001), the percentage the total distance covered at high intensity (P<0.001) and tactical variables (team surface area: P=0.002; spreading: P=0.001) in the second period of the simulated game. In addition, there was significant reduction in the percentage of the total distance at low intensity (P≤0.05) in the second period, and there was a strong association between the percentage of change delta of creatine kinase and lactate dehydrogenase with the displacement patterns in the simulated game.
CONCLUSIONS: The results show that indirect markers of muscle damage have great association with displacement patterns in game performed in training conditions for young soccer players, evidencing a need for reflection on the post-training recovery sessions strategies, contributing to better planning of sessions throughout the macrocycle.

KEY WORDS: Computational biology - Athletic performance - Muscles - Soccer - L-lactate dehydrogenase - Creatine kinase

Full text

1554 THE JOURNAL OF SPORTS MEDICINE AND PHYSICAL FITNESS December 2016
Anno: 2016
Mese: December
Volume: 56
No: 12
Rivista: The Journal of Sports Medicine and Physical Fitness
Cod Rivista: J Sports Med Phys Fitness
Lavoro:
titolo breve: BIOCHEMICAL, PHYSICAL AND TACTICAL ANALYSIS OF SIMULATED GAME
primo autore: AQUINO
pagine: 1554-61
citazione: J Sports Med Phys Fitness 2016;56:1554-61
Among the different methodologies of analysis, the
total distance and the intensity of displacement during
the soccer match are important variables to character-
ize the metabolic demands of the sport and the physical
performance of athletes. During a match, elite players
reach values of average and peak heart rate of 85 to
98%, respectively,1 run 8 to 12 km, perform an average
of 30 efforts above 25 km/h and reach speeds of over 30
km/h at distances between 30-40 m.6-8 These high inten-
sity activities can promote disturbances in the muscular,
In the last decades, the soccer season has been experi-
encing a signicant increase in the number of match-
es and competitions. This has led to a grueling schedule
which imposes substantial physiological demands to
athletes. Researchers have explored the area of track-
ing and monitoring systems in order to determine the
patterns of displacement and other variables (i.e., tech-
nical-tactical aspects) aiming to contribute to the char-
acterization of the games played by soccer teams during
in-season 1-4 or pre-season.5
Biochemical, physical and tactical analysis
of a simulated game in young soccer players
Rodrigo L. Q. T. AQUINO 1, 2, Luiz G. C. GONÇALVES 2, Luiz H. P. VIEIRA 2, Lucas P. OLIVEIRA 2,
Guilherme F. ALVES 2, Paulo R. P. SANTIAGO 3, Enrico F. PUGGINA 3 *
1Faculty of Sports Science, Porto University, Porto, Portugal; 2Faculty of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão
Preto, Brazil; 3School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
*Corresponding author: Enrico F. Puggina, School of Physical Education and Sport of Ribeirão Preto of the University of São Paulo. Av. Bandeirantes 3900,
Monte Alegre, 14040-907 Ribeirão Preto, São Paulo, Brazil. E-mail: enrico@usp.br
ABSTRACT
BACKGROUND: The objectives of this study were to describe and compare the displacement patterns and the tactical performance of the play-
ers in the rst to the second game time and verify possible associations between indirect markers of muscle damage with displacement patterns
in a simulated game played by young soccer players.
METHODS: Eighteen young soccer players were submitted to a simulated game and two blood collections, one before and another 30 minutes
post-game to analyze the behavior of creatine kinase and lactate dehydrogenase enzymes. The patterns of displacement and tactics variables were
obtained through functions developed in MATLAB environment (MathWorks, Inc., Natick, MA, USA).
RESULTS: It is observed a signicant increase in average speed (P=0.05), number of sprints (P<0.001), the percentage the total distance covered
at high intensity (P<0.001) and tactical variables (team surface area: P=0.002; spreading: P=0.001) in the second period of the simulated game.
In addition, there was signicant reduction in the percentage of the total distance at low intensity (P≤0.05) in the second period, and there was
a strong association between the percentage of change delta of creatine kinase and lactate dehydrogenase with the displacement patterns in the
simulated game.
CONCLUSIONS: The results show that indirect markers of muscle damage have great association with displacement patterns in game per-
formed in training conditions for young soccer players, evidencing a need for reection on the post-training recovery sessions strategies, con-
tributing to better planning of sessions throughout the macrocycle.
(Cite this article as: Aquino RLQT, Gonçalves LGC, Vieira LHP, Oliveira LP, Alves GF, Santiago PRP, et al. Biochemical, physical and tactical
analysis of a simulated game in young soccer players. J Sports Med Phys Fitness 2016;56:1554-61)
Key words: Computational biology - Athletic performance - Muscles - Soccer - L-lactate dehydrogenase - Creatine kinase.
ORIGINAL ARTICLE
EPIDEMIOLOGY AND CLINICAL MEDICINE
The Journal of Sports Medicine and Physical Fitness 2016 December;56(12):1554-61
© 2016 EDIZIONI MINERVA MEDICA
Online version at http://www.minervamedica.it

BIOCHEMICAL, PHYSICAL AND TACTICAL ANALYSIS OF SIMULATED GAME AQUINO
Vol. 56 - No. 12 THE JOURNAL OF SPORTS MEDICINE AND PHYSICAL FITNESS 1555
Lavoro:
titolo breve: BIOCHEMICAL, PHYSICAL AND TACTICAL ANALYSIS OF SIMULATED GAME
primo autore: AQUINO
pagine: 1554-61
citazione: J Sports Med Phys Fitness 2016;56:1554-61
body mass 62.1±4.3 kg; fat percentage 12.1±2.2%; peak
height velocity 1.68±0.6 years; VO2max 49.98±3.12
mL/kg/min) with a mean playing experience of 4 years,
belonging to under-16 category of a rst division club
(São Paulo state, Brazil). Participants trained four times
per week for approximately 110 minutes per training
session and participated in a competition match once
per week. It was adopted as inclusion criteria uninter-
rupted year of training in soccer, not present any injury
and not be engaged with any additional training (i.e.,
resistance training) either in season or off season.
This study was approved by the Research Ethics
Committee of the Clinics Hospital of the Ribeirão Preto
Medical School, University of São Paulo (no. 710 998)
and it was in accordance with the Helsinki Declara-
tion. All participants and their legal guardians signed an
Informed Consent Agreement and informed about the
procedures and objectives of the study.
Procedures
The subjects underwent to a simulated match and
two blood samples collections (pre and post-game).
The simulated match was carried out in a soccer eld
(70×50 m) and usual time of training (05:15 p.m.). The
purpose of checking the behavior of these variables in
these circumstances was to minimize possible external
interference that could inuence our results.
Simulated match lasted 60 minutes, being 30 min-
utes for each half time with 15-minute interval between
them. Prior to the beginning of the collection, players
performed a standardized warm-up protocol. The tem-
perature at the beginning of the rst time was 30 °C (86
°F), and at the beginning of the second time was 25 °C
(77 °F) (climate record of Institute of Meteorological
Research [IPMet], Brazil).
The game was fully monitored using two digital vid-
eo cameras (Casio EX-FH25) at 30 Hz (720×480 pixel
and 24-bit color resolution), which each covered about
3/4 of the total area of game. After the images sequenc-
es transference to the computer, it was used the track-
ing software DVIDEOW,13, 14, 16-18 to obtain the players
displacements trajectories.
The synchronization of the images from the cameras
was done by identifying common events in the overlap-
ping areas.14, 18 Calibration was constructed using 6 ref-
erence points with previously measured distances from
endocrine and immune systems, leading to a reection
on the recovery strategies after ofcial matches and
training sessions.9
One of the various forms of evaluation of distur-
bances in the muscular system, the muscular isoform of
creatine kinase (CK) and lactate dehydrogenize (LDH)
enzyme activities are characterized as two important
biomarkers for the indirect detection of muscle dam-
age.10 Another application of monitoring these enzymes
refers to the exercise physiology context, since studies
have shown that an acute bout of exercise can modify
these enzyme activities in accordance with the load and
intensity of the stimuli.11
Additionally, the analysis of physical gaming perfor-
mance, identifying the position of the players in each
interval of time allows the verication of tactical sys-
tems in the game context. Thus, the way the team is
organized in the eld reects the strategy adopted and
guidelines set by the coaching staff. In these perspec-
tives, the variables named team surface area and spread
of the team can represent the tactical performance in the
game. Previous studies have pointed to an association
between the tactical and physical behavior of teams in
soccer.12-14
Despite the relatively large number of studies in the
literature devoted to investigate the game analysis in
soccer,1, 13-16 it is possible to identify the predominance
of data with professional players in an ofcial game,
leaving a lack of research of this issue with young soc-
cer players in training environment. In addition, there
is the need to explore possible associations between in-
direct markers of muscle damage and physical perfor-
mance variables in training sessions.
Based on these observations, the objectives of this
study were: 1) verify possible associations between in-
direct markers of muscle damage (CK and LDH) with
the patterns of displacement in a simulated soccer match
played by young soccer players; 2) analyze the effect of
a simulated match on CK and LDH plasmatic activities;
and 3) characterize and compare the team surface area
and the spread of the team in the rst and in the second
half of the game.
Materials and methods
This study was conducted with 18 male soccer players
(mean age 15.6±0.4 years; mean height 1.742±0.053 m;

AQUINO BIOCHEMICAL, PHYSICAL AND TACTICAL ANALYSIS OF SIMULATED GAME
1556 THE JOURNAL OF SPORTS MEDICINE AND PHYSICAL FITNESS December 2016
pying area and the spreading of the players (Figure 2),
calculated as function of time (i.e., at each frame ana-
lyzed) using a technique previously used in professional
soccer.13, 14
Blood samples collections were carried in two mo-
ments: pre-game (15 minutes before) and post-game
(30 minutes after the simulated match). Ten milliliters
of blood were collected from each participant in tubes
with addition of anticoagulant (Vacutainer, BD, Brazil),
and centrifuged at 3,500 rpm for 15 minutes to sepa-
rate the blood cells from the plasma. Then, the plasma
samples were aliquoted in 1.5 mL tubes and frozen at
-80 °C for later biochemical analysis.
CK and LDH plasmatic activities were determined
with commercial kits from Bioliquid® (Pinnhais, Bra-
zil) following the method proposed by manufacturer,
which uses the addition of N-acetyl-cysteine (NAC) in
the reaction to ensure full activation of LDH and CK-
MM (muscular isoform).
Biochemical analyzes were conducted adding the
buffer solution (2.5 mL bottle) to a specic reactive,
leaving the new solution in a water bath at 37 °C for one
minute. The second step was to add 20 μL of plasma to
the reactive solution, leaving again the mixture in a wa-
the coordinate system origin. Then, through a specic
algorithm 17 the segmentation was performed based on
morphological ltering technique (Figure 1). The track-
ing was performed with 75.13% automation. Finally,
data arrays containing the 2-D position versus time, for
each player on the eld [x(t), y(t)] were obtained from
the reconstruction by the DLT method.14, 16, 17
Using a specic MATLAB routine (MathWorks, Inc.,
Natick, MA, USA), the aforementioned matrices were
smoothed by the third order low-pass Butterworth digi-
tal lter adopting a cutoff frequency of 0.4 Hz.14, 18 af-
ter residual analysis of the signal as function of time.14
Through specic routines, players displacement patterns
were obtained as follows: total distance covered (m), av-
erage speed (m/min) and percentage of the total distance
in seven speed ranges, determined based on the study of
Castagna, Impellizzeri, Cecchini, Rampinini, Alvarez:19
V1≤0.4 km/h (standing); 0.4<V2≤3 km/h (walking);
3.1<V3≤8 km/h (jogging); 8.1<V4≤13 km/h (medium in-
tensity running [MIR]); 13.1<V5≤18 km/h (high-intensity
running [HIR]); V6>18 km/h (sprint); V7=V5+V6 (high-
intensity activity [HIA]). The number of sprints (arbitrary
units) was dened by the frequency of sprints in V6.
The tactical variables selected were the team occu-
Figure 1.—Morphological ltering procedures: A) reading of the cur-
rent frame; B) identication of the background image; C) separation and
binarization of the remaining elements.
Figure 2.—Representation of tactical variables in a time step: A) spread
of the team, and B) team surface area.
A
A
B
B
C

BIOCHEMICAL, PHYSICAL AND TACTICAL ANALYSIS OF SIMULATED GAME AQUINO
Vol. 56 - No. 12 THE JOURNAL OF SPORTS MEDICINE AND PHYSICAL FITNESS 1557
terns and tactics variables). It is observed that in the sec-
ond half of the simulated match there was greater play-
ers involvement in high intensity activity in detriment
of low and medium intensity. That is, when comparing
the rst with the second half, there was a signicant de-
crease in the percentage of the total distance covered
in jogging and MIR (P=0.04 and P=0.01, respectively).
Additionally, when the same comparison was per-
formed with the variables SPR and HIA, it was found
signicant increase (P<0.0001 for both). The same was
observed for the average speed and number of sprints
(P=0.05 and P<0.0001, respectively).
In parallel to the results cited above, tactical variables
behave similarly, a signicant increase was found com-
paring of the rst with the second half time for the team
surface area of the team (P=0.002; P=0.001).
Table II shows the results for plasmatic activities of
CK and LDH pre and post-the simulated game as well
as the percentage of change (Δ%). Comparing pre to
post-match it was noted an increase of 95.25±46.64%
and 118.80±61.77% in the plasmatic activity of CK
and LDH, which represents a signicant difference
(P=0.001 and P<0.0001 respectively).
ter bath at 37 °C for one more minute. Immediately the
end of one minute, four measurements (334 nm wave-
length at 37 °C) were performed at each minute to ob-
tain the Δ activity value. The CK and LDH (in arbitrary
units) were calculated using the equations:
CK = 8252 × Δ absorbance / minute and LDH =
= 8321 × Δ, respectively.
Statistical analysis
Statistical analysis was performed using SPSS soft-
ware (IBM Corp., Armonk, NY, USA) for Windows,
v.17.0. The normality of the data was veried by Shapiro-
Wilk test. It was used the Student’s paired t-test to com-
pare the results with pre to post-match for indirect muscle
damage variables (CK and LDH) and to compare the data
obtained through the computational tracking (displace-
ment patterns and tactics variables) of the rst with the
second half. Pearson correlation was used to associate
the dependent variables (CK and LDH) with the inde-
pendent variables (displacement patterns). According to
Hopkins,20 it was adopted for the correlation magnitude
the following coefcient values: negligible (r<0.1), small
(0.1≤r<0.3) moderate (0.3≤r<0.5), large (0.5≤r<0.7),
large (0.7≤r≤0.9), nearly perfect (0.9<r<1.0) and perfect
(r=1.0). P values ≤0.05 were considered signicant.
Results
Table I shows the results for the variables obtained
through the computational tracking (displacement pat-
Table I.—Displacements patterns, team surface area and spread of the team in the rst and second half of the simulated match.
Variables First half Second half Total
Standing (%) 0.08±0.04 0.09±0.05 0.08±0.04
Walking (%) 6.42±1.61 6.00±1.49 6.17±1.38
Jogging (%) 42.49±5.45 41.06±5.59* 41.64±5.11
MIR (%) 28.51±3.39 26.84±2.13* 27.98±2.62
HIR (%) 15.14±2.96 15.74±2.99 15.67±2.47
SPR (%) 7.36±2.96 10.27±2.76* 9.06±2.40
HIA (%) 22.50±4.44 26.01±4.87* 24.73±4.29
Total distance (m) 3085.70±295.67 3163.06±306.56 6248.76±575.06
Average speed (km/h) 6.18±0.59 6.35±0.62* 6.25±0.58
Number of sprints 37±12 48±15* 85±25
Team surface area 585.29±71.83 752.50±22.71* 669.03±207.85
Spread of the team 136.35±7.95 155.93±2.39* 146.15±23.49
MIR: medium intensity running; HIR: high-intensity running; SPR: sprinting; HIA: high-intensity activity.
*Means differences compared to the rst half (P≤0.05).
Table II.—Plasmatic activities of CK and LDH pre and post simu-
lated match.
CK (U/A) LDH (U/A)
Pre 171.51±69.21 158.25±46.14
Post 329.14±143.46* 327.45±70.21*
Δ% 95.25±46.64 118.80±61.77
CK: creatine kinase; LDH: lactate dehydrogenase.
*Means differences compared to the pre-simulated match (P≤0.05); Δ%: percent-
age of change of CK and LDH.

AQUINO BIOCHEMICAL, PHYSICAL AND TACTICAL ANALYSIS OF SIMULATED GAME
1558 THE JOURNAL OF SPORTS MEDICINE AND PHYSICAL FITNESS December 2016
portance of play in the competition) that may interfere
in the results.21 The use of data acquired in training en-
vironment contributes to the study of variables related
to the physical and tactical performance. In this direc-
tion, this information may be useful in the preparation
of guidelines and recovery strategies of athletes for the
next training session, in search of overcompensation.
The results of the present study show that, for these
participants, was found signicant increases in total
distance covered in high intensity (HIR, SPR, HIA) in
the second half of the game. These results contradict
the usually found in the literature. Castagna et al.22
examined the relationship between aerobic eld tests
with physical performance of young soccer players
(14.4±0.1 years) during the formal game. In this study
they found a signicant decrease of the total distance
in the second half (-3.8%) and distance in MIR (11%).
Other studies have also reported signicant drop for
these variables.19, 23 However, possible differences in
the characteristics of the participants (i.e., training ex-
perience, competitive level, environment of data col-
lection — training versus competition) may explain the
opposition between the literature and our results.
Additionally, Lago et al.24 veried that game outcome
may inuence the behavior (i.e., dynamic of changes)
of displacement patterns at high intensity during a soc-
cer game. In addition, Faude et al.25 found that high-
intensity actions are directly related to the outcome of
the match. In this regard, it is noteworthy that through-
out the second half of the simulated game analyzed in
our study, one of the teams remained at a disadvantage
on the scoreboard, which possibly led to seek alterna-
tives to reverse this situation, increasing the intensity of
Table III presents the results of the Pearson correla-
tion coefcient (r) for associations between the vari-
ables of displacement patterns with the Δ% the CK and
LDH. It is found that there is a large signicant negative
correlation when combined low intensity characterized
standards (walking and jogging) with the Δ% of the CK
and LDH. As for the Δ% of the LDH with the variable
jogging there was a signicant inverse correlation too
large. That is, it turns to the study participants that the
higher the percentage of the total distance at low inten-
sity, the lower the Δ% of the CK and LDH.
Additionally, it was found a positive association be-
tween HIR with LDH Δ%. In Table III, the associations
between SPR and HIA with CK Δ% is possible to ob-
serve a positive correlation coefcient, while the same
variables in association with LDH Δ% revealed also
strong correlation. Finally, when total distance covered,
average speed and number of sprints were correlated
with CK Δ% and LDH Δ%, strong correlation coef-
cients were found.
Discussion
The main objectives of this study was to evaluate pos-
sible associations between indirect markers of muscle
damage with displacement patterns during a simulated
soccer match, and compare the physical and tactical
performance variables of the rst with the second half
of the game. One of the contributions and particularities
of this study was to evaluate these variables in young
soccer athletes in their usual training eld and sched-
ule, minimizing external interference (fans, eld size,
environmental conditions, quality of the opponent, im-
Table III.—Correlation matrix and respective P values between the percentage of change (Δ%) of CK and LDH with the displacement
patterns obtained in the computational tracking.
Variables CK Δ% P values LDH Δ% P values
Standing (%) -0.37 0.12 -0.41 0.08
Walking (%) -0.64* 0.004 -0.63* 0.005
Jogging (%) -0.55* 0.01 -0.81* <0.0001
MIR (%) 0.23 0.35 0.40 0.10
HIR (%) 0.40 0.09 0.66* 0.003
SPR (%) 0.68* 0.002 0.75* <0.0001
HIA (%) 0.62* 0.006 0.80* <0.0001
Total distance (m) 0.70* 0.001 0.79* <0.0001
Average speed (km/h) 0.70* 0.001 0.79* <0.0001
Number of sprints 0.83* <0.0001 0.90* <0.0001
CK: creatine kinase; LDH: lactate dehydrogenase; MIR: medium intensity running; HIR: high-intensity running; SPR: sprinting; HIA: high-intensity activity.
*P≤0.05.

BIOCHEMICAL, PHYSICAL AND TACTICAL ANALYSIS OF SIMULATED GAME AQUINO
Vol. 56 - No. 12 THE JOURNAL OF SPORTS MEDICINE AND PHYSICAL FITNESS 1559
membrane, increased plasmatic levels suggests their ex-
travasation into the extracellular medium, as a result of
changes in the membrane or muscle damage.
Similar results to those obtained in this study were
found in the study conducted by Magalhaes et al.11 The
authors investigated the effects of a formal game on
blood parameters in adult players of second and third
division of Portuguese soccer league during the com-
petitive phase. Signicant increases were found in the
serum CK levels in the 30 min, 24, 48 and 72 hours after
the match.
Studies that have also included the LDH analysis
found a similar response, namely, a signicant increase
post-match.23 In contrast to the data obtained and also
with the data of Magalhaes et al.,11 the study of Thorpe
and Sunderland 28 must be considered. Despite the av-
erage increase of 74% in plasmatic activity of CK, the
authors found no statistical signicance when the pre
and thirty minutes post-match were compared in semi-
professional soccer players.
On the association of data between the CK and LDH
percentage change and displacement patterns, the key
ndings of this research were the positive associations
with SPR, HIA, total distance covered, average speed
and number of sprints, and negative correlation with
jogging and walking.
Soccer consists of an intermittent efforts sport, in-
volving activities such as jumping, accelerations and de-
celerations, possessing a large amount of eccentric mus-
cle actions. It has been shown that the smaller muscular
activity found in this type of muscle action, compared
to the concentric action, can induce greater mechanical
stress, increasing the incidence of tissue damage,29, 30
explaining the increase of CK and LDH post game.10
Other studies with soccer, and even with other sports
with similar requirements and duration, such as Ameri-
can football and rugby, obtained similar results.25, 31-33
Thorpe and Sunderland 26 recently found the associa-
tion between the displacement patterns during a match
with CK activity in adult soccer players. Using GPS
tracking technology, the authors found positive associa-
tions between CK percent of change with the number of
sprints (r=0.86), and distance at high intensity (r=0.92).
In our study, all other variables related to high intensity
efforts (i.e., SPR, HIA, average speed and number of
sprints) revealed positive association with markers of
muscle damage.
the game. This fact was evidenced by the signicant in-
crease in SPR, HIA and number of sprints in the second
half (12.94%, 57.1%, and 36.30% respectively). At the
same time, the team with advantage on the scoreboard
did not show any difference in the variables studied.
Thus, the framework above partly explains the increase
in the percentage of high intensity actions in the second
half.
Moreover, another explanatory variable for the in-
creased intensity in the second half of the analyzed game
may be related to climate change. According to Nassis
et al.,26 soccer players appear to modulate the displace-
ment patterns in a game according to the environment
temperature (i.e,. in a hot environment, the percentage
of high-intensity actions is decreased). In this study, the
rst half of the match began at ~05:30 p.m., 15 minutes
after warm-up (i.e., middle-end of the afternoon, with
presence of sunlight, 30 °C) and the second half started
at ~6:15 p.m. and extended to ~6:45 p.m. (i.e., begin-
ning of night in the absence of sunlight, 25 °C). During
the second half there was certainly decrease of tempera-
ture in the gaming environment (not controlled). This
temperature change may have interfered in the modula-
tion of high-intensity displacement patterns, resulting in
increased intensity due to the drop of temperature (i.e.,
increased high-intensity activities and average speed
from the rst to the second half time), as outlined the
study of Nassis et al.26
Another issue to be addressed to explain the differ-
ences of the results usually found in the literature refers
to the place of data collection. In the present study the
data collection was carried in the training environment,
which can inuence the disposal of participants related
to the intensity of the game. Thus it is suggested that
participants have executed the “preserved behavior”,
originally proposed by Castagna et al.,23 in the rst half
of the time, resulting in the increase of intensity during
the second half. In addition, simultaneous changes from
the rst to the second time in the physical performance
and tactical behavior also indicates a clear association
between these parameters in young Brazilian players
U-16, which corroborates the ndings at the profession-
al level (i.e., in the Brazilian First Division League).14
Regarding the behavior of CK and LDH from pre
to post-game, signicant increases were found. Given
that these enzymes are located in the cell cytoplasm,
and being unable to cross the barrier of sarcoplasmic

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Based on these ndings, it appears that a simulated
game conducted in training environment, is able to
signicantly increase the plasmatic activity of indirect
markers of muscle damage (CK, LDH). In addition, As-
cenção et al.34 found that the increase of these indicators
may be maintained for up to 72 hours after the effort,
suggesting that for proper recovery, a period longer than
72 hours to perform a new simulated game.
Conclusions
It was concluded that there was a signicant increase
in the total distance, average speed, number of sprints
and percentage of the total distance at high intensity in
the second half of the simulated game. In addition, there
was signicant reduction in the percentage of the total
distance at low intensity. In addition, it was observed
positive association between the percentage of change
CK and LDH and the displacement patterns in the simu-
lated match.
The results and discussions presented in this study are
important to provide information about the training pro-
cess of young soccer players in three areas: 1) identica-
tion and monitoring of physical and tactical performance
within the training reality; 2) information about the dis-
turbances caused by a simulated match in the muscular
system, linking indirect markers of muscle damage with
physical performance; 3) adjust the recovery periods of
the athletes throughout the training sessions.
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Funding.—This work was supported by the CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior).
Conicts of interest.—The authors certify that there is no conict of interest with any nancial organization regarding the material discussed in the manuscript.
Article rst published online: January 14, 2016. - Manuscript accepted: January 7, 2016. - Manuscript revised: December 22, 2015. - Manuscript received:
June 30, 2015.