Speed synchronization, physical workload and match-to-match performance variation of elite football players
Speed synchronization, physical workload and match-to-match performance variation of elite football players
Bruno GoncË alves 1 2 3 4
Diogo Coutinho 1 2 3 4
Bruno Travassos 0 1 2 4
Hugo Folgado 1 2 4
Pedro Caixinha 1 2 3 4
Jaime Sampaio 1 2 3 4
0 University of Beira Interior , Covilhã , Portugal , 4 University of EÂ vora , EÂvora , Portugal
1 NanoSTIMA: Macro-to-Nano Human Sensing: Towards Integrated Multimodal Health Monitoring and Analytics , NORTE-01-0145-FEDER-000016
2 Data Availability Statement: In order to protect the subjects confidentiality and privacy, data are only available on request. Interested researchers may contact the board from the Research Center in Sports Sciences, Health Sciences and Human Development to request access to the data (cidesd
3 University of TraÂ s-os-Montes and Alto Douro, Vila Real, Portugal, 2 Research Center in Sports Sciences, Health Sciences and Human Development, CIDESD, CreativeLab Research Community , Vila Real , Portugal
4 Editor: Alessandro Moura Zagatto, Sao Paulo State University - UNESP , BRAZIL
This study aimed to: (i) examine whether the speed synchronization and physical performance of an elite football team changed between the first and the second half, using match time blocks of 15-min, and (ii) explore the match-to-match variation of players' speed synchronization performance. Twenty-eight outfield elite footballers participated in 51 official matches. Positional data were gathered and used to calculate the total distance covered as a physical workload indicator. For all the outfield teammate dyad combinations (45 pairs), it was processed the percentage of time that players' speed was synchronized during walking, jogging and running using relative phase (Hilbert Transform). Also, the match-to-match variation of the players' speed synchronization, expressed in coefficient of variation was computed. The differences in the total distance covered from all players within the different match's time block periods revealed a moderate decrease in the distance covered in the last 15-min of the match compared to the first 15-min (-6.5; ±1.07%, most likely: change in means with 95% confidence limits). However, when compared the last minutes from both halves a small increase was observed (2.7; ±1.2%, likely) from first to second half. The synchronization of the players' speed displacements revealed small to moderate decreases in the % of synchronization in the second half periods for the jogging and running speed, while the opposite was found for the walking speed (~13 to 24% more, most likely). The playing position analysis for the walking zone showed similar trends between the groups, with small to moderate higher values in the second half, with the exception of [30'-45'] vs [75'-90'] in the midfielder's dyads and in [15'-30'] vs [60'-75'] match periods for forwards. Similar trend was found during the running speed, in which small to moderate higher synchronization was found during the first half periods, with the exception of [15'-30'] vs [60'-75'] and [30'-45'] vs [75'-90'] in midfielder's dyads. Regarding to the match-to-match variation of the players' speed synchronization, overall results showed small to moderate increases in coefficient of variation during jogging and running displacements from the beginning to the end of the match (32.1; ±13.2% increase in jogging and 26.2; ±10.5% in running, both comparisons most likely). The higher distance covered during most of the first half periods and the higher dyadic synchronization at high speeds might have limited players' performance in the
co-financed by Fundo Europeu de
Desenvolvimento Regional (FEDER) - NORTE
Competing interests: The authors have declared
that no competing interests exist.
second half. In addition, the decrease trend in speed synchronization during the second half
periods might have resulted from accumulated muscular and mental fatigue towards the
match. Within, the match-to-match variation in tactical-related variables increased across
the match duration, with especial focus in the midfielder dyads. Dyadic speed
synchronization might provide relevant information concerning the individual and collective
The analysis of team sports performance requires a multidimensional approach that helps to
capture the adaptive behaviour of players and teams [
]. Football is a complex team sport, in
which the players' performance derived from their interaction with the surrounding context
information that sustain the emergence of the players' physical, technical and tactical actions
[3±6]. According to that, during the last years, it has been highlighting that a more
comprehensive interpretation of players' performance might emerge if different performance
perspectives, such as tactical and physical indicators, are considered together [
3, 4, 7
]. However, most
of previous studies have been focused in only one dimension of performance (i.e. physical,
technical or tactical actions), or approach them independently, neglecting the mutual influence
between them. For example, time-motion analysis has been extensively used to analyse and
characterize the competitive workload demands of football. Generally, it was showed that
players cover between 10 to 13 km during an official match [
]. However, only around 10%
from this total distance covered represents the hight intensity movements, since most of the
movement activities are performed at walking and running speed zones [
players' physical performance seems to be different between match halves, with declines being
reported during the second half [10±13]. Accordingly, these changes are suggested to be
related with high values of distance covered at jogging and running during the first half ,
which may limit the players' performance during the second half [
While the division of the activity demands from the first to the second half allowed a better
understanding on how players' effort changes across a competitive match, analysing players
physical performance during shorter periods might provide additional information. In this
sense, Mohr et al. [
] reported decrements of 15% to 45% in the distance covered in
highintensity running in the last 15-min compared with the first half 15-min match periods.
Similarly, Carling et al. [
] analysed the total distance covered and the high-speed distance
covered during 15-min match intervals in midfielders and found higher values in these variables
during the first 15-min of the match compared with the last 15-min (75-min to 90-min).
Research has also demonstrated that the activity demands are dependent on specific players'
11, 14, 16
]. Midfielders have been shown to cover more distance than defenders or
]. Furthermore, when considering the distance covered at high speeds, both
forwards and midfielders revealed higher distance covered than defenders [
such demands are not constant for the entire match and can change according to the periods
of the match in analysis. Indeed, research has shown decrements in the total distance covered
for the midfielders and defenders when compared the first minutes of the second half with the
same period in the first half [
]. Also, both forwards and midfielders shown decrements in
high-intensity running mainly in the final part of the second half [
Clearly, the analysis of players' physical performance during competitive matches has been
considerably investigated [
8, 12, 15
]. In turn, the analysis of tactical performance or the
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integration of physical and tactical behaviour to understand the emergent team performance is
still scarce [
]. For example, the analysis of tactical behaviour in team sports have been assessed
through relative phase processing technique to understand the spatial-temporal coordination
between players direction displacements during football competitive matches as proposed by
McGarry et al. [
]. Following previous works in Basketball [
] and Futsal [
], some authors
quantified the time that players spent synchronized in longitudinal and lateral directions as a
tactical performance indicator [
3, 4, 20
]. Considering that players seems to coordinate their
actions with the aim of achieve a common goal in a shared surrounding [
], higher time
spent synchronized has been linked with high tactical performances . Overall, tactical
analysis revealed that players exhibit higher interpersonal coordination tendencies when facing
strong oppositions [
]. In turn, lower team movement synchronization has been found when
teams faced congested periods, and mental fatigue has been pointed as a possibly reason for
this decrease [
]. However, one limitation from this approach is that it capture the players'
movement synchronization divided into longitudinal and lateral movements, not considering
the compounded direction of players' movements. Thus, an integrated variable that captures
players' synchronization should be used to improve the understanding of players' tactical
performance. In this regard, the use of speed continuously captures the adjustments of players on
the field and allows to capture the rhythmic of move and the level of coordination between
them. In fact, high intensity displacements have been linked with goal-scoring opportunities
] and with actions that could lead to break the symmetry with the opponents defence [
Thus, a better understanding on how players coordinate their actions might emerge if the
analysis of movement synchronization considers the speed of players' displacements, however, no
study to date has addressed this issue. Also, the analysis of movement synchronization between
players and teams over the match time allows to capture the dynamics of tactical behaviour of
players and teams in a reliable way. For instance, the analysis of teams' behaviour across
15-min time block periods during one match, revealed differences in teams dispersion across
periods and more regular patterns towards the end of the match [
Another important issue that has been gathering research interest over the last years is the
concept of the match-to-match variation of the player's performance [25±30]. In general, it
was revealed that match-to-match variations occurs especially in technical parameters and in
high-speed running workloads. According to such results, it seems very important to improve
current knowledge by addressing match-to-match variations in tactical-related variables. The
outcomes may address reference values that allow coaches to better understand the
adaptability of the own team according to match environment. Accordingly, performance variability
can be seen as advantageous, because it reflects adjustments of repeated behaviours to the
dynamic environment [
]. Functional variations might reflect the behaviour flexibility when
facing environmental boundary conditions [
] as occur over the match.
Based on previous assumptions, it is clear that performance analysis is a multidimensional
approach. Thus, since physical behaviour reflects an exploratory behaviour of players to
perform, research that crosses tactical and physical variables are required to provide more
accurate and reliable information regarding players performance variations during matches [
]. Also, no study has addressed how players' positional role and match time periods
constraint their players' tactical and physical performance during competitive matches. In
addition, while the performance variabily may reflect players' ability to adapt to the environmental
], in fact, the match-to-match variation in tactical-realted variables is an
unknown topic. Thus, this study aimed to: (i) examine whether the tactical and physical
performances of an elite football team varied between the first and the second half using 15-min
match time blocks and (ii) explore the match-to-match variation of players tactical
performances. In line with previous research it was expected that the physical performance decreased
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from the first minutes to the last minutes of the match with differences according to the
players' role. Also, it was expected to observe different trends on tactical behaviour and
match-tomatch performance variation for defenders, midfielders and forwards.
Materials and methods
Twenty-eight male outfield professional football players (age: 24.7±4.7 y; height: 178.2±6.2 cm;
weight: 72.9±6.7 kg; professional playing experience 6.5±4.7 y) participated in 51 official
matches. For each match, the analysis have only considered the players who were part of the
starting line-up and performed the entire match duration. The club technical staff and the
players provided a written and informed consent to participate in this study after a detailed
explanation about the aims and risks involved in the investigation. The study protocol was
approved and followed the guidelines stated by the Ethics Committee of the of University of
TraÂs-os-Montes and Alto Douro, based ate Vila Real (Portugal) and conformed to the
recommendations of the Declaration of Helsinki.
Data collection and processing
The positional data from each outfield player were tracked and collected using the Match
Analysis Camera System1. The system records the precise location of all 22 players on the
field at subsecond frequency. The total distance covered was computed as physical workload
indicator. Taking into consideration the all-possible intra-team dyads formed by the outfield
teammates (45 dyads), it was processed the frequency of near-in-phase synchronization from
the players' speed displacements (expressed in % of time). After, this variable was processed
(and the % of time calculated) based on the mean speed from dyads according to following
intensity zones (adapted from Folgado et al. [
]): walking (0.0 to 3.5 km.h-1), jogging (3.6 to
14.3 km.h-1) and running ( 14.4 km.h-1). The considered variables were processed for all
intra-team dyads and it was only considered the defender, midfielders and forward dyads.
Also, to evaluate the changes associated with evolving time across the match, six match time
blocks of 15-mins were considered and analysed as following periods [
[15'30']; [30'-45']; [45'-60']; [60'-75']; [75'-90']). The extra time in both halves was not accounted
to keep consistent the matches duration.
The Hilbert Transform [
] was used to compute the relative phase of the time series
corresponding to speed displacements of all dyads. Near-in-phase synchronization (i.e. % of time
spent between -30Ê and 30Ê of relative phase) was used to access players' interpersonal speed
coordination. This method has been recently proposed to better inform on the dynamics of
coordination between dyads in effective performance contexts [
3, 35, 36
], however no study
has applied it to the players' speed displacements time series.
The within-dyads match-to-match variation was expressed by the coefficient of variation
(CV) of each match case [
26, 27, 37
]. The differences of variation of match performance
between players' speed displacement dyads were compared according to the match time
periods and playing positions. In order to calculate the within-dyads CV, only the dyads who
performed at least two entire matches were selected.
Magnitude-based inferences and precision of estimation were used to analyse the data [
Prior to the comparisons, all processed variables were log-transformed to reduce the
non-uniformity of error. Descriptive analysis were graphically represented using individual case values
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and mean±standard deviations for all variables (the presented mean is the back-transformed
mean of the log transform). Differences in within-match time periods ([0'-15'] vs [45'-60'];
[15'-30'] vs [60'-75']; [30'-45'] vs [75'-90']; and [0'-15'] vs [75'-90']) were expressed in
percentage units with 95% confidence limits. The threshold for a change to be considered practically
important (the smallest worthwhile difference) was 0.2 x between standard deviation.
Uncertainty in the true effects of the conditions were evaluated based on non-clinical inferences. The
following magnitudes of clear effects were considered: <0.5%, most unlikely; 0.5±5%, very
unlikely; 5±25%, unlikely; 25 to 75%, possibly; 75% to 95% likely; 95% to 99%, very likely;
>99% most likely . Also, the within-match time periods comparisons were assessed via
standardized mean differences and respective 95% confidence intervals. Thresholds for effect
sizes statistics were 0.2, trivial; 0.6, small; 1.2, moderate; 2.0, large; and >2.0, very large [
All statistical computations were processed with a specific post-only crossover spreadsheet for
all players and when considering only defenders, midfielders and forwards [
Descriptive analysis can be observed in both Fig 1 and Fig 2 for distance covered and speed
displacements synchronization of the teammate's dyads, respectively. The corresponding
differences from all players within the different match's time block periods (i.e. [0'-15'] vs
[45'60']; [15'-30'] vs [60'-75']; [30'-45'] vs [75'-90']; and [0'-15'] vs [75'-90']) are shown in Table 1.
Finally, the Fig 3 presents the standardized (Cohen) differences for all considered previous
The results from all players revealed a moderate decrease in the distance covered in the last
minutes of the match, i.e. [75'-90'], compared to the first minutes of the match, i.e., [0'-15']
(change in means; ±95% confidence limits: -6.5; ±1.1%, most likely). However, when
compared the last minutes from both halves ([30'-45'] vs [75'-90']), a small increase was observed
(2.7; ±1.2%, likely) from first to second half. Similar results were found when accounting for
Fig 1. Descriptive values for players' distance covered according to the match period and playing positions. Each dot represents an individual value and the black
error bars indicate mean±standard deviation.
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Players’ speed synchronization
Fig 2. Descriptive values for players' speed synchronization according to the match period and playing positions while walking, jogging
and running. Each dot represents an intra-team dyad value and the black error bars indicate mean±standard deviation.
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0 - 3.5 km.h-1
3.6 - 14.4 km.h-1
≥ 14.5 km.h-1
Players’ speed synchronization
Fig 3. Standardized (Cohen) differences in players' distance covered and speed synchronization at different intensity zones and according to different match periods
and playing positions (left panel: a, e±all dyads; left central panel: b, f±defender dyads; right central panel: c, g±midfielder dyads; right panel: d, h±forward dyads). Error
bars indicate uncertainty in the true mean changes with 95% confidence intervals.
the different playing position analyses, as both the defenders and midfielders showed a
moderate decrease in the distance covered in the [75'-90'] compared to the [0'-15'] (~6 to 7% less,
most likely) and a small increase from the [30'-45'] to [75'-90'] (~3 to 4% more, likely).
Although the forwards showed a moderate decrease in the distance covered comparing the
[0'15'] vs [75'-90'] (-7.5; ±2.5%, most likely), unclear/trivial effects were found in all the other
match periods comparisons (see Fig 1 and Table 1 for complement statistical information).
The data from all teammate's dyads (Fig 3E) revealed a small to moderate decrease in the %
of synchronization in the second half periods for the jogging and running speed, while the
opposite was found for the walking speed with small to moderate increase (~13 to 24% more,
most likely). The playing positions analysis (Fig 2 and Fig 4F, 4G and 4H) for the walking zone
showed similar trends between the groups, with small to moderate higher values in the second
half, with the exception of [30'-45'] vs [75'-90'] in the midfielder dyads and in [15'-30'] vs
[60'75'] periods in forwards. In contrast, small to moderate increases in the synchronization were
found during the first half periods for the jogging speed, apart from the [15'-30'] vs [60'-75'] in
midfielder dyads, and in the [30'-45'] vs [75'-90'] in both the defender and midfielder dyads.
Similar trend was found during the running speed, in which small to moderate increases in
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Match-to-match variation of the players’ speed synchronization
Walking Jogging Running
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Fig 4. Match-to-match variation of the players' speed synchronization. Each dot represents the coefficient of variation (CV) for each
intrateam dyad value. The whiskers connect all points, from the minimum to the maximum; + represents the mean; and the box middle solid line
represents the median.
synchronization was found during the first half periods, with the exception of [15'-30'] vs
[60'75'] and in last 15-min of each half for midfielders (see Table 1, Figs 2 and 3 for complement
The descriptive and inferential results for the match-to-match variation of the players'
speed synchronization, expressed in CV, according to match period and playing positions can
be observed in both Fig 4 and Table 2, respectively. Considering all dyads, the CV increased
across first half and decrease till the end of the match during walking displacements. However,
during jogging and running displacements, the match-to-match variation showed small to
moderate increases from the beginning to the end of the match ([0'-15'] vs [75'-90']: 32.1; ±
13.2% increase in jogging and 26.2; ±10.5% in running, both comparisons most likely). The
defender dyads showed unclear trend for walking values and a moderate increase in the last
period of the match when considering the jogging and running displacements. The midfielder
dyads showed small to moderate decreases in the walking zones during the last period of
second half, compared to the first, and small to moderate increases in jogging and running zones
in same comparisons. In addition, the forward dyads showed unclear results for the majority
of the comparisons, however a moderate decrease was identified in [30'-45'] vs [75'-90']
match-to-match variation during walking displacements (-53.8; ±18.3, most likely) and a small
increase in [0'-15'] vs [75'-90'] during running (31.6; ±40.5, likely).
This study aimed to (i) examine whether the players' speed synchronization and physical
performances of an elite football team varied between the first and the second half using 15-min
match time block periods. Also, (ii) it explored the match-to-match variation of players' speed
synchronization performance. The findings revealed higher dyadic synchronization at higher
speeds (jogging and running) during the first half and higher dyadic synchronization at low
speed (walking) during the second half. The specific positioning analysis showed less effects
between halves for the midfielders, while the forwards showed a clear decrease in dyadic
synchronization at high speeds during the second half. Also, the match-to-match variation on
tactical performance increased across the match duration, with especial focus to the midfielders
During the match, the competing teams develop tactical adjustments through dynamic
spatial-temporal relations within teammates and opponents with the aim of stablish space
dominance and numerical superiority [
]. However, such adjustments on space dominance and
numerical superiority vary according to changes on the game and strategical shared
information between players. For example, at the beginning of the match, players probably use their
teammates positioning to regulate their behaviour, as result of the strategical aspects trained
for the match preparation. During the match progression, as the local information about the
opponents' performance builds up, players may adapt their behaviour accordingly. In fact, the
results found in the match-to-match variation of players' speed synchronization seems to
support these findings. That is, the team in analysis started the match with higher regularity (less
variability) in their behaviours, however, as the match progressed it can be depicted an
increase in the variability in speed displacements synchronization between teammates.
Accordingly, the movement variability has been related with a characteristic of dynamical
adaptive systems and also of the best teams [
], whereas it may reveal the ability to adapt to
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the environmental requirements. In fact, these results suggest that teammates change the
team's interactions over the natural course of the matches through the recognition of the
spatial-temporal relations and the collective possibilities for action that sustain their functional
The analysis of players' movement synchronization has been used as a performance
indicator that aims to assess the tactical behaviour of players from the same team [
3, 7, 20, 35
], and it
has been suggested that higher time spent synchronized may reflect better tactical
performances, considering the overall extent of the match [
7, 20, 43
]. While the spatial proximity
seems to contribute to higher level of movement synchronization, in addition, the speed of
displacement seems also to be a key factor [
]. In fact, it has been shown that high speed
movements behaviours are linked with decisive actions in football, such as disrupting the
opposing team [
] and goal scoring situations [
]. Thus, the movement speed seems to
reflect the way how players explore the performance context to adjust their behaviour and to
ensure functional spatial-temporal relations within teammates and opponents according to the
different match moments and intensity demands.
The results from our study revealed that different dyadic speed displacements'
synchronization was found when considering different speed categories between halves. For instance, the
first half presented higher speed synchronization at jogging and running speeds, while in turn,
the second half showed higher speed synchronization at walking. Similarly, previous studies
have shown decrements in the physical performance during the second half when compared
with the first, possibly as result of the accumulated muscular fatigue [
10, 12, 13
the distance covered at high intensity during the second half seems to be influenced by the
activity of the first half [
], and therefore, the lower values in dyadic synchronization found
during the second half may be related with the higher dyadic synchronization at higher speeds
during the first half. It can be identified a decreasing trend in the speed displacements
synchronization from the [0'-15'] vs [45'-60'], to the [15'-30'] vs [60'-75'] towards the [30'-45'] vs
[75'90]. In addition to the muscular fatigue, another possible reason for the results may be related
with mental fatigue. That is, the ability to perform movements of high intensity and maintain
dyadic synchronization require perceptual and decision-making skills, such as attention [
accuracy and speed of decision making [
], that have been found to be diminished during
periods of mental fatigue. For example, lower movement synchronization has been identified
during moments of mental fatigue in football [
]. As so, the lower speed synchronization
found at higher speeds towards the matches' halves might suggest that players experience
periods of mental fatigue during the match, mainly during the second half, with consequences on
their movement synchronization. The results from the physical variables seems to support
these findings, as in general higher distance was covered in the [75'-90'] period compared to
the [30'-45'] period. These outcomes may indicate that players have to increase their distance
covered in an attempt to correct and adjust their positioning due to lower interpersonal
movement speed coordination [
The specific playing position analysis showed similar dyadic speed synchronization during
different intensity zones. In this sense, all considered dyads showed higher synchronization at
high speeds during the first half compared to the second half. The opposite was observed for
low intensity displacements. Thus, higher speed synchronization was found during the
beginning of the match with a trend to decrease over time. These results may be related with the
team strategy or even match events. In fact, different team behaviours have been shown to
emerge when considering different time block periods [
] and were related with match
critical moments [
]. Therefore, the higher dyadic speed synchronization, in line with the higher
distance covered found in this period, may suggests specific team behaviour (e.g. applying a
high pressure on the opponent). In the same line of reasoning, some other authors showed
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that the match-to-match variation in total high-speed running declines across halves [
However, the same authors arise some doubts on the appropriateness of general measures of
high-speed activity for determining variability in an elite soccer team. Accordingly, the results
from this study may contribute to a more holistic overview about how the players'
performance change in a match-to-match basis.
The midfielders showed trivial effects between time periods in the dyadic synchronization
at high speeds between the [15'-30'] vs [60'-75'] and between the [30'-45'] vs [75'-90']. This
outcome seems to reinforce previous findings that the first match period may be related with
specific and strategical movement behaviours. Furthermore, it may be realted with the key role
of these players, which have the main responsibility of linking the defensive and offensive
sectors, by controlling the space and maintaining a more regular coordination with them [
Also, the midfields have been found to evidence high scores in decision-making and
positioning than the other sectors [
], and thus, it may attenuate the detrimental effects in movement
synchronization in other playing positions towards the end of the match. The increase of the
speed synchronization CV according to match-to-match variation during jogging and running
over the course of match (and based on unclear differences in defender and forward dyads),
emphasizes the specificity of this playing position role according to the match contextual
requirement. The forwards clearly showed lower results of dyadic synchronization during the
second half at higher speed categories. A determined movement speed is required for the
players to achieve collective behaviours [
], and previous reports shown that there is a decrease in
the distance covered while jogging and running during the second half, mainly in jogging
speed for forwards [
This study points out new insights about changes in players' dyadic speed synchronization
according to temporal changes during football competitive matches. Common movement
synchronization analysis has been done using the players' positional data, which allows to
understand the time that players spent synchronized in the longitudinal and lateral directions.
However, players may also be synchronized during other type of movements (e.g. diagonal
movements), and therefore using the players dyadic speed synchronization may complement
the information derived from positional data, and provide an update understanding on how
players coordinate their actions at different speeds. Nevertheless, some limitations should be
acknowledged such as it was only considered the players who played the entire match, and
therefore, substitute players might have influenced the behaviour of the whole team.
The assessment of dyadic synchronization during competitive matches and how it changes
from to match-to-match seems to provide relevant information regarding on how players
couple their movements according to different speed categories. Accordingly, this study found
higher dyadic speed synchronization during the first half at high speed categories (jogging and
running), while during the second half the players showed higher dyadic synchronization
while walking. The decrement in speed synchronization towards the match as well as their
increase in match-to-match variation (from [0'-15'] vs [45'-60'] to [30'-45'] vs [75'-90]) might
suggest that players experience mental fatigue, as they are exposed to highly variable contextual
situations with consequences on their physical and tactical performances. Despite higher
distance covered, less half effects were found on the midfielders, mainly between [15'-30'] vs
[60'75'] and [30'-45'] vs [75'-90], possibly due to their key role in linking all sectors, as well as their
possibly higher ability of decision making and positioning skills. Overall, the decrements of
dyadic synchronization found during the second half, mainly for forwards, may indicate that
coaches should prepare physical and mental fatiguing practice tasks to increase players ability
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to adapt and perform under these scenarios. Also, coaches may expect an increase variation in
their players' performances over the match and therefore, the training situation may benefit if
some of these concerns become trainable. That is, the training exercises should expose players
to different match conditions that promote adaptability on the behaviour of players and teams
over time. Also, specific training tasks can, and should, be developed under fatigue situations,
both mental and physical, where the contextual information (e.g. winning/losing, unbalance,
etc.) change continuously.
Conceptualization: Bruno Travassos.
Data curation: Bruno GoncËalves.
Formal analysis: Bruno GoncËalves.
Funding acquisition: Jaime Sampaio.
Resources: Pedro Caixinha.
Software: Bruno GoncËalves, Hugo Folgado.
Supervision: Jaime Sampaio.
Visualization: Bruno GoncËalves.
Writing ± original draft: Diogo Coutinho.
Methodology: Bruno GoncËalves, Diogo Coutinho, Bruno Travassos, Hugo Folgado.
Writing ± review & editing: Bruno GoncËalves, Diogo Coutinho, Bruno Travassos, Hugo
Folgado, Pedro Caixinha, Jaime Sampaio.
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