sensors
Article
The Inﬂuence of Time Winning and Time Losing on
Position-Speciﬁc Match Physical Demands in the Top One
Spanish Soccer League
José C. Ponce-Bordón 1
, Jesús Díaz-García 1,*
, Miguel A. López-Gajardo 1
, David Lobo-Triviño 1,
Roberto López del Campo 2
, Ricardo Resta 2
and Tomás García-Calvo 1


Citation: Ponce-Bordón, J.C.;
Díaz-García, J.; López-Gajardo, M.A.;
Lobo-Triviño, D.; López del Campo,
R.; Resta, R.; García-Calvo, T. The
Inﬂuence of Time Winning and Time
Losing on Position-Speciﬁc Match
Physical Demands in the Top One
Spanish Soccer League. Sensors 2021,
21, 6843. https://doi.org/10.3390/
s21206843
Academic Editor: Angelo Maria
Sabatini
Received: 17 September 2021
Accepted: 11 October 2021
Published: 14 October 2021
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1
Faculty of Sport Sciences, University of Extremadura, Boulevard of the University s/n, 10003 Caceres, Spain;
jponcebo@gmail.com (J.C.P.-B.); malopezgajardo@unex.es (M.A.L.-G.); davidlobo123@gmail.com (D.L.-T.);
tgarciac@unex.es (T.G.-C.)
2
LaLiga Sport Research Section, 28043 Madrid, Spain; rlopez@laliga.es (R.L.d.C.); rresta@laliga.es (R.R.)
*
Correspondence: jdiaz@unex.es; Tel.: +31-927-257-460
Abstract: The aim of the present study was to analyze the inﬂuence of time winning and time losing
on position-speciﬁc match physical demands with and without ball possession in the top Spanish
professional soccer league. All matches played in the First Spanish soccer league over four consecutive
seasons (from 2015/16 to 2018/19) were recorded using an optical tracking system (i.e., ChyronHego),
and the data were analyzed via Mediacoach®. Total distance (TD), and TD > 21 km·h−1 covered
with and without ball possession were analyzed using a Linear Mixed Model, taking into account
the contextual variables time winning and losing. Results showed that TD and TD > 21 km·h−1
covered by central midﬁelders (0.01 and 0.005 m/min, respectively), wide midﬁelders (0.02 and
0.01 m/min, respectively), and forwards (0.03 and 0.02 m/min, respectively) signiﬁcantly increased
while winning (p < 0.05). By contrast, TD and TD > 21 km·h−1 covered by central defenders
(0.01 and 0.008 m/min, respectively) and wide defenders (0.06 and 0.008 m/min, respectively)
signiﬁcantly increased while losing (p < 0.05). In addition, for each minute that teams were winning,
total distance with ball possession (TDWP) decreased, while, for each minute that teams were
losing, TDWP increased. Instead, TDWP > 21 km·h−1 obtained opposite results. Total distance
without ball possession increased when teams were winning, and decreased when teams were losing.
Therefore, the evolution of scoreline signiﬁcantly inﬂuences tactical–technical and physical demands
on soccer matches.
Keywords: contextual variables; match running performance; ball possession; positional; professional
soccer
1. Introduction
Context-related variables are considered the most inﬂuencing variables on match
physical demands in soccer [1]. Time–motion analysis research has reported a large amount
of information about context-related variables such as match status, match location, and
opponent level [2]. Speciﬁcally, it has been previously shown that ﬁnal and partial match
status (analyzed by epochs of time—i.e., 15-min periods or half-time) modify match physi-
cal demands as well as ball possession [3,4]. However, this method of analysis is probably
to do with the interaction of other variables such as the evolution of the match-scoreline [5].
Regardless of ﬁnal match status, the time each team was leading, drawing, or trailing
during a match could be different, with matches taking place where a team has won
throughout 70 min (i.e., team A scored a goal in the 20th min and team B did not score) or
matches where a team has won throughout 1 min (i.e., teams were drawing over the match,
and one team scored a goal in the 89th min). Moreover, it is possible that one team that was
ahead for a long time would end up losing on the ﬁnal scoreline. Match physical demands
Sensors 2021, 21, 6843. https://doi.org/10.3390/s21206843
https://www.mdpi.com/journal/sensors
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are believed to depend on evolving scoreline (i.e., whether a team is winning or losing)
since, when a team is losing, players try to reach their maximal physical capacity in order to
draw or win the match [2]. Therefore, this limitation could be solved by taking into account
the minutes that teams were ahead and behind during a match separately. According to
our knowledge, the inﬂuence of time winning and time losing on position-speciﬁc match
physical demands according to the evolution of the scoreline is less known.
Match status has been arguably analyzed enough to prove that it inﬂuences soccer
teams’ behavior [6]. In this vein, Lago–Peñas [7] reported that losing teams frequently
increase their percentage of possession; meanwhile, certain winning teams preferred
counterattacking or playing directly. In addition, match status clearly impacts teams
playing style [5], and both variables (i.e., match status and playing style) also inﬂuence
match physical demands; however, several studies about this topic have drawn the opposite
conclusions. For instance, elite Spanish soccer players performed less high-intensity
distance (19 km·h−1) when winning than when they were losing, since winning is a
comfortable status, it is possible that players assume a ball contention strategy, keeping the
game slower, which results in lower speeds [8]. Moreover, Castellano et al. [2] analyzed
one Spanish team of LaLiga and they showed that the distances covered at high intensity
by the reference team were greater when the result was adverse. Moalla et al. [3] obtained
the same results in a study from the Stars League during 2013/14 and 2014/15 seasons.
Conversely, during qualifying round matches of the World Cup 2010, drawing teams
covered a lower average speed than the winning and losing teams [9]. In this line, variables
that determine the intensity of the game (maximum speed and frequency of high-intensity
activity) in a professional Brazilian football team were signiﬁcantly lower when the team
lost [10], meanwhile greater intensity running distances were observed in matches that the
team won as opposed to losing [11]. Therefore, coaches should take into account the match
status to analyze the external load implied by the match [12].
However, soccer players could have not been affected by this contextual variable in
the same way due to playing style, since playing style changes associated with match status
could affect different players differently in ways that are position-speciﬁc [13]. For example,
in the German Bundesliga during the 2014/15 season, central defenders and full-backs
covered shorter distances at high intensity in won matches than in lost matches (p < 0.01);
however, forwards covered signiﬁcantly longer total distance in won matches than in
drawn and lost matches (p < 0.05) [14]. Despite these conclusions, position-speciﬁc match
physical demands can also vary depending on the evolution of scoreline status. In this vein,
when a team was winning, during preseason matches of the 2011/12 season Australian
League soccer, the average speed was 4.17% lower than when the team was drawing
(p < 0.05) [15]. Regarding player position-speciﬁc data, in the English Premier League,
Redwood-Brown et al. [16] found midﬁelders covered more distance at high intensity when
level, defenders more when losing, and attackers more when winning. Similarly, losing
status increased the total distance covered by defenders from Spanish First soccer league,
while attacking players showed the opposite trend [17]. Therefore, these previous studies
have suggested that, due to the player position, players perform different tactical roles,
and match status and the associated playing style changes could have different inﬂuences
on match running performance by positions.
The knowledge about the inﬂuence of time that teams were ahead or behind on
position-speciﬁc match physical demands could have important practical applications
during the competitive season to program the training load in a more strategic way based
on physical data [12]. In addition, less is known about the inﬂuence of time which teams
spend winning or losing on position-speciﬁc match physical demands. Therefore, the main
objective of the present study was to analyze the inﬂuence of time winning and losing
on position-speciﬁc match physical demands in the top Spanish soccer league across four
seasons (2015/2016–2018/2019). As a secondary objective, the study also aimed to analyze
the match physical demands with and without ball possession according to time winning
and time losing.
Sensors 2021, 21, 6843
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Based on previous ﬁndings obtained by the aforementioned studies, the following
hypotheses were proposed. Firstly, concerning match physical demands with and without
ball possession, it was expected that total distance with ball possession would be less
during time winning [7]. Secondly, concerning position-speciﬁc match physical demands,
it was expected that total distance would be greater in attackers during time winning and
defenders during time losing, based on previous results [16,17].
2. Materials and Methods
2.1. Participants
The sample comprised 36,883 individual match observations of 1037 professional
soccer players who competed in the First Spanish professional soccer league (i.e., LaLiga
Santander) over four consecutive seasons (from 2015/16 to 2018/19). All players who
participated in matches (starters and non-starters) and played 10 min at least were included.
Only goalkeepers were excluded. According to previous studies [18], players were divided
into ﬁve position-speciﬁc groups: Central Defenders (CD; n = 6787 observations), Wide
Defenders (WD; n = 6530 observations); Central Midﬁelders (CM; n = 6826 observations);
Wide Midﬁelders (WM; n = 8394 observations); Forwards (FW; n = 8346 observations).
Data were provided to the authors by LaLigaTM, and the study received ethical approval
from the University of Extremadura; Vice-Rectorate of Research, Transfer and Innovation-
Delegation of the Bioethics and Biosafety Commission (Protocol number: 239/2019).
2.2. Procedure and Variables
Match physical demands data were collected by an optical tracking system
(ChyronHego®; TRACAB, New York, NY, USA). This multi-camera tracking system con-
sists of 8 different super 4K-High Dynamic Range cameras situated strategically to follow
and track the 22 players on the ﬁeld throughout the match. These cameras ﬁlm from several
angles and analyze X and Y coordinates of each player, providing real-time tracking with
data recorded at 25 Hz. Mediacoach® is also based on data correction of the semi-automatic
video technology (the manual part of the process) [19]. The validity and reliability of the
Tracab® video tracking system has been analyzed, reporting average measurement errors
of 2% for total distance covered [20–22].
The physical performance variables used for this study were categorized according
to the ball possession as follows [23,24]: with possession (WP) and without possession
(WOP). The following variables were studied for each of these categories: total distance
(m) covered by players (i.e., TD) and total distance covered at more than 21 km·h−1 (i.e.,
TD > 21 km·h−1).
To determine if the scoreline inﬂuenced position-speciﬁc match physical demands, the
cumulative time that each team was losing or winning during a match was included in the
analysis (not the ﬁnal match result). For example, if team A scored a goal in the 20th min
and team B equalized in the ﬁnal minute, team A was classiﬁed as losing for 0 min and
winning for 70 min, while team B was classiﬁed as losing for 70 min and winning for 0 min
2.3. Data Analysis
All statistical analyses were performed using R-studio [25]. A Linear Mixed Model
(LMM) was conducted for each of the physical variables using the lme4 package [26]. This
model allows for the analyzing of data with a hierarchical structure in nested units and
has demonstrated its ability to cope with unbalanced and repeated-measures data [27]. For
example, variables related to the distance covered in matches are nested for players (i.e.,
each player has a record for every match they have participated in), and players are nested
into teams. Also, cumulative times spent winning or losing are nested into matches and
these matches can also be nested into teams. This represents a threefold levels structure,
where teams are the topmost unit in the hierarchy.
A general multilevel-modelling strategy was applied [27], where ﬁxed and random
effects had been included in different steps from the simplest to the most complex. First,
Sensors 2021, 21, 6843
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unconditional models were analyzed exclusively including dependent variables (i.e., dis-
tance variables) to check if the grouping variables at levels 2 and 3 (i.e., players and teams)
signiﬁcantly affected the intercept (mean) of each dependent variable. These models may
be used as baselines for comparing more complex models. Later, different models were
performed for each of the dependent variables, setting as ﬁxed effects the position of
the players and the time winning/losing. Following the procedure proposed by Heck &
Thomas [27], models with different random effects (intercepts and slope) were created
for each variable. A model comparison for each step was performed using the Akaike
Information Criterion (AIC) [28] and a chi-square likelihood ratio test [29], where a lower
value represented a ﬁtter model. Final models presented in Tables 1 and 2 (with random
intercept and slope effect) were chosen according to better values of AIC, log-likelihood,
and signiﬁcant effect of variables. Maximum Likelihood (ML) estimation for model com-
parison and for the ﬁnal model of each physical variable was used, the best model, again,
using Restricted Maximum Likelihood (REML) estimation, was reﬁtted. Marginal and
conditional R2 metrics [30] for each LMM to provide some measure of effect sizes were
reported. Signiﬁcance level was set at p < 0.05.
For a suitable interpretation of the results, the time winning/losing was group-mean
centered, being centered to the team’s mean in each season.
Table 1. Differences by ball possession of position-speciﬁc total distance covered according to the scoreline evolution.
CD
WD
CM
WM
FW
TD
(m/min)
Intercept
107.30
b, c, d, e
109.90
a, c, d, e
116.10
a, b
115.90
a, b
115.60
a, b, c
Slope Time Winning
−0.006
c, d, e
−0.005
c, d, e
0.01
a, b, d, e
0.02
a, b, c, e
0.03
a, b, c, d
Slope Time Lossing
0.01
c, d, e
0.006
c, d, e
−0.003
a, b, d, e
−0.02
a, b, c, e
−0.02
a, b, c, d
TDWP
(m/min)
Intercept
35.93
b, c, d, e
38.41
a, c, d, e
42.21
a, b, e
42.54
a, b, e
43.04
a, b, c, d
Slope Time Winning
−0.03
−0.04
e
−0.04
e
−0.04
−0.03
b, c
Slope Time Lossing
0.03
0.03
0.03
e
0.02
0.02
c
TDWOP
(m/min)
Intercept
42.50
b, c, d
43.80
a, c, d, e
47.39
a, b, d, e
45.36
a, b, c, e
42.16
b, c, d
Slope Time Winning
0.01
c, d, e
0.02
d, e
0.03
a, d, e
0.04
a, b, c
0.01
a, b, c
Slope Time Lossing
0.002
d, e
−0.003
d, e
−0.003
d, e
−0.01
a, b, c
−0.02
a, b, c
Note. CD = Central defenders; WD = Wide defenders; CM = Central midﬁelders; WM = Wide midﬁelders; FW = Forwards; TD = Total
distance; TDWP = Total distance with ball possession; TDWOP = Total distance without ball possession; a = signiﬁcant differences compared
to central defenders; b = signiﬁcant differences compared to wide defenders; c = signiﬁcant differences compared to central midﬁelders;
d = signiﬁcant differences compared to wide midﬁelders; e = signiﬁcant differences compared to forwards.
Sensors 2021, 21, 6843
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Table 2. Differences by ball possession of position-speciﬁc total distance covered at more than 21 km·h−1 according to the
scoreline evolution.
CD
WD
CM
WM
FW
Total distance > 21 km·h−1
(m/min)
Intercept
5.74
b, c, d, e
6.68
a, d, e
6.68
a, d, e
7.24
a, b, c, e
7.57
a, b, c, d
Slope Time Winning
−0.008
c, d, e
−0.005
c, d, e
0.005
a, b, d, e
0.01
a, b, c, e
0.02
a, b, c, d
Slope Time Lossing
0.008
c, d, e
0.008
c, d, e
−0.004
a, b, d, e
−0.001
a, b, c, e
−0.01
a, b, c, d
Total distance with ball
possession > 21 km·h−1
(m/min)
Intercept
2.21
b, c, d, e
2.81
a, c, d, e
3.14
a, b, d, e
3.57
a, b, c, e
4.01
a, b, c, d
Slope Time Winning
0.001
c, d, e
−0.001
c, d, e
0.005
a, b, e
0.007
a, b, e
0.01
a, b, c, d
Slope Time Lossing
−0.001
a, c, d, e
0.001
a, b, d, e
−0.006
a, b, c
−0.009
a, b, c
−0.009
a, c, d, e
Total distance without ball
possession > 21 km·h−1
(m/min)
Intercept
3.54
b, c, d, e
3.80
a, c, d, e
3.37
a, b, e
3.40
a, b, e
3.16
a, b, c, d
Slope Time Winning
−0.008
b, c, d, e
−0.005
a, c, d, e
−0.001
a, b, d, e
0.002
a, b, c
0.004
a, b, c
Slope Time Lossing
−0.009
b, c, d, e
0.007
a, c, d, e
0.002
a, b, d, e
−0.001
a, b, c, e
−0.002
a, b, c
Notes. CD = Central defenders; WD = Wide defenders; CM = Central midﬁelders; WM = Wide midﬁelders; FW = Forwards; a = signiﬁcant
differences compared to central defenders; b = signiﬁcant differences compared to wide defenders; c = signiﬁcant differences compared to
central midﬁelders; d = signiﬁcant differences compared to wide midﬁelders; e = signiﬁcant differences compared to forwards.
3. Results
Firstly, the Wald test and intraclass correlation coefﬁcient (ICC) suggested statistically
signiﬁcant variability in the distances covered by players according to time winning and
losing (ICC > 0.10); therefore, LMM was justiﬁed for the purpose of the study. Also, AIC
suggested that the twofold levels model was the one ﬁtter for this purpose.
Secondly, Table 1 shows the differences of TD covered according to ball possession
and to the scoreline evolution by player positions. Regardless of scoreline, CM covered
signiﬁcantly greater TD than the rest of the players (p < 0.05). TD covered by CD and WD
decreased signiﬁcantly with respect to CM, WM, and FW (p < 0.05) for each minute that
teams were ahead. By contrast, for each minute that teams were trailing, TD covered by
CD and WD increased signiﬁcantly with respect to CM, WM, and FW (p < 0.05).
During the match, FW covered signiﬁcantly greater TDWP than CD, WD, CM, and
WM (p < 0.05). However, for each minute that teams were ahead, TDWP decreased for
all positions. Signiﬁcant differences were found between WD and CM with respect to FW
(p < 0.01). On the contrary, for each minute that teams were trailing, TDWP increased for
all positions. Signiﬁcant differences between CM and FW were observed (p < 0.05).
On the other hand, CM covered TDWOP signiﬁcantly greater than the rest of the
players (p < 0.05). However, for each minute that teams were ahead, TDWOP increased for
all positions. CM and WM signiﬁcantly increased TDWOP with respect to CD, WD, and
FW (p < 0.01). By contrast, for each minute that teams were trailing, TDWOP signiﬁcantly
decreased for all positions, except CD (p < 0.05).
Thirdly, Table 2 shows the differences by ball possession of TD > 21 km·h−1 according
to the scoreline evolution by player positions. Regardless of the scoreline, FW covered
TD > 21 km·h−1 signiﬁcantly greater than the rest of the players (p < 0.05). However, for
each minute that teams were ahead, CD and WD signiﬁcantly decreased TD > 21 km·h−1
with respect to CM, WM, and FW (p < 0.05). By contrast, for each minute that teams were
trailing, CD and WD signiﬁcantly increased TD > 21 km·h−1 with respect to CM, WM, and
FW (p < 0.05).
During the match, FW covered TD > 21 km·h−1 with ball possession signiﬁcantly
greater than CD, WD, CM, and WM (p < 0.05). Moreover, for each minute that teams were
Sensors 2021, 21, 6843
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ahead, TD > 21 km·h−1 signiﬁcantly increased for all positions, except WD (p < 0.05). By
contrast, for each minute that teams were trailing, TD > 21 km·h−1 signiﬁcantly decreased
for all positions, except WD (p < 0.05).
Finally, WD covered signiﬁcantly greater TD > 21 km·h−1 without ball possession than
the rest of the players (p < 0.01). For each minute that teams were ahead, TD > 21 km·h−1
without ball possession covered by WM and FW increased signiﬁcantly, with respect to
CD, WD, and CM (p < 0.05). Likewise, for each minute that teams were trailing, WD and
CM signiﬁcantly increased TD > 21 km·h−1 without ball possession, with respect to CD,
WD and FW (p < 0.05).
4. Discussion
The aim of the present study was to analyze the inﬂuence of time winning and losing
on position-speciﬁc match physical demands in the top Spanish professional soccer league
across four seasons (from 2015/2016 to 2018/2019). Subsequently, match physical demands
with and without ball possession according to time winning and losing were examined.
The main results showed that TDWP was less while teams were winning, while it was
greater while teams were losing. In addition, TDWOP increased while teams were winning,
while it decreased while teams were losing. Finally, TD and TD > 21 km·h−1 covered by
CM, WD, and FW were greater while teams were winning, while TD and TD > 21 km·h−1
covered by CD and WD were greater while teams were losing.
Firstly, it had been hypothesized that TDWP would be less during time winning
(Hypothesis 1). Our results showed that TDWP decreased during time winning for all player
positions and increased during time losing, therefore Hypothesis 1 was conﬁrmed. These
results suggest that during time winning, teams frequently decrease their percentage of
possession, which could be associated to defending closer to the goal, counterattacking,
or playing directly [7]. It has also been shown that teams that were ahead performed a
higher number of defensive actions which, in turn, are related to lower ball possession
levels during a match [31]. By contrast, during time losing, these results suggest teams
frequently increase their percentage of possession, attacking closer to the other team’s
goal [7]. Evidence has reported that successful teams normally have longer possession
times than less successful teams [23] or that ball possession might increase in teams that
are either losing or trying to tie the match [32]. Therefore, our results reported the need to
take into account the evolution of the scoreline.
In contrast, TDWP >21 km·h−1 increased during time winning for all player positions
and decreased during time losing. A possible reason to explain this result could be the fact
that teams adopt an indirect playing style to perform counterattacks [7]. Therefore, players
need to execute high-intensity speciﬁc technical and tactical tasks on the pitch when they
are in ball possession, such as receiving passes and crosses on the run, followed by dribbling
the ball in the opponent’s area to obtain a goal [33]. In fact, it has been demonstrated that
high-intensity actions are important within decisive situations in professional football [34].
Furthermore, Yang et al. [24] reported that total sprint distance was signiﬁcantly greater
for the best-ranked teams compared to lower-ranked teams, highlighting the importance
of sprinting for tactical teamwork that generates offensive actions. A systematic review
conducted by Lago–Peñas & Sanromán–Álvarez [35] pointed out that successful teams
covered greater high-intensity running distance in ball possession. Therefore, our results
suggest that teams perform a greater number of high-intensity actions in ball possession
while winning or trying to maintain the advantage; meanwhile, TDWP decreases.
During time winning, TDWOP increased for all player positions and decreased dur-
ing time losing for all player positions, except CD. One potential reason for this situa-
tion could be the fact of ball possession decrease, like Lago-Peñas [7] reported, showing
that winning teams preferred counterattacking or playing directly. On the other hand,
research has shown that lower-ranked teams covered signiﬁcantly greater TDWOP com-
pared with better-ranked teams, which likely represented a greater match time under-
taking defensive activities by these teams [24]. Our ﬁndings disagree with those from
Sensors 2021, 21, 6843
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other studies where ball possession increased when teams were ahead [36]. Similarly,
TDWOP > 21 km·h−1 covered by WM and FW signiﬁcantly increased when teams were
ahead, and TDWOP > 21 km·h−1 covered by WD and CM increased when teams were
behind. This fact could be explained due to that, when the team is not in possession of
the ball, the forwards often perform high-intensity activities (high pressing), attempting to
recover the lost ball [14,37].
Secondly, it had been hypothesized that TD would be greater in attackers while
teams were ahead and in defenders when teams were losing (Hypothesis 2). The results
showed that TD and TD > 21 km·h−1 covered by CM, WM, and FW signiﬁcantly increased
when teams were ahead (p < 0.05), and TD and TD > 21 km·h−1 covered by CD and WD
signiﬁcantly increased when teams were losing (p < 0.05). These ﬁndings are in line with
previous studies that found that attackers covered more distance at high intensity when
winning and defenders more when losing [16]. Lago–Peñas et al. [17] also reported that
losing status increased total distance covered by defenders, while attacking players showed
the opposite trend. Thus, it seems to be conﬁrmed that CM, WM, and FW cover greater
TD when winning and CD and WD when losing, therefore Hypothesis 2 was accepted.
A possible explanation may be due to attackers´ work rate of the opposing team since,
when the opposing team is ahead or chasing a goal, attackers maintain a high work rate,
implying a defenders´ high work rate [16,38]. In addition, similar results were obtained by
Andrzejewski et al. [14], showing that defenders covered shorter distances at high intensity
in lost matches, while forwards covered longer total distances in won matches. Another
possible reason could be the playing style that the team adopted, for example, a direct style
of play when teams are winning can induce higher match intensity in running from the
attackers [7,11]. In particular, these ﬁndings indicate that physical demands vary according
to position-speciﬁcities and the evolution of the scoreline.
4.1. Study Limitations and Future Directions
The present study increases the knowledge about this research topic; however, a
number of limitations could be recognized with a view to future research. First, other
context-related variables such as match location or opposing team level were not consid-
ered. Ball possession percentages of teams have been also not considered, and it would be
interesting to analyze this variable when teams are winning or losing with the interaction of
match physical demands. Moreover, the comparison between ﬁve players’ positions accord-
ing to previous studies was analyzed [18]; however, the existence of more player positions
is possible than have been previously analyzed, therefore it would be interesting to conduct
a comparison between more player positions. In addition, further research is required,
considering several factors such as the playing style, since the player position could depend
on the playing style of teams. Finally, research has reported that external load variables
such as accelerations and decelerations belong to match physical demands [39], in which
case it would be necessary to know the full player´s work rate, including these variables.
4.2. Practical Applications
The ﬁndings of this study provide useful information on the variability of match
physical demands for practitioners in Spanish professional soccer. In particular, the study
extends previous research demonstrating that time that teams were winning or losing
inﬂuences both match physical demands and ball possession. This information could help
strength and conditioning coaches with personalizing recovery work after match play,
according to the different physical efforts performed in matches. Finally, goals scored are
the most important of all critical events, therefore the evolution of the scoreline should
be taken into account during training sessions to optimize physical aspects of soccer
performance. In this vein, it is necessary to know how these situations inﬂuence the
player’s capacity to deal with critical events in a match [40].
Sensors 2021, 21, 6843
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5. Conclusions
The main ﬁndings reported that the evolution of scoreline signiﬁcantly inﬂuences
match tactical–technical and physical demands. First, TDWP was less while teams were
winning, while it was greater while teams were losing, and TDWOP evolved conversely;
therefore, teams modify their playing style and tactical behavior according to the demands
of matches. Secondly, attackers covered greater distances when winning, and defenders
covered greater distances when losing; therefore, professional soccer players regulate their
physical efforts according to the periods of the game. Finally, the inﬂuence of scoreline is
reﬂected in changes in the teams and players’ tactical–technical and physical demands as a
response to the evolution of match outcome.
Author Contributions: Conceptualization, T.G.-C.; methodology, T.G.-C., J.C.P.-B. and J.D.-G.; formal
analysis, T.G.-C.; investigation, J.C.P.-B., J.D.-G., M.A.L.-G., D.L.-T., R.L.d.C., R.R. and T.G.-C.; re-
sources, R.L.d.C. and R.R.; writing—original draft preparation, J.C.P.-B., J.D.-G. and D.L.-T.; writing—
review and editing, M.A.L.-G. and T.G.-C.; funding acquisition, R.L.d.C. and R.R. All authors have
read and agreed to the published version of the manuscript.
Funding: This research was funded by the European Regional Development Fund (ERDF), the
Government of Extremadura (Department of Economy and Infrastructure) and LaLiga Research and
Analysis Sections.
Institutional Review Board Statement: The study was conducted according to the guidelines of
the Declaration of Helsinki, and approved by the Institutional Review Board of the University of
Extremadura; Vice-Rectorate of Research, Transfer and Innovation-Delegation of the Bioethics and
Biosafety Commission (Protocol number: 239/2019).
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: Restrictions apply to the availability of these data. Data was obtained
from LaLiga and are available with the permission of corresponding author.
Conﬂicts of Interest: The authors declare no conﬂict of interest. Also, the funders had no role in
the design of the study; in the collection, analyses, or interpretation of data; in the writing of the
manuscript, or in the decision to publish the results.
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The Influence of Time Winning and Time Losing on Position-Specific Match Physical Demands in the Top One Spanish Soccer League.
Ponce-Bordón, José C,Díaz-García, Jesús,López-Gajardo, Miguel A,Lobo-Triviño, David,López Del Campo, Roberto,Resta, Ricardo,García-Calvo, Tomás