Citation: Olaizola, A.; Errekagorri, I.;
Lopez-de-Ipina, K.; María Calvo, P.;
Castellano, J. Comparison of the
External Load in Training Sessions
and Ofﬁcial Matches in Female
Football: A Case Report. Int. J.
Environ. Res. Public Health 2022, 19,
15820. https://doi.org/10.3390/
ijerph192315820
Academic Editors: José Alberto Frade
Martins Parraca, Bernardino
Javier Sánchez-Alcaraz Martínez
and Diego Muñoz Marín
Received: 29 October 2022
Accepted: 25 November 2022
Published: 28 November 2022
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International  Journal  of
Environmental Research
and Public Health
Article
Comparison of the External Load in Training Sessions and
Ofﬁcial Matches in Female Football: A Case Report
Aratz Olaizola 1,*
, Ibai Errekagorri 1,2
, Karmele Lopez-de-Ipina 3,4
, Pilar María Calvo 4
and Julen Castellano 1,2
1
Department of Physical Education and Sport, Faculty of Education and Sport, University of the Basque
Country (UPV/EHU), 01007 Vitoria-Gasteiz, Spain
2
Society, Sports and Physical Exercise Research Group (GIKAFIT), Department of Physical Education and
Sport, Faculty of Education and Sport, University of the Basque Country (UPV/EHU),
01007 Vitoria-Gasteiz, Spain
3
Department of Psychiatry, Cambridge Neuroscience, University of Cambridge, Cambridge 01223, UK
4
Department of Computers’ Arquitecture and Technology, University of the Basque Country (UPV/EHU),
Paseo M. Lardizabal, 1, 20018 San Sebastian, Spain
*
Correspondence: olaizola525@gmail.com
Abstract: The objective of this study was to compare the external load of training sessions using as a
reference an ofﬁcial competition match in women’s football in order to ﬁnd if the training sessions
replicate the competition demands. Twenty-two semi-professional football players were analyzed
during 17 weeks in the ﬁrst phase of the competitive period of the 2020–2021 season of Spanish
women’s football. In addition to the competition (Ofﬁcial Matches, OM), four types of sessions
were distinguished: strength or intensity (INT), endurance or extensity (EXT), velocity (VEL), and
activation or pre-competitive (PREOM). The external load variables recorded were total distance
(TD), high-speed running (HSR), sprint (Sprint), accelerations (ACC2), decelerations (DEC2), player
load (PL), distance covered per minute (TDmin), high metabolic load distance (HMLD), and total
impacts. The main results were that the external load demanded was different according to the type
of session, being, in all cases, much lower than OM. The variables referring to the neuromuscular
demands (ACC2 and DEC2) were higher in the INT sessions, the TD variable in the EXT sessions
and the velocity variables (HSR and Sprint) in the VEL sessions. We can conclude that there was an
alternating horizontal distribution of training loads within the competitive micro-cycle in women’s
football, although the order was not the usual one for tactical periodization.
Keywords: team sport; women; external load; periodization; electronic performance; tracking systems
1. Introduction
In recent decades, there has been exponential global development of women’s football,
both in its practice and in the entities and institutions that promote and manage it [1,2].
This has been accompanied by a greater professionalization in elite game standards, in
addition to an increase in audiences, leading to the creation of professional leagues and
clubs, generating greater professionalization [3]. The scientiﬁc interest in women’s football
has not been left out of this reality, which is why competition analysis is now a focus with
the aim of deepening its knowledge [4–7].
It is essential to know the demands of women’s competition [8] in order to have
reference values to guide training content. In a complementary way, the evaluation of the
training process is essential to verify the effectiveness of the intervention and to search
for the best strategy to stimulate the athlete, that is, to distribute training and recovery [9]
in order to optimize physical condition [10]. It is also important to pay attention to load
management in order to reduce the probability that players could suffer over-training or
even injury [11–13].
Int. J. Environ. Res. Public Health 2022, 19, 15820. https://doi.org/10.3390/ijerph192315820
https://www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2022, 19, 15820
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In men’s football, the two usual planning strategies are the structured micro-cycle
together with tactical periodization [10,14]. Elite football teams use the latter because
the proposed content prioritizes technical/tactical objectives over conditional and psy-
chological capabilities simultaneously [15]. Previous studies [4,14,16–19] agree that the
planning strategy of a competitive micro-cycle with a single competitive game is three
main acquisition sessions during the week in order to prepare and sustain physical abilities,
such as strength, endurance, and velocity. This ﬁrst part of acquisition is followed by a
load reduction phase at the end of the week (tapering phase) to ensure greater freshness
and, therefore, a greater willingness to compete [18,20]. Both phases result in a horizontal
alternation in the distribution of conditional demands during the micro-cycle [16,17].
In order to improve the knowledge of types of load management strategies in women’s
football in a novel way, the objective of the present study is to describe the external load
in the different types of training and competitive matches in women’s football during a
competitive micro-cycle. The starting hypothesis is that there is a horizontal alternation
in the conditional demand between the training sessions in the competitive micro-cycle,
but none of the sessions replicates the competition demand. In this sense, the results of this
study will allow increasing the information on the type of periodization that is proposed in
an elite women’s football team, which could help to facilitate load management in women’s
football, which is still little known and under research.
2. Materials and Methods
2.1. Participants
A total of 22 semi-professional female football players (age: 24.6 ± 4.0 years; height:
163.9 ± 5.0 cm; weight: 58.5 ± 4.2 kg; skinfolds (i.e., the sum of 6 skinfolds: triceps,
subscapular, supraspinal, abdominal, front thigh, and medial calf): 65.4 ± 17.9 mm) took
part in the study. The data recording was carried out during 17 weeks of the competitive
period of the Second Women’s Football Division (Reto Iberdrola) during the 2020–2021
season. Usually, the team completed four days of training and one day of competition
per week.
2.2. Procedures
In order to obtain position data, the players were monitored with WIMU PRO devices
(RealTrack Systems, Almeria, Spain) using the global positioning system (GPS). The GPS de-
vice used in this study can operate at 10 Hz, and it is compatible with the Galileo and Ameri-
can satellite constellation, which seems to provide more precision [21]. For the analysis, data
were collected on outdoor football ﬁelds without any possibility of infrastructure interfering
with the data collection. During the sessions, a mean of 12 satellites were connected with
each device. The value of DDOP was 0.95. This equipment and its measurements are valid
and reliable using the GNSS for time-motion analysis in football (distance covered variable:
accuracy = 0.69–6.05%, test–retest reliability = 1.47, inter-unit reliability = 0.25; mean veloc-
ity variable: accuracy = 0.18, intra-class correlation = 0.95, inter-unit reliability = 0.03) [22],
and has been awarded with the FIFA Quality Performance certiﬁcate. Each WIMU PRO
device was placed in a vertical position between the players’ shoulder blades, in a pocket
of a speciﬁc chest vest (dimensions of the devices = 81 × 45 × 16 mm). The GPS devices
were activated 15 min before the start of each session or match in accordance with the
manufacturer’s instructions. All the players were familiar with the use of GPS. Only the
players that completed ofﬁcial matches or training sessions were included in the analy-
sis. To avoid possible differences between devices, during the entire registration period,
each player wore the same device [23,24]. The records were downloaded using the SPRO
software (RealTrack Systems, Almeria, Spain) after the end of each session. Once the data
were ﬁltered through the software, they were imported into a Microsoft Excel spreadsheet
(Microsoft Corporation, Washington, DC, USA) to conﬁgure a matrix.
Int. J. Environ. Res. Public Health 2022, 19, 15820
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2.3. Physical Variables
The duration of the session was recorded considering only the effective time, that is, the
time in which the players were active, excluding times of inactivity (e.g., stoppages between
tasks). The external load variables were: total distance (TD, in m); high speed running
(HSR, in m), established as 60% of the maximum individual velocity of the participants [25];
sprint (Sprint, in m), deﬁned as the distance accumulated above 85% of the maximum
individual velocity [26]; accelerations over 2 m/s2 (ACC2, in n); decelerations of less than
−2 m/s2 (DEC2, in n); player load (PL, in au), distance traveled per minute (TDmin,
in m/min1); high metabolic load distance (HMLD, in m), deﬁned as the distance covered
by a player when their metabolic power is above 25.5 W/kg1, ratios per kilogram [14]; and,
total impacts (Total Impacts, in n) using an Earth sensor to calculate the three axes value
of the module. As for the choice of the maximum individual velocity, the highest value
recorded during the 17-week period of the study was chosen, considering both the training
sessions and the competition.
2.4. Type of Training Sessions and Ofﬁcial Matches
Apart from the ofﬁcial matches (OM, n = 12), the types of sessions were differentiated
based on the priority conditional objective that was developed: strength or intensity session
(INT, n = 10); endurance or extensity session (EXT, n = 15); velocity session (VEL, n = 7);
and activation session (PREOM, n= 14). In total, 805 recordings were collected from ofﬁcial
matches (n = 49) and 756 training sessions, distributed as follows: VEL = 114, INT = 173,
EXT = 239, and PREOM = 230. The number of records per player was 36.8 ± 10.6.
The order of the sessions in the training micro-cycle was conditioned to the number
of days after (OM+) and before (OM−) of the OM, following the proposal of previous
studies [10,14].
The VEL session was usually the ﬁrst acquisition session, located 2 days after the OM
(OM + 2) and 5 or 6 days before the next ofﬁcial match (OM − 6 or OM − 5), characterized
by velocity work, locomotive-oriented and based on tasks of intermittent nature or in waves
(with breaks of 1 or 2 min between drills). The tasks were mostly carried out with goalposts
and goalkeepers and were made up of a large relative space per player (e.g., >250 m2).
The INT session was the second acquisition session of the week, usually located 3 or 4
days after the OM (OM + 3 or OM + 4) and 3 or 4 days before the next competition (OM
− 3 or OM − 4), characterized by neuromuscular and mechanically-oriented work, based
on reduced and positional games, with a relative space per player of less than 100 m2 and
with a number of participants ranging from one to six per team.
The EXT session was usually the third acquisition session of the micro-cycle, located 4
or 5 days after the OM (OM + 4 or OM + 5) and 2 or 3 days before the next competition
(OM − 2 or OM − 3), characterized by cardiovascular work, based on large-format tasks,
that is, with a moderate to high number of participants per team (>6), in a relative space
equal to or greater than 250 m2 per player, and with goalposts and goalkeepers.
Pre-match day (PREOM) was the ﬁne-tuning session. It was always conducted the day
before match day (OM − 1). The contents that were developed in it were activation tasks
based on activities with a large number of participants (>6) in a medium relative space
(equal to or less than 250 m2 per player) or small (equal to or less than 100 m2 per player)
with a polarized orientation and a tactical and strategic approach.
The last day of the week was match day (OM). To calculate the load on the day of the
competition, the previous warm-up carried out by the players was taken into account in
addition to the two parts of the match, which had the following approximate load: duration
was 20.1 ± 2.1 min, and the physical demands were as follows: TD: 1280 ± 266 m, HSR:
64.3 ± 37.7 m, Sprint: 5 ± 10.7 m, ACC2: 27.9 ± 9.6 n, DEC2: 28.4 ± 9.6 n, PL 20.6 ± 4.3 au
and TDmin 64 ± 12.3 (m/min1).
Int. J. Environ. Res. Public Health 2022, 19, 15820
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2.5. Statistical Analysis
Descriptive statistics data from variables were presented using mean and standard
deviation. Tests for normality (Shapiro–Wilk) and equality of variances (Levene) were
applied. The null hypothesis was accepted because the distribution of the data met the
normality criterion. Furthermore, the variances were homogeneous. Therefore, a one-way
ANOVA analysis of variance for independent samples was used to test for differences in
the variables between the different sessions (INT, EXT, VEL, PREOM, and OM). Signiﬁcant
results were then analyzed using post hoc Tukey’s test. Effect size (ES) was also calculated
to determine meaningful differences with magnitudes classiﬁed as [27] trivial (<0.2), small
(>0.2–0.6), moderate (>0.6–1.2), large (>1.2–2.0), and very large (>2.0–4.0). The level of
signiﬁcance was set at p < 0.05. The statistical analysis was conducted using the software
JASP 0.14.1 (University of Amsterdam, Amsterdam, The Netherlands) and a customized
Microsoft Excel spreadsheet (Microsoft Corporation, Washington, DC, USA) for Windows.
3. Results
Figure 1 shows the total time (min), effective time (min), and density (%) of the training
and competition sessions. There were signiﬁcant differences (p < 0.05) between training
sessions for all variables. The PREOM session had the lowest (p < 0.05) volume (total and
effective time) but with higher density than the VEL and INT sessions. The INT session
had the highest volume (total and effective time) but with a lower density than the EXT
and PREOM sessions and higher than VEL.
TDmin 64 ± 12.3 (m/min ). 
2.5. Statistical Analysis 
Descriptive statistics data from variables were presented using mean and standa
deviation. Tests for normality (Shapiro–Wilk) and equality of variances (Levene) were a
plied. The null hypothesis was accepted because the distribution of the data met the n
mality criterion. Furthermore, the variances were homogeneous. Therefore, a one-w
ANOVA analysis of variance for independent samples was used to test for differences
the variables between the different sessions (INT, EXT, VEL, PREOM, and OM). Sign
cant results were then analyzed using post hoc Tukey’s test. Effect size (ES) was also c
culated to determine meaningful differences with magnitudes classified as [27] triv
(<0.2), small (>0.2–0.6), moderate (>0.6–1.2), large (>1.2–2.0), and very large (>2.0–4.0). T
level of significance was set at p < 0.05. The statistical analysis was conducted using t
software JASP 0.14.1 (University of Amsterdam, Amsterdam, Kingdom of the Neth
lands) and a customized Microsoft Excel spreadsheet (Microsoft Corporation, Washin
ton, DC, USA) for Windows. 
3. Results 
Figure 1 shows the total time (min), effective time (min), and density (%) of the tra
ing and competition sessions. There were significant differences (p < 0.05) between tra
ing sessions for all variables. The PREOM session had the lowest (p < 0.05) volume (to
and effective time) but with higher density than the VEL and INT sessions. The INT s
sion had the highest volume (total and effective time) but with a lower density than t
EXT and PREOM sessions and higher than VEL. 
 
Figure 1. Total duration (min, in dark blue), effective duration (min, in light blue), and density 
fective/total, %, in green) of the sessions. Note: VEL is velocity day, INT is intensity or strength d
EXT is extensity or endurance day, PREOM is previous day to match day, OM is official match d
Significant differences (p < 0.05) are represented: 1 is higher than VEL, 2 is higher than INT, 3
higher than EXT, and 4 is higher than PREOM. 
As shown in Table 1, all external load variables were higher in OM compared to t
rest of the training sessions, with a difference ranging from moderate to extremely lar
(ES = 0.7–6.6). On the contrary, the session with the lowest load in all the variables w
Figure 1. Total duration (min, in dark blue), effective duration (min, in light blue), and density
(effective/total, %, in green) of the sessions. Note: VEL is velocity day, INT is intensity or strength
day, EXT is extensity or endurance day, PREOM is previous day to match day, OM is ofﬁcial match
day. Signiﬁcant differences (p < 0.05) are represented: 1 is higher than VEL, 2 is higher than INT, 3 is
higher than EXT, and 4 is higher than PREOM.
As shown in Table 1, all external load variables were higher in OM compared to the
rest of the training sessions, with a difference ranging from moderate to extremely large
(ES = 0.7–6.6). On the contrary, the session with the lowest load in all the variables was
the PREOM. The variables ACC2 and DEC2 oriented towards neuromuscular work were
higher in INT, the variable TD oriented towards cardiovascular work was higher in EXT,
Int. J. Environ. Res. Public Health 2022, 19, 15820
5 of 10
and variables of velocity (HSR and Sprint) oriented towards locomotor work were higher
in VEL. The values of the intensity variable (TDmin) were highest in OM with respect to all
training sessions.
Table 1. Mean and standard deviation (SD) of the external load variables in different training and
competition sessions.
Type of Sessions
VEL
INT
EXT
PREOM
OM
Variables
Mean
(SD)
Mean
(SD)
Mean
(SD)
Mean
(SD)
Mean
(SD)
TD
5058.3
(712.3) 2,3
4840.0
(1237.8) 4
5418.5
(957.6) 1,2,4
3546.8
(1007.8)
10,576.33
(602.77) 1,2,3,4
(m)
HSR
614.5
(318.1) 2,3,4
184.0
(187.1)
424.3
(247.7) 2,4
245.3
(126.0) 2
906.7
(208.0) 1,2,3,4
(m)
Sprint
35.1
(49.6) 2,3,4
1.5
(5.5)
28.2
(42.4) 2,4
7.8
(15.2) 2
69.2
(51.2) 1,2,3,4
(m)
ACC2
115.3
(25.2) 3,4
145.0
(40.7) 1,3,4
99.7
(24.7) 4
71.1
(24.2)
181.8
(35.1) 1,2,3,4
(n)
DEC2
118.5
(29.2) 3,4
138.1
(39.0) 1,3,4
99.0
(24.4) 4
70.1
(23.9)
190.2
(33.7) 1,2,3,4
(n)
PL
66.9
(11.0) 2,4
66.4
(18.1) 4
69.0
(14.8) 1,2,4
46.7
(15.2)
142.1
(15.6) 1,2,3,4
(au)
TDmin
85.1
(9.2) 2,4
72.7
(10.5) 4
85.4
(11.3) 1,2,4
65.1
(13.2)
90.8
(5.3) 1,2,3,4
(m/min1)
Note: VEL is velocity day, INT is intensity or strength day, EXT is extensity or endurance day, PREOM is previous
day to match day, OM is ofﬁcial match day. TD is total distance expressed in meters (m), HSR is high-intensity
running distance (m), Sprint is sprint running distance (m), ACC2 is the number of accelerations at >2 m/s2 (n),
DEC2 is the number of decelerations at <−2 m/s2 (n), PL (au) is player load, and TDmin is distance per min
(m/min1). Signiﬁcant differences (p < 0.05) are represented: 1 is higher than VEL, 2 is higher than INT, 3 is higher
than EXT, and 4 is higher than PREOM.
Figure 2 shows the mean and standard deviations of two external load variables: High
Metabolic Load Distance (HMLD) and Total Impacts. Signiﬁcant differences were found
for both variables in the different training and competition sessions. In line with the rest
of the variables, the highest values were obtained in OM and the lowest in PREOM. The
VEL session obtained the highest HMLD values compared to the other training sessions.
Likewise, the EXT session accumulated the highest values in Total Impacts compared to
the other training sessions.
Table 2 shows the effect size (ES) of the external load variables obtained from the
comparison between training sessions and ofﬁcial matches. As can be seen, the magnitude
of the differences ranged from a very large decrease (ES = −2.17) to an extremely large
increase (ES = 7.4).
Int. J. Environ. Res. Public Health 2022, 19, 15820
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Int. J. Environ. Res. Public Health 2022, 19, x  
6 of 10 
 
 
Figure 2. Means and deviations of the high metabolic load distance (HMLD, m, in blue) and total 
impacts (Total impacts, n, in green) of the players on the different training days. Note: VEL is veloc-
ity day, INT is intensity or strength day, EXT is extensity or endurance day, PREOM is previous day 
to match day, OM is official match day. Significant differences (p < 0.05) are represented: 1 is higher 
than VEL, 2 is higher than INT, 3 is higher than EXT, and 4 is higher than PREOM. 
Table 2 shows the effect size (ES) of the external load variables obtained from the 
comparison between training sessions and official matches. As can be seen, the magnitude 
of the differences ranged from a very large decrease (ES = −2.17) to an extremely large 
increase (ES = 7.4). 
Table 2. Effect size of external load variables in different training and competition sessions. 
Comparison of Type 
of Sessions 
Variables 
TD 
HSR 
Sprint 
ACC2 
DEC2 
PL 
TDmin 
VEL vs. OM 
8.4 (ELI) 
1.1 (MI) 
0.7 (MI) 
2.2 (VLI) 
2.3 (VLI) 
5.6 (ELI) 
0.8 (MI) 
VEL vs. PREOM 
−1.8 (LD) 
−1.7 (LD) 
−0.8 (MD) 
−1.8 (LD) 
−1.8 (LD) 
−1.5 (LD) 
−1.8 (LD) 
VEL vs. INT 
−0.2 (SD) 
−1.7 (LD) 
−1.2 (LD) 
0.9 (MI) 
0.6 (MI) 
0.0 (T) 
−1.2 (LD) 
VEL vs. EXT 
0.4 (SI) 
−0.7 (MD) 
−0.2 (SD) 
−0.6 (MD) 
−0.7 (MD) 
0.2 (SI) 
0.1 (T) 
EXT vs. OM 
6.6 (ELI) 
2.1 (VLI) 
0.9 (MI) 
2.7 (VLI) 
3.1 (VLI) 
4.8 (ELI) 
0.8 (MI) 
EXT vs. PREOM 
−1.9 (LD) 
−1.0 (MD) 
−0.7 (MD) 
−1.2 (LD) 
−1.2 (LD) 
−1.5 (LD) 
−1.7 (LD) 
EXT vs. INT 
−0.5 (MD) −1.1 (MD) 
−1.1 (MD) 
1.4 (LI) 
1.2 (LI) 
−0.2 (SD) 
−1.2 (LD) 
INT vs. OM 
6.2 (ELI) 
3.7 (VLI) 
2.4 (VLI) 
1.0 (MI) 
1.4 (LI) 
4.5 (ELI) 
2.3 (VLI) 
INT vs. PREOM 
−1.2 (LD) 
0.4 (SI) 
0.6 (MI) 
−2.3 (VLD) 
−2.2 (VLD) 
−1.2 (LD) 
−0.6 (MD) 
PREOM vs. OM 
8.7 (ELI) 
4.0 (ELI) 
1.8 (LI) 
3.7 (VLI) 
4.2 (ELI) 
6.2 (ELI) 
2.8 (VLI) 
Note: ELD is extremely large decrease, VLD is very large decrease, LD is large decrease, MD is 
moderate decrease, SD is small decrease, T is trivial, SI is small increase, MI is moderate increase, LI 
is large increase, VLI is very large increase, ELI is extremely large increase. VEL is velocity day, INT 
is intensity or strength day, EXT is extensity or endurance day, PREOM is previous day to match 
day, OM is official match day. TD is total distance expressed in meters (m), HSR is high-intensity 
running distance (m), Sprint is sprint running distance (m), ACC2 is the number of accelerations at 
>2 m/s2 (n), DEC2 is the number of decelerations at <−2 m/s2 (n), PL (au) is player load, and TDmin 
is distance per min (m/min1). 
 
 
Figure 2. Means and deviations of the high metabolic load distance (HMLD, m, in blue) and total
impacts (Total impacts, n, in green) of the players on the different training days. Note: VEL is velocity
day, INT is intensity or strength day, EXT is extensity or endurance day, PREOM is previous day to
match day, OM is ofﬁcial match day. Signiﬁcant differences (p < 0.05) are represented: 1 is higher
than VEL, 2 is higher than INT, 3 is higher than EXT, and 4 is higher than PREOM.
Table 2. Effect size of external load variables in different training and competition sessions.
Comparison of
Type of Sessions
Variables
TD
HSR
Sprint
ACC2
DEC2
PL
TDmin
VEL vs. OM
8.4 (ELI)
1.1 (MI)
0.7 (MI)
2.2 (VLI)
2.3 (VLI)
5.6 (ELI)
0.8 (MI)
VEL vs. PREOM
−1.8 (LD)
−1.7 (LD)
−0.8 (MD)
−1.8 (LD)
−1.8 (LD)
−1.5 (LD)
−1.8 (LD)
VEL vs. INT
−0.2 (SD)
−1.7 (LD)
−1.2 (LD)
0.9 (MI)
0.6 (MI)
0.0 (T)
−1.2 (LD)
VEL vs. EXT
0.4 (SI)
−0.7 (MD)
−0.2 (SD)
−0.6 (MD)
−0.7 (MD)
0.2 (SI)
0.1 (T)
EXT vs. OM
6.6 (ELI)
2.1 (VLI)
0.9 (MI)
2.7 (VLI)
3.1 (VLI)
4.8 (ELI)
0.8 (MI)
EXT vs. PREOM
−1.9 (LD)
−1.0 (MD)
−0.7 (MD)
−1.2 (LD)
−1.2 (LD)
−1.5 (LD)
−1.7 (LD)
EXT vs. INT
−0.5 (MD)
−1.1 (MD)
−1.1 (MD)
1.4 (LI)
1.2 (LI)
−0.2 (SD)
−1.2 (LD)
INT vs. OM
6.2 (ELI)
3.7 (VLI)
2.4 (VLI)
1.0 (MI)
1.4 (LI)
4.5 (ELI)
2.3 (VLI)
INT vs. PREOM
−1.2 (LD)
0.4 (SI)
0.6 (MI)
−2.3 (VLD)
−2.2 (VLD)
−1.2 (LD)
−0.6 (MD)
PREOM vs. OM
8.7 (ELI)
4.0 (ELI)
1.8 (LI)
3.7 (VLI)
4.2 (ELI)
6.2 (ELI)
2.8 (VLI)
Note: ELD is extremely large decrease, VLD is very large decrease, LD is large decrease, MD is moderate decrease,
SD is small decrease, T is trivial, SI is small increase, MI is moderate increase, LI is large increase, VLI is very large
increase, ELI is extremely large increase. VEL is velocity day, INT is intensity or strength day, EXT is extensity or
endurance day, PREOM is previous day to match day, OM is ofﬁcial match day. TD is total distance expressed in
meters (m), HSR is high-intensity running distance (m), Sprint is sprint running distance (m), ACC2 is the number
of accelerations at >2 m/s2 (n), DEC2 is the number of decelerations at <−2 m/s2 (n), PL (au) is player load, and
TDmin is distance per min (m/min1).
4. Discussion
The aim of this study is to describe the distribution of external load in different training
sessions and competitions in competitive micro-cycles in women’s football. According
to the current state of the art, this is the ﬁrst study carried out on the description of
tactical periodization in women’s football. The results conﬁrm the starting hypotheses
because despite describing a distribution of the conditional demands (for example, strength,
Int. J. Environ. Res. Public Health 2022, 19, 15820
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resistance, and speed) based on the horizontal alternation during the competitive micro-
cycle sessions, none of them replicated the demands of the competition.
In line with the results obtained in previous studies carried out in men’s football [14,28],
the total and effective duration was signiﬁcantly shorter in the training sessions compared
to those obtained in ofﬁcial matches (Figure 1). Among the three acquisition sessions (VEL,
INT, and EXT), the VEL session was the one with the lowest density, probably due to
the intermittent or dividing nature of the tasks of this session. It should be highlighted
as well that the lowest values in all the variables are obtained in the PREOM session,
conﬁrming the existence of tapering in the training load in the days prior to competition in
order to favor the recovery of the players and, consequently, to guarantee greater freshness
and willingness to compete [10,16,17,19]. The results of this study concur with these
previous contributions in men’s football, where the weekly periodization was described,
accumulating the highest loads in the middle of the week, that is, 2 or 3 days before the
match (OM − 2 or OM − 3), coinciding with the EXT day, and lower loads at the end of the
week, the 2 days before the competition.
On the other hand, unlike previous studies [10,18], the location of the VEL session
within the weekly distribution was novel. This was probably motivated by the distribution
of the training sessions that the team arranged, trying to distance the VEL session from
the EXT session, thereby stimulating the distance covered at high-speed ranges (e.g., HSR
and Sprint) and that of the following match. The reason could lie in the need to emphasize
this conditional capacity given its low stimulation both in the competition itself (e.g.,
players accumulated little distance in high-speed ranges) and throughout the competitive
micro-cycle. The VEL session was located on the second day after the match played in the
previous micro-cycle (OM + 2), that is, 5 or 6 days prior to the following match (OM − 5 or
OM − 6). Signiﬁcantly more HSR and Sprint were accumulated in these sessions, with a
volume load (TD) similar to the EXT session.
Regarding the INT session, which was usually carried out on the central days of
the week (OM − 5 or OM − 4) and prior to the EXT session, a predominance of the
force variables (accelerations and decelerations) was described compared to the other
sessions, as described in men’s football in previous works [10,29]. However, although
Stevens et al. (2017) described that medium (1.5–3 m/s2 and −1.5–3 m/s2) and high (>3
m/s2 and <−3 m/s2) accelerations and decelerations during training were similar to the
competition values in this type of session, in this research work, the competition values
were signiﬁcantly higher than the rest of the types of training sessions.
With regard to the EXT session, which was usually carried out in the middle of the
week (OM − 4 or OM − 3), high values were described in TD and PL compared to the
other sessions, showing a similar trend as in previous studies [18,30]. In elite male football,
these studies described greater distances covered in OM − 3 sessions compared to OM − 4
sessions, which could be related to the EXT and INT sessions described in this study.
Despite the global coincidence of this approach, not all the works [17,31–33] concurred
in the same weekly proﬁle of the loads. While some showed a downward progression or
from more to less [31], others described two peaks, Monday and Thursday [33], with a
remarkable peak in the main session of the week [32] or with high values in the middle of
the week without showing great differences between sessions [17]. Likewise, the present
work shows three load sessions (VEL, INT, AND EXT), of which two obtain higher values
(VEL and EXT), located at the beginning and middle of the week, as represented in the
study by [33].
This study describes a variant of tactical periodization, which, while respecting hori-
zontal alternation, proposes a novel distribution in the orientation of content throughout
the competitive micro-cycle. The possible practical application of this study is that the
content of the training sessions with different conditional orientations could present a
different ordering than the one proposed by the tactical periodization. In this way, instead
of respecting the usual order of the sessions proposed by the tactical periodization (e.g.,
INT+EXT+VEL), it could be altered by proposing VEL+INT+EXT when the contextual
Int. J. Environ. Res. Public Health 2022, 19, 15820
8 of 10
needs and/or the characteristics of the type of population to which it is directed requires
adapting content to optimize their preparation process.
It has been veriﬁed that none of the training sessions obtained higher values than those
of the competition in all the variables (e.g., oriented towards neuromuscular, cardiovascular,
and locomotor works). Therefore, coaches should be careful in the return-to-play process
and should prepare players adequately because there could be an excessive gap between
the demands of training sessions and those of competition, putting players at risk [11–13].
This work has some context limitations. In the ﬁrst place, since just one team was
analyzed, the periodization results should not be interpreted as something generalized in
women’s football; more case studies would be required to approach an extrapolation. In ad-
dition, the inclusion of internal load variables [34] could have allowed knowing in greater
detail the internal response generated in the athlete [35]. Likewise, it could be interesting
to carry out a battery of physical tests or to pass wellness and readiness questionnaires to
assess the physical condition of the players or their willingness to compete [10,26]. How-
ever, it is worth mentioning that the team achieved promotion to the highest category of
women’s football at the national level; therefore, it could support the idea that the proposed
periodization strategy not only had no negative effects on the performance of the players
but also had possibly a great impact on the competitive performance.
5. Conclusions
In conclusion, this research work provides a description of the proﬁle of training
loads throughout a competitive week in women’s football. A horizontal alternation in the
stimulation of physical capacities in female football was described, although the order of
the training contents varied with respect to the original proposal of tactical periodization.
This study could open the possibility of proposing a variant that can better adapt to a
particular reality conditioned by the schedules and pitches established by the sports club
of the players. In this sense, in ongoing works, a larger sample and other contexts will
be included.
Author Contributions: Investigation, A.O., I.E., K.L.-d.-I., P.M.C. and J.C. All authors have read and
agreed to the published version of the manuscript.
Funding: This study was supported by the Universidad del País Vasco/Euskal Herriko Unibertsitatea,
EUSK22/17, PES22/30, COLAB22/15, COST Actions CA18106 supported by COST (European
Cooperation in Science and Technology).
Institutional Review Board Statement: The Ethics Committee of research with humans (CEISH) of
the University of the Basque Country (UPV/EHU) gave its institutional approval of the study (code
M10-2019-099).
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: The datasets generated by and/or analyzed during the current study
are not publicly available due to ethics and privacy requirements, but they are available from the
corresponding author upon reasonable request.
Acknowledgments: This study was supported by the Spanish government subproject Mixed method
approach on performance analysis (in training and competition) in elite and academy sport [PGC2018-
098742-B-C33] (2019-2021) [Ministerio de Ciencia, Innovación y Universidades (MCIU), la Agencia
Estatal de Investigación (AEI) y el Fondo Europeo de Desarrollo Regional (FEDER)], that is part
of the coordinated project New approach of research in physical activity and sport from mixed
methods perspective (NARPAS_MM) [SPGC201800 × 098742CV0]. The University of Cambridge,
the Basque Government, Engineering and Society and Bioengineering Research Groups, IT1489-22,
and ELKARTEK (KK-2020/00092, KK-2021/00033), “Ministerio de Ciencia e Innovación” (SAF2016
77758 R), FEDER funds.
Conﬂicts of Interest: No potential conﬂict of interest was reported by the authors.
Int. J. Environ. Res. Public Health 2022, 19, 15820
9 of 10
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Comparison of the External Load in Training Sessions and Official Matches in Female Football: A Case Report.
Olaizola, Aratz,Errekagorri, Ibai,Lopez-de-Ipina, Karmele,María Calvo, Pilar,Castellano, Julen