Journal of Physical Education and Sport ® (JPES), Vol. 24 (issue 8), Art 202, pp. 1814 - 1822, August 2024
online ISSN: 2247 - 806X; p-ISSN: 2247 – 8051; ISSN - L = 2247 - 8051 © JPES

Original Article
Comparison of neuromuscular performance, perceived effort, and well-being
across menstrual cycle phases in female youth soccer players
RODRIGO VILLASECA‐VICUÑA1, FRANCISCO MORALES-ACUÑA2, LORETO ROJAS-TRELLES3,
ÁLVARO SEGUEIDA-LORCA4, ELIZABETH FLORES FERRO5, FELIPE HERMOSILLA-PALMA6, LUISVALENZUELA7, GUILLERMO CORTÉS-ROCO8, PABLO MERINO-MUÑOZ9
1,5,7
Faculty of Education, School of Science and Technology, Physical Education Pedagogy, Silva Henríquez
Catholic University (UCSH), CHILE.
2
Specialty in Sports Medicine and Physical Activity, Faculty of Medical Sciences, University of Santiago,
CHILE.
3
Chilean Football Federation (FFCH), Santiago, CHILE.
4Sports Sciences and Physical Activity, Faculty of Health, Santo Tomás University, CHILE.
6
Physical Education Pedagogy, Faculty of Education, Autonomous University of Chile, CHILE.
8
School of Education, Sports Coach, Viña del Mar University, Viña del Mar 2572007, CHILE.
9
Biomedical Engineering Program, COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, BRAZIL.
9
Research Center in Human Motor Sciences, Adventist University of Chile, Ñuble, CHILE.
Published online: August 31, 2024
Accepted for publication : August 15, 2024
DOI:10.7752/jpes.2024.08202
Abstract:
The nature of the human being, especially that of women, is complex (de Jonge et al., 2019). Various interacting
variables, including physiological, biomechanical, physical, psychological, and emotional factors, constitute thenature of women. In this context, across the menstrual cycle (MC) there are fluctuations in the levels of sex
hormones such as progesterone, estrogen, follicle-stimulating hormone (FSH), and luteinizing hormone (LH),which is crucial to regulate ovulation and delimiting phases (Romero-Moraleda et al. 2019). This study aimed tocompare neuromuscular performance, perceived exertion, and well-being across menstrual cycle (MC),specifically follicular phase (FPh) and luteal phase (LPh) in under-17 players from national soccer team.
Thirteen players (age = 15.69 ± 0.48 years) were assessed for mean propulsive velocity (MPV) in the back squat,
countermovement jump (CMJ), 10-meter time (T10). Additionally, subjective measures were collected using awell-being questionnaire (WQ) administered before training, wich evaluated muscular pain, mood, stress, sleep,
fatigue and overall well-being (the sum of these five factors), as the rating of perceived exertion (RPE) scale
after training. Just T10 exhibited only trivial to small differences between phases (p = .040; ES = 0.13), favoring
LPh. Both MPV30 and CMJ showed trivial differences between phases. The remaining variables demonstrated
unclear differences (p > .05) across the MC phases. Based on the results, it can be inferred that the MC phases
had a discernible impact only on T10 in this sample, where participants exhibited superior performance in LPh,albeit with trivial to small effects that may lack clinical significance. Conversely, subjective measures obtained
from the WQ and RPE scale indicated unclear differences between phases.
Key Words: woman, athletic, fatigue, physiological, ovulation.
Introduction
According to data published by the International Federation of Association Football (FIFA), thedevelopment of women's football has grown in recent years. In fact, 73% of federations have an active women's
national team, surpassing the 55% reported in 2015 (FIFA, 2019). Globally, there are currently 13 million
women participating in organized football, but only 4 million are officially registered with federations. Of these,
945 thousand are over 18 years old, and 3 million are under 18 years old (FIFA, 2019). The nature of the humanbeing, especially that of women, is complex (de Jonge et al., 2019). Various interacting variables, including
physiological, biomechanical, physical, psychological, and emotional factors, constitute the nature of women. In
this context, across the menstrual cycle (MC) there are fluctuations in the levels of sex hormones such asprogesterone, estrogen, follicle-stimulating hormone (FSH), and luteinizing hormone (LH), which is crucial toregulate ovulation and delimiting phases (Romero-Moraleda et al. 2019). The MC is traditionally divided into
two phases: follicular phase (FPh) and luteal phase (LPh), or three phases, which includes the ovulatory phase,based on the ovarian function (Janse De Jonge, 2003).
The FPh begins on the first day of menstruation, lasts an average of 9-14 days, where follicles growunder the influence of FSH and estrogen levels secreted by the surrounding cells increase slowly. This isfollowed by pituitary gland’ LH secretion. As estrogen levels increase, an LH surge occurs, leading to ovulation
approximately 1 day later. This marks the beginning of the ovulatory phase, which lasts about 5 days (Julian et1814---------------------------------------------------------------------------------------------------------------------------------Corresponding Author: RODRIGO VILLASECA‐VICUÑA, E-mail: rvillaseca@ucsh.cl

RODRIGO VILLASECA‐VICUÑA, FRANCISCO MORALES-ACUÑA, LORETO ROJAS-TRELLES,
ÁLVARO SEGUEIDA-LORCA, ELIZABETH FLORES FERRO, FELIPE HERMOSILLA-PALMA, LUISVALENZUELA, GUILLERMO CORTÉS-ROCO, PABLO MERINO-MUÑOZ
--------------------------------------------------------------------------------------------------------------------------------------al. 2020). During these phases, the endometrial thickness increases to receive the embryo. A few days after thefollicle releases the egg, it transforms into the progesterone-secreting corpus luteum, giving rise to the LPh,which typically lasts 14 days. Towards the end of the Lph, progesterone secretion ceases, the endometrium is nolonger sustained, and menstrual bleeding occurs. As estrogen levels decrease during these days, FSH secretion
increases, restarting the cycle. The three phases of the cycle differ from each other in the proportions of estrogenand progesterone levels: (1) in the early FPh, there are low levels of both estrogen and progesterone; (2) in the
pre-ovulatory phase, estrogen levels are high, and progesterone levels are low; and (3) in the LPh, both estrogenand progesterone levels are high (Constantini et al. 2005).
The MC has historically been the focus of myths and misinformation, leading to ideas that limit
women's activities (García-Pinillos et al., 2021). Circulating estrogen and progesterone cause variations in thelevels of some cardiovascular, respiratory, and metabolic parameters, with subsequent consequences for strengthand aerobic-anaerobic performance (Constantini et al. 2005). The evolution of women's football has promptedscientific and sports professionals to increase research on the MC and its influence on athletes' performance(Sánchez et al. 2022). However, studies have yielded contradictory results. For example, Romero-Moraleda et al.
(2019) investigated the influence of the MC on strength and power performance, finding no differences among
the three phases (LPh vs. early FPh vs. late FPh). On the other hand, Julian et al. (2020), examined differences inmatch load in professional adult female players in Germany, using a global positioning system, and founddifferences in speed band 17-20 km/h (FPh vs. FPh). The study by García-Pinillos et al. (2021), analyzed abattery of jumping tests and sprint performance in trained adult women, showing differences only in squat jump
between the ovulatory phase and the early FPh, reaching the same conclusion as previous studies regarding these
physical tests. Another study on young football players found no differences in sprint, change of direction, andvertical jump performance, but did find differences in the overall well-being obtained by self-reported
questionnaires between the menstruation phase and LPh vs. FPh (Sánchez et al. 2022). Additionally, theexistence of menstrual symptoms in the LPh and premenstrual symptoms in the FPh, such as fluid retention(causing swelling, congestion, and discomfort), weight gain, mood changes (irritability, depression, loss ofmotivation), and dysmenorrhea, could lead to a deterioration of athletes' well-being (Villa del Bosque, 2013).
Similarly, psychological and physiological stress or mood changes during the premenstrual and menstrual phases
are associated with decreased energy levels and/or impaired cognitive function due to the MC (Konovalova,
2013). Such changes could be reflected in common measures of training load quantification, such as subjective
rate of perceived exertion (RPE) scale and fatigue perception, such as well-being obtained by self-reported
questionnaires (Merino-Muñoz, Pérez-Contreras, et al. 2021; Villaseca-Vicuña et al. 2020).
Therefore, it seems that the information is contradictory, and there is no consensus on the effect of the
MC on female athletes (García-Pinillos et al. 2021; Romero-Moraleda et al. 2019; Sánchez et al. 2022). Hence,
the objective of this study was to compare neuromuscular performance, perceived exertion, and well-being
during the phases of the MC in under-17 female soccer players.

LUTEAL PHASE

FOLLICULAR PHASE
Ovulation(+) Estrogen(-) Progesterone

1

2

3

4

5

6

7

8

Subjective tests

well-being Rating ofquestionnaire Perceived
Exertion

9

10

11

12

13

(+) Estrogen(+) Progesterone
14

Neuromuscular tests

Back squat

CMJ

T10

15

16

17

18

19

20

21

22

Subjective tests

well-being Rating ofquestionnaire Perceived
Exertion

23

24

25

26

27

28

Neuromuscular tests

Back squat

CMJ

T10

Material & methods
DesignThis study employed a quantitative, cross-sectional, descriptive, and comparative design. It focused oncomparing neuromuscular performance, perceived exertion, and well-being during the phases of the MC in
under-17 female soccer players.
Participants
A non-randomized convenience sampling method was utilized. The participants consisted of 13 under17 female soccer players (age = 15.69 ± 0.48 years; body mass = 56.6 ± 7.3 kg; height = 161.72 ± 6.32 cm) from----------------------------------------------------------------------------------------------------------------------------1815
JPES ® www.efsupit.roRODRIGO VILLASECA‐VICUÑA, FRANCISCO MORALES-ACUÑA, LORETO ROJAS-TRELLES,
ÁLVARO SEGUEIDA-LORCA, ELIZABETH FLORES FERRO, FELIPE HERMOSILLA-PALMA, LUISVALENZUELA, GUILLERMO CORTÉS-ROCO, PABLO MERINO-MUÑOZ
--------------------------------------------------------------------------------------------------------------------------------------one national soccer team. They participated in official competitions proposed by the South American Football
Confederation (CONMEBOL), specifically in the South American Championship in Uruguay in March 2022 andthe FIFA World Cup in India in 2022. Inclusion criteria were: i) completion of training during the study period,ii) a minimum experience of at least 4 years in a federated soccer practice, iii) regularity in MC during theevaluation period (27 ± 2 days, range = 24-31 days), iv) no injury during the assessment period, v) no menstrual
disorders (e.g., dysmenorrhea, amenorrhea, or intense symptoms associated with premenstrual syndrome), andvi) no use of oral contraceptive methods. Ten players with irregular menstrual cycles were excluded from thestudy. All players were informed about the study and its objectives.
Ethical considerations
This intervention did not disrupt the normal soccer training and did not involve motor actions different
from regular training or common physical assessments conducted by the team. Participants provided signed
informed consent before data collection and were free to withdraw from the study at any time. Additionally,signed consent was obtained from parents or guardians. Before the soccer season began, all players underwent acomprehensive medical examination. The study was conducted in accordance with the Declaration of Helsinki(World Medical Association, 2013), which outlines ethical principles for medical research involving humansubjects. Additionally, the study received approval from the Institutional Ethics Committee of the Virgen
Macarena and Virgen del Rocío University Hospitals in Seville, Spain (C.P. RENFEFUTCHILE—C.I. 2355-N 20, June 28, 2021). This ensured that the participants were actively engaged in official competitions, contributing
to the study's relevance.
Procedure
The MC was divided into two phases for estimation. The FPh was defined from the first day of
menstruation until the day of ovulation. The first assessment was conducted between days 12 and 13,
characterized by low progesterone levels and high estrogen concentrations. On the other hand, LPh wasestablished after ovulation, concluding just before the onset of the next MC. The second measurement was taken
between days 24 and 25, coinciding with the highest peaks of estrogen and progesterone. The phases were
determined by My Calendar application. (Gonçalves et al. 2021). Each player downloaded the application andrecorded her MC. According to the calendar filled out by the participants, neuromuscular performance wasassessed using the following neuromuscular tests in the specified order: mean propulsive velocity (MPV) in backsquat, countermovement jump (CMJ), and 10-meter sprint time (T10). Additionally, subjective tests wererecorded throughout the MC using the well-being questionnaire (WQ) (McLean et al. 2010). These evaluations
occurred 30 minutes before and after training, utilizing the RPE scale (Impellizzeri et al. 2004) (Figure 1). The
assessment period began in January and concluded in February 2022, just before the start of the Under-17 SouthAmerican Championship, which served as a qualifier for the 2022 World Cup in India.
The players were already familiar with these evaluations as the physical conditioning area of thenational team utilized these assessment protocols with both the senior and junior teams (Villaseca-Vicuña,
Jesam-Sarquis et al. 2021). To ensure consistency, a standardized warm-up routine was established, involving
slow running, multidirectional movements, and dynamic stretching, followed by a specific warm-up for each test
lasting 15-20 minutes. The tests were conducted individually at the training center, maintaining consistent spatialconditions to minimize potential influences on the results. All assessments were conducted at the headquarters of
the team Soccer Federation at 10:00 AM, with a temperature of 15 °C and a relative humidity of 54%.
Variables and instruments
Menstrual cycle phases (MC)The phases of the MC were determined using the MY CALENDAR® mobile application for Apple and
Google. This app allows players to record their menstrual period, facilitating the estimation of the FPh and LPh
for each player. The application has demonstrated utility in determining menstrual phases and is regularly usedamong women participating in sports (Gonçalves et al. 2021).
Neuromuscular Performance
Mean Propulsive Velocity in Back Squat (MPV)This test has been validated to assess levels of muscular strength in the lower limbs of soccer players(Pareja-Blanco et al. 2020; Villaseca-Vicuña, Otero-Saborido et al. 2021). Prior to measurement, each player
performed a specific warm-up consisting of 3 sets and 3 repetitions with a load of 20 kg. During the evaluation,
each player performed 2 sets (1 set per load) of 3 repetitions each, with loads of 20 and 30 kg, respectively, witha recovery time of 3 minutes between sets. The concentric phase of the exercise was to be performed at the
maximum possible velocity. Two variables were recorded: (a) the estimated one-repetition maximum (RM),
determined from the mean propulsive velocity (MPV) of the last load of the test (30 kg), calculated using theequation proposed by Pareja-Blanco et al. (2020) for a female athlete population and (b) relative strength (RS),obtained from the ratio RM/body mass. A linear velocity transducer (Chronojump®, Barcelona, Spain) was used
for measuring MPV. The equation for calculating 1RM in the squat based on the MPV in the last load is asfollows: %1RM = (−42.196 MPV2 − 31.018 MPV + 112.937).
1816---------------------------------------------------------------------------------------------------------------------------JPES ® www.efsupit.roRODRIGO VILLASECA‐VICUÑA, FRANCISCO MORALES-ACUÑA, LORETO ROJAS-TRELLES,
ÁLVARO SEGUEIDA-LORCA, ELIZABETH FLORES FERRO, FELIPE HERMOSILLA-PALMA, LUISVALENZUELA, GUILLERMO CORTÉS-ROCO, PABLO MERINO-MUÑOZ
--------------------------------------------------------------------------------------------------------------------------------------Countermovement Jump (CMJ)
This test is regularly conducted to measure the lower limb power of female soccer players (Bishop et al.
2018; Villaseca-Vicuña, Molina-Sotomayor, et al. 2021). Prior to the test, each player performed a specificwarm-up consisting of 5 jumps to a jump box with a target surface 30 cm above the ground. During the test,
participants executed 3 attempts. The starting position was upright with hands on hips throughout the test to
eliminate any influence from arm swinging. From this position, the participant rapidly flexed the knees toapproximately 90 degrees and then immediately propelled themselves to jump vertically as high as possible,
landing on both feet simultaneously with extended knees (approximately 180 degrees) (Kammoun et al. 2020). If
the evaluator observed an execution error, the jump was invalidated, and the attempt was repeated. This test wasassessed using the mobile application My Jump 2 app® (Madrid, Spain), with 3 repetitions and a 3-minute rest
between each trial. Jump height (cm) was recorded, and the average of the 3 attempts was selected for statisticalanalysis. Recently, Balsalobre-Fernández et al. (Balsalobre-Fernández et al. 2015), validated this application
using a high-speed camera of 120 Hz mounted on an iPhone 5s (Apple®, California, USA). For convenience, inthe present investigation, the application was installed on an iPhone XR (Apple®, California, USA), which
included the same functions as the iPhone 5s. To standardize video recording analysis, the tablet was placed
vertically on the ground facing the participants' feet at a distance of 1.5 m and a recording speed of 240 Hz.
10-Meter Sprint Time (T10)This test is commonly used to assess acceleration in soccer players (Pardos- Mainer et al. 2019;
Villaseca-Vicuña, Molina-Sotomayor, et al. 2021). Prior to the assessment, each player performed a specificwarm-up consisting of 5 progressive 10-meter sprints. There were 3 attempts at the 10-meter sprint, with a 3minute recovery time between repetitions. The evaluation took place on a natural grass soccer field at 10:00 AM,
with a temperature of 15 °C and a relative humidity of 54%. The starting position was standing, with the front
foot placed just behind a line located 0.5 m from the first photoelectric cell at a height of 1 m, to prevent the laserfrom being interrupted by the head or arms at the start of the sprint. Two photoelectric cells (Microgate®,
Bolzano, Italy) were positioned at the start and at the 10-meter mark. The average of the 3 attempts in the 10meter sprint (T10) was used for analysis.
Subjetive tests
Well-being Questionnaire (WQ)
During the study period, players completed the WQ 30 minutes before each training session, using acloud-based Google Drive® spreadsheet (Google Drive®, California, USA). The approach proposed by(McLean et al., 2010). Fatigue (FAT), sleep quality (SQ), muscle soreness (MS), stress level (SL), and mood(MD) were assessed using the WQ on a scale of 1 to 5 points, with 5 indicating maximum well-being (very, verygood). Total well-being (TB) was then determined by summing the five scores (McLean et al. 2010). There wasno presence of peers during the response to avoid biases in responses (Minett et al. 2021)
Rate Perception of Effort (RPE)
To quantify the intensity of each training session, the RPE scale was used 30 minutes after each training
session (Borg, 1990). Each player rated their perceived exertion using a scale from 0 to 10 on a Google Drive®
cloud-based spreadsheet (Google Drive®, California, USA). There was no presence of peers during the response
to prevent biases in responses (Minett et al. 2021).
Statical Analysis
The distribution of variables was examined using the Shapiro-Wilk test and histograms. Mean (M) andstandard deviation (SD) are reported for normal variables, while median and 25th and 75th percentiles arepresented for non-normal variables. The paired Student's t-test was conducted for normal variables; if normality
assumptions were not met, the Wilcoxon test was employed.
The magnitude of differences for normal variables was assessed using the Cohen's d, with the average
standardizer being the mean of SD [(SD1 + SD2) / 2] (Lakens, 2013). Results were categorized based on thefollowing thresholds: <0.2: trivial; 0.21–0.6: small; 0.61–1.2: moderate; 1.21–2.0: large; and >2.0: very large(Hopkins et al., 2009). For non-normal variables, the Wilcoxon's r was used as the effect size (Z/√n) (Fritz et al.
2012). Categorization followed these thresholds: <0.1: trivial; 0.11–0.3: small; 0.31–0.5: moderate; and >0.50:
large. Effects surpassing trivial levels were considered unclear (Hopkins et al. 2009). A 95% confidence interval
was calculated for both effect sizes. An alpha level of 0.05 was established. The analysis was conducted using
SPSS software for Microsoft Windows (SPSS IBM®, version 24, New York, USA).
Results
Table 1 displays the results for variables with a normal distribution. Only T10 exhibited trivial to small
differences between phases (p = .040; ES = 0.13), while the remaining variables MPV30 and CMJ showed trivial
differences between phases (p > .05).
----------------------------------------------------------------------------------------------------------------------------1817
JPES ® www.efsupit.roRODRIGO VILLASECA‐VICUÑA, FRANCISCO MORALES-ACUÑA, LORETO ROJAS-TRELLES,
ÁLVARO SEGUEIDA-LORCA, ELIZABETH FLORES FERRO, FELIPE HERMOSILLA-PALMA, LUISVALENZUELA, GUILLERMO CORTÉS-ROCO, PABLO MERINO-MUÑOZ
--------------------------------------------------------------------------------------------------------------------------------------Table 1. Comparison between menstrual cycle phases in the performance of normal variables.
FPh

LPh

Variables

M

±SD

M

±SD

p

CMJ (cm)

28.5

2.59

28.9

3.75

.662

MPV30 (m/s)

1.05

0.08

1.05

0.11

.848

T10 (s)
1.86*
0.07
1.91
0.10
.040
Note. *: Difference p < .05; M: mean; SD: standard deviation; CMJ: countermovement jump;
MPV30: mean propulsive velocity 30 kg; T10: 10-Meter sprint time.

In Figure 2, the magnitudes of effect size in the performance of normal variables can be observed.

Figure 2. Effect Sizes (ES) Cohen's d with 95% Confidence Interval.
In Table 2, the results of non-normal variables are presented. All variables showed unclear differences(p > .05).
Table 2. Comparison between menstrual cycle phases in the performance and subjective tests of nonnormal variables.
FPh

LPh

Variables

Md

P25

P75

Md

P25

P75

p

MPV20

1.16

1.12

1.25

1.18

1.10

1.24

.528

RM (kg)

88.6

69.5

103

91.9

71.4

119

.583

RS (RM/kg)

1.43

1.37

1.87

1.58

1.43

1.89

.480

Fatigue (UA)

3.40

3.00

4.00

3.50

3.00

4.25

.506

Sleep quality (UA)

4.00

3.60

4.00

3.67

3.25

4.00

.092

Muscle Soreness (UA)

3.29

3.11

4.00

3.80

3.00

4.25

.222

Stress level (UA)

3.29

3.00

4.00

3.50

3.00

4.00

.917

Mood (UA)

4.00

4.00

4.70

4.00

4.00

5.00

.866

Total Well-being (UA)

17.5

17.0

20.2

17.3

16.0

20.8

.727

RPE (UA)

6.00

4.00

6.50

5.50

3.75

6.20

.346

Note. Md: Median; P25: 25th Percentile; P75: 75th Percentile; MPV20: Mean Propulsive Velocity 20 kg;
RM: Maximum Repetition in squat test; RS: Relative Strength; UA: Arbitrary Units.

In Figure 3, the magnitudes of effect size in the performance of non-normal variables are observed.
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ÁLVARO SEGUEIDA-LORCA, ELIZABETH FLORES FERRO, FELIPE HERMOSILLA-PALMA, LUISVALENZUELA, GUILLERMO CORTÉS-ROCO, PABLO MERINO-MUÑOZ
---------------------------------------------------------------------------------------------------------------------------------------

Figure 3. Effect Sizes (ES) r Wilcoxon with 95% Confidence Interval.
Dicussion
The objective of this study was to compare neuromuscular performance, perceived exertion, and wellbeing during the phases of the MC in under-17 female soccer players. The main findings of the present
investigation were that only T10 showed trivial to small differences between phases, demonstrating better
performance in the follicular phase (FPh). The remaining variables exhibited trivial and unclear effects. From aphysiological perspective, the potential differences could be explained by the fact that in the FPh athletes haveelevated estrogen levels, which may enhance muscular strength, speed, and endurance (Constantini et al. 2005;
Janse De Jonge, 2003), and thus explain that they were faster in the follicular phase (FF) compared to the luteal
phase (FL). However, these results are not in agreement with those found by Sánchez et al. (2022) who did not
find differences between MC phases in female soccer players during the 40-meter sprint test. Although they
divided the MC into three phases, no differences were evident in any of these. On the other hand, the 10-meterand 40-meter tests may assess different capacities, such as acceleration and maximum speed, respectively.
Strong associations have been found between these capacities, but not as strong in female soccer players (r = .77
to .88) (Merino-Muñoz, Vidal-Maturana et al. 2021; Villaseca-Vicuña, Otero-Saborido et al. 2021), whichsuggested that hormonal changes do not lead to performance differences in sprinting (Sánchez et al. 2022).
Additionally, it has been reported that isolated natural concentrations of 17b-estradiol with low progesterone
levels do not have an effect on sprint performance (Tsampoukos et al. 2010). Similar findings were reported by
García-Pinillos et al. (García-Pinillos et al. 2021) in endurance athletes, where they found trivial differences in
T10 (p > .05). These studies highlight contradictions with the results obtained in relation to the sprint test.
Although these effects seem to be not clinically significant, a 1% difference is mentioned to make a significant
impact during soccer matches (Haugen & Buchheit 2016). In this regard, a similar pattern is observed in thevertical jump test, where Sánchez et al. (Sánchez et al. 2022) noted trivial to small differences in squat jump (p >.05), and García-Pinillos et al. (García-Pinillos et al. 2021) reported small differences in SJ (p < .05) but not in
CMJ (p > .05). Both studies concluded that MC phases do not significantly affect neuromuscular performance,
possibly because the effects are trivial to small. In fact, a recent narrative review mentioned that studies
analyzing neuromuscular performance report unclear and inconsistent effects on the impact of the MC. However,this review also states that studies examining perceived performance consistently demonstrate that female
athletes identify their performance as relatively worse during the early follicular and late luteal phases(Carmichael et al. 2021), which could be reflected in a higher perception of effort and poorer well-being,associated with a greater perception of motor performance fatigue (Behrens et al. 2022).
On the other hand, the results regarding RPE, and well-being state showed no differences between
phases of the CM (Comparative Model) (p > .05). These findings are contradictory to those reported by Sánchez
et al. (Sánchez et al. 2022) in adolescent female soccer players were the results revealed a significantly poorer
overall well-being state (p < .01) during LPh to the FPh. The observed variations may be attributed to several
factors. Firstly, it should be noted that the study conducted by Sánchez et al. (Sánchez et al., 2022) characterized
the MC in three phases. Additionally, the well-being questionnaire employed in the study did not encompass themood item. Furthermore, one should take into account the potential influence of athletic proficiency, as higher
levels of experience in sports might mitigate fluctuations in well-being states, as suggested by previous research(Esteves et al. 2020; Villaseca-Vicuña, Pérez-Contreras et al. 2021).
While this study contributes to the existing research on MC in young female soccer players, it is notwithout limitations. Firstly, no direct hormonal assessment was performed to define MC phases. In fact, an----------------------------------------------------------------------------------------------------------------------------1819
JPES ® www.efsupit.roRODRIGO VILLASECA‐VICUÑA, FRANCISCO MORALES-ACUÑA, LORETO ROJAS-TRELLES,
ÁLVARO SEGUEIDA-LORCA, ELIZABETH FLORES FERRO, FELIPE HERMOSILLA-PALMA, LUISVALENZUELA, GUILLERMO CORTÉS-ROCO, PABLO MERINO-MUÑOZ
--------------------------------------------------------------------------------------------------------------------------------------analysis of hormone concentrations related to performance in each MC phase could contribute to understanding
the reasons for the absence of performance changes across the MC. Secondly, it is crucial to acknowledge thatsoccer performance is multifactorial; therefore, it would
have been important to evaluate other performance variables during MC phases, such as bodycomposition, aerobic endurance, or the physical and technical demands during competition. Future researchshould examine the individual effects of MC phases, considering the potential inter-subject variability in theeffects of MC phases. Analyzing individual inferences through single-subject (n=1) or magnitude-based
inferences could reveal different effects among players (Barry, 1996; Buchheit, 2016, 2017)
Practical applications
While the literature is inconclusive regarding how the MC influences neuromuscular performance, thisresearch provides relevant information on MC and measures of neuromuscular performance, as well as
subjective perceptions of effort and well-being. This information could benefit the scientific community andsports coaches in establishing both objective (physical tests) and subjective (questionnaires) monitoring
strategies on an individual basis. This, in turn, allows for the development of protocols tailored to the needs ofeach athlete, enabling the application of transdisciplinary strategies. Ultimately, controlling performancevariables is a crucial element in sports and applied sciences. Therefore, the use of low-cost applications andquestionnaires could significantly contribute to the sports community, as they are economically accessible to any
staff member (López, 2017).
Conclusions
Based on the results, it can be concluded that CM phases only affected T10 in this sample, where there
was a higher performance in FPh, but with trivial to small effects that may not be substantial in practice. On theother hand, subjective measures from the well-being questionnaire and RPE showed unclear differences between
phases. Further studies with a larger number of subjects (statistical power) are needed to validate the results ofthis study.
Acknowledgments
We would like to thank the players and staff at the Football Association of Chile for their cooperation
throughout the study.
Conflicts of interest
No potential conflict of interest was reported by the author(s)References
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