Fatigue and recovery time-course after women's futsal,handball,basketball,and volleyball matches: A systematic review

Abstract

This study aimed to analyse acute and residual fatigue after women's futsal, basketball, handball, and volleyball matches and the ensuing recovery time-course of performance, physiological, and perceptual responses. This study was pre-registered in the International Prospective Register of Systematic Reviews. The search was conducted in PubMed (MEDLINE), Web of Science, and Scopus in April 2024 and updated in February 2025. Studies were included when participants were female futsal, volleyball, basketball, or handball players, regardless of their ability level. Further, the intervention was an official or friendly match following official rules in an indoor environment with performance, physiological, and perceptual parameters collected pre- and post-match (immediately, 24 h, 48 h, or 72 h-post). A total of 17 studies (n = 326 female athletes) were included for systematic review. Most studies reported changes in performance parameters immediately after the matches. Acute and residual fatigue was observed through increased physiological (cortisol, creatine kinase) and perceptual (muscle soreness) parameters at 24–72 h post-basketball and futsal matches. This study highlights the complexity of fatigue and recovery in women's team sports, suggesting the need for specific recovery strategies and monitoring using different parameters.

Keywords

Creatine kinase female athletes menstrual cycle muscle soreness team sports

Introduction

Female athletes cover an average distance of 4–7 km during basketball,¹ handball,² and futsal³ matches, with more than 50% of this distance in high-intensity domains (>80–85% of maximum heart rate).³ Furthermore, repetitive high-intensity actions such as jumping, sprinting, accelerating and decelerating, changes of direction, agility with and without the ball, attacks, blocks, and dribbling are crucial for team sports performance.^4–7 Thus, intermittent sports with high-intensity actions are prone to cause fatigue. Fatigue can be defined as a symptom derived from the interaction between perceived fatigability (i.e., homeostasis and subjective psychological state of the athlete) and performance fatigability (i.e., the decline in objective performance parameters derived from the nervous system capacity and muscle contractile properties over time).^8,9 Considering that fatigue impairs performance in training and ensuing matches, it is important to understand the recovery process through performance, physiological, and perceptual parameters after matches of different team sports.

Specifically, women's participation in team sports has increased in the last decades.¹⁰ For instance, female athletes in the Olympics rose from 2% (in 1900) to 48% (in 2020).¹¹ Notably, the first women's futsal world cup will occur in 2025.¹² Despite the increasing popularity of women's team sports, limited research exists in women compared to men.^13,14 Thus, results reported for men have been applied to female athletes. However, physiological¹⁴ and anthropometric¹⁵ differences between sexes exist, alongside evidence of differences in performance and actions during matches.^16,17 Therefore, these differences highlight the need for dedicated research in female sports.

Team sports (i.e., basketball, futsal, handball, and volleyball) require physical and cognitive demands that can result in both acute (immediately after) and residual (up to 24–72 h post-match) fatigue.^18,19 Along with single-match demands, other factors may contribute to higher fatigue levels. For example, rule changes – such as reducing the time available to attempt a shot during offensive possession in basketball (i.e., from 30 to 24 s) - have increased basketball match intensity.²⁰ Similarly, the increased demands of futsal matches have been documented over time.²¹ In addition to that, after a goal has been scored in handball, the match restarts as soon as an attacking player is in possession of the ball at the centre line, regardless of the defender's position on the court.²² Demands for squatting positions and excessive jumping during women's volleyball matches may also result in potential fatigue in the lower limbs.²³ Given these factors associated with basketball, futsal, handball, and volleyball match demands, different levels of fatigue may occur, and they require investigation. Accordingly, post-match fatigue responses may vary between team sports due to unique movement patterns and match structure.^24,25 Therefore, conducting studies in ecologically valid conditions is crucial to ensure the applicability of findings in real-world scenarios in each sport and explore potential differences in terms of post-exercise fatigue.²⁵

Of note, congested schedules are observed during competitive seasons in team sports, which represents an additional challenge for fatigue management. For example, professional basketball players have an official match every three days, which can result in accumulated fatigue due to the large number of matches and the short recovery time between matches.^26,27 Research assessing congested match-related fatigue indicates a potential worsening in physiological and perceived fatigue in team sports.²⁶ Thus, this regular congested schedule highlights the importance of managing player fatigue, avoiding hampering their readiness for subsequent training or matches.

Therefore, this review aimed to analyse acute and residual fatigue after women's basketball, futsal, handball, and volleyball matches and the recovery time course of performance, physiological, and perceptual responses.

Methods

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines²⁸ and was pre-registered on the International Prospective Register of Systematic Reviews (PROSPERO, registration number: CRD42024557008, 21 June 2024).

Search strategies

The search was conducted on 09 April 2024, with no date restrictions, and all included studies were written in English. An updated search was conducted on 08 February 2025. Studies were searched for in three databases: PubMed (MEDLINE), Web of Science, and Scopus. The following terms were combined using Boolean operators: (match OR game) AND (“female basketball” OR “female futsal” OR “female volleyball” OR “female handball”) AND (agility OR “change of direction” OR “delayed onset muscle soreness” OR fatigue OR hormones OR immunity OR inflammation OR jump OR “menstrual cycle” OR mood OR “muscle damage” OR “muscle soreness” OR neuromuscular OR performance OR recovery OR “repeated sprint” OR sprint OR “ muscular power” OR technical).

Study inclusion and exclusion criteria

The following inclusion criteria were defined: (1) Participants should be female futsal, volleyball, basketball, or handball athletes, regardless of their ability level and age; (2) intervention should be an indoor official or an indoor friendly match following official rules; (3) fatigue-related parameters included performance, physiological, and perceptual indicators; (4) all parameters must have been measured at pre- and at some time point post-match.

Reviews, summaries, letters, and case studies were not included, though consulted before exclusion during the first screening phase. Furthermore, the following exclusion criteria were set: (1) outcome merged with male results or other sports (2) intervention consisting of small-sided games or simulated matches (i.e.,: in-court and/or laboratory treadmill protocols simulating match loads); (3) matches occurring in outdoor environments; (4) studies examining fatigue responses only following training sessions; (5) use of energy drinks, supplements or anabolic steroids before, during or after matches.

Study selection and quality assessment

The studies were inserted in the Rayyan web application (https://www.rayyan.ai). Firstly, studies were screened for inclusion reviewing titles and abstracts by two researchers (CS, RM), with all cases of disagreement discussed until consensus was reached. Inclusion and exclusion decisions were duly labelled in the Rayyan web application. At a second stage, the same researchers reviewed the remaining full-text manuscripts for exclusion. The exclusion reasons were presented in Figure 1.

Figure 1.

Flow chart of study inclusion process.

The methodological quality and risk of bias from the studies were determined using a qualitative assessment tool, consisting of 13 questions adapted from Goulart et al.²⁹ (Table 1). This was an independently paired process, with answer categories of “yes”, “partially,” and “no”, scoring 2, 1, or 0, respectively. When the total score difference of a given study was higher than 3, a third researcher (KG) completed the qualitative assessment, and the mean score of the three analyses was presented. Finally, the three researchers discussed disagreements until consensus was reached for assigning a final score for each criterion.

Table 1.

Qualitative assessment tool and average methodological quality scores of the 13 criteria.

Item		Qualitative assessment
1	Was the study question or objective clearly described?	2.0 ± 0.0
2	Were the inclusion criteria stated?	1.5 ± 0.8
3	Were the main outcomes to be measured clearly described in the introduction or methods section?	2.0 ± 0.0
4	Were the main outcomes measured using accurate procedures?	1.4 ± 0.9
5	Were the players’ participation level (e.g., amateur, professional, elite), training background (e.g., years of training), training status (e.g., training hours or sessions/ matches per week) described?	1.3 ± 0.8
6	Were the anthropometric characteristics described? (e.g., body mass, height, and body fat)	1.5 ± 0.7
7	Was the season period when the match took place stated? (e.g., off-season/ pre-season/ competitive-season)	1.7 ± 0.8
8	Were the environmental conditions described? (e.g., temperature and humidity)	0.2 ± 0.6
9	Was the use of hormonal contraceptives or menstrual cycle phase reported?	0.5 ± 0.8
10	Were external (e.g., time motion analyses/ performance measures) and internal (e.g., RPE/ heart rate) measures of match intensity recorded?	1.0 ± 0.8
11	Was playing time reported?	1.4 ± 1.0
12	Was the activity undertaken during the recovery period (e.g., 12–72 h post-match) described? (studies with only pre and immediately post-match measures were scored as 2)	1.8 ± 0.6
13	Was a limitation paragraph with possible confounding factors included in the study?	1.4 ± 1.0

Data extraction strategy

Two researchers (CS and RM) independently extracted and included the data in a spreadsheet, according to the type of parameter (i.e., performance, physiological, and perceptual). The description of the studies, including match conditions and sample characteristics, are reported in Table 2. Players were categorized according to competitive level, following the classification by Russell et al.³⁰: Level 1: untrained or sedentary (did not meet inclusion criteria for this review). Level 2: habitually active; physically fit, recreationally trained (i.e., youth state/ regional competition). Level 3: trained and competitive (i.e., youth national competition, NCAA). Level 4: highly trained and competitive (i.e., part-time international competition, semi-professional). Level 5: Professional (i.e., full-time paid athletes in professional competitive leagues).

Table 2.

Description of studies included in the systematic review.

Study	Sport	Sample size (n)	Age(years)	Height(cm)	Body mass(kg)	Body fat(%)	Training experience (years)	Competitive level	Match characteristics
Akarçeşme et al. (2022)³⁷	Volleyball	ALL: 24 L: 6 MB: 6 SE: 6 SPI: 6	L: 20.50 ± 1.7 MB: 22.50 ± 2.0 SE: 22.20 ± 2.6 SPI: 21.80 ± 1.5	L: 172.00 ± 6.7 MB: 183.80 ± 4.8 SE: 180.20 ± 2.6 SPI: 183.70 ± 6.0	L: 59.50 ± 1.9 MB: 68.50 ± 7.6 SE: 61.30 ± 5.2 SPI:67.60 ± 2.9	N/A	L: 9.00 ± 1.8 MB: 10.50 ± 3.2 SE: 12.50 ± 4.8 SP: 10.30 ± 3.6	3	Three friendly matches
Corvillo et al. (2013)³⁸	Handball	19	18.47 ± 2.26	164.0 ± 1.0	58.96 ± 2.75	N/A	N/A	2	Regional league “Extremaduran Cup”
Dal’Maz et al. (2023)³⁹	Futsal	10	27.70 ± 4.9	165.30 ± 4.8	60.40 ± 2.3	N/A	N/A	5	European Women’ Futsal tournament
Delextrat et al. (2012)⁴⁴	Basketball	9	24.3 ± 4.1	173.0 ± 7.9	65.1 ± 10.9	21.1 ± 3.8	At least 5	4	Six weeks after the start of the English Basketball National League
Delextrat et al. (2013)⁴²	Basketball	8	22.0 ± 2.0	179.0 ± 8.5	77.6 ± 9.2	22.5 ± 6.6	At least 3	3	First phase of the competitive season
Delextrat et al. (2014)⁴³	Basketball	8	21.0 ± 3.0	176.4 ± 8.1	73.9 ± 9.7	21.9 ± 5.5	At least 3	3	First phase of the competitive season
García-Ceberino et al. (2022)⁴⁷	Basketball	12	14.00 ± 1.41	167.00 ± 0.05	57.18 ± 5.86	N/A	4.00 ± 0.85	2	Quarter-finals match / Spanish cadet championship qualifier
Izquierdo et al. (2021)⁴⁵	Basketball	68	16.45 ± 0.92	177.01 ± 5.51	67.54 ± 7.26	N/A	7.04 ± 2.48	3	Second half of the season - Official federated matches
Izquierdo et al. (2020)⁴⁶	Basketball	ALL: 37 G: 11 F: 15 C: 11	ALL: 17.21 ± 0.44 G: 17.16 ± 0.44 F: 17.36 ± 0.44 C: 17.06 ± 0.42	ALL: 177.54 ± 5.35 G: 172.63 ± 2.8 F: 177.46 ± 5.09 C: 182.54 ± 2.25	ALL: 67.06 ± 8.15 G: 63.50 ± 6.4 F: 66.76 ± 9.02 C: 71.04 ± 7.28	ALL: 21.25 ± 2.25 G: 21.32 ± 2.34 F: 21.15 ± 2.47 C: 21.31 ± 2.03	ALL: 7.54 ± 2.82 G: 6.90 ± 2.98 F: 7.73 ± 3.19 C: 7.90 ± 2.21	2	Second half of the season - official federation matches
Kassiano et al. (2019)⁴¹	Futsal	6	21.8 ± 3.9	159.00 ± 2.7	57.40 ± 4.1	19.00 ± 3.3	7.80 ± 1.8	4	Friendly match
Lukonaitiené et al. (2021)⁴⁹	Basketball	ALL: 21 U-18: 10 U-20: 11	U-18: 18.0 ± 0.4 U-20: 20.5 ± 2.9	U-18: 179.9 ± 6.6 U-20: 178.4 ± 8.8	U-18: 70.2 ± 5.1 U-20: 73.0 ± 9.7	N/A	U-18: 9.1 ± 1.8 U-20: 9.6 ± 2.4	3	Prior to European championships
Mariscal et al. (2019)³⁶	Handball	ALL: 21 W&F: 10 DEF: 11	ALL: 23.00 ± 5.4 W&F: 25.00 ± 6.3 DEF: 21.00 ± 3.2	ALL: 170.20 ± 4.1 W&F: 168.70 ± 3.2 DEF: 171.60 ± 4.6	ALL: 67.10 ± 7.5 W&F: 64.90 ± 5.9 DEF: 69.20 ± 8.6	ALL: 28.90 ± 5.7 W&F: 28.60 ± 3.6 DEF: 29.30 ± 7.5	N/A	3	Spanish national women's league
Moreira et al. (2014)²⁷	Basketball	11	27.40 ± 4.8	179.50 ± 5.5	72.00 ± 7.8	N/A	At least 5	5	Seventh match in the first phase of the Brazilian National Championship
Ronglan et al. (2006)²²	Handball	8	23.10 ± 2.0	176.00 ± 0.05	71.20 ± 1.8	N/A	N/A	4	3-day international tournament during the in-season phase
Rossi et al. (2024)⁴⁸	Volleyball	20	12.07 ± 07	N/A	N/A	N/A	N/A	2	Final match of the provincial volleyball championship in Palermo
Sepahvand et al. (2017)⁴⁰	Futsal	10	20.00 ± 2.0	162.70 ± 5.0	55.20 ± 3.5	N/A	N/A	2	Women's Futsal League of Lorestan Province
Souglis et al. (2023)³⁵	Futsal	34	22.60 ± 2.1	167.40 ± 3.6	57.50 ± 3.0	16.90 ± 0.8	12.50 ± 2.3	3	Unofficial Match

C: centres; DEF: defenders; F: forwards; G: guards; L: libero; MB: middle blocker; N/A: not available; SE: setter; SPI: spiker; U-18: under 18; U-20: under 20; W&F: Wingers & Forwards

Competitive level was defined according to Russell et al.³⁰: Level 1, untrained or sedentary participants; Level 2, habitually active, physically fit or recreationally-trained participants; Level 3, trained and competitive players; Level 4, highly-trained and competitive players; Level 5, professional players.

Performance parameters analysed were presented in Table 3: countermovement jump (CMJ); running tests (20 and 10 m sprints); repeated sprint ability test (RSA); agility T-test; isokinetic peak torque (IPT); 1 repetition maximum (RM) in the bench press and 1 RM in the leg press. Physiological parameters included were presented in Table 4: alpha-amylase; total androgens; cortisol; creatine kinase (CK); tumor necrosis factor alpha (TNF-α); heart rate; immunoglobulin A; interleukin-6 (IL-6); lactate; lactate dehydrogenase (LDH); leukocytes; serum myoglobin (MB); C-reactive protein (CRP); progesterone; testosterone; testosterone/cortisol. Perceptual parameters were presented in Table 5: delayed onset muscle soreness (DOMS), total quality of recovery (TQR), rating of perceived exertion (RPE), and well-being. The following information was extracted: first author and year of publication, sport, screened parameter, and measurement time points (pre, immediately after, 24 h, 48 h, and 72 h post-matches). Data from control groups (sedentary individuals) were not extracted from the articles. Data from control conditions were extracted from studies using strategies to accelerate post-match recovery. However, studies were excluded if the control condition consisted of any placebo intervention (i.e.,: sham stimulation via light-emitting diode devices³¹), as previous research shows that the placebo effect may influence performance-related measures³² and perceived well-being,³³ which may introduce bias in our findings. The Webplotdigitizer application (version 4.7) was used to extract data from graphs. This tool has acceptable validity and reliability in extracting graph data.³⁴ Corresponding authors of two studies^27,35 were contacted by email to request additional data. However, only partial data were obtained through these contacts, justifying the missing values in the tables.

Table 3.

Acute fatigue and recovery time-course of performance parameters.

Author (year)	Sport	Variable	Pre	Post	24h	48h	72h	Statistical change
Delextrat et al. (2012)⁴⁴	Basketball	IPT quadriceps (N.m)	108.8 ± 8.80	103.5 ± 8.00
		IPT hamstrings (N.m)	77.8 ± 9.14	71.6 ± 8.57*				p < 0.05
		CMJ (cm)	33.8 ± 0.83	29.2 ± 2.02*				p < 0.05
		20 m sprint (s)	3.85 ± 0.32	4.13 ± 0.30*				p < 0.05
Delextrat et al. (2013)⁴²	Basketball	CMJ (cm)	34.41 ± 2.50		31.55 ± 2.68			No significant differences. Data extracted from baseline (pre) and control condition (24 h)
		RSA - Total time (s)	63.51 ± 2.33		64.49 ± 2.93
		RSA - Ideal time (s)	61.32 ± 2.24		62.40 ± 3.20
		RSA - Performance decrement (%)	3.6 ± 0.3		3.5 ± 0.7
Delextrat et al. (2014)⁴³	Basketball	CMJ (cm)	34.82 ± 3.00		31.91 ± 3.27			No significant differences. Data extracted from baseline (pre) and control condition (24 h)
		RSA - Total time (s)	63.5 ± 2.2		64.5 ± 2.8
		RSA - Ideal time (s)	61.3 ± 2.1		62.4 ± 3.0
		RSA - Performance decrement (%)	3.7 ± 0.9		3.5 ± 1.7
Izquierdo et al. (2021)⁴⁵	Basketball	CMJ (cm)
		Under-16	30.06 ± 3.19	26.49 ± 3.3				0/0/100 (almost certain)
		Under-18	32.84 ± 3.37	28.94 ± 2.97				0/0/100 (almost certain)
		20 m sprint (s)
		Under-16	3.48 ± 0.19	3.6 ± 0.16				96/4/0 (very likely)
		Under-18	3.2 ± 0.13	3.3 ± 0.19				97/3/0 (very likely)
		10 m sprint (s)
		Under-16	2.13 ± 0.14	2.18 ± 0.17				70/28/2 (possible)
		Under-18	1.91 ± 0.11	1.94 ± 0.15				55/39/6 (possible)
Izquierdo et al. (2020)⁴⁶	Basketball	CMJ (cm)
		Centres	32.28 ± 3.00	29.49 ± 3.46				1/6/93 (likely)
		Forwards	33.86 ± 3.71	29.22 ± 3.19				0/0/100 (almost certain)
		Guards	31.95 ± 3.12	27.94 ± 1.91				0/1/99 (very likely)
		20 m sprint (s)
		Centres	3.21 ± 0.13	3.31 ± 0.19				83/13/5 (likely)
		Forwards	3.21 ± 0.14	3.32 ± 0.19				89/9/2 (likely)
		Guards	3.15 ± 0.14	3.26 ± 0.22				84/11/5 (likely)
		10 m sprint (s)
		Centres	1.93 ± 0.14	1.91 ± 0.13				19/38/43 (possibly)
		Forwards	1.92 ± 0.09	1.98 ± 0.13				85/12/3 (likely)
		Guards	1.9 ± 0.11	1.92 ± 0.21				50/23/27 (possibly)
Kassiano et al. (2019)⁴¹	Futsal	CMJ (cm)	41.9 ± 2.9	41.6 ± 3.5				31/28/41 (unclear)
Kassiano et al. (2019)⁴¹	Futsal	CMJ during 30 s (cm)	31.1 ± 3.1	31.9 ± 4.8				46/24/30 (unclear)
Moreira et al. (2014)²⁷	Basketball	1RM bench press (kg)	50.72 ± 10.16		49.36 ± 9.57	50.5 ± 9.67		No significant differences
		1RM leg press (kg)	280.45 ± 77.40		277.72 ± 77.18	279.54 ± 75.64
		Agility T-test (s)	N/A	N/A	N/A	N/A
Ronglan et al. (2006)²²	Handball	20 m sprint (s)						The performance in the 20 m sprint was reduced by 3.7 ± 0.4% over the course of the matches in 3 days.
		Match 1	3.17 ± 0.03	3.17 ± 0.03
		Match 2	3.15 ± 0.03	3.20 ± 0.03*
		Match 3	3.19 ± 0.02	3.21 ± 0.02
		10 m sprint (s)
		Match 1	1.78 ± 0.02	1.79 ± 0.01
		Match 2	1.78 ± 0.02	1.81 ± 0.01
		Match 3	1.79 ± 0.01	1.80 ± 0.01
Souglis et al. (2023)³⁵	Futsal	CMJ (cm)	N/A	N/A*	N/A*	N/A*	N/A	p < 0.05, for all *
		10 m sprint (s)	N/A	N/A*	N/A*	N/A*	N/A*	p < 0.05, for all *
		20 m sprint (s)	N/A	N/A*	N/A*	N/A*	N/A*	p < 0.05, for all *

C: centres; CMJ: countermovement jump; F: forwards; G: guards; IPT: isokinetic peak torque; N/A: not available; RM: repetition maximum. Total time: defined as the sum of the ten sprint times; Ideal Time: calculated as the best sprint time multiplied by 10; RSA: repeated sprint ability test. Data are presented as mean and standard deviation. Of note, the data of Mariscal et al. (2019) are reported as median and interquartile ranges. Additionally, data from Sepahvand et al. (2017) are reported as mean and standard error of the mean (SEM).

*Means significantly different from pre

Table 4.

Acute fatigue and recovery time course of physiological parameters.

Author (year)	Sport	Variable	Pre	Post	24h	48h	72h	Statistical change
Akarçeşme et al. (2022)³⁷	Volleyball	Heart rate (bpm)						N/A comparisons between post and pre-measures. Only comparisons between positions were reported
		Libero	82.2 ± 3.8	82.0 ± 12.2
		Middle blocker	75.0 ± 8.3	91.0 ± 15.4
		Setter	77.5 ± 12.4	98.0 ± 24.2
		Spiker	78.0 ± 12.9	103.3 ± 12.4
		Lactate (mmol/L)
		Libero	2.5 ± 1.1	1.5 ± 0.9
		Middle blocker	2.5 ± 0.9	2.4 ± 0.9
		Setter	1.9 ± 0.7	2.1 ± 0.9
		Spiker	1.8 ± 0.8	2.1 ± 1.9
Corvillo et al. (2013)³⁸	Handball	Cortisol (ng/mg)	62.59 ± 33.55	100.01 ± 48.15				NS
		TA/TG (ng/mg)	1.07 ± 0.83	0.58 ± 0.42*				p < 0.05
		Testosterone (ng/mg)	24.11 ± 8.57	25.5 ± 7.85				NS
		T/C (ng/mg)	0.44 ± 0.32	0.33 ± 0.25				NS
		Total glucocorticoids (ng/mg)	1922.65 ± 737.88	3394.91 ± 1366.78 *				p < 0.05
		Total Androgens (ng/mg)	2085.31 ± 875.14	1982.33 ± 1038.13				NS
García-Ceberino et al. (2022)⁴⁷	Basketball	Heart rate (bpm)	89.91 ± 11.34	104.30 ± 11.17*				p < 0.001
Kassiano et al. (2019)⁴¹	Futsal	Lactate (mmol/L⁻¹)	2.1 ± 0.3	5.4 ± 1.3*				100/0/0 (most likely)
Mariscal et al. (2019)³⁶	Handball	Alpha-amylase (U/ml)	395.93 ± 581.72	569.54 ± 368.52				N/A
		Cortisol (ng/ml)	4.65 ± 4.53	7.39 ± 5.44*				p < 0.01
		Immunoglobulin A (ug/ml)	742.99 ± 654.20	289.71 ± 368.52*				p < 0.01
Moreira et al. (2014)²⁷	Basketball	CK (u.l−¹)	194.2 ± 71.8	317.2 ± 141.8	392.4 ± 204.0*	279.3 ± 133.7		p < 0.05, for all *
Moreira et al. (2014)²⁷	Basketball	Serum Mb (ng-ml−¹)	35.6 ± 17.5	52.7 ± 15.8	148.7 ± 90.3*	109. ± 57.7*		p < 0.05, for all *
Rossi et al. (2024)⁴⁸	Volleyball	Progesterone (pg/ml)
		Winners	266.9 ± 136	244.5 ± 76				p = 0.46
		Losers	266.0 ± 72	311.0 ± 181				p = 0.22
		Cortisol (ng/ml)
		Winners	7.7 ± 1.1	4.5 ± 2.2*				p = 0.039
		Losers	7.8 ± 0.7	6.6 ± 2.2				p = 0.42
		Alpha-amylase (U/ml)
		Winners	166.01 ± 250	291.59 ± 241*				p = 0.01
		Losers	216.1 ± 142	259.5 ± 240				p = 0.34
Sepahvand et al. (2017)⁴⁰	Futsal	Salivary cortisol (mMol/dL)	23.18 ± 1.11	10.87 ± 0.98*				p < 0.001
Souglis et al. (2023)³⁵	Futsal	Cortisol (nmol/l)	N/A	N/A*	N/A*	N/A*	N/A*	p < 0.05, for all *
		CRP (mg.l⁻¹)	N/A	N/A*	N/A*	N/A*	N/A*	p < 0.05, for all *
		CK (u.l⁻¹)	N/A	N/A*	N/A*	N/A*	N/A*	p < 0.05, for all *
		Heart rate (bpm)	N/A	N/A*				p < 0.05, for all *
		LDH (u.l⁻¹)	N/A	N/A*	N/A*	N/A*	N/A*	p < 0.05, for all *
		IL-6 (pg.ml⁻¹)	N/A	N/A*	N/A	N/A	N/A	p < 0.05, for all *
		Lactate (mmol/l)	N/A	N/A*				p < 0.05, for all *
		TNF-α (pg.ml⁻¹)	N/A	N/A*	N/A	N/A	N/A	p < 0.05, for all *

CK: creatine kinase; CRP: c-reactive; IL-6: interleukin 6; LDH: lactate dehydrogenase; Mb: Myoglobin; N/A: not available; NS: differences not statistically significant; TA: total androgens; T/C:testosterone/cortisol; TG: total glucocorticoids; TNF-a: tumor necrosis factor alpha.

*Means significantly different from pre values;

Table 5.

Acute fatigue and recovery time-course of perceptual parameters.

Author (year)	Sport	Variable	Pre	Post	24h	48h	72h	Statistical change
Dal’Maz et al. (2023)³⁹	Futsal	TQR (AU)	17.56 ± 0.75		15.14 ± 0.59			NS
Izquierdo et al. (2021)⁴⁵	Basketball	RPE (AU)
		Under-16	0.55 ± 0.51	7.35 ± 1.02				N/A
		Under-18	0.51 ± 0.51	7.19 ± 1.00				N/A
Izquierdo et al. (2020)⁴⁶	Basketball	RPE (AU)
		Centres	0.36 ± 0.5	7.09 ± 0.83				N/A
		Forwards	0.6 ± 0.51	7.2 ± 1.08				N/A
		Guards	0.55 ± 0.52	7.27 ± 1.1				N/A
Lukonaitiené et al. (2021)⁴⁹	Basketball	Well-being (AU)
		Under-18	19.61 ± 2.40		19.12 ± 1.93			NS
		Under-20	20.57 ± 1.28		20.13 ± 1.14			NS
Moreira et al. (2014)²⁷	Basketball	Muscle soreness hamstrings (mm)	N/A	N/A	N/A*	N/A*		p < 0.05, for all *
Moreira et al. (2014)²⁷	Basketball	Muscle soreness pectoralis major (mm)	N/A	N/A	N/A	N/A		N/A
Souglis et al. (2023)³⁵	Futsal	DOMS DKE (AU)	N/A	N/A*	N/A*	N/A*	N/A*	p < 0.05, for all *
		DOMS NDKE (AU)	N/A	N/A*	N/A*	N/A*	N/A*	p < 0.05, for all *
		DOMS DKF (AU)	N/A	N/A*	N/A*	N/A*	N/A*	p < 0.05, for all *
		DOMS NDKF (AU)	N/A	N/A*	N/A*	N/A*	N/A*	p < 0.05, for all *
		RPE (AU)	N/A	N/A*	N/A*	N/A*	N/A*	p < 0.05, for all *

AU: arbitrary units; DOMS: delayed onset muscle soreness; DKE: dominant knee extensors; DKF: dominant knee flexors; N/A: not available; NDKE: non-dominant knee extensors; NDKF : non-dominant knee flexors; NS: differences not statistically significant; RPE: rating of perceived exertion; TQR: total quality recovery; VAS: visual analogue scale.

TQR data from Dal’Maz et al. (2023) were recorded during a 4-day congested tournament, with matches occurring on days 1, 2, and 4. TQR was asked before each match. Therefore, only data regarding the first match were included, with pre-match corresponding to match 1 and 24-h data corresponding to pre-match 2.

Well-being data from Lukonaitiene et al. (2021) were recorded every morning, throughout a 10-day congested competition period. Therefore, only data regarding the first match were included with pre-match corresponding to match 1 day morning and 24 h corresponding to match 2 day morning.

*Means significantly different from pre

Data analysis

The mean and standard deviation values of the parameters were obtained from the data provided in the consulted research papers or from the authors’ response upon request, except data from Mariscal et al.,³⁶ presented as median and interquartile range. Furthermore, significant differences between time points were reported in the tables using the symbols duly described in the captions. Of note, Akarçeşme et al.³⁷ only reported comparisons between volleyball players’ positions.

Results

Review statistics

A total of 898 studies were identified from three databases: PubMed (185), Web of Science (361) and Scopus (352). Rayyan identified 393 duplicates, which were removed by the first author (CS), while additional 476 studies were excluded after screening titles and abstracts, as they did not meet the inclusion criteria. Therefore, 29 studies underwent full-text examination, with 14 studies eventually included in the systematic review. Finally, 3 additional studies were identified by consulting the reference list from individual full-text articles, resulting in 17 studies in the systematic review (Figure 1).

Study characteristics

The characteristics of the female athletes and match conditions are summarized in Table 2. A total of 326 female players were included from the reported studies, with data from the following sports: futsal (n = 60, 4 studies), basketball (n = 174, 8 studies), handball (n = 48, 3 studies), and volleyball (n = 44, 2 studies). Participants were competitive level 2 (n = 5 studies), level 3 (n = 7 studies), level 4 (n = 3 studies), and level 5 (n = 2 studies). The analysed matches consisted of an international tournament [handball (n = 1) and futsal (n = 1)]; national championships [basketball (n = 4), handball (n = 1)]; regional championships [futsal (n = 1), volleyball (n = 1), handball (n = 1), basketball (n = 1)]; university premier leagues [basketball (n = 2)]; friendly volleyball and futsal matches (n = 2); and unofficial futsal match (n = 1). Furthermore, 3 out of 17 studies mentioned results for the different positions occupied in the match. It is worth noting that of the 7 studies with sports that had goalkeepers (futsal and handball), 5 did not specify whether fatigue and recovery were evaluated for this position.^{22,38,39,40,41} While Souglis et al.³⁵ mentioned that futsal goalkeepers were not included in analyses, Mariscal et al.³⁶ reported goalkeepers’ data merged with defenders in handball.

Main results of the systematic review

Physical performance parameters

A total of nine studies used performance parameters to assess acute and residual fatigue after female team sports matches. The most frequently examined performance parameters were countermovement jump (n = 7 studies) and 10 and 20 m sprint tests (n = 5 studies), followed by repeated sprint ability test (n = 2 studies), isokinetic peak torque, 1RM bench press test, 1RM leg press test and agility T-test (n = 1 study for all four tests). Overall, in basketball, 3 out of 6 studies showed no acute²⁷ or residual^27,42,43 fatigue in female basketball athletes at post-matches, since no significant differences were found in physical performance parameters (i.e., CMJ, sprint ability test, agility T-test, 1RM bench press and 1 RM leg press). Contrastingly, one study showed that the hamstrings’ peak torque, CMJ, and 20 m sprint performance reduced at post compared to pre-match.⁴⁴ Furthermore, “almost certain” negative effects in CMJ were reported for under-16 and under-18 basketball players.⁴⁵ Additionally, “very likely” and “almost certain” negative effects were also reported for guards and forwards at post compared to pre-match in basketball.⁴⁶ When measuring acute fatigue during an international handball tournament (consisting of three matches over three days), Ronglan et al.²² reported a reduction in 20 m sprint performance only after the second match of the tournament. Futsal studies revealed inconsistent findings, with Kassiano et al.⁴¹ reporting no changes in CMJ performance immediately post-match, while Souglis et al.³⁵ observed decreased CMJ performance (lasting up to 48 h) and reduced 10 and 20 m sprint performance (up to 72 h post-match), indicating the presence of acute and residual fatigue.

Physiological parameters

A total of nine studies used physiological parameters to assess acute^{27,35–38,40,41,47,48} and residual fatigue^27,35 after matches. The most investigated physiological parameter was cortisol (n = 5 studies). Cortisol increased following a handball match³⁶ and remained elevated for up to 72 h after a futsal match,³⁵ compared to pre-match values. Conversely, one study reported a significant reduction in salivary cortisol immediately after a futsal match,⁴⁰ while no significant changes in cortisol were observed after a handball match.³⁸ Interestingly, cortisol increased following a volleyball match only in the winner's group, while no significant differences were observed in the loser's group.⁴⁸ Creatine kinase was monitored in two studies,^27,35 with significant increases observed for up to 24 h after a basketball match and for up to 72 h following a futsal match, compared to pre-match values. As expected, lactate level and heart rate were increased post- compared to pre-match, and this was reported in basketball,⁴⁷ futsal,^35,41 and volleyball³⁷ studies. The response of all the physiological parameters is presented in Table 4.

Perceptual parameters

A total of six studies investigated perceptual parameters. The most investigated perceptual parameters were RPE (n = 3 studies) and muscle soreness (n = 2 studies). Muscle soreness showed peak values at 24 h post-futsal³⁵ and basketball²⁷ matches, remaining elevated at 48 h^27,35 and 72 h post-matches.³⁵ Of note, only descriptive statistics were reported for RPE measures.^45,46 Finally, when analyzing the first match in a futsal tournament³⁹ and the first match in a congested basketball competition period,⁴⁹ no significant differences were observed in TQR and well-being at 24 h post compared to pre-match, respectively. However, well-being for players from combined U-18 and U-20 teams was significantly reduced during the final part (days 7 and 10) of the congested period (comprising seven basketball matches) compared to day 1.⁴⁹

Study quality assessment

Results of the qualitative assessment (Table 6) showed a mean score of 17 out of 26. Of note, green, yellow, and red circles corresponds to scoring 2, 1, and 0, respectively. Five studies presented a complete sample characterization, including information on the players’ participation level (i.e., amateur, professional), training background (i.e., years of training), and training status (i.e., training hours or sessions/matches per week) (Q5). Furthermore, two studies did not state the season period when the match took place (Q7). Only 30% reported the use of contraceptives or menstrual cycle phase (Q9), and 70% of the studies reported external (i.e., time motion analyses/ performance measures) or internal (i.e., RPE, heart rate) measurements of match intensity (Q10).

Table 6.

Quality assessment of the studies. (Colour version available online).

Study	Q1	Q2	Q3	Q4	Q5	Q6	Q7	Q8	Q9	Q10	Q11	Q12	Q13
Akarçeşme et al. (2022)³⁷	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Corvillo et al. (2013)³⁸	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Dal’Maz et al. (2023)³⁹	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Delextrat et al. (2012)⁴⁴	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Delextrat et al. (2013)⁴²	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Delextrat et al. (2014)⁴³	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
García-Ceberino et al. (2022)⁴⁷	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Izquierdo et al. (2021)⁴⁵	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Izquierdo et al. (2020)⁴⁶	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Kassiano et al. (2019)⁴¹	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Lukonaitiené et al. (2021)⁴⁹	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Mariscal et al. (2019)³⁶	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Moreira et al. (2014)²⁷	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Ronglan et al. (2006)²²	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Rossi et al. (2024)⁴⁸	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Sepahvand et al. (2017)⁴⁰	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●
Souglis et al. (2023)³⁵	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●	_●

Discussion

The current systematic review showed that basketball, futsal, handball, and volleyball matches result in acute and residual changes observed in physical, physiological, and perceptual parameters in female athletes. Overall, changes in physical performance were predominant immediately post-match (peak torque, CMJ, 10 and 20 m sprint) in basketball and futsal. Most physical performance parameters were recovered at 24 h post-match in basketball players, whereas muscle damage marker (CK) was still increased at this time point in basketball and futsal athletes. Muscle soreness peaked at 24 h post basketball and futsal matches. However, the limited number of studies investigating extended recovery after female matches makes it difficult to draw more assertive conclusions.

Considering the physical demands during team sports matches, such as covering total distances of 4 to 7 km^1–3 and the repetitive high-intensity actions (jumps, sprints, accelerations and decelerations, attacks, blocking, dribbling, rebound, kicks and shots on goal), it was expected that fatigue would affect muscle function, generating a reduction in physical performance in female athletes,⁵⁰ possibly for days after the matches. This performance decrease following exercise may be explained by several fatigue-related mechanisms, such as depletions in phosphocreatine and glycogen stores, acidosis, decreased central motor output, inflammation, exercise-induced muscle damage, hormonal changes, and the presence of metabolites.^51–53 Indeed, CMJ performance was reduced in 4 out of 5 studies investigating acute fatigue (“almost certain”, “very likely” negative effects or p < 0.05). While no significant differences in CMJ performance were observed at 24 h post-match in basketball players,^42,43 residual fatigue persisted up to 48 h post-match in futsal players.³⁵ Although these studies consisted of players with similar competitive levels (level 3) and ages (22 ± 2 years), the playing time differed across studies (31.1 ± 5.3 min and 31.4 ± 5.0 min in basketball vs 2 × 20 min in futsal). Longer duration of exercise may cause longer recovery time courses.²⁴ However, these differences between sports are hard to explain considering that only two studies in basketball and one in futsal summarize these results.

Sprint performance, specifically in 20 m, was reduced in all basketball^44,45,46 and futsal studies³⁵ immediately post- compared to pre-match (p < 0.05, “very likely” and “likely” negative effects), persisting reduced for up to 72 h in futsal players.³⁵ Furthermore, a significant reduction in 20 m sprint performance was observed immediately post- the second match during a handball tournament with three consecutive matches.²² This result suggests that the effect of fatigue during congested match scheduling is verified in handball athletes. Contrastingly, no residual fatigue was observed in agility, strength, and repeated sprint ability performance in basketball players.^27,42,43 It is also worth mentioning that no studies investigated acute and residual fatigue after volleyball matches through performance parameters. In summary, heterogeneous responses were observed considering the investigated sports, although the small number of studies with female athletes is the main limitation.

The most investigated physiological parameter was cortisol. Cortisol is a hormone known to increase in response to stress, including physical exertion.^54,55 In the current review, cortisol was measured post-futsal, handball, and volleyball matches, though inconsistent responses were observed acutely. While significant increases³⁶ or absence of changes³⁸ in cortisol were observed post-handball matches, reduced responses immediately post-matches were reported in futsal⁴⁰ and volleyball.⁴⁸ These inconsistencies may occur due to factors outside of sporting participation.⁵⁶ For example, the time-of-day impact on cortisol measurement⁵⁷ could suggest the inclusion of baseline measurements on a time-matched control day. Furthermore, cortisol increases may display a dose-response relationship (i.e., higher loads or playing for more minutes may cause stronger responses and longer recovery times²⁴). Interestingly, the only study³⁵ reporting increased acute and residual (up to 72 h post-match) cortisol levels consisted of unofficial futsal matches with all participants playing the entire duration of a match (two periods of 20 min). Thus, this research requirement may contribute to longer cortisol responses. Therefore, when comparing results from different studies, the methodological details specified in each study must be considered.

Muscle damage markers are typically related to muscle soreness and reductions in functional capacity, which may impact performance,⁵¹ and were reported in two studies.^27,35 While CK levels only increased up to 24 h post-match, myoglobin levels remained elevated for up to 48 h, indicating at least some residual muscle damage in basketball players.²⁷ Furthermore, increased CK levels up to 72 h were observed post-futsal match.³⁵ The shorter changes in muscle damage markers after basketball matches could again be explained by the short playing time, ranging from 4 to 30 min (mean 18.2 ± 7.5 min) compared to playing time in futsal matches (2 × 20 min). Of note, the authors highlighted that the basketball team won by 30 points and indicated a moderate RPE session, suggesting the match was not very strenuous for the players.²⁷ Additionally, the longer residual response for muscle damage markers compared to the neuromuscular force parameters may be due to the blood kinetics of these physiological parameters, which are more dependent on their degradation following an exercise stimulus.⁵¹ Finally, post-match muscle damage still needs to be investigated in handball and volleyball female athletes.

The physiological parameters investigated can also be classified according to their functional characteristics. For example, match intensity can be monitored through changes observed in lactate responses. From the included studies, lactate levels between 1.8 and 2.5 mmol/L at pre- and 1.5 and 2.4 mmol/L at post-match were observed in volleyball players, depending on the position occupied,³⁷ while changes from pre (2.1 mmol/L) to post-match (5.4 mmol/L) were observed in futsal players,⁴¹ demonstrating greater use of the lactic anaerobic system for the latter compared to the former. Probably, such difference is due to the greater mean speed and distance covered by futsal players, along with the greater number of time-outs/rest in volleyball, which results in the balance between production-removal of lactate.⁴¹

Six studies used perceptual parameters to monitor fatigue, recovery, and match intensity in the team sports investigated. Overall, basketball matches were perceived as “very difficult” (10-point RPE score = 7),^37,38 while a simulated futsal match was perceived as “difficult” (6–20 RPE score = 15),³⁵ which is a good indicator of players’ exertion and fatigue.³⁵ Moreover, muscle soreness is typically associated with impaired muscle function, stiffness, and swelling,^58,59 which may impact performance. In the current review, muscle soreness peaked at 24 h post-basketball²⁷ and futsal³⁵ matches, and remained increased at 48 h and 72 h post-matches. Thus, team matches were perceived as high-intensity loads, and muscle soreness was a sensitive parameter to verify residual fatigue in female athletes.

Similarly, deteriorations in overall well-being can negatively influence competitive readiness, injury risk, technical, and tactical performance.²⁶ Despite its practical relevance, only one study reported TQR scores during a 4-day congested futsal tournament,³⁹ and one study reported well-being during a 10-day congested basketball competition period,⁴⁹ with both studies reporting no significant differences at 24 h post compared to pre-values of the first match. Although no significant differences in TQR were reported across three futsal matches,³⁹ continuous competition over a 10-day period decreased well-being in basketball players towards the end of this period.⁴⁹ Therefore, the fatigue effect in congested schedules may be observed only for longer periods.

Overall, the studies included in the systematic review had good methodological quality scores. Although most studies did not describe the environmental conditions during the matches, this factor may not be determinant considering the indoor environment. Furthermore, most studies did not report the use of contraceptives or the menstrual cycle phase from the athletes when the match occurred. Considering possible influences of the menstrual cycle phase on cortisol levels⁶⁰ and perceptual parameters,⁶¹ future studies could investigate post-match recovery during the different menstrual cycle phases.

Although this systematic review gathers specific findings for women on acute and residual fatigue post-team matches, the main limitation is the small number of studies investigating recovery in these four sports, especially in volleyball. In addition, the heterogeneity of the player's levels and categories should be highlighted when considering the results of this review. Finally, missing data existed for some parameters due to the lack of response from the authors contacted by e-mail. Therefore, the listed reasons made it difficult to perform comparisons throughout studies, and further high-quality research is needed.

Conclusion

Fatigue caused by futsal, handball, volleyball, and basketball matches alters muscle function and reduces physical performance in female athletes, especially immediately post-matches. Performance-related residual fatigue was reported only in one study with reduced CMJ (up to 48 h), 10 m and 20 m sprint (up to 72 h post-match) in female futsal players. Additionally, acute and residual fatigue was observed through physiological and perceptual parameters, with significant increases in CK and muscle soreness at 24–72 h post-basketball and futsal matches. Monitoring fatigue and recovery in female athletes can assist in specific planning and training information for match preparation, especially during congested scheduling, in which a longer recovery time may be required.

Footnotes

Ethical considerations

Not applicable. The manuscript submitted is a systematic review. Ethics is not required for systematic reviews.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Data availability

Not applicable.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, (grant number 001).

ORCID iD

Karine Naves de Oliveira Goulart

References

Stojanović

Stojiljković

Scanlan

, et al. The activity demands and physiological responses encountered during basketball match-play: a systematic review. Sport Med 2018; 48: 111–135.

Bělka

Hůlka

Šafář

, et al. External and internal load of playing positions of elite female handball players (U19) during competitive matches. Acta Gymnica 2016; 46: 12–20.

Barbero-Alvarez

Subiela

Granda-Vera

, et al. Aerobic fitness and performance in elite female futsal players. Biol Sport 2015; 32: 339–344.

Dal Pupo

Detanico

Arins

, et al. Capacidade de sprints repetidos e níveis de potência muscular em jogadores de futsal das categorias sub 15 e sub 17. Rev Bras Ciencias do Esporte 2017; 39: 73–78.

Erčulj

Blas

Bračič

. Physical demands on young elite European female basketball players with special reference to speed, agility, explosive strength, and take-off power. J Strength Cond Res 2010; 24: 2970–2978.

Karpan

Škof

Bon

, et al. Analysis of female handball players’ effort in different playing positions during official matches. Kinesiology 2015; 47: 100–107.

Sheppard

Gabbett

Taylor

, et al. Development of a repeated-effort test for elite men’s volleyball. Int J Sports Physiol Perform 2007; 2: 292–304.

Edwards

Spiteri

Piggott

, et al. Monitoring and managing fatigue in basketball. Sports 2018; 6: 1–14.

Enoka

Duchateau

. Translating fatigue to human performance. Med Sci Sport Exerc 2016; 48: 2228–2238.

10.

Fink

. Female athletes, women’s sport, and the sport media commercial complex: have we really ‘come a long way, baby’? Sport Manag Rev 2014; 18: 331–342.

11.

International Olympic Committee. Gender equality and inclusion report 2021. 2022; 0–30.

12.

FIFA. FIFA women’s futsal world cup: everything you need to know, https://www.fifa.com/pt/tournaments/womens/futsalwomensworldcup/philippines-2025/articles/copa-mundo-feminina-futsal-fifa-2025 (2024).

13.

Pérez Armendáriz

Spyrou

Alcaraz

. Match demands of female team sports: a scoping review. Biol Sport 2024; 41: 175–199.

14.

Sims

Heather

. Myths and methodologies: reducing scientific design ambiguity in studies comparing sexes and/or menstrual cycle phases. Exp Physiol 2018; 103: 1309–1317.

15.

Nakić

Tkalčić

Jukić

. Differences in standard performance indicators between male and female basketball senior teams participating in the 2003 European championships. In: 4th International Scientific Conference on Kinesiology, pp. 526–552. University of Zagreb, Faculty of Kinesiology.

16.

Milanović

Vuleta

Jerak

. International scientific conference on kinesiology - 20 - Competition performance of elite male and female handball teams: features and differences. 2017.

17.

Costa

Afonso

Brant

, et al. Differences in game patterns between male and female youth volleyball. Kinesiology 2012; 44: 60–66.

18.

McNeese

Cooke

Fedele

, et al. Perspectives on team cognition and team sports. Sport Exerc Psychol Res From Theory to Pract 2016: 123–141.

19.

Taylor

K-L

. Monitoring neuromuscular fatigue in high performance athletes Australian Cycling Federation. Epub ahead of print 2012. DOI: https://doi.org/10.13140/RG.2.2.36468.55685.

20.

Abdelkrim

El Fazaa

El Ati

Time-motion analysis and physiological data of elite under-19-year-old basketball players during competition. Br J Sports Med 2007; 41: 69–75.

21.

Naser

Ali

Macadam

. Physical and physiological demands of futsal. J Exerc Sci Fit 2017; 15: 76–80.

22.

Ronglan

Raastad

Børgesen

. Neuromuscular fatigue and recovery in elite female handball players. Scand J Med Sci Sport 2006; 16: 267–273.

23.

Vlantes

Readdy

. Using microsensor technology to quantify match demands in collegiate women’s volleyball. J Strength Cond Res 2017; 31: 3266–3278.

24.

Doeven

Brink

Kosse

, et al. Postmatch recovery of physical performance and biochemical markers in team ball sports: a systematic review. BMJ Open Sport Exerc Med 2018; 4: 1–10.

25.

Pernigoni

Perazzetti

Digno

, et al. Chill without thrill: a crossover study on whole-body cryotherapy and postmatch recovery in high-level youth basketball players. Int J Sports Physiol Perform 2024; 19: 1218.

26.

Pernigoni

Ferioli

Calleja-González

, et al. Match-related fatigue in basketball: a systematic review. J Sports Sci 2024; 42: 1727–1758.

27.

Moreira

Nosaka

Nunes

, et al. Changes in muscle damage markers in female basketball players. Biol Sport 2014; 31: 3–7.

28.

Page

McKenzie

Bossuyt

, et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ 2021; 372: 1–9.

29.

Goulart

KNO

Coimbra

Campos

, et al. Fatigue and recovery time course after female soccer matches: a systematic review and meta-analysis. Sport Med - Open 2022; 8: 1–21.

30.

Russell

Mclean

Impellizzeri

, et al. Measuring physical demands in basketball: an explorative systematic review of practices. Sport Med 2021; 51: 81–112.

31.

Pernigoni

Kreivytė

Lukonaitienė

, et al. Is foam rolling as effective as its popularity suggests? A randomised crossover study exploring post-match recovery in female basketball. J Sports Sci 2023; 41: 1718–1725.

32.

Hurst

Schipof-Godart

Szabo

, et al. The placebo and nocebo effect on sports performance: a systematic review. Eur J Sport Sci 2020; 20: 279–292.

33.

Nasser

Zorgati

Chtourou

, et al.

Cold water immersion after a soccer match: does the placebo effect occur?

Front Physiol 2023; 14: 1–12.

34.

Drevon

Fursa

Malcolm

. Intercoder reliability and validity of WebPlotDigitizer in extracting graphed data. Behav Modif 2017; 41: 323–339.

35.

Souglis

Bourdas

Gioldasis

, et al. Time course of performance indexes, oxidative stress, inflammation, and muscle damage markers after a female futsal match. Sports 2023; 11: 1–22.

36.

Mariscal

Vera

Platero

, et al. Changes in different salivary biomarkers related to physiologic stress in elite handball players: the case of females. Sci Rep 2019; 9: 1–8.

37.

Akarçeşme

Cengizel

Şenel

, et al. Heart rate and blood lactate responses during the volleyball match. Sci Rep 2022; 12: 1–8.

38.

Corvillo

Timon

Maynar

, et al. Urinary excretion of steroid hormones after a female handball match. Rev Int Med Y Ciencias La Act Fis Y Del Deport 2013; 13: 737–747.

39.

Dal’Maz

Gimunová

Parpa

, et al. Description of perceived exertion, recovery and menstrual status across a single-congested tournament of European women futsal: the case of the winning team. Rev Bras Futsal e Futeb 2023; 15: 281–288.

40.

Sepahvand

Jahromi

Sahraei

, et al. Studying the perceptive and cognitive function under the stress of match in female futsal players. Asian J Sports Med 2017; 8: 1–5.

41.

Kassiano

Jesus

Assumpção

, et al. Physiological and neuromuscular responses during the game in female futsal players. J Phys Educ 2019; 30: 4–11.

42.

Delextrat

Calleja-González

Hippocrate

, et al. Effects of sports massage and intermittent cold-water immersion on recovery from matches by basketball players. J Sports Sci 2013; 31: 11–19.

43.

Delextrat

Hippocrate

Leddington-Wright

, et al. Including stretches to a massage routine improves recovery from official matches in basketball players. J Strength Cond Res 2014; 28: 716–727.

44.

Delextrat

Trochym

Calleja-González

. Effect of a typical in-season week on strength jump and sprint performances in national-level female basketball players. J Sports Med Phys Fitness 2012; 52: 128–136.

45.

Izquierdo

. Quantitative assessment of the effects of official match on physical performance factors on under-16 and under-18 female basketball players at national league level. Eur J Hum Mov 2021; 46: 16–27.

46.

Izquierdo

Redondo

. Acute effects of basketball competition on physical performance factors in under-18 female players. [influencia de la competición sobre los factores de rendimiento físico en jugadoras de baloncesto sub-18]. RICYDE Rev Int Ciencias del Deport 2020; 16: 285–297.

47.

García-Ceberino

Fuentes-García

Villafaina

Impact of basketball match on the pre-competitive anxiety and HRV of youth female players. Int J Environ Res Public Health 2022; 19: 7894.

48.

Rossi

Amato

Alesi

, et al. Hormonal and psychological influences on performance anxiety in adolescent female volleyball players: a multi-approach study. PeerJ 2024; 12: 1–17.

49.

Lukonaitiene

Conte

Paulauskas

, et al. Investigation of readiness and perceived workload in junior female basketball players during a congested match schedule. Biol Sport 2021; 38: 341–349.

50.

Beato

Coratella

Schena

, et al. Evaluation of the external and internal workload in female futsal players. Biol Sport 2017; 34: 227–231.

51.

Skorski

Mujika

Bosquet

, et al. The temporal relationship between exercise, recovery processes, and changes in performance. Int J Sports Physiol Perform 2019; 14: 1015–1021.

52.

Gandevia

. Spinal and supraspinal factors in human muscle fatigue. Physiol Rev 2001; 81: 1725–1789.

53.

Silva

Rumpf

Hertzog

, et al. Acute and residual soccer match-related fatigue: a systematic review and meta-analysis. Sports Med 2018; 48: 539–583.

54.

Lee

Fragala

Kavouras

, et al. Biomarkers in sports and exercise: tracking health, performance, and recovery in athletes. J Strength Cond Res 2017; 31: 2920–2937.

55.

Davies

Few

. Effects of exercise on adrenocortical function. J Appl Physiol 1973; 35: 887–891.

56.

Clark

Heyward

Paul

, et al. Acute fatigue in indoor court-based team sports: a systematic review. PLoS One 2025; 20: 1–28.

57.

Hayes

Bickerstaff

Baker

. Interactions of cortisol, testosterone, and resistance training: influence of circadian rhythms. Chronobiol Int 2010; 27: 675–705.

58.

Bongiovanni

Genovesi

Nemmer

, et al. Nutritional interventions for reducing the signs and symptoms of exercise-induced muscle damage and accelerate recovery in athletes: current knowledge, practical application and future perspectives. Eur J Appl Physiol 2020; 120: 1965–1966.

59.

Hotfiel

Freiwald

Hoppe

, et al. Advances in delayed-onset muscle soreness (DOMS): part I : pathogenesis and diagnostics delayed onset muscle soreness – teil I : pathogenese und diagnostik authors mechanisms and pathogenesis. Sport Sport 2018; 32: 243–250.

60.

Genazzani

Lemarchand-Béraud

Aubert

, et al. Pattern of plasma acth, hgh, and cortisol during menstrual cycle. J Clin Endocrinol Metab 1975; 41: 431–437.

61.

Paludo

Paravlic

Dvořáková

, et al. The effect of menstrual cycle on perceptual responses in athletes: a systematic review with meta-analysis. Front Psychol 2022; 13: 1–10.