
==== Front
PeerJ
PeerJ
peerj
PeerJ
2167-8359
PeerJ Inc. San Diego, USA

39131612
17756
10.7717/peerj.17756
Anatomy and Physiology
Sports Medicine
Effects of strength training on repeated sprint ability in team sports players: a systematic review
Osses-Rivera Andrés 1
Yáñez-Sepúlveda Rodrigo 2
Jannas-Vela Sebastián 3
Vigh-Larsen Jeppe F. 4
Monsalves-Álvarez Matías matias.monsalves@unab.cl
5
1 Escuela de Educación, Universidad Mayor, Santiago, Chile
2 Faculty Education and Social Sciences, Universidad Andrés Bello, Viña del Mar, Chile
3 Instituto de Ciencias de la Salud, Universidad de O’Higgins, Rancagua, Chile
4 Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
5 Exercise and Rehabilitation Sciences Institute, Faculty of Rehabilitation Sciences, Universidad Andrés Bello, Santiago, Chile
Barbosa Tiago
6 8 2024
2024
12 e177565 12 2023
25 6 2024
©2024 Osses-Rivera et al.
2024
Osses-Rivera et al.
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

Objective

This systematic review was conducted to analyze the existing evidence on the effects of strength training (ST) and complex/contrast training (CCT) on repeated sprint ability (RSA) in team sports players.

Methods

A systematic review of the literature was performed following the PRISMA statement. PubMed, Web of Science, and Scopus databases were used. Original full-text articles were analyzed, without date restriction until May 26, 2024, written in English, peer-reviewed, and for eligibility must have included (1) male or female team sports players, amateur or professional category, without age restriction (2) lower extremity ST and/or CCT program (3) active control group (4) running RSA test (e.g., repeated shuttle sprint ability test or straight-line repeated sprint ability test) before and after the intervention period (5) controlled trial.

Results

A total of 3,376 studies were identified and screened. Finally, 10 articles were included based on the inclusion and exclusion criteria, all with moderate methodological quality according to the PEDro scale. The best time, mean time, and total time presented significant pre and post-test changes, using ST in 3, 2, and 1 experimental groups, respectively, and using CCT in 1, 1, and 1 experimental groups, respectively, with almost no differences in the percentage decrement most commonly reported in RSA tests. There were no changes in the control groups.

Conclusion

Together, ST performed in a range of maximal power provides benefits in the best time and mean time and performed between 80 to 95% of 1 repetition maximum (RM) provides benefits in the best time, mean time, and total time in RSA tests. CCT performed between 75 to 90% of 1 RM combined with jumps and sprints provides benefits in the best time, mean time, and total time in RSA test, but no unaltered percentage decrement in ST and CCT in elite and semi-professional team sport players.

Physical fitness
Athletic performance
Power
Muscular strength
Post-activation performance enhancement
The authors received no funding for this work.
==== Body
pmcIntroduction

Team sports are characterized by an intermittent high-intensity exercise pattern, including sequences of repeated maximal or near maximal efforts ≤10s interspersed with short recovery intervals ≤60s (Spencer et al., 2005; Girard, Mendez-Villanueva & Bishop, 2011). During a match, the frequency, duration and distance of sprinting on average range 7–61 of 2.0 s for 15.2 m, 18–105 of 0.5–2.4 s for 3.9–9.5 m, 19-25 of 0.9–3.0 s for 10.0–19.1 m and 7.4 ± 3.3 of 1.6–1.9 s for 7.8–13.0 m, in elite male soccer, basketball, handball, and futsal players respectively (Taylor et al., 2017).

The ability to maintain sprint performance as maximal efforts are repeated has been termed repeated sprint ability (RSA) (Spencer et al., 2005; Girard, Mendez-Villanueva & Bishop, 2011), and even though recent evidence has questioned the frequency by which such sequences occur (Schimpchen et al., 2016; Taylor et al., 2016), they may indeed represent critical “worst case” scenarios during games where fatigue has been shown to manifest both transiently after intense efforts, as well as during the latter stages of a match (Mohr, Krustrup & Bangsbo, 2005). For example, in soccer, the RSA tests have been reported to be valid in discriminating playing levels and highly reliable (Altmann et al., 2019).

In general, the physiological factors of importance for team sport performance are derived from the initial sprint performance and the ability to sustain performance during subsequent bouts, that is, maximal and repeated sprint ability (Bishop & Girard, 2013). Ultimately, sprint performance is determined by the stride length and frequency, where stride length is related to muscular power, elastic properties of musculotendinous unit/tissue, and dynamic flexibility (Bishop, Girard & Mendez-Villanueva, 2011; Bishop & Girard, 2013). In contrast, stride frequency is related to intramuscular coordination (Bishop, Girard & Mendez-Villanueva, 2011; Bishop & Girard, 2013), which includes neuromuscular activation (i.e., recruitment of motor units (MU) and the discharge rates of action potentials, MU synchronization, and neuromuscular inhibition) (Girard, Mendez-Villanueva & Bishop, 2011). Single sprint performance is predominantly fueled by phosphocreatine hydrolysis and anaerobic glycolysis (e.g., almost 50/50 during a single 6-s sprint) (Gaitanos et al., 1993; Parolin et al., 1999). At the same time, the importance of aerobic metabolism increases with repeated sprint efforts (Gaitanos et al., 1993; Parolin et al., 1999). Recovery between sprints is strongly related to phosphocreatine resynthesis capacity, ultimately determined by aerobic capacity (Bishop, Girard & Mendez-Villanueva, 2011; Bishop & Girard, 2013). In contrast, other factors, such as hydrogen buffering and restoration of ionic homeostasis, may also be important (Sahlin & Harris, 2011; Hostrup & Bangsbo, 2017). As such, multiple factors interact to determine repeated sprint ability, with strength/power and metabolic factors being key components.

Importantly, greater muscular strength is strongly associated with enhanced force-time characteristics (rate of force development (RFD) and external mechanical power), with both being critical muscular factors that determine sprint performance in team sports (Suchomel, Nimphius & Stone, 2016) and the evidence is compelling that sprint performance can be enhanced by different modalities of strength training programs (Suchomel, Nimphius & Stone, 2016).

Traditional strength training (ST) is characterized by high loads (70–100% 1 repetition maximun (1 RM)) performed with low repetitions, typically between 12-1 and separated by longer durations of passive rest of approximately 2–5 min. Instead, power training is characterized by using loads >80% 1 RM for enhanced strength characteristics or 30–60% 1RM for enhanced velocity characteristics, 3-6 sets, 1-6 reps, and >3 min rest (heavy) or 1–2 min rest (moderate) respectively (Kraemer & Ratamess, 2004). In contrast, complex/contrast training (CCT) is characterized by a combination of high-load, low-velocity strength exercise, also called conditioning activity (CA), followed immediately by a low-load, high-velocity plyometric/ballistic exercise, set by set within the same session (Cormier et al., 2022). This sequence elicits the “post-activation potentiation” effect with a short half-life of (∼28 s), classically defined as an improvement in muscle strength that results from phosphorylation of myosin regulatory light chain by myosin light chain kinase in the muscle fibers type II (Blazevich & Babault, 2019).

In the last decade, a considerable amount of published studies as meta-analyses have analyzed the effects of ST (characterized by actions against external resistance) and CCT of the lower extremities, highlighting substantial improvements in sprint performance in team sports players (Seitz et al., 2014; Freitas et al., 2017; Thapa et al., 2020). On the other hand, the effects of ST and CCT on RSA are less clear because, unlike a single sprint, initial sprint performance is associated with a more significant subsequent drop in performance. It is unclear how a potential strength-mediated improvement in sprint performance affects repeated sprint performance when several bouts are performed (Girard, Mendez-Villanueva & Bishop, 2011). On this topic, only one meta-analysis study has explored the effects of CCT with a negligible effect on RSA (p = 0.156; ES = 0.32) in male soccer players (Thapa et al., 2022). However, some studies did not include control groups, so the efficacy is not adequately addressed. No previous studies have systematically explored the effects of ST and CCT on RSA in different team sports. Therefore, this systematic review aims to analyze the existing evidence on (1) The effects of ST on the RSA, (2) The effects of CCT on the RSA, and (3) The effects of ST and CCT on fatigue in team sports players. We hypothesized that ST and CCT would effectively improve the initial sprint performance (i.e., best time) but not recovery between sprints (i.e., fatigue index or percentage decrement).

Materials & Methods

Search strategy

This study is a systematic literature review, following the Preferred Reported Items for Systematic Reviews and Meta-Analysis (PRISMA) statements (Liberati et al., 2009), in which original, peer-reviewed articles published in English without date restrictions were considered. The PubMed, Web of Science (Core Collection), and Scopus databases were considered until May 26, 2024.

Eligibility criteria

Inclusion and exclusion criteria were structured through a PICOS approach (participants, intervention, comparators, outcomes, and study design) and are presented in detail in Table 1.

10.7717/peerj.17756/table-1 Table 1 Inclusion and exclusion criteria following the PICOS approach.

Category	Inclusion criteria	Exclusion criteria	
Population	Male and female team sports players (field- or court-based invasion sports), without previous injuries or other health problems, of amateur or professional category, without age restriction	Non-team sports (e.g., individuals, racquet or combat sports), or water-based team sports. Team sports players with health problems and injured	
Intervention	Lower extremity strength training program, defined as the ability to exert force over some type of external object or resistance (e.g., traditional strength or power training) (Kraemer & Ratamess, 2004), lower extremity complex/contrast training program, defined as a combination of heavy load strength exercise (slower speed) followed by low load plyometric/power exercise (faster speed), set by set fashion within the same session (Cormier et al., 2022)	Programs that included other motor gestures to strength or complex/contrast training of the lower extremity (e.g., circuit training). Program that used only body weight (e.g., plyometric or Nordic hamstring exercises)	
Comparator	Active control group (CG) that only performed regular training in their respective team sport. It could include low-intensity exercise (e.g., injury prevention)	Absence of an active control group	
Outcomes	At least one measure of physical performance (running RSA test) before and after the intervention period. Also, RSA test was performed over the ground on a flat surface at maximal intensity, with a mean work duration of ≤ 10 s or ≤ 80 m in distance, a recovery duration of ≤ 60 s and ≥ 2 repetitions performed in total. Single set and multi-set repeated-sprints (Thurlow et al., 2023)	Lack of physical performance measures before and after the intervention period.
RSA test was performed on a treadmill, cycle ergometers or another implement.
RSA test was performed at submaximal intensity, with a work duration of > 10 s or > 80 m, a recovery duration of > 60 s, and only a single sprint repetition	
Study design	Controlled and/or parallel trials	Non-controlled trials	

Selection of articles

Search criteria were performed using the following descriptors: “ballistic training”, “resistance training” [Mesh], “strength training” [Mesh], “complex training”, “contrast training”, “weight training”, “repeated change of direction”, “repeated sprint ability”, “repeated sprint exercise”. The search equation in PubMed, Web of Science (Core Collection), and Scopus databases originated with the Boolean operators “AND” and “OR”. Table 2 shows in detail the search strategies used in the three databases.

10.7717/peerj.17756/table-2 Table 2 Search strategies used in each database.

Search equation	Filters	Databases	Results	Date	
((“ballistic training”[Title/Abstract] OR “resistance training”[Title/Abstract] OR “strength training”[Title/Abstract] OR “complex training”[Title/Abstract] OR “contrast training”[Title/Abstract] OR “weight training”[Title/Abstract]) AND “repeated change of direction “[Title/Abstract]) OR “repeated sprint ability”[Title/Abstract] OR “repeated sprint exercise”[Title/Abstract]	Title/Abstract	PubMed	664
678
723	14-05-2023
27-08-2023
26-05-2024	
(ballistic training OR resistance training OR strength training OR complex training OR contrast training OR weight training) AND (repeated change of direction OR repeated sprint ability OR repeated sprint exercise)	Topic: Searches
title, abstract,
author keywords,
and Keywords
Plus	Web of
Science
(Core
Collection)	812
832
893	14-05-2023
27-08-2023
26-05-2024	
(“ballistic training”  OR  “resistance training”  OR  “strength training”  OR   “complex training”  OR  “contrast training”  OR  “weight training”  AND   “repeated change of direction”  OR   “repeated sprint ability”  OR  “ repeated sprint exercise”)	All fields/Article	Scopus	1,477
1,568
1,760	14-05-2023
27-08-2023
26-05-2024	

In addition, manual searches were performed by consulting grey literature, and reference lists were analyzed from selected articles in search of possible studies.

Extraction and evaluation process

Articles were selected by title and abstract; then, the full text was reviewed to finally apply the inclusion criteria described in Table 1. Duplicate articles were removed manually using Zotero (version 6.0.37) reference management software, and the full-text articles excluded were recorded in a Microsoft Excel table with the causes for their exclusion. Two authors conducted the search independently (AO-RY); if necessary, a third reviewer acted as judge (MMA) to resolve potential discrepancies between the two authors.

Data extraction

Data extraction was performed by the lead author using a standardized form created in Microsoft Excel. The repeated sprint ability was considered the primary variable, measured with different RSA tests recorded in execution time in seconds as mean ± standard deviation (SD). From the extracted data, means, SD, first author’s last name, year of publication of the studies, sport, competition season, training intervention characteristics (frequency (days/week), duration (weeks), total sessions (frequency/duration), general characteristics of training (protocol), pause between sets and exercises (seconds), rest between sessions (hours), intervention time (minutes)) and descriptive characteristics of team sports players (number of subjects per group (size), chronological age (years), height (cm), body weight (kg), sex (M/F), performance level and training experience (years of training)) were recorded in a results table.

Study and assessment of the risk of bias

The Physiotherapy Evidence Database (PEDro) scale was used to assess the risk of bias and methodological quality of the included studies (Moseley et al., 2002). This scale was developed to quickly identify trials that tended to be internally valid and to have enough statistical information to guide decision-making. The PEDro scale is designed with eleven items, all but the first (external validity) awarding one point if present, so the final score should be between 0 and 10 points. According to the predetermined cut-off points, studies are classified as high (eight to ten), medium (four to seven), or low quality (less than four). (Table 3). The lead author assessed the risk of bias for all studies. Also, p and ES values were collected (if available) for each selected article. The percent of change (Δ%) was calculated (if not available) of each article to evaluate the magnitude of the effects using the following equation: Δ% = (Mpost –Mpre/Mpre) ×100, where Mpost represents the mean value after intervention and Mpre the baseline mean value.

10.7717/peerj.17756/table-3 Table 3 Risk of bias in studies.

Author	Criteria		
	1	2	3	4	5	6	7	8	9	10	11	Total	Study quality	
Chatzinikolaou et al. (2018)	1	1	0	1	0	0	0	1	1	1	1	6	Moderate	
Durán-Custodio et al. (2023)	1	1	0	1	0	0	0	0	1	1	1	5	Moderate	
Gonzalo-Skok et al. (2016)	1	1	0	1	0	0	0	1	1	1	1	6	Moderate	
Hammami et al. (2019)	1	1	0	1	0	0	0	1	1	1	1	6	Moderate	
Hammami et al. (2018)	1	0	0	1	0	0	0	1	1	1	1	5	Moderate	
Hammami et al. (2017b)	1	1	0	1	0	0	0	1	1	1	1	6	Moderate	
Hammami et al. (2017a)	1	1	0	1	0	0	0	1	1	1	1	6	Moderate	
Hermassi et al. (2017)	1	1	0	1	0	0	0	1	0	1	1	5	Moderate	
Torres-Torrelo, Rodríguez-Rosell & González-Badillo (2017)	1	1	0	1	0	0	0	1	1	1	1	6	Moderate	
Torres-Torrelo et al. (2018)	1	1	0	1	0	0	0	1	1	1	1	6	Moderate	
Notes.

Note: 1. eligibility criteria were specified 2. subjects were randomly allocated to groups (in a crossover study, subjects were randomly allocated an order in which treatments were received) 3. allocation was concealed 4. the groups were similar at baseline regarding the most important prognostic indicators 5. there was blinding of all subjects 6. there was blinding of all therapists who administered the therapy 7. there was blinding of all assessors who measured at least one key outcome 8. measures of at least one key outcome were obtained from more than 85% of the subjects initially allocated to groups 9. all subjects for whom outcome measures were available received the treatment or control condition as allocated or, where this was not the case, data for at least one key outcome was analysed by “intention to treat” 10. the results of between-group statistical comparisons are reported for at least one key outcome 11. the study provides both point measures and measures of variability for at least one key outcome.

A detailed explanation for each PEDro scale item can be accessed at the study by Moseley et al. (2002).

Results

Selection of the studies

Through the realization of the literature search in the selected databases, a total of 723 studies were identified in PubMed, 893 in Web of Science, and 1,760 from Scopus. After removing duplicates, meta-analyses, systematic reviews, and abstracts, a total of 2,807 results of full texts were available. After reading the titles and abstracts, 39 relevant articles remained, and 2,768 were excluded for not presenting the eligibility criteria. The full texts of the 39 articles were read using the inclusion and exclusion criteria specified for the eligibility of the studies. Finally, ten articles were selected (Fig. 1).

10.7717/peerj.17756/fig-1 Figure 1 PRISMA flow diagram.

The methodological quality of the 10 studies included in this systematic review was quantified through the PEDro scale, yielding moderate quality in the 10 studies (five to six points). None of the studies reported whether the allocation was concealed (criterion 3) (Table 3).

Study characteristics

Among the main characteristics of ten studies (Chatzinikolaou et al., 2018; Durán-Custodio et al., 2023; Gonzalo-Skok et al., 2016; Hammami et al., 2019; Hammami et al., 2018; Hammami et al., 2017b; Hammami et al., 2017a; Hermassi et al., 2017; Torres-Torrelo, Rodríguez-Rosell & González-Badillo, 2017; Torres-Torrelo et al., 2018), these are composed of 10 active control groups (continued with their regular training in their respective sport) and 11 experimental groups (replaced a part of the training of their respective sport by ST or CCT), of nine studies, included only one experimental group. Only one study experimented with more than one group (Hammami et al., 2017a). All studies were randomized controlled trials except for one study (Hammami et al., 2018), which was not randomized. A total of nine studies included only men, and one included only women (Hammami et al., 2019). The age ranged from 14.1 ± 0.6 (Chatzinikolaou et al., 2018) to 25.8 ± 2.0 years (Durán-Custodio et al., 2023).

Training and strength measurements

Regarding the types of training, four studies included traditional ST with free-weight using halfback squat (Chatzinikolaou et al., 2018; Hammami et al., 2018; Hammami et al., 2017a; Hermassi et al., 2017), three included CCT also with free-weight (Chatzinikolaou et al., 2018; Hammami et al., 2017b; Hammami et al., 2017a) but one (Hammami et al., 2019) with free-weight and machine, two studies included ST with free-weight using full squat with a linear velocity transducer (T-Force System, Ergotech, Murcia, Spain) to record bar velocity (Torres-Torrelo, Rodríguez-Rosell & González-Badillo, 2017; Torres-Torrelo et al., 2018), one included ST with machine (Technogym™  and Precor™, Madrid, Spain) (Durán-Custodio et al., 2023) and another study included optimal power output load training with leg press (Gonzalo-Skok et al., 2016). Regarding movement velocity, five studies indicated “maximal voluntary effort” (Hammami et al., 2019; Hammami et al., 2018; Hammami et al., 2017b; Hammami et al., 2017a; Hermassi et al., 2017), three studies indicated “maximal concentric repetition velocity” (Gonzalo-Skok et al., 2016; Torres-Torrelo, Rodríguez-Rosell & González-Badillo, 2017; Torres-Torrelo et al., 2018), while two studies did not report it. All the studies included exercises in dynamic contractions (isotonic), multi-joint, and bilateral except the studies by Chatzinikolaou et al. (2018) and Durán-Custodio et al. (2023), which included some unilateral exercises, besides the study by Hammami et al. (2019), which included some exercises in static contractions (isometric) and single-joint.

RSA testing

Regarding RSA testing, six studies included repeated shuttle sprint ability test (6 × 15 − 20 + 15 − 20 m; 20 s passive recovery; 180° turn) (Gonzalo-Skok et al., 2016; Hammami et al., 2019; Hammami et al., 2018; Hammami et al., 2017b; Hammami et al., 2017a; Hermassi et al., 2017) and four studies included straight-line repeated sprint ability Test (5 − 9 × 20 − 30 m; 25 s active recovery) (Chatzinikolaou et al., 2018; Durán-Custodio et al., 2023; Torres-Torrelo, Rodríguez-Rosell & González-Badillo, 2017; Torres-Torrelo et al., 2018).

Also, the measures found in the RSA tests were as follows: the best time (the fastest of all sprints), the mean time (the average time of all sprints), the total time (the sum of all sprints), fatigue index (data not provided in the studies) and the percentage decrement score calculated as follows (100 × (total sprint time ÷ ideal sprint time)) –100, where total sprint time = sum of sprint times from all sprints. Ideal sprint time = the number of sprints × fastest sprint time.

Main results of strength and complex training (EG) on RSA

Effects of strength training on best time

Five studies provided data for best time. Gonzalo-Skok et al. (2016), using maximal power training, found that for elite male basketball players, no substantial improvements were evident within-group (small ES; 0.24) or compared to CG (trivial ES; 0.2). Similar results were found by Hammami et al. (2018); Hammami et al. (2017a), both using traditional ST, where junior male soccer players had no significant changes compared to CG (all trivial ES; <0.2). Instead, Hermassi et al. (2017), using traditional ST, found that elite male handball players had significant changes compared to CG (large ES [η2]; 0.246). Also, Torres-Torrelo et al. (2018), using ST with a linear velocity transducer, found that elite male futsal players had significant improvement within-group in best 10 m sprint time (moderate ES; −0.62) and best 20 m sprint time (small ES; −0.46) but this difference was not statistically different from the CG (p > 0.05, small ES; 0.50, 0.53).

Effects of strength training on mean time

Six studies provided data for mean time. Gonzalo-Skok et al. (2016) showed substantial improvements within-group (small ES; 0.49) with “likely” improvements compared to CG. Instead, Hammami et al. (2018); Hammami et al. (2017a) had no significant changes compared to CG (all trivial ES; <0.2). In contrast, Hermassi et al. (2017) had significant changes compared to CG (large ES (η2); 0.183). Instead, Torres-Torrelo, Rodríguez-Rosell & González-Badillo (2017), using ST with a linear velocity transducer, found that elite male futsal players had no significant changes within-group (trivial ES; −0.10) neither compared to CG (p > 0.05). Neither Torres-Torrelo et al. (2018) had any significant changes within-group in mean 10 m sprint time (trivial ES; −0.05) and mean 20 m sprint time (trivial ES; −0.11) neither compared to CG (p > 0.05, trivial ES; −0.06, 0.20).

Effects of strength training on fatigue index or percentage decrement

Seven studies provided data for fatigue index or percentage (%) decrement. Chatzinikolaou et al. (2018), using traditional ST and CCT in different sessions, had no significant intragroup changes (p > 0.05) in fatigue index in junior elite male soccer players, which neither were significant compared to the control condition. Gonzalo-Skok et al. (2016) showed “unclear” improvements within-group (small ES; 0.54) and compared to CG (small ES) in % decrement. Hammami et al. (2018); Hammami et al. (2017a) had no significant effects compared to CG (all trivial ES; <0.2) in % decrement and fatigue index, respectively. Also, Torres-Torrelo, Rodríguez-Rosell & González-Badillo (2017) had no significant changes within the group in % decrement (small ES; 0.41) or compared to CG (p > 0.05). Instead, Torres-Torrelo et al. (2018) had significant changes within the group in % decrement 10 m (small ES; 0.46), but not % decrement 20 m (small ES; 0.44), neither compared to CG (p > 0.05, small ES; 0.42, 0.41) and Durán-Custodio et al. (2023), using ST, found that semi-professional male soccer players had significant changes within the group (large ES; 1.25) in decrement (s) but not compared to CG (p = 0.141).

Effects of strength training on total time

Four studies provided data for total time. Hammami et al. (2018); Hammami et al. (2017a) had no significant changes compared to CG (all trivial ES; <0.2). Also, Hermassi et al. (2017) had no significant changes compared to CG (moderate ES (η2); 0.078). In contrast, Durán-Custodio et al. (2023) had significant changes within the group (large ES; 5.34) and compared to CG (p < 0.001).

Effects of complex/contrast training on best time, mean time, fatigue index, and total time

Three studies provided data for best time, mean time, fatigue index, and total time. Hammami et al. (2019), using CCT, found that elite female handball players had significant changes compared to CG in all outcomes (all trivial ES; 0.08), except in the fatigue index (trivial ES; 0.01). Instead, the studies by Hammami et al. (2017b); Hammami et al. (2017a), both using CCT, found that junior male soccer players had no significant changes compared to CG in all outcomes (all trivial ES; <0.2).

Effects of active control groups on RSA

The active control groups in the different studies continued their regular training in their respective team sport without performing ST or CCT and showed no significant intra-group changes in any measure. The descriptions of the selected studies, including the subjects’ characteristics and the ST and CCT intervention, are shown in Tables 4 and 5. The main results of the RSA tests are in detail in Table 6.

10.7717/peerj.17756/table-4 Table 4 Subjects’ characteristics.

Author	Sport	Group	No of
subjects
(size)	Age
(years)
(mean ± SD)	Height
(cm)
(mean ± SD)	Weight (kg)
(mean ± SD)	Sex
(M/F)	Training
experience
(years)
(mean ± SD)	Performance
level	Season	
Chatzinikolaou et al. (2018)	Soccer	STG
CG	12
10	14.3 ± 0.7
14.1 ± 0.6	179 ± 0.1
178 ± 0.1	69.13 ± 5.0
72.24 ± 8.1	M	≥6/no experience in strength	Junior Elite	Off-season	
Durán-Custodio et al. (2023)	Soccer	STG
CG	10
10	24.5 ± 3.1
25.8 ± 2.0	176.6 ± 4.4
178.3 ± 3.6	72.8 ± 6.6
74.7 ± 5.7	M	with experience in strength	Semi-professional	In-season	
Gonzalo-Skok et al. (2016)	Basketball	RMPG
CG	11
11	16.2 ± 1.2
16.2 ± 1.2	190.0 ± 10.0
190.0 ± 10.0	82.9 ± 10.1
82.9 ± 10.1	M	7 years/ with experience in strength	Elite	In-season	
Hammami et al. (2019)	Handball	CCTG
CG	14
14	16.6 ± 0.3
16.6 ± 0.3	163 ± 0.04
164 ± 0.04	60.8 ± 4.7
60.4 ± 4.3	F	NR/with experience in strength	Elite	In-season	
Hammami et al. (2018)	Soccer	STG
CG	19
12	16.2 ± 0.6
15.8 ± 0.2	175 ± 0.03
168 ± 0.05	58.1 ± 7.3
58.2 ± 5.0	M	NR/with experience in strength	Junior	In-season	
Hammami et al. (2017b)	Soccer	CCTG
CG	17
12	16.0 ± 0.5
16.8 ± 0.2	177 ± 5
169 ± 5	58.9 ± 6.6
58.4 ± 5.2	M	NR/with experience in strength	Junior	In-season	
Hammami et al. (2017a)	Soccer	STG
CCTG
CG	16
16
12	16.2 ± 0.6
16.0 ± 0.5
16.8 ± 0.2	175 ± 0.03
178 ± 0.05
168 ± 0.05	58.0 ± 6.2
59.3 ± 6.5
58.1 ± 5.2	M	NR/with experience in strength	Junior	In-season	
Hermassi et al. (2017)	Handball	STG
CG	12
10	18.9 ± 0.2
18.9 ± 0.6	195 ± 0.2
190 ± 0.3	93.4 ± 10.2
91.2 ± 10.1	M	9.2 ± 0.9
9.0 ± 0.6/with experience in strength	Elite	In-season	
Torres-Torrelo, Rodríguez-Rosell & González-Badillo (2017)	Futsal	STG
CG	12
10	23.8 ± 2.4
24.7 ± 4.7	177.2 ± 0.05
176.5 ± 0.06	73.6 ± 7.0
75.9 ± 7.1	M	10.0 ± 3.1
10.0 ± 3.3/no experience in strength	Elite	In-season	
Torres-Torrelo et al. (2018)	Futsal	STG
CG	12
10	23.8 ± 2.4
24.7 ± 4.7	177 ± 0.05
177 ± 0.06	73.6 ± 7.0
75.9 ± 7.1	M	10.0 ± 3.1
10.0 ± 3.3/no experience in strength	Semi-professional	In-season	
Notes.

Abbreviations CG control group

RMPG repeated maximal power group

STG strength training group

CCTG complex contrast training group

M male

F female

10.7717/peerj.17756/table-5 Table 5 Strength and complex training intervention.

Author	F	D	TS	Training type	General training characteristics	Speed of movement	Rest between session (hours)	Time of intervention
(minutes)		
Chatzinikolaou et al. (2018)	4	5	20	Strength	2 sessions
(squat, Romanian deadlift (RDL), strides or step-ups, one-legged RDL)
60–70 to 80–90% of 1RM
Sets: 2
Repetitions: 10–14 to 6–3
Pause: 60 s to 120 s	NR	NR	30		
				Complex	2 sessions
(combination of multi-joint
Olympic-style lifts, plyometric,
and speed work; e.g., barbell
cleans, kettlebell snatches,
box jumps, speed/power drills)
Sets: 3
Repetitions: 6–8
Pause: 90–120 s
Linear Periodization *	NR	NR	30		
Durán-Custodio et al. (2023)	2	12	24	Strength	Unilateral horizontal leg press,
unilateral lateral leg press
with 45° inclination of the
supporting foot with respect
to the surface, knee extension
and knee flexion
85–95% of 1 RM
Sets: 3 per each exercise
Repetitions: 3–4
Pause: 3 min between sets
Periodization progressive	NR	48	35–40		
Gonzalo-Skok et al. (2016)	2	6	12	Repeated
maximal
power	Leg press exercise using
the load that maximizes
power output 120.3 ± 22.1 kg or 937.4 ± 248.4 watts.
Weeks 1 to 3: 1 block
Sets: 5
Repetitions: 5
Pause: 20 s passive recovery
Weeks 4 to 6: 2 blocks
Sets: 5
Repetitions: 5
Pause: 20 s between sets
and 3 min between blocks, passive recovery
Periodization progressive	Maximum speed
concentric
repetition.
The eccentric
phase was
performed at a
slower speed	48	10–20		
Hammami et al. (2019)	2	10	20	Complex	4 times each series/session
Series 1: 6 repetitions half
squat at 85% of 1 RM + 6
hurdle jumps to 40 cm + 10 m sprints
Series 2: 6 repetitions thigh
press at 85% of 1 RM + 6 horizontal
jumps + 10 m sprints
Series 3: half isometric squat of
8 s at 75% of 1RM + 6 jumps on
1 foot [3 on the right side and
3 on the left side] + 10 m sprints
Series 4: 6 repetitions of calf
extension at 90% of 1RM + 6
hurdle jumps to 30 cm
with legs extended + 10 m sprints
Pause: 1–2 min between sets
Linear Periodization **	Maximum
verbal
effort	NR	40		
Hammami et al. (2018)	2	8	16	Strength	Halfback squat
Tuesday: ascending set 70–90%
followed by a descending set 90–70% of 1RM
Thursday: upward set 70–90%
of 1RM 3 sets x 8 reps at 70%
5 sets x 4 reps at 80%
4 sets x 3 reps at 85%
3 sets x 3 reps at 90%
Pause: NR
Linear Periodization **	Maximum
verbal
effort	NR	30		
Hammami et al. (2017b)	2	8	16	Contrast	Weeks 1–4: halfback squat + 3
consecutive CMJs
Weeks 5–8: halfback squat
+ 1 CMJ + 15 m sprint
Tuesdays: ascending set 70–90%
followed by a descending set
90–70% of 1RM
Thursday: upward set 70–90% of 1RM
3 sets x 8 reps at 70%
5 sets x 4 reps at 80%
4 sets x 3 reps at 85%
3 sets x 3 reps at 90%
Pause: NR
Linear Periodization **	Maximum
verbal
effort	NR	45		
Hammami et al. (2017a)	2	8	16	Strength	Halfback squat
Tuesday: ascending set 70–90%
followed by a descending set 90–70% of 1RM
Thursday: upward set
70–90% of 1RM 3 sets x 8 reps at 70%
5 sets x 4 reps at 80%
4 sets x 3 reps at 85%
3 sets x 3 reps at 90%
Pause: NR	Maximum verbal effort	NR	45		
				Contrast	Weeks 1–4: halfback squat + 3 consecutive CMJs
Weeks 5–8: halfback squat +
1 CMJ + 15 m sprint
Tuesdays: ascending set 70–90%
followed by a descending set 90–70% of 1RM
Thursday: upward set 70–90% of 1RM
3 sets x 8 reps at 70%
5 sets x 4 reps at 80%
4 sets x 3 reps at 85%
3 sets x 3 reps at 90%
Pause: NR
Linear Periodization **			45		
Hermassi et al. (2017)	2	10	20	Strength	Halfback squat
80 to 95% of 1 RM
Sets: 3-6
Repetitions: 3-1
Pause: 3-4 min between sets
Periodization Non-progressive	Maximum
verbal
effort	48	NR		
Torres-Torrelo, Rodríguez-Rosell & González-Badillo (2017)	2	6	12	Strength	Full squat
∼1.20 m-s-1
(∼45% 1RM) to ∼1 m-s-1
(∼58% 1RM)
36.8 ± 8.0 kg
to 49.6 ± 8.3 kg
Sets: 2-3
Repetitions: 6-4
Pause: 3 min between sets
Linear Periodization	Maximum speed
concentric
repetition	48–72	20–25		
Torres et al. (2018)	2	6	12	Strength	Full squat
∼1.20 m - s-1 (∼45% 1RM)
to ∼1 m - s-1 (∼60% 1RM)
36.8 ± 8.0 kg to 49.6 ± 8.3 kg
Sets: 2–3
Repetitions: 6-4
Pause: 3 min between sets
Linear Periodization	Maximum speed
concentric
repetition	48–72	20–25		
Notes.

Abbreviations F frequency (days/week)

D duration (weeks)

TS total sessions

1 RM repetition maximum

CMJ countermovement jump

NR not reported

* The 1 RM value was reassessed every two weeks, and the strength loadings were adjusted accordingly.

** The 1 RM value was reassessed at the fourth week, and the strength loadings were adjusted accordingly.

10.7717/peerj.17756/table-6 Table 6 Main results of the RSA tests.

Author	Physical test	Measure	Group	Pre-test
(mean ± SD)	Post-test
(Seconds)
(mean ± SD)	Within- group changes	Within-group p-value, effect size (ES)	% Δ	Group x Time interaction
p-value, effect size (ES)	Between- group Cohen’s ES	
Chatzinikolaou et al. (2018)	Repeated sprint ability Test RSA (s) (5 x 30 m; 25 s active rest)	Fatigue index (%)	STG
CG	N/A	N/A	→
→	>0.05
>0.05	N/A	>0.05	N/A	
Durán-Custodio et al. (2023)	Repeated sprint ability Test RSA (s) (5 x 30 m; 25 s active rest)	Total Time (s)	STG
CG	22.34 ± 0.70
21.85 ± 0.43	21.50 ± 0.66
21.71 ± 0.45	↑
↑	<0.001 (5.34)
0.010 (1.02)	−3.92
−0.64	<0.001 (F)87.34		
		Decrement (%)	STG
CG	4.15 ± 1.24
3.11 ± 0.95	3.10 ± 0.76
3.04 ± 0.68	↑
→	0.003 (1.25)
0.775 (0.09)	−33.94
−2.33	0.141 (F) 2.38		
Gonzalo-Skok et al. (2016)	Repeated shuttle sprint ability Test RSSA (s) (6 x 20 + 20 m; 20 s
passive rest)	Fastest Time (s)	RMPG
CG	7.16 ± 0.23
7.17 ± 0.24	7.10 ± 0.18
7.17 ± 0.24	→
→	(0.24)
(−0.01)	−0.8
0.0	Unclear	Small	
		Mean Time (s)	RMPG
CG	7.52 ± 0.23
7.50 ± 0.24
	7.40 ± 0.23
7.51 ± 0.22	↑
→	(0.49)
(−0.03)	−1.6
0.1	Likely *	Small	
		Slowest Time (s)	RMPG
CG	7.86 ± 0.29
7.76 ± 0.27	7.67 ± 0.29
7.79 ± 0.22	↑
→	(0.61)
(−0.13)	−2.4
0.5	Likely *	Small	
		Percentage of
decrement (%)	RMPG
CG	5.1 ± 1.8
4.6 ± 1.8	4.3 ± 1.7
4.7 ± 2.2	→
→	(0.54)
(−0.04)	−19.0
1.9	Unclear	Small	
Hammami et al. (2019)	Repeated shuttle
sprint ability
Test RSSA (s)
(6 x 20 + 20 m; 20 s
passive rest)	Fastest Time (s)	CCTG
CG	7.13 (0.32)
7.21 (0.13)	7.01 (0.32)
7.16 (0.13)	↑
→	<0.05
>0.05	−1.7
−0.7	.050 (0.08) *	Trivial	
		Mean Time (s)	CCTG
CG	7.39 (0.33)
7.44 (0.15)	7.27 (0.33)
7.40 (0.15)	↑
→	<0.05
>0.05	−1.6
−0.5	.051 (0.08) *	Trivial	
		Fatigue index (%)	CCTG
CG	3.71 (1.35)
3.11 (1.69)	3.77 (1.38)
3.13 (1.70)	→
→	>0.05
>0.05	1.6
0.6	.527 (0.01)	Trivial	
		Total Time (s)	CCTG
CG	44.4 (2.0)
44.6 (0.9)	43.6 (2.0)
44.4 (0.90)	↑
→	<0.05
>0.05	−1.8
−0.4	.051 (0.08) *	Trivial	
Hammami et al. (2018)	Repeated shuttle sprint ability Test RSSA (s)
(6 x 20 + 20 m; 20 s passive rest)	Fastest Time (s)	STG
CG	7.40 ± 0.11
7.37 ± 0.27	7.23 ± 0.07
7.28 ± 0.23	→
→	>0.05
>0.05	−2.3
−1.2	0.380 (0.013)	Trivial	
		Mean Time (s)	STG
CG	7.40 ± 0.11
7.37 ± 0.27	7.23 ± 0.07
7.28 ± 0.23	→
→	>0.05
>0.05	−2.3
−1.2	0.958 (0.000)	Trivial	
		RSSA decrement (s)	STG
CG	4.02 ± 1.42
3.41 ± 1.66	3.57 ± 1.39
3.27 ± 1.25	→
→	>0.05
>0.05	−11.2
−4.1	0.132 (0.039)	Trivial	
		Total Time (s)	STG
CG	46.2 ± 0.9
45.2 ± 2.8	45.0 ± 0.5
45.2 ± 1.7	→
→	>0.05
>0.05	−2.6
0	0.113 (0.043)	Trivial	
Hammami et al. (2017b)	Repeated sprint
ability Test RSA (s)
(6 x 20 m; 20 s
active rest)	Fastest Time (s)	CCTG
CG	7.39 ± 0.14
7.41 ± 0.35	7.23 ± 0.10
7.33 ± 0.35	→
→	>0.05
>0.05	−2.2
−1.1	0.511 (0.007)	Trivial	
		Mean Time (s)	CCTG
CG	7.64 ± 0.18
7.68 ± 0.38	7.45 ± 0.13
7.59 ± 0.39	→
→	>0.05
>0.05	−2.5
−1.2	0.496 (0.008)	Trivial	
		Fatigue index (%)	CCTG
CG	3.44 ± 1.14
2.26 ± 4.67	3.29 ± 1.04
3.52 ± 1.46	→
→	>0.05
>0.05	−4.4
55.8	0.243 (0.023)	Trivial	
		Total Time (s)	CCTG
CG	45.84 ± 1.11
45.45 ± 3.22	44.80 ± 0.73
45.53 ± 2.34	→
→	>0.05
>0.05	−2.3
0.2	0.257 (0.022)	Trivial	
Hammami et al. (2017a)	Repeated shuttle sprint ability Test RSSA (s)
(6 x 20 + 20 m; 20 s
passive rest)	Fastest Time (s)	CCTG
STG
CG	7.41 ± 0.15
7.42 ± 0.13
7.44 ± 0.38	7.23 ± 0.09 #
7.24 ± 0.08
7.37 ± 0.36	→
→
→	>0.05
>0.05
>0.05	−2.4
−2.4
−0.9	0.656 (0.010)	Trivial	
		Mean Time (s)	CCTG
STG
CG	7.64 ± 0.20
7.68 ± 0.13
7.71 ± 0.39	7.46 ± 0.13 #
7.60 ± 0.17
7.62 ± 0.40	→
→
→	>0.05
>0.05
>0.05	−2.4
−1.0
−1.2	0.724 (0.008)	Trivial	
		Fatigue index (s)	CCTG
STG
CG	3.16 ± 1.09
3.57 ± 1.08
2.18 ± 4.67	3.46 ± 1.02 #
3.66 ± 1.37
3.39 ± 1.41	→
→
→	>0.05
>0.05
>0.05	9.5
2.5
55.5	0.777 (0.006)	Trivial	
		Total Time (s)	CCTG
STG
CG	45.85 ± 1.18
46.10 ± 0.79
45.65 ± 3.30	44.87 ± 0.72 #
45.00 ± 0.53
45.69 ± 2.38	→
→
→	>0.05
>0.05
>0.05	−2.1
−2.4
0.08	0.378 (0.023)	Trivial	
Hermassi et al. (2017)	Repeated shuttle sprint ability Test RSSA (s)
(6 x 15 + 15 m; 20 s passive rest)	Fastest Time (s)	STG
CG	6.74 ± 0.31
6.76 ± 0.33	6.24 ± 0.12
6.60 ± 0.13	↑
→	<0.05 (2.33)
>0.05 (0.70)	−7.4
−2.4	0.019 (0.246) *	Large (η2) 	
		Mean Time (s)	STG
CG	6.93 ± 0.31
6.97 ± 0.33	6.51 ± 0.08
6.81 ± 0.10	↑
→	<0.05 (2.15)
>0.05 (0.74)	−6.06
−2.3	0.047(0.183) *	Large	
		Total Time (s)	STG
CG	40.5 ± 3.39
40.4 ± 3.73	39.1 ± 0.45
41.0 ± 1.38	→
→	>0.05 (0.73)
>0.05 (−0.24)	−3.5
1.5	0.208 (0.078)	Moderate	
Torres-Torrelo, Rodríguez-Rosell & González-Badillo (2017)	Repeated sprint
ability Test
RSA (s) (9 x 20 m;
25 s active rest)	Mean Time (s)	STG
CG	3.17 ± 0.12
3.19 ± 0.11	3.16 ± 0.12
3.20 ± 0.11	→
→	>0.05 (−0.10)
>0.05 (0.09)	−0.4
0.3	0.025 *	Trivial	
		Decrement (%)	STG
CG	3.60 ± 1.43
5.41 ± 2.99	4.81 ± 2.62
5.27 ± 3.07	→
→	>0.05 (0.41)
>0.05 (0.02)	25.6
1.2	>0.05	Trivial	
Torres-Torrelo et al. (2018)	Repeated sprint ability Test RSA (s) (9 x 20 m; 25 s active rest)	Fastest Time 10 m (s)	STG
CG	1.74 ± 0.05
1.73 ± 0.06	1.71 ± 0.08
1.73 ± 0.06	↑
→	<0.05 (−0.62)
>0.05 (−0.06)	−1.9
−0.2	>0.05 (0.50)	Small	
		Fastest Time 20 m (s)	STG
CG	3.06 ± 0.10
3.03 ± 0.09	3.02 ± 0.10
3.04 ± 0.08	↑
→	<0.05 (−0.46)
>0.05 (0.05)	−1.6
0.2	<0.05 (0.53) *	Small	
		Mean Time 10 m (s)	STG
CG	1.82 ± 0.07
1.84 ± 0.06	1.82 ± 0.08
1.83 ± 0.06	→
→	>0.05 (−0.05)
>0.05 (−0.13)	0.0
−0.4	>0.05(−0.06)	Trivial	
		Mean Time 20 m (s)	STG
CG	3.17 ± 0.12
3.19 ± 0.11	3.16 ± 0.12
3.20 ± 0.11	→
→	>0.05 (−0.13)
>0.05 (−0.11)	−0.4
0.3	<0.05 (0.20)*	Small	
		Decrement 10 m (%)	STG
CG	8.07 ± 3.88
11.57 ± 6.10	10.49 ± 5.02
11.00 ± 5.32	↑
→	<0.05 (0.46)
>0.05 (−0.02)	26.8
−1.3	>0.05 (0.42)	Small	
		Decrement 20m (%)	STG
CG	6.47 ± 2.50
9.59 ± 4.51	8.05 ± 3.44
9.80 ± 6.02	→
→	>0.05 (0.44)
>0.05 (0.05)	20.5
2.4	0.05 (0.41)	Small	
Notes.

Abbreviations CG control group

RMPG repeated maximal power group

STG strength training group

CCTG complex contrast training group p <0.05

N/A not available

↑ presented significant change within-group

→ no significant change within-group

* Significant “group x time” interaction.

# A main effect of time.

Discussion

The present review aimed to delineate the evidence on the effects of ST and CCT on RSA in team sports players. The main findings were that ST and CCT performed ∼twice weekly, between six to twelve weeks, which led to some improvements in best, mean, and total sprint time. It is also worth highlighting that these interventions, in general, were ineffective in significantly improving the fatigue index or percentage decrement. In addition, these effects seemed to be present irrespective of playing level, age, or sex.

Effects of strength training on the RSA

Four studies (Durán-Custodio et al., 2023; Gonzalo-Skok et al., 2016; Hermassi et al., 2017; Torres-Torrelo et al., 2018) presented significant changes in their EG in specific measures in the RSA tests (best time, mean time, and total time). These results are coincident with previous studies that only performed ST with similar exercises of the lower extremity (although with different % loads) and similar RSA tests in young male soccer players, professional male futsal players, and elite male soccer players, respectively (Sanchez-Sanchez et al., 2022; Paz-Franco, Rey & Barcala-Furelos, 2017; Spineti et al., 2016).

The improvements in initial sprint performance (i.e., best time) after heavy ST and maximal power training may be attributed to specific neural adaptations (ability to activate all high threshold MUs with maximum discharge rate rapidly) and morphological adaptations (cross-sectional area, muscle architecture, and muscle–tendon stiffness) which are achieved by executing the concentric phase of lifting with the maximum intensity. Previous research indicated that both heavy ST and explosive ST are effective in improving RFD (i.e., the ability of the neuromuscular system to express the greatest amount of force in the shortest possible time) (Maffiuletti et al., 2016; Suchomel, Nimphius & Stone, 2016). Therefore, an increase in the propulsion impulse and RFD could allow a greater force to be produced over a given time, resulting in greater acceleration and shorter ground contact times (Maffiuletti et al., 2016; Suchomel, Nimphius & Stone, 2016). Another possible explanation, according to Seitz et al. (2014), is the increases in lower-body strength levels after ST, using a medium (60–84.9% 1 RM; ES = −0.97) and high (>85% 1 RM; ES = −0.52) intensity, transfer positively to sprint performance (higher peak GRF, impulse and RFD) (r = −0.77; p = 0.0001).

For example, strong relationships have been found between 1 RM strength of the half squat and 10 m (r = 0.94; p < 0.001) and 30 m sprint time (r = 0.71; p < 0.01), respectively, in elite male soccer players (Wisløff et al., 2004). Also, relationships between full squats using relative loads that maximize the mechanical power output have been found (∼60% 1 RM; mean propulsive velocity of ∼1.00 m⋅ s −1) and best time (r = −0.76; p = 0.007), mean time of the first 3 sprints (r = −0.64; p = 0.004) and mean time of 9 sprints (r = −0.52; p = 0.04) in under-19 soccer players (López-Segovia et al., 2015). Although this suggests that strength qualities are interrelated with sprint performance, this does not prove causality; however, the present results support these findings.

On the other hand, the improvements in the mean time (Gonzalo-Skok et al., 2016; Hermassi et al., 2017) and total time (Durán-Custodio et al., 2023) could be attributed to an increase in RFD and/or power through adaptations in the stiffness of the muscle–tendon unit, which result from more efficient stretch-shortening cycles (i.e., improvement storage and reuse of elastic energy during the braking and propulsion phases) (Li et al., 2019). In particular, mean time is related to the initial sprint performance due to a perfect correlation (r = 0.93; p = 0.000) between the best time and mean time of the first 3 sprints, whereas this relationship decreases for the subsequent sprints (López-Segovia et al., 2015). In contrast, the lack of improvements in mean and total time in the other studies could be explained because despite maximal strength increases (1 RM) in six studies (Table S1), the importance of 1RM decreases when the number of sprints increases. Here, the aerobic capacity could be more relevant for improving recovery between sprints and/or avoiding the drop performance in the subsequent sprints (López-Segovia et al., 2015). Therefore, other, more specific training methods are needed to improve RSA. Previous research found a positive relationship between 1 RM strength of the half squat and best time (r = 0.811; p < 0.001) and total time (r = 0.625; p = 0.002) (Hermassi et al., 2019), also in the mean time (r = 0.50; p < 0.05) and total time (r = 0.78; p = 0.01) in male handball players respectively (Hermassi et al., 2014). In other words, the subjects with greater 1 RM performed the worst results on the RSA test.

The main mechanical factor determining RSA performance is the technical ability to apply a large forward-oriented ground reaction force vector effectively (i.e., ground reaction impulse in the forward direction of the movement) during the acceleration of each sprint instead of the amount (magnitude) of total force applied, minimizing the decrease in the stride frequency (Morin et al., 2011; Brocherie et al., 2016; Jiménez-Reyes et al., 2019). Exercises of high force to low speed with a horizontally directed force vector would be more specific for improving forward acceleration from a static start or reacceleration from each sprint (Hicks et al., 2019). Therefore, the lack of improvements in the best and mean time (Gonzalo-Skok et al., 2016; Hammami et al., 2018; Hammami et al., 2017a; Torres-Torrelo, Rodríguez-Rosell & González-Badillo, 2017) could be due in part to the lack of a specific stimulus (force vector theory) during the acceleration of each sprint (Loturco et al., 2018). However, Junge et al. (2021) did not find significant associations between hip thrust exercise and acceleration in 30 m (r = 0.18; p = 0.36). In contrast, Loturco et al. (2018) found a strong association (r = 0.93) between hip thrust with maximal acceleration (zero to 10 m) and jump squats with sprints above 40 m in both sprinters and high-level jumpers. However, studies that showed improvement in RSA used similar exercises of back squats in the vertical direction as those that did not show improvement. Therefore, the force vector theory is inconclusive because it has only been measured in single-sprint tests, not RSA tests. On the other hand, there is no relation between straight-line and shuttle sprint performance (Wisløff et al., 2004); we speculate that the lack of improvements in the studies (Gonzalo-Skok et al., 2016; Hammami et al., 2018; Hammami et al., 2017a) could be because the strength exercises do not accentuate the eccentric phase, since the straight-line sprint with one 180° change of direction requires the inclusion of a deceleration movement before a reacceleration.

Effects of complex training on the RSA

Regarding the effects of CCT on RSA, one of three studies (Hammami et al., 2019) reported a trivial significant change in their EG in specific measures (best time, mean time, and total time) in the RSA test. This result coincides with the meta-analysis of Thapa et al. (2022), where three studies on youth, junior, and professional male soccer players found a small non-significant effect (p = 0.156; ES = 0.32) in the RSA tests.

After the CCT, improvements in the RSA test may be specifically related to optimizing the entire spectrum of the force-velocity curve in the same session (Thapa et al., 2022). Heavy load training and low speed (e.g., squat 90% of 1RM) increase the excitability of the MUs (i.e., recruitment and synchronization of MU higher order/high threshold and the potentiation of reflexes), creating optimal and favorable conditions for plyometric or power training (e.g., CMJ) after maximal muscle contractile activity (Freitas et al., 2017; Cormier et al., 2022). These neural adaptations may ultimately lead to a higher RFD (Maffiuletti et al., 2016) and improved efficiency of the stretch-shortening cycle. However, the time course of the potentiation effect also depends on the time course of fatigue (the net balance determining if there is an increased or decreased output).

Previous studies compared CCT vs. ST. Spineti et al. (2016) observed that CCT induced a significant improvement in percentage decrement (moderate ES; −0.91) and mean time (moderate ES; −0.85) when compared with ST in under-20 elite male soccer players. Hammami et al. (2017a) observed that CCT presented more significant changes for the mean (p ≤ 0.001) and total time (p ≤ 0.01) compared to ST in junior male soccer players. This suggests that CCT could be an effective strategy to optimize and improve performance during the competitive season compared to ST alone. However, the methodology used in the present systematic review and the lack of studies do not allow a comparison of the results to conclude that CCT is superior to ST. The lack of improvements in the studies by Hammami et al. (2017b); Hammami et al. (2017a), could be due to the lack of a specific stimulus, as aerobic capacity is an important factor in recovery between sprints; CCT does not develop this quality. Also, it could be due to a nonspecific recovery post-CA (i.e., the relation between the CA on subsequent exercises) (Cormier et al., 2022); however, none of the studies reported the pause intra-contrast rest to affirm it.

Effects of strength and complex training on fatigue

Fatigue was assessed through two measures (fatigue index or percentage decrement); only one study (Durán-Custodio et al., 2023) presented a large significant change (p = 0.003; ES = 1.25), except for the study by Hermassi et al. (2017) that did not report this measure (does not allow us to know its meaning). However, this unique positive result does not coincide with other studies (Paz-Franco, Rey & Barcala-Furelos, 2017; Spineti et al., 2016). These results should be interpreted with caution because a better initial performance of the first sprint will commonly lead to a high fatigue index (an indicator of the loss of performance between the best and the worst sprint), given that there is a positive correlation with the decrease performance in the following sprints; therefore, the subjects with higher anaerobic power reserve could be impaired in subsequent bouts (Girard, Mendez-Villanueva & Bishop, 2011). Probably, this decrease in performance would be a combination of neural factors (i.e., lower recruitment and discharge frequency fast twitch MUs), as well as alterations in intermuscular coordination patterns (agonist-antagonist ratio) (Girard, Mendez-Villanueva & Bishop, 2011) and muscular (i.e., accumulation of hydrogen ions (H+), inorganic phosphate and extracellular potassium secondary to decreased sodium-potassium pump ATPase activity), also limitations in the energy supply of phosphocreatine availability, anaerobic glycolysis and oxidative metabolism (Girard, Mendez-Villanueva & Bishop, 2011), that may alter the sprint mechanics, such as reductions in forward-oriented ground reaction force (total force), increase in the contact time (i.e., decreased efficiency of the stretch-shortening cycle), increased vertical displacement of the center of mass during the braking phase and increased swing time, reductions in vertical stiffness and stride frequency (Morin et al., 2011; Brocherie et al., 2016; Jiménez-Reyes et al., 2019). In summary, ST or CCT would influence the neuro-mechanical properties of initial sprint performance; however, other training methods targeting oxidative capacity, phosphocreatine recovery, and H+ buffering would be the most suitable for improving recovery between sprints and/or fatigue resistance (Bishop, Girard & Mendez-Villanueva, 2011; Gaitanos et al., 1993). Nevertheless, Edge et al. (2006) and Hill-Haas et al. (2007) showed in females recreationally active in various team sports that high-repetition resistance training that includes a high metabolic load (because of short rest periods 20 s) improved not only single-sprint performance but also the performance of subsequent sprints (peak and mean power). Although those studies were evaluated on a cycloergometer and did not comply with the principle of specificity, high-repetition resistance training is an effective method to improve the H+ regulation and avoid the drop performance in subsequent bouts.

Some limitations can be identified. Firstly, since allocation was concealed, the moderate quality of the studies could produce systematic biases in random allocation. Also, it is difficult to mask the application of treatments or programs. The small number of studies on the effectiveness of ST on RSA does not allow us to compare the results regarding the characteristics of the subjects and intervention of the training. Furthermore, the heterogeneity of the characteristics of the subjects and intervention are factors to consider, mainly because subjects with lower levels of strength and experience could have a more considerable margin of adaptations. Future studies should include exercises in all the spectrum of the force-velocity curve, including exercises in the horizontal direction, ballistic where higher RFDs can be achieved, and high repetition with short rest periods. Finally, the diversity of RSA tests and the lack of measurements in 5 studies do not precisely allow us to know the interventions’ efficacy.

Conclusions

The findings of this systematic review suggest that ST performed in a range of maximal power provides benefits in the best time and mean time and performed between 80 to 95% of 1 RM provides benefits in the best time, mean time, and total time of the RSA tests, respectively, in elite and semi-professional male players during the competitive season. CCT performed between 75 to 90% of 1 RM combined with jumps and sprints provides benefits in the best time, mean time, and total time of the RSA test in elite female players during the competitive season; however, only one study reported a trivial significant change, it would not be correct to report that it is effective.

The improvements in the best time, mean time, and total time may be due to neuro-mechanical factors that affect initial sprint performance rather than the capacity to recover between efforts.

Practical applications

According to the findings of the articles reviewed in the present study, coaches should consider ST and CCT to improve RSA in team sports. Specifically, training maximal strength, RFD, and power using a combination of heavy/low load strength exercises while executing the concentric phase with maximum intensity may improve the propulsion impulse over the ground during the acceleration or reacceleration of each single sprint. Including exercises specific in a horizontal direction should also be considered to minimize the reduction in forward-oriented GRF during repeated sprinting, which could lead to important changes in RSA.

Supplemental Information

10.7717/peerj.17756/supp-1 Supplemental Information 1 1 repetition maximum test

10.7717/peerj.17756/supp-2 Supplemental Information 2 PRISMA checklist abstract

10.7717/peerj.17756/supp-3 Supplemental Information 3 Full PRISMA checklist

10.7717/peerj.17756/supp-4 Supplemental Information 4 Systematic Review Rationale

Additional Information and Declarations

Competing Interests

Author Contributions

Data Availability

The authors declare there are no competing interests.

Andrés Osses-Rivera conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft.

Rodrigo Yáñez-Sepúlveda analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft.

Sebastián Jannas-Vela analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft.

Jeppe F. Vigh-Larsen analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft.

Matías Monsalves-Álvarez conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft.

The following information was supplied regarding data availability:

This is a systematic review.
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References

Altmann et al. (2019) Altmann S Ringhof S Neumann R Woll A Rumpf MC 2019 Validity and reliability of speed tests used in soccer: a systematic review PLOS ONE 14 e0220982 10.1371/journal.pone.0220982 31412057
Bishop & Girard (2013) Bishop DJ Girard O 2013 Determinants of team-sport performance: implications for altitude training by team-sport athletes British Journal of Sports Medicine 47 Suppl 1 i17 i21 10.1136/bjsports-2013-092950 24282200
Bishop, Girard & Mendez-Villanueva (2011) Bishop D Girard O Mendez-Villanueva A 2011 Repeated-sprint ability—part II: recommendations for training Sports Medicine 41 741 756 10.2165/11590560-000000000-00000 21846163
Blazevich & Babault (2019) Blazevich AJ Babault N 2019 Post-activation potentiation versus post-activation performance enhancement in humans: historical perspective, underlying mechanisms, and current issues Frontiers in Physiology 10 1359 10.3389/fphys.2019.01359 31736781
Brocherie et al. (2016) Brocherie F Millet GP Morin J-B Girard O 2016 Mechanical alterations to repeated treadmill sprints in normobaric Hypoxia Medicine & Science in Sports & Exercise 48 1570 1579 10.1249/MSS.0000000000000937 27031740
Chatzinikolaou et al. (2018) Chatzinikolaou A Michaloglou K Avloniti A Leontsini D Deli CK Vlachopoulos D Gracia-Marco L Arsenis S Athanailidis I Draganidis D Jamurtas AZ Williams CA Fatouros IG 2018 The trainability of adolescent soccer players to brief periodized complex training International Journal of Sports Physiology and Performance 13 645 655 10.1123/ijspp.2017-0763 29431546
Cormier et al. (2022) Cormier P Freitas TT Loturco I Turner A Virgile A Haff GG Blazevich AJ Agar-Newman D Henneberry M Baker DG McGuigan M Alcaraz PE Bishop C 2022 Within session exercise sequencing during programming for complex training: historical perspectives, terminology, and training considerations Sports Medicine 52 2371 2389 10.1007/s40279-022-01715-x 35816233
Durán-Custodio et al. (2023) Durán-Custodio R Castillo D Raya-González J Yanci J 2023 Is a maximal strength-training program effective on physical fitness, injury incidence, and injury burden in semi-professional soccer players? A randomized controlled trial Healthcare 11 3195 10.3390/healthcare11243195 38132085
Edge et al. (2006) Edge J Hill-Haas S Goodman C Bishop D 2006 Effects of resistance training on H+ regulation, buffer capacity, and repeated sprints Medicine and Science in Sports and Exercise 38 2004 2011 10.1249/01.mss.0000233793.31659.a3 17095936
Freitas et al. (2017) Freitas TT Martinez-Rodriguez A Calleja-González J Alcaraz PE 2017 Short-term adaptations following complex training in team-sports: a meta-analysis PLOS ONE 12 e0180223 10.1371/journal.pone.0180223 28662108
Gaitanos et al. (1993) Gaitanos GC Williams C Boobis LH Brooks S 1993 Human muscle metabolism during intermittent maximal exercise Journal of Applied Physiology 75 712 719 10.1152/jappl.1993.75.2.712 8226473
Girard, Mendez-Villanueva & Bishop (2011) Girard O Mendez-Villanueva A Bishop D 2011 Repeated-sprint ability—part I: factors contributing to fatigue Sports Medicine 41 673 694 10.2165/11590550-000000000-00000 21780851
Gonzalo-Skok et al. (2016) Gonzalo-Skok O Tous-Fajardo J Arjol-Serrano JL Suarez-Arrones L Casajús JA Mendez-Villanueva A 2016 Improvement of repeated-sprint ability and horizontal-jumping performance in elite young basketball players with low-volume repeated-maximal-power training International Journal of Sports Physiology and Performance 11 464 473 10.1123/ijspp.2014-0612 26356548
Hammami et al. (2019) Hammami M Gaamouri N Aloui G Shephard RJ Chelly MS 2019 Effects of a complex strength-training program on athletic performance of junior female handball players International Journal of Sports Physiology and Performance 14 163 169 10.1123/ijspp.2018-0160 29952672
Hammami et al. (2018) Hammami M Negra Y Billaut F Hermassi S Shephard RJ Chelly MS 2018 Effects of lower-limb strength training on agility, repeated sprinting with changes of direction, leg peak power, and neuromuscular adaptations of soccer players Journal of Strength and Conditioning Research 32 37 47 10.1519/JSC.0000000000001813 28678768
Hammami et al. (2017a) Hammami M Negra Y Shephard RJ Chelly MS 2017a The effect of standard strength vs. contrast strength training on the development of sprint, agility, repeated change of direction, and jump in junior male soccer players Journal of Strength and Conditioning Research 31 901 912 10.1519/JSC.0000000000001815 28328713
Hammami et al. (2017b) Hammami M Negra Y Shephard RJ Chelly M-S 2017b Effects of leg contrast strength training on sprint, agility and repeated change of direction performance in male soccer players The Journal of Sports Medicine and Physical Fitness 57 1424 1431 10.23736/S0022-4707.17.06951-1 28094488
Hermassi et al. (2017) Hermassi S Chelly MS Fieseler G Bartels T Schulze S Delank K-S Shephard RJ Schwesig R 2017 Effects of in-season explosive strength training on maximal leg strength, jumping, sprinting, and intermittent aerobic performance in male handball athletes Sportverletzung Sportschaden: Organ der Gesellschaft Fur Orthopadisch-Traumatologische Sportmedizin 31 167 173 10.1055/s-0043-103469 28662531
Hermassi et al. (2019) Hermassi S Chelly MS Wagner H Fieseler G Schulze S Delank K-S Shephard RJ Schwesig R 2019 Relationships between maximal strength of lower limb, anthropometric characteristics and fundamental explosive performance in handball players Sportverletzung Sportschaden: Organ der Gesellschaft Fur Orthopadisch-Traumatologische Sportmedizin 33 96 103 10.1055/s-0043-124496 29444539
Hermassi et al. (2014) Hermassi S Gabbett TJ Spencer M Khalifa R Chelly MS Chamari K 2014 Relationship between explosive performance measurements of the lower limb and repeated shuttle-sprint ability in elite adolescent handball players International Journal of Sports Science & Coaching 9 1191 1204 10.1260/1747-9541.9.5.1191
Hicks et al. (2019) Hicks D Schuster JG Samozino P Morin J-B 2019 Improving mechanical effectiveness during sprint acceleration: practical recommendations and guidelines Strength and Conditioning Journal 42 45 62 10.1519/SSC.0000000000000519
Hill-Haas et al. (2007) Hill-Haas S Bishop D Dawson B Goodman C Edge J 2007 Effects of rest interval during high-repetition resistance training on strength, aerobic fitness, and repeated-sprint ability Journal of Sports Sciences 25 619 628 10.1080/02640410600874849 17454528
Hostrup & Bangsbo (2017) Hostrup M Bangsbo J 2017 Limitations in intense exercise performance of athletes - effect of speed endurance training on ion handling and fatigue development The Journal of Physiology 595 2897 2913 10.1113/JP273218 27673449
Jiménez-Reyes et al. (2019) Jiménez-Reyes P Cross M Ross A Samozino P Brughelli M Gill N Morin J-B 2019 Changes in mechanical properties of sprinting during repeated sprint in elite rugby sevens athletes European Journal of Sport Science 19 585 594 10.1080/17461391.2018.1542032 30409072
Junge et al. (2021) Junge N Lundsgaard A Hansen MF Samozino P Morin J-B Aagaard P Contreras B Nybo L 2021 Force-velocity-power profiling of maximal effort sprinting, jumping and hip thrusting: exploring the importance of force orientation specificity for assessing neuromuscular function Journal of Sports Sciences 39 2115 2122 10.1080/02640414.2021.1920128 33956567
Kraemer & Ratamess (2004) Kraemer WJ Ratamess NA 2004 Fundamentals of resistance training: progression and exercise prescription Medicine and Science in Sports and Exercise 36 674 688 10.1249/01.mss.0000121945.36635.61 15064596
Li et al. (2019) Li F Wang R Newton RU Sutton D Shi Y Ding H 2019 Effects of complex training versus heavy resistance training on neuromuscular adaptation, running economy and 5-km performance in well-trained distance runners PeerJ 7 e6787 10.7717/peerj.6787 31086736
Liberati et al. (2009) Liberati A Altman DG Tetzlaff J Mulrow C Gøtzsche PC Ioannidis JPA Clarke M Devereaux PJ Kleijnen J Moher D 2009 The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration BMJ 339 b2700 10.1136/bmj.b2700 19622552
López-Segovia et al. (2015) López-Segovia M Pareja-Blanco F Jiménez-Reyes P González-Badillo JJ 2015 Determinant factors of repeat sprint sequences in young soccer players International Journal of Sports Medicine 36 130 136 10.1055/s-0034-1385880 25259593
Loturco et al. (2018) Loturco I Contreras B Kobal R Fernandes V Moura N Siqueira F Winckler C Suchomel T Pereira LA 2018 Vertically and horizontally directed muscle power exercises: relationships with top-level sprint performance PLOS ONE 13 e0201475 10.1371/journal.pone.0201475 30048538
Maffiuletti et al. (2016) Maffiuletti NA Aagaard P Blazevich AJ Folland J Tillin N Duchateau J 2016 Rate of force development: physiological and methodological considerations European Journal of Applied Physiology 116 1091 1116 10.1007/s00421-016-3346-6 26941023
Mohr, Krustrup & Bangsbo (2005) Mohr M Krustrup P Bangsbo J 2005 Fatigue in soccer: a brief review Journal of Sports Sciences 23 593 599 10.1080/02640410400021286 16195008
Morin et al. (2011) Morin J-B Samozino P Edouard P Tomazin K 2011 Effect of fatigue on force production and force application technique during repeated sprints Journal of Biomechanics 44 2719 2723 10.1016/j.jbiomech.2011.07.020 21839456
Moseley et al. (2002) Moseley AM Herbert RD Sherrington C Maher CG 2002 Evidence for physiotherapy practice: a survey of the physiotherapy evidence database (PEDro) The Australian Journal of Physiotherapy 48 43 49 10.1016/s0004-9514(14)60281-6 11869164
Parolin et al. (1999) Parolin ML Chesley A Matsos MP Spriet LL Jones NL Heigenhauser GJ 1999 Regulation of skeletal muscle glycogen phosphorylase and PDH during maximal intermittent exercise The American Journal of Physiology 277 E890 E900 10.1152/ajpendo.1999.277.5.E890 10567017
Paz-Franco, Rey & Barcala-Furelos (2017) Paz-Franco A Rey E Barcala-Furelos R 2017 Effects of 3 different resistance training frequencies on jump, sprint, and repeated sprint ability performances in professional futsal players Journal of Strength and Conditioning Research 31 3343 3350 10.1519/JSC.0000000000001766 28225522
Sahlin & Harris (2011) Sahlin K Harris RC 2011 The creatine kinase reaction: a simple reaction with functional complexity Amino Acids 40 1363 1367 10.1007/s00726-011-0856-8 21394603
Sanchez-Sanchez et al. (2022) Sanchez-Sanchez J Raya-González J Ramirez-Campillo R Chaabene H Petisco C Nakamura FY 2022 The increased effectiveness of resistance training on unstable vs. stable surfaces on selected measures of physical performance in young male soccer players Journal of Strength and Conditioning Research 36 888 894 10.1519/JSC.0000000000003590 32412970
Schimpchen et al. (2016) Schimpchen J Skorski S Nopp S Meyer T 2016 Are classical tests of repeated-sprint ability in football externally valid? A new approach to determine in-game sprinting behaviour in elite football players Journal of Sports Sciences 34 519 526 10.1080/02640414.2015.1112023 26580089
Seitz et al. (2014) Seitz LB Reyes A Tran TT De Villarreal ES Haff GG 2014 Increases in lower-body strength transfer positively to sprint performance: a systematic review with meta-analysis Sports Medicine 44 1693 1702 10.1007/s40279-014-0227-1 25059334
Spencer et al. (2005) Spencer M Bishop D Dawson B Goodman C 2005 Physiological and metabolic responses of repeated-sprint activities:specific to field-based team sports Sports Medicine 35 1025 1044 10.2165/00007256-200535120-00003 16336007
Spineti et al. (2016) Spineti J Figueiredo T Bastos DE Oliveira V Assis M Fernandes DE Oliveira L Miranda H Ribeiro Reis VM Machado DE Simão R 2016 Comparison between traditional strength training and complex contrast training on repeated sprint ability and muscle architecture in elite soccer players The Journal of Sports Medicine and Physical Fitness 56 1269 1278 26609969
Suchomel, Nimphius & Stone (2016) Suchomel TJ Nimphius S Stone MH 2016 The importance of muscular strength in athletic performance Sports Medicine 46 1419 1449 10.1007/s40279-016-0486-0 26838985
Taylor et al. (2016) Taylor JM Macpherson TW Spears IR Weston M 2016 Repeated sprints: an independent not dependent variable International Journal of Sports Physiology and Performance 11 693 696 10.1123/ijspp.2016-0081 27197118
Taylor et al. (2017) Taylor JB Wright AA Dischiavi SL Townsend MA Marmon AR 2017 Activity demands during multi-directional team sports: a systematic review Sports Medicine 47 2533 2551 10.1007/s40279-017-0772-5 28801751
Thapa et al. (2020) Thapa RK Lum D Moran J Ramirez-Campillo R 2020 Effects of complex training on sprint, jump, and change of direction ability of soccer players: a systematic review and meta-analysis Frontiers in Psychology 11 627869 10.3389/fpsyg.2020.627869 33551937
Thapa et al. (2022) Thapa R Narvariya P Weldon A Talukdar K Ramirez-Campillo R 2022 Can complex contrast training interventions improve aerobic endurance, maximal strength, and repeated sprint ability in soccer players? A systematic review and meta-analysis Montenegrin Journal of Sports Science and Medicine 11 45 55 10.26773/mjssm.220906
Thurlow et al. (2023) Thurlow F Weakley J Townshend AD Timmins RG Morrison M McLaren SJ 2023 The acute demands of repeated-sprint training on physiological, neuromuscular, perceptual and performance outcomes in team sport athletes: a systematic review and meta-analysis Sports Medicine 53 1609 1640 10.1007/s40279-023-01853-w 37222864
Torres-Torrelo, Rodríguez-Rosell & González-Badillo (2017) Torres-Torrelo J Rodríguez-Rosell D González-Badillo JJ 2017 Light-load maximal lifting velocity full squat training program improves important physical and skill characteristics in futsal players Journal of Sports Sciences 35 967 975 10.1080/02640414.2016.1206663 27414074
Torres-Torrelo et al. (2018) Torres-Torrelo J Rodríguez-Rosell D Mora-Custodio R Pareja-Blanco F Yañez García JM González-Badillo JJ 2018 Effects of resistance training and combined training program on repeated sprint ability in futsal players International Journal of Sports Medicine 39 517 526 10.1055/a-0596-7497 29768643
Wisløff et al. (2004) Wisløff U Castagna C Helgerud J Jones R Hoff J 2004 Strong correlation of maximal squat strength with sprint performance and vertical jump height in elite soccer players British Journal of Sports Medicine 38 285 288 10.1136/bjsm.2002.002071 15155427
