This study adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines (Page et al., 2021). It was registered on 19 December 2023, on the Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY2023120078).

In accordance with the PICOS framework (Table 1) (Amir-Behghadami and Janati, 2020), the inclusion criteria were: 1) full-text articles published in English; 2) studies involving healthy female basketball players with no restrictions on age or skill level; 3) plyometric training (upper and/or lower limb) as the intervention in the experimental group; 4) control groups that did not undergo a PT program, or studies without control groups; 5) outcome measures that included basketball skill-related performance (e.g., shooting, passing, dribbling) or physical fitness (e.g., jump, change of direction, sprint, muscle strength); 6) randomized controlled trials (RCTs). The exclusion criteria were: 1) review articles; 2) studies recruiting male players either solely or combined with female players with data not reported separately; 3) studies that did not include a plyometric intervention or combined it with other interventions; 4) unpublished studies.

The search was conducted on 20 December 2023. The following databases were utilised: Web of Science, Scopus, PubMed, EBSCOhost, and Google Scholar (Table 2). The search terms included plyometric* OR “stretch-shortening cycle” OR “jump training” OR “jump exercise*” AND Female* OR wom?n OR girl* and basketball. Additionally, the references within the included studies were also screened.

First, duplicates were eliminated using Endnote software (X20, Thomson Reuters, New York City, NY, United States). Subsequently, two independent authors (SC and JL) screened the titles, abstracts, and full texts based on inclusion, exclusion, and PICOS criteria. Another author (HS) then double-checked the results and resolved any discrepancies through discussions with a third author (SKG) to reach the final decision. The role of each investigator was defined according to their academic titles. SPSS software (IBM Corp. Released 2022. IBM SPSS Statistics for Macintosh, Version 29.0. Armonk, NY: IBM Corp.) was used to calculate the Kappa statistic to determine the selection agreement (Narducci et al., 2011).

Following the selection of studies, specific data were extracted by the authors (SC and JL), including: 1) participant characteristics (age, height, body mass, playing level, and training experience); 2) intervention; 3) comparison (control group); 4) intervention characteristics (training content, program length, frequency, session duration, training volume, time of season); 5) assessment tests; and 6) outcomes (Table 3). Another author (HS) reviewed the information in the Microsoft Excel spreadsheet (XP professional edition; Microsoft, Redmond, WA, United States) for accuracy.

The Cochrane risk of bias tool (RoB 2) was employed by two authors (SC and JL) to assess the risk of bias in all included randomized controlled trials (RCTs), following the guidelines by Sterne et al. (2019) (Sterne et al., 2019). RoB two evaluates bias in five domains: bias arising from the randomization process, deviations from the intended interventions, missing outcome data, measurement of the outcome, and selection of the reported result. In case of disagreements in the risk of bias assessments, the third author (XW) resolved them. Ultimately, an overall risk of bias score was determined. The certainty of the evidence was evaluated using “The Grading of Recommendations Assessment, Development, and Evaluation (GRADE)” approach (Goldet and Howick, 2013). This assessment considers factors such as study design, risk of bias, inconsistency, indirectness, imprecision, and publication bias to determine the certainty of evidence. A summary of the findings table was generated with the assistance of GRADEpro GDT and carried out independently by two authors.

In accordance with previous research, studies that provided three or more sets of baseline and follow-up data for the same variables underwent meta-analysis using Meta-analysis software (version 3.0), with a statistical significance threshold of p < 0.05. The meta-analysis employed the inverse-variance random-effects model to account for heterogeneity among studies. The I² statistic was used to assess heterogeneity, categorized into low (<25%), moderate (25%–75%), and high (>75%) values. Effect sizes (ES) between groups were computed using Hedge’s g, and 95% confidence intervals (CIs) were reported for the ES values. Effect sizes were categorized as trivial (<0.2), small (0.2–0.6), moderate (>0.6–1.2), large (>1.2–2.0), very large (>2.0–4.0), and extremely large (>4.0) (Hopkins et al., 2009). The extended Egger’s test was used to evaluate the risk of publication bias across studies (Egger et al., 1997). A sensitivity analysis was performed when Egger’s test indicated a low p-value (p < 0.05), suggesting significant asymmetry in the funnel plot, indicating that smaller studies with non-significant or negative results might be underrepresented in the meta-analysis. A higher p-value (p ≥ 0.05) suggested that the funnel plot was symmetrical, indicating no strong evidence of missing studies based on their size and effect (Egger et al., 1997).

A total of 192 studies were initially identified through the search process, and 80 duplicates were removed using Endnote software. Following screening titles, abstracts, and full-text articles, ten articles met the criteria for inclusion in the systematic review, and eight were eligible for inclusion in the meta-analysis (Figure 1). Two articles were not included for the meta-analysis due to heterogeneity in outcomes. The Kappa statistic for agreement between authors, calculated using SPSS software, was 1.00.

Figure 2 shows the risk of bias for each study according to RoB 2, and the overall risk of bias across all studies is presented in Figure 3. Notably, all included articles demonstrated a low risk of bias in the domains related to deviations from the intended interventions, missing outcome data, and selection of the reported results. However, only three studies employed proper randomization techniques. Attene et al. (2015) implemented block randomization to ensure equal group sizes. Sánchez-Sixto et al. (2021) used balanced randomization to assign participants to groups. Haghighi et al. (2023) electronically generated the randomization sequence and concealed the process until interventions were assigned. One study had limitations in its outcome measurement methodology (McCormick et al., 2016). In summary, most of the included studies exhibited concerns regarding the risk of bias. Furthermore, the summary of findings table generated using GRADEpro GDT indicated that the certainty of evidence ranged from high to very low (see Supplementary Appendix A).

(1) Sample Size. The ten articles comprised 246 subjects, with individual studies ranging from 14 (McCormick et al., 2016) to 36 participants (Attene et al., 2015; Sánchez-Sixto et al., 2021). The mean sample size across all studies was 24.6 participants (SD = 7.1).

The intervention characteristics of the ten articles were summarized as follows.

1. Training Program Length: The duration of PT in these studies ranged from 6 to 8 weeks.

All ten included articles examined various physical fitness outcomes, including power, agility, speed, balance, and muscular strength. Only one included assessments of skill-related basketball performance (Haghighi et al., 2023).

1. Effect of PT on power-related attributes: Seven studies evaluated the impact of PT on power-related attributes, utilizing measurements such as CMJ (height, power, velocity, strength, speed) (Vescovi et al., 2008; Attene et al., 2015; McCormick et al., 2016; Meszler and Váczi, 2019; Cherni et al., 2020; Sánchez-Sixto et al., 2021), squat jump (SJ) (height, power, strength, speed) (Attene et al., 2015; Cherni et al., 2020), Sargent jump power (Haghighi et al., 2023), standing long jump distance (McCormick et al., 2016), and lateral hop distance (McCormick et al., 2016). Four studies reported significant improvements in power-related attributes following PT, indicated by increased performance in CMJ (height, power, velocity) (Attene et al., 2015; McCormick et al., 2016; Cherni et al., 2020; Sánchez-Sixto et al., 2021), Sargent jump power (Haghighi et al., 2023), standing long jump distance (McCormick et al., 2016), and lateral hop distance (McCormick et al., 2016). However, two studies found no significant difference in CMJ performance before and after PT (Vescovi et al., 2008; Cherni et al., 2020), and one study showed decreased CMJ performance following PT (Meszler and Váczi, 2019). Additionally, one study evaluated the effect of PT on medicine ball throw distance (Haghighi et al., 2023), showing significant improvement.

Eight of the articles were analysed using meta-analysis software (version 3.0), including the effect of PT on power, agility, and speed.

Power-related attributes are crucial for basketball players due to the sport’s dynamic and multidirectional nature, which requires rapid and explosive movements (Delextrat and Cohen, 2008; Abdelkrim et al., 2010; Scanlan et al., 2011; Gonzalez et al., 2013). Four studies in the review demonstrated that PT had a significant positive effect on various types of jump performance (Attene et al., 2015; Cherni et al., 2020; Sánchez-Sixto et al., 2021) and medicine ball throw distance (Haghighi et al., 2023). These findings align with results from previous reviews (Markovic, 2007; Stojanović et al., 2017; Silva et al., 2019). Improvements in power-related performance, particularly jump ability, are highly relevant for basketball players as they are essential for executing advanced skills like rebounding, sprinting, and jump shots during games (Altavilla et al., 2018). The mechanism of PT concerning the stretch-shortening cycle (SSC) can explain the improvement in power. Plyometric exercises engage the SSC, allowing muscles to store elastic energy during the eccentric phase (muscle lengthening) and release it quickly during the concentric phase (muscle shortening) (Chu, 1998; Chu and Meyer, 2013). This results in more powerful and explosive movements. Additionally, the high-intensity, rapid nature of plyometric exercises enhances the nervous system’s ability to recruit muscle fibers more effectively, increasing the speed and coordination of muscle contractions (Zubac et al., 2019; Galay et al., 2021).

However, two studies indicated that PT did not enhance CMJ performance (Vescovi et al., 2008; Cherni et al., 2020). These divergent results may be attributed to specific participant characteristics, such as their prior experience with PT and the training content (Moran et al., 2017; Stojanović et al., 2017). Compared to the studies that showed the significant improvement of PT on power-related attributes, participants in Vescovi et al. (2008) had over 3 years of training experience, which was the least except for two studies that did not report the experience (Vescovi et al., 2008). Three years of training experience may not be sufficient to develop the foundational strength and technical skills necessary for effective plyometric exercises (Sole et al., 2022). Players still developing neuromuscular coordination might struggle to achieve optimal muscle activation patterns required for maximal power gains (Bompa and Carrera, 2015). Cherni et al. (2020) showed that PT significantly improved SJ but not CMJ performance, which runs counter to the previous study that reported somewhat greater positive effects in CMJ than SJ performance (Stojanović et al., 2017). More studies are needed to explore the reasons for the divergence.

Additionally, one study reported adverse effects of PT on CMJ height (Meszler and Váczi, 2019). This might be due to the PT program being implemented during the in-season basketball competition. During the season, players already experience physical and mental fatigue from regular practices, games, and travel. Adding PT might overload their recovery capacity, leading to cumulative fatigue and decreased performance (Chelly et al., 2010). The busy game schedule during the season may not provide sufficient recovery time between PT sessions (Asadi, 2013), leading to inadequate muscle recovery and reduced benefits from PT. PT should be periodized with specific attention to high-load and low-load phases to maximize performance gains while minimizing fatigue (Chelly et al., 2010).

COD speed is critical in basketball. For instance, defenders rely on COD ability to stay in front of their opponents, adjust to sudden movements, and close out on shooters (Ivanović et al., 2022). Good COD speed ability, combined with proper technique, can help reduce the risk of injuries (Dos’ Santos et al., 2021). The results of PT on COD speed were inconsistent, aligning with results from previous reviews (Asadi et al., 2016; Sole et al., 2021). Most studies demonstrated that PT had a significantly positive effect on the lateral shuffle test (McCormick et al., 2016), t-Test (Cherni et al., 2019; Cherni et al., 2020), and lane agility drill (Haghighi et al., 2023) among female basketball players. The lateral shuffle test assesses an athlete’s lateral movement agility (Patowary and Das, 2023). The t-Test assesses forward, lateral, and backward movement, providing a more comprehensive evaluation of agility compared to the lateral shuffle test (Keš et al., 2020). The lane agility drill also includes a combination of forward, lateral, and backward movements, similar to the t-Test but within a confined space (Čaušević et al., 2023). Neural adaptations, including increased recruitment of motor units (Miller et al., 2006; Markovic and Mikulic, 2010; Asadi et al., 2016) and enhanced neural drive to agonist muscles induced by PT, can improve cutting skills, allowing players to exhibit better body control and skill performance during games (Markovic and Mikulic, 2010).

However, two studies did not indicate a significant difference in the t-Test (Meszler and Váczi, 2019) and the Illinois agility test (Pinheiro Paes et al., 2022). The meta-analysis also revealed a small PT effect size (ES = 0.32) on the t-Test. Aside from the issue of PT being conducted in-season (Meszler and Váczi, 2019), the lower number of jumps per session (50–100 jumps) in Pinheiro Paes et al. (2022) compared to others (72–174 jumps) might be another reason. Volume plays a critical role in neuromuscular adaptation, and if the jump count is too low, it may not generate sufficient muscle engagement or neural activation (Ramírez-Campillo et al., 2013). Additionally, both the t-Test and Illinois agility test combine lateral movements, forward sprints, and backward runs, which demand high levels of coordination in multiple planes of motion (Raya et al., 2013). However, most plyometric exercises in the included studies primarily focused on the sagittal plane, such as vertical jumps, box jumps, and bounding. These exercises are excellent for improving power and explosiveness in forward and backward movements but may not fully address the lateral and rotational movements required in the t-Test and Illinois agility test (Weltin et al., 2017).

In basketball competitions, players sprinting down the court to score quickly on offense or stop a fast break on defense need excellent linear speed (Scanlan et al., 2014). In two studies, results showed that PT significantly improved 20-m sprint performance (Pinheiro Paes et al., 2022; Haghighi et al., 2023). The meta-analysis indicated a small effect size (ES = 0.24) of PT on the 20-m sprint. These results are in line with those reported in a previous review showing PT was effective in improving sprint performance (ES = 0.37) (de Villarreal et al., 2012). The improvement in linear speed performance can be explained in several ways. First, specific PT exercises such as depth jumps, box jumps, and bounding enhance the explosive power of the lower body (Aksović et al., 2021), aiding in rapid force generation at the start of the sprint (de Villarreal et al., 2012). Additionally, plyometrics improves the SSC, which involves a rapid muscle stretch followed by a quick contraction (Galay et al., 2021). Enhanced SSC efficiency maximizes force production with minimal ground contact time, crucial for fast acceleration (de Villarreal et al., 2012). Moreover, participants in the studies by Haghighi et al. (2023) and Pinheiro Paes et al. (2022) implemented PT during the pre-season. During this period, there is less pressure from games or competitions, allowing athletes to focus on training quality without the risk of fatigue affecting in-season performance.

However, one study found no impact of PT on 10-m, 20-m, and 30-m sprint speed (Cherni et al., 2020). This could be due to the PT being implemented during the in-season, the training content including only three types of jumps, and the elite players potentially reaching a performance plateau. These reasons have already been discussed previously.

Strong muscles, particularly in the legs and core, provide the power necessary for high jumps, quick acceleration, and effective pivoting in basketball competition (Cabarkapa et al., 2022). However, only two included studies investigated the effects of PT on muscle strength (Cherni et al., 2019; Meszler and Váczi, 2019), and their findings were contradictory. Cherni et al. (2020) demonstrated that PT increased leg and thigh muscle volume and maximum thigh CSA, leading to improvements in strength. This aligns with a previous review that reported PT has a significant positive effect on maximal strength compared to other training methods such as weight training, eccentric training, and isometric training (De Villarreal et al., 2010). Plyometric exercises improve the communication between the nervous system and muscles, allowing for more coordinated and rapid muscle contractions (Chimera et al., 2004). This efficiency means that muscles can apply more force in a controlled and effective manner. Additionally, plyometrics enhances tendon stiffness, allowing tendons to store and release more elastic energy during explosive movements (Fouré et al., 2010; Ramírez-delaCruz et al., 2022). This contributes to greater force production and muscle strength.

In contrast, Meszler and Váczi (2019) indicated that PT did not impact knee extensors and flexors strength. This discrepancy may be due to the participants in this study being younger than 16 years old. At this age, the musculoskeletal system is still maturing, and they have not fully developed the hormonal environment that supports muscle growth to the same degree as adults (Fink et al., 2018). Lower levels of testosterone and growth hormone reduce the potential for significant muscle growth (Gharahdaghi et al., 2021).

Good balance provides a solid, upright, and steady foundation for playing basketball. This stability supports various aspects of basketball, including running, defending, shooting, dribbling, passing, and rebounding (Halabchi et al., 2020). Additionally, good balance can help reduce the risk of sustaining injuries (Sañudo et al., 2019; Crossley et al., 2020). Two included articles have shown that PT improved both stable and dynamic leg balance (Sedaghati, 2018; Cherni et al., 2019), which is in lines with results from previous review (Ramachandran et al., 2021). Neuromuscular adaptations and proprioception enhancement are key factors contributing to improved balance. Specifically, plyometric exercises involve rapid stretching and contracting of muscles, enhancing the neuromuscular system’s ability to respond quickly and efficiently (Huang et al., 2021). This improved neuromuscular control is crucial for maintaining balance during dynamic movements (Piirainen et al., 2014). Furthermore, plyometrics often require athletes to perform exercises on unstable surfaces or in challenging positions, improving proprioception, which is the body’s ability to sense its position and movement in space (Alikhani et al., 2019; Zhou et al., 2022). Better proprioception leads to better balance and stability.

Haghighi et al. (2023) demonstrated that PT can lead to improvements in dribbling, passing, shooting skills, and other basketball-specific performance measures. Basketball shooting skills rely on physical fitness such as upper body and leg strength for generating shot power, and core stability for balance and control (Candra et al., 2018; Aksović et al., 2020; Cabarkapa et al., 2022; Jing, 2023). Upper body strength, especially in the shoulders, arms, and chest, is essential for generating the necessary power to shoot the basketball, which is particularly important for long-range shots such as three-pointers (Cabarkapa et al., 2022). Explosive power in the legs and core allows for a quick and high jump, which is essential for creating space from defenders and getting the shot off cleanly (Candra et al., 2018; Aksović et al., 2020). Good balance provides a solid foundation for shooting. It allows players to set their feet properly, align their body towards the basket, and execute the shot with proper form (Jing, 2023). The improvement of these physical fitness attributes in included studies could explain the effectiveness of PT on shooting skills. Strength, COD ability, and balance are important in executing basketball passing skills (Nikolaos et al., 2012; Spiteri et al., 2015). The upper body strength allows players to deliver passes over varying distances with the necessary force (Ahmed, 2013). Good COD ability enables players to position themselves correctly for making effective passes (Spiteri et al., 2015). Being able to move swiftly and change directions helps in avoiding defenders and creating passing lanes (Spiteri et al., 2015). Balance is essential when making passes while in motion or after a quick COD (Nikolaos et al., 2012; Fisek and Agopyan, 2021). Basketball dribbling skills are not only related to ball control, vision, and court awareness but also depend on various physical fitness factors such as hand speed, coordination, changes in pace and speed, and directional control (Ferioli et al., 2020; Vencúrik et al., 2021). The present study already shows that PT improved physical attributes, including explosiveness and speed, which are essential for quick changes of direction and acceleration while dribbling.

However, without sufficient research focusing on these areas, it is challenging to draw comprehensive conclusions about the benefits of PT on skill-related performance in female players. Male and female athletes may respond differently to the same training protocols due to physiological and hormonal differences (Ziv and Lidor, 2010; Gasperi et al., 2023; Landen et al., 2023). Understanding these unique responses is crucial for developing optimized and effective training programs tailored to female athletes. Therefore, comprehensive research involving multiple studies is necessary to understand the full impact of PT on basketball skills in female players. This line of research should include examining different types of plyometric exercises, training durations, and their specific effects on various basketball skills.