Next Article in Journal
Reduction of the Disturbance Effects in a Twin Rotor Multi-Input Multi-Output System Based on a Modified Smith Predictor Control Scheme
Previous Article in Journal
Influence of Category and Sex in Game Structure Variables in Young Elite Tennis
Previous Article in Special Issue
Dynamic Expected Threat (DxT) Model: Addressing the Deficit of Realism in Football Action Evaluation
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Applied Sciences
Volume 15
Issue 10
10.3390/app15105497
applsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Systematic Review

High-Speed Running and Sprinting Thresholds in Elite Female Team Sports: A Systematic Review

by
Raúl Nieto-Acevedo
1,
Alfonso de la Rubia
2,*,
Enrique Alonso-Pérez-Chao
1,3,
Moisés Marquina Nieto
2 and
Carlos García-Sánchez
2,*
1
Facultad de Ciencias Biomédicas y de la Salud, Universidad Alfonso X el Sabio (UAX), Avenida de la Universidad, 1, 28691 Villanueva de la Cañada, Spain
2
Deporte y Entrenamiento Research Group, Departamento de Deportes, Facultad de Ciencias de la Actividad Física y del Deporte (INEF), Universidad Politécnica de Madrid, C/Martín Fierro 7, 28040 Madrid, Spain
3
Faculty of Sports Science, Universidad Europea de Madrid, 28670 Villaviciosa de Odón, Spain
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2025, 15(10), 5497; https://doi.org/10.3390/app15105497
Submission received: 31 March 2025 / Revised: 6 May 2025 / Accepted: 9 May 2025 / Published: 14 May 2025
(This article belongs to the Special Issue Sports Performance: Data Measurement, Analysis and Improvement)
Browse Figures
Versions Notes

Abstract

:
Over the past decade, participation in female team sports has increased significantly, leading to greater interest in monitoring their training and competition load using wearable technology. Despite this, there is currently no systematic review or meta-analysis that has specifically focused on quantifying and comparing high-speed running (HSR) and sprinting thresholds in female team sports. This systematic review aimed (1) to summarize and describe the evidence on absolute speed thresholds used to classify HSR and sprinting in female team sports and (2) to compare HSR and sprinting thresholds between female team sports. A total of 82 studies were included, encompassing a range of female team sports such as Australian football, basketball, field hockey, soccer, Gaelic football, handball, lacrosse, and different codes of rugby (league, sevens, and union). This systematic review was conducted following the PRISMA 2020 guidelines. This review found that to date, there is no consensus on defining high-speed and sprint running thresholds in female team sports, showing considerable variability in the thresholds used to define HSR (ranging from 11.1 to 21.6 km·h⁻1) and sprinting (from 15.0 to 30.0 km·h⁻1). Our results showed that the mean velocity for the HSR threshold was 16 km·h⁻1, although the most frequently used velocity was 18.0 km·h⁻1. In relation to the sprint threshold, the mean and the mode were similar: 21 km·h⁻1 and 20.0 km·h⁻1, respectively. The lack of standardized thresholds highlights the need for personalized approaches when monitoring training loads in female athletes. Despite apparent variability, these findings provide valuable insights for practitioners in designing evidence-based training programs aimed at optimizing high-speed exposure in female team sports. Further research is needed to establish sport-specific and standardized velocity thresholds for women’s team sports.

1. Introduction

Within the category of multi-directional sports (e.g., soccer, basketball, or handball), the physical demands registered during training and competition vary widely for running [1,2,3]. Some multi-directional sports require frequent and consistent sagittal plane sprinting and high-intensity running [4], while others emphasize more lateral shuffling or cutting, and some are heavily reliant on jumping [4]. Indeed, a range of sport-specific considerations could impact the physical demands, including the playing dimensions, player density, positional characteristics, game rules, or timing structure [5].
Wearable technology, such as accelerometers, inertial measurement units (IMUs), local positioning systems (LPSs), ultra-wide band (UWB) systems, or global positioning systems (GPSs), provide valid and reliable measures that help performance staff quantify and track the volume of sport-specific demands during match play [5,6,7]. Previous research has utilized different metrics or variables to quantify the external load [8,9]. The most commonly used tracking metrics are as follows: total distance, relative distance (distance/duration), distance and/or time in speed zones (total, relative, and percentages), high-intensity actions (usually referred to as distance, time and/or counts of accelerations, decelerations, and jumps), and peak velocity [5,10,11].
There have been several systematic reviews addressing activity demands in team sports. For example, Taylor et al. (2017) [4] analyzed running demands, including the total distance, characteristics of sprinting and high speed/intensity running, and the differences in these variables across sports, sex, and age. In another systematic review, Harper et al. 2019 [11] aimed to quantify and compare high- and very-high-speed acceleration vs. deceleration demands occurring during competitive match play in elite team sport contexts.
Additionally, a systematic review quantified the acceleration events in elite team sports [10]. More recently, Torres-Ronda et al., 2022 [5] published a narrative review about tracking systems and their applications in team sports. Furthermore, some scoping reviews have addressed match demands of female team sports [2], as well as the use of traditional arbitrary (absolute) thresholds compared to individualized running speed thresholds in team sports players [12].
Despite this growing body of knowledge, there is currently no systematic review or meta-analysis that has specifically focused on quantifying and comparing high-speed running (HSR) and sprinting thresholds in female team sports. The existing literature shows a variety of approaches in defining running speed thresholds among team sports [12]. To classify the intensity of movements, commonly, five threshold ranges have been utilized (e.g., covered distance: standing, walking, jogging, running, and sprinting) [4]. These thresholds are specific for the device manufacturer (e.g., covered distance: standing >6 km/h, walking 6–12 km/h, jogging 12–18 km/h, running 18–24 km/h, and sprinting >24 km/h) [4]. However, these thresholds may not be universally applicable to all sports [8,9,12,13] or for both genders [13].
The novelty of this review lies in its specific focus on elite female team sports, addressing a critical gap in the literature not covered by previous reviews. By systematically analyzing speed thresholds applied to female athletes, this study offers unique insights into monitoring and prescribing training loads for this population.
This review is essential for guiding future research and providing practical applications in sports science, particularly in the accurate monitoring of training loads in female team sports. Moreover, this systematic review could prove useful designing training contents and drills, as it would allow practitioners to make evidence-informed decisions when planning training sessions to ensure adequate HSR and sprint distance exposure.
While most studies have focused on male athletes, some have suggested that the thresholds established for men may not be applicable to women due to the underestimation of efforts and inaccurate results [14,15]. Beyond physiological differences such as lower absolute speed capacity or muscle strength, female athletes may exhibit distinct movement patterns, technical–tactical roles, and contextual demands (e.g., different game dynamics, positional responsibilities, and competitive structures), further justifying the need for female-specific thresholds.
Despite the existing literature, there is no consensus on speed thresholds in female sports. Therefore, the aims of this systematic review were (1) to summarize and describe the evidence on absolute speed thresholds used to classify high-speed running (HSR) and sprinting in female team sports and (2) to compare HSR and sprinting thresholds between female team sports.

2. Materials and Methods

2.1. Experimental Approach to the Problem

The study design corresponded to a systematic review of the scientific literature with regard to the establishment of absolute running speed thresholds used in female team sports. The systematized review protocol was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) checklist and the Population, Interventions, Comparisons, Outcomes, and Study Design (PICOS) question model for the definition of inclusion criteria [16].

2.2. Study Selection and Eligibility Criteria

Full-text original and primary scientific research published in peer-reviewed journals with an impact factor included in the Journal Citation Reports of the Web of Science (JCR of WoS) or SCImago Journal Rank of Scopus were considered. Studies whose status was “in press” or “ahead of print” were also included. No limitations were set regarding the publication date, and only papers in English were included.
According to the Population, Interventions, Comparisons, Outcomes, and Study Design (PICOS) question model, the inclusion criteria were as follows: (1) population: invasion team sport female players integrated in the training/performance dynamics of teams placed in competition tier 2 (trained/developmental), tier 3 (highly trained/national level), tier 4 (elite/international level), or tier 5 (world class) [17], and studies that have not analyzed pathologies or injuries; (2) intervention: definition and use of running velocity thresholds in official team activities (e.g., competition, game, match observations, etc.), with the aim of assessing the game demands through scientifically validated tracking technologies (global positioning system—GPS, global navigation satellite system—GNSS, local positioning system—LPS, and/or inertial movement unit—IMU) in real sport environments; (3) comparison: analysis of running thresholds according to the type of sport, competition level, sport context (geographical location), and season; (4) results: measuring time and/or distance (absolute and relative terms) elapsed at different arbitrary absolute running thresholds; and (5) study design: retrospective descriptive–observational study.
The exclusion criteria were as follows: (1) studies carried out on men or referees; (2) players in tiers 0 or 1 or with an injury or pathology; (3) studies conducted in other team sports, such as net ball games (e.g., tennis, badminton, and volleyball), wall games (e.g., squash), wicket games (e.g., cricket), or base running games (e.g., baseball and softball), in simplified modalities of invasion sports (e.g., 3 × 3 basketball), in ice-, sand-, or water-based team sports (e.g., beach handball or water polo), or in individual sports (e.g., cycling, swimming, and athletics) (Hughes and Bartlett (2002) [18]); (4) intervention protocols in simulated (e.g., small-sided games) or non-competitive (e.g., friendly) matches designed to examine training demands or game-based training demands and validation/reliability protocols with athletes using wearable technologies in an experimental setting; (5) partial presentation of competition data (i.e., first or second half, extra time, etc.); (6) the use of tracking technology based on time–motion analysis (TMA) or digital video-based analysis; (7) a definition of running speed thresholds according to a prior individualized assessment of the athlete(s) (e.g., 20 m linear sprint or peak speed at training/match); (8) prospective models for the determination of thresholds according to the sample characteristics (e.g., age); (9) the validation of accelerometers in relation to the definition of speed thresholds; and (10) the reporting of other external load variables (i.e., accelerometry). Systematic reviews and other types of articles (i.e., reviews, letters to the editors, non-peer reviewed articles, editorial, books, periodicals, surveys, opinion pieces, conference abstracts, dissertations, and theses) were not included.

2.3. Search Strategy and Systematic Review Protocol

The search process for published scientific studies was carried out through four electronic databases (PubMed, Scopus, Sport Discus, and the Web of Science) and by reviewing email alerts from research databases and the bibliographies of other systematic reviews. The keywords that formed the four search strings were as follows: (1) “women” OR “woman” OR “girl*” OR “female”; (2) “team sport*” OR “team-sport*” OR “intermittent sport*” OR “professional team sport*” OR “elite sport*” OR “elite team sport*” OR “associative sport*” OR “collaborative sport*” OR “Australian football” OR “soccer” OR “football” OR “hockey” OR “field hockey” OR “rugby” OR “rugby sevens” OR “lacrosse” OR “American football” OR “National Collegiate Athletic Association” OR “NCAA” OR “basketball” OR “handball” OR “futsal” OR “netball”; (3) “standing still” OR “walking” OR “jogging” OR “slow running” OR “moderate-speed running” OR “high-speed running” OR “high-speed running/min*” OR “HSR” OR “HSR/min*” OR “running” OR “high-intensity running” OR “sprint” AND ALL (“speed” OR “velocity” OR “quickness” OR “intensity” OR “running” OR “sprint*”) AND ALL (“threshold*” OR “zone*”); (4) “match demands” OR “competitive demands” OR “physical demands” OR “movement demands” OR “movement pattern” OR “external load” OR “external demands” OR “physical workload” OR “activity demand” OR “activity profile” OR “match profile” OR “match play” OR “match-play” OR “match intensity” OR “game load” OR “game intensity”; and (5) “global positioning system*” OR “GPS” OR “global navigation satellite system*” OR “GNSS” OR “local positioning system*” OR “LPS” OR “microtechnology” OR “microsensor*” OR “tracking system*” OR “athlete tracking system” OR “optical tracking system” OR “ultra-wide band”.
According to the criteria for preparing systematic reviews, PRISMA, the Cochrane Consumers and Communication Review Group’s data extraction protocol [16] was carried out in the months of August and September 2024, being composed of four stages (Figure 1): (1) identification: the second author (A.d.l.R.) found a total of 705 studies in the four databases consulted (PubMed, n = 107; Scopus, n = 204; Sport Discus, n = 97; and the Web of Science, n = 296), plus 2 from other sources; (2) screening: after the elimination of duplicate records (n = 204) by the second author (A.d.l.R.), 501 articles were considered for further analysis; (3) eligibility: after reading the title, abstract, and/or keywords, the second author (A.d.l.R.) ruled out 76 articles, leaving 425 records at the end of this phase; and (4) inclusion: after complete reading, 307 articles were excluded by the first (R.N.A.), second (A.d.l.R.), third (E.A.P.C.), and fourth (C.G.S.) authors for the following reasons: R1: referees and/or only men (n = 56); R2: tiers 0 and 1 (n = 23); R3: other team sports/individual sports (n = 40); R4: experimental setting (n = 84); R5: partial data presentation (n = 4); R6: tracking technology (n = 16); R7: individualized thresholds (n = 34); R8: prospective models of speed thresholds (n = 4); R9: validation of accelerometers (n = 13); and R10: other external load variables (n = 33). Moreover, of the full-text articles assessed for eligibility (n = 118), systematic reviews (n = 18), documents with a different format (i.e., theses or proceedings) (n = 16), or those non-published in JCR or SJR (n = 2) were eliminated. Finally, the total number of studies included in the systematic review was 82.
The authors worked separately and independently to ensure the reliability of the process and the eligibility of the studies. Nevertheless, any discrepancies (n = 5) in the final inclusion–exclusion criteria were resolved by consensus discussion. Once the included studies were finally selected (n = 0), no specific assessment of methodological quality was performed.

2.4. Data Extraction and Management

The information extracted from the studies included in this systematic review was distributed in the following categories and subcategories: (A) year of publication; (B) sample characteristics: (B1) competition level or (B2) sport modality; and (C) threshold: (C1) HSR or (C2) sprint.

2.5. Study Quality Assessment

The quality of all eligible cross-sectional studies was evaluated using the criteria for “strengthening the reporting of observational studies in epidemiology” (STROBE) [19]. The following scale was used to rate the quality of the studies: (a) good quality (>14 points, low risk of major or minor bias), (b) acceptable quality (7–4 points, moderate risk of major bias), and (c) poor quality (<7 points, high risk of major bias). The score was obtained through the 22 points on the STROBE checklist. Two independent reviewers (C.G.S and R.N.A) conducted study quality assessment. Rating disagreements were resolved by A.d.l.R.

3. Results

The 82 studies included in this systematic review were carried out between 2010 and 2024. The number of participants included per study averaged 42.2 (standard deviation = 47.2), totaling 3421 participants. The number of total matches recollected was 1849 (median = 25.7; standard = 53.2). The number of total observations registered was 13,770 (median = 275.4; standard = 460.1) (Table 1).
The quality analysis (“STROBE” checklist) produced the following results (Table 2): (a) the quality scores ranged from 17 to 21; (b) the average score was 20.12 points; (c) 100% of the 82 included studies were categorized as “very high quality” (17–22 points); (d) most of the studies (78 of 82) lacked information in relation to Item 10, related to an explicit justification of the study sample size calculation; (e) in addition, some studies (45 of 82) also lacked information in relation to Item 22, which provides information related to the source of funding and the role of the funders.
The absolute and relative frequencies of the studies published by year are shown in Figure 2. According to the classification described by McKay et al., 2022 [102], 2 studies (2.4%) involved “tier 5” (world class athletes), 31 studies (37.8%) involved “tier 4” (elite/international-level athletes), 45 studies (54.9%) involved “tier 3” (highly trained/national-level), and 4 studies (4.9%) involved “tier 2” (trained/developmental individuals).
Regarding the sport modality, four studies were conducted in Australian football (4.9%), three in basketball (3.7%), sixteen in field hockey (19.5%), thirty-three in soccer (40.2%), one in Gaelic football (1.2%), six in handball (7.3%), two in lacrosse (2.4%), one in rugby league (1.2%), eleven in rugby seven (13.4%), and five in rugby union (6.1%).
The descriptive data of HSR and sprint thresholds according to sport are presented in Table 3 and Figure 3, Figure 4 and Figure 5. The velocity corresponding to the HSR threshold was reported in 82 of the 82 studies (100%) included in this systematic review. However, in the case of the sprint threshold, it was only reported in 59 of the 82 studies (71.9%). In addition, the mean velocity for the HSR threshold was 16.0 km·h−1, although the most frequently used velocity was 18.0 km·h−1 (23.2% of the studies; n = 19). In relation to the sprint threshold, the mean and the mode were similar: 21.0 km·h−1 and 20.0 km·h−1 (44.1% of the studies; n = 26), respectively.

4. Discussion

This systematic review provides an overview of the research on high-speed running and sprinting in elite female athletes in team sports. The aims of this systematic review were (1) to summarize and describe the evidence on absolute speed thresholds used to classify high-speed running (HSR) and sprinting in female team sports and (2) to compare HSR and sprinting thresholds between female team sports. The main findings were that (1) non-standard thresholds are used to monitor HSR and sprinting demands among professional female sports and that (2) HSR and sprint distances are sport dependent and highly variable across sports. This variability is expected, given the difference in the playing field sizes, player density, and technical and tactical characteristics of each sport [5].
The definition of HSR threshold was highly variable, ranging from a low 11.1 km·h−1, to a high 21.6 km·h−1 (Table 3). We found even greater variability between sports in terms of sprint thresholds, ranging from 15.0 km·h−1 to 30.0 km·h−1 (Figure 3, Figure 4 and Figure 5). This highlights considerable heterogeneity in the velocity criteria used to assess the same external load metric, limiting comparability across studies and complicating practical application. Moreover, different sprint thresholds were identified depending on the field size. Authors tend to set a higher threshold for sprinting in sports with larger pitch sizes (e.g., soccer, hockey, or rugby), as previously reported in other studies [5]. Nevertheless, the sprint threshold appears to be more consistent in the literature on female team sports, with 44.1% of the studies setting it at 20.0 km·h−1.
In indoor sports like handball, five studies were found on female handball matches using the same threshold for HSR (18.0 km·h−1) [41,42,43,44,45]. This agreement contrasts with the greater variability observed in outdoor sports and suggests a potential link between the playing area size and velocity thresholds. In male handball players, the thresholds differed; some authors set 19.8 km·h⁻1 [103,104,105], while others set 21.0 km·h⁻1 [106,107] for HSR. However, for the sprint threshold, there is less variability, with most studies setting it at >24.0 km·h⁻1 or >25.2 km·h⁻1 [103,104,105,106,107]. Significantly fewer studies have been reported on high-speed running in female basketball matches, although three studies reported a similar HSR (≈14.0 km·h−1) [71,75,76]. In contrast, male basketball studies commonly set HSR at 18 km·h⁻1 and sprinting at >24.0 km·h⁻1 [108,109,110,111,112,113,114]. Additionally, we found differences between handball and basketball female HSR thresholds (18.0 km·h−1 vs. 14.0 km·h−1, respectively), which could be explained by the differences in the field size between the sports [5]. In handball and basketball, the HSR threshold for females is set lower than in men. This could be justified from a physiological standpoint, as evidence suggests differences in the absolute running performance between men and women [115,116].
In field hockey, the majority of studies (9 out of 16) set the threshold for HSR at 16.0 km·h⁻1. However, there is no consensus on the sprint threshold, with significant variability across studies (see Figure 3). In studies on men players, activity categories were classified as high-speed running (>15.5 km·h−1) and sprinting (>20.0 km·h−1) [117]. This variation allows for direct comparisons with previous research on male elite hockey, as similar methodologies and speed zones were used.
In outdoor sports, four studies used the same thresholds to define HSR and sprint in female Australian football [27,28,29,89] (see Figure 3). The consistency of these four studies supports the robustness of the proposed thresholds for Australian football in female athletes. These findings suggest that despite rule differences across rugby codes, thresholds may be interchangeable; however, caution is warranted given the potential differences in game dynamics.
Similarly, rugby sevens and rugby union show considerable variability in HSR and sprinting thresholds. However, nearly 50% of the studies applied the same thresholds for HSR (18.0 km·h⁻1) and sprinting (20.0 km·h⁻1). Based on our findings, despite the differences in rules and disciplines across rugby modalities, the thresholds for HSR and sprinting could be interchangeable within the rugby codes. The same variability in GPS speed-zone metrics has been observed in men’s rugby leagues [118]. Haugen et al. 2016 [119] found significant variations in speed-zone classifications across studies, making it difficult to compare player performance consistently. For example, different studies defined low-speed zones or low-speed activities using thresholds like 0.1–6.9, 0–10.8, 0–12.6, 0–14.4, 0–18, and 0–19.4 km·h⁻1. Similarly, while some studies categorized high-speed/intensity running starting at 14.4 km·h⁻1, the majority used 18.0 km·h⁻1 as the baseline [118].
In female soccer, some differences were observed for HSR (minimum 12.5 km·h−1 and maximum 19.0 km·h−1) and sprint (minimum 19.0 km·h−1 and maximum 25.0 km·h−1) (Table 3). Therefore, based on the current literature, the definitions of the thresholds for HSR and sprint remain arbitrary, with no consensus in the soccer literature. However, 36% of authors used 20.0 km·h⁻1 to define sprint velocities, while most studies in professional adult soccer set the sprint threshold at >25.2 km·h⁻1 [120]. This indicates that using male-derived thresholds may underestimate high-intensity distances in female athletes, reinforcing the need for sex-specific benchmarks.
In lacrosse, only two studies met our inclusion criteria [35,50]. Both studies fixed the same HSR threshold (16.0 km·h⁻1) and similar sprint velocities of 19.0 (25) and 20.0 km·h⁻1 (49). The consistency of speed zones and movement pattern definitions demonstrated in the two previous lacrosse studies could enable more accurate comparisons and performance analyses among players and across various levels of competition within the sport.
In outdoor sports, the mean HSR threshold was 16.0 km·h⁻1 ± 2.8 km·h⁻1, and for sprint velocity, the most frequently used threshold across different outdoor sports was 20.0 km·h⁻1, with the exception of lacrosse (19.0 km·h⁻1) and rugby union (15.0 km·h⁻1). This similarity in HSR between outdoor sports may be partly explained by their comparable field sizes [5]. For outdoor sports, our analysis suggests that some measures of external load (e.g., high-speed running or sprinting) may be used interchangeably, but this is not the case for indoor modalities such as handball or basketball.
Another critical consideration rarely addressed in the literature is the influence of tracking technology on the reported thresholds. Differences in sampling rates, device placement, and data processing methods may substantially impact speed measurements. Therefore, interpreting results within the technological context is essential, and future research should promote greater standardization of tracking methodologies to improve cross-study comparability.
Overall, the variability observed in the literature highlights an urgent need to establish sport- and sex-specific velocity thresholds while explicitly accounting for the characteristics of the measurement systems used. Only through such standardization will it be possible to rigorously compare studies and effectively translate research findings into practice.

4.1. Limitations and Future Research Perspectives

It is important to note that this systematic review is not without limitations. First, the lack of clarification and consensus across different researchers and manufacturers regarding tracking systems on which they standardize speed ranges or thresholds for HSR and sprinting may make it difficult to generalize the findings to other sport categories under tier 2 [102], such as recreational or amateur athletes. Moreover, this systematic review only considered official matches; therefore, these data may differ for other types of matches (e.g., friendly matches). Therefore, coaches and practitioners should be cautious when generalizing and extrapolating the results. Second, some studies on female sports have used the same HSR and sprint thresholds as those used for male athletes. This represents a disadvantage when comparing and generalizing data in female team sports. Future research should establish female-specific speed thresholds to build consensus in the literature and facilitate comparisons between leagues or different categories. Third, it is important to note that some sports, such as Gaelic football and rugby league, were represented by only one study each. In particular, one of these studies reported an unusually low HSR threshold (12 km·h⁻1), which may have influenced the overall mean value. This suggests that future studies with larger and more balanced samples across sports could help to refine and contextualize the average thresholds more accurately. Finally, our systematic review contains only a few studies with “youth” samples (n = 3), so coaches and professionals should exercise caution when extrapolating adult thresholds to young athletes. Finally, the exclusion of non-English papers and systematic reviews from our search may have led to the omission of relevant publications in other languages, which could have provided valuable insights for this review.

4.2. Practical Applications

Given the lack of consensus on specific absolute thresholds for defining high-speed running (HSR) and sprinting in female athletes and the absence of an international standard, practitioners may consider using the velocity ranges identified in this review as a practical reference. Understanding the speed characteristics of each sport is essential for designing training programs tailored to the demands of female team sports.
Establishing appropriate HSR and sprint thresholds in female athletes can support coaches and performance staff in managing weekly training loads and reducing injury risk, particularly for soft-tissue injuries associated with chronic exposure to high-speed efforts. Moreover, accurate threshold determination is especially valuable for guiding return-to-play protocols, ensuring that injured players are progressively and safely reintroduced to high-speed activities.
Additionally, having sport-specific reference values is critical for practitioners working across different disciplines. For sports scientists, the ability to adjust or reprocess data using shared benchmarks facilitates collaboration and data comparison with clubs, federations, or organizations that may apply different standards in female sports.
Nevertheless, implementing individualized or sport-specific thresholds may pose challenges, particularly in teams with mixed experience levels or in settings with limited access to advanced tracking technologies and analysis resources. Practitioners may need to balance the ideal application of individualized thresholds with practical constraints, opting for simplified approaches where necessary
Key points:
-
In the absence of standardized thresholds, coaches and practitioners should apply the velocity ranges identified in this review (e.g., ~16 km/h for HSR; ~20–21 km/h for sprinting) as reference points while considering the specific demands of each sport and player role.
-
Appropriate HSR and sprint thresholds can help manage weekly training loads and minimize injury risk, especially for soft-tissue injuries linked to high-speed running exposure. Tracking these thresholds is also valuable for safe and effective return-to-play protocols.

5. Conclusions

In conclusion, this systematic review highlights the lack of standardization in defining high-speed running (HSR) and sprinting thresholds across female team sports. The findings show an average HSR threshold of 15.9 km·h⁻1, with 18.0 km·h⁻1 being the most frequently reported threshold (23.2% of studies; n = 19). For sprinting, both the mean and mode were similar, at 21.0 km·h⁻1 and 20.0 km·h⁻1, respectively (44.1% of studies; n = 26). These results provide valuable reference points for coaches, practitioners, and researchers aiming to monitor and prescribe training loads in elite female athletes. However, the current variability across studies underscores the need for greater consistency in reporting and applying speed thresholds. To advance the field, we recommend the establishment of expert consensus panels or the development of sport- and sex-specific guidelines to standardize the use of HSR and sprinting thresholds in female team sports.

Author Contributions

Conceptualization, R.N.-A.; methodology, A.d.l.R.; software, C.G.-S.; validation, R.N.-A., A.d.l.R., and C.G.-S.; formal analysis, M.M.N.; investigation, E.A.-P.-C.; resources, C.G.-S.; data curation, R.N.-A.; writing—original draft preparation, R.N.-A.; writing—review and editing, C.G.-S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All the relevant material is included in the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Reina, M.; García, J.; Ibáñez, S. Training and Competition Load in Female Basketball: A Systematic Review. Int. J. Environ. Res. Public Health 2020, 17, 2639. [Google Scholar] [CrossRef] [PubMed]
  2. Armendáriz, M.L.P.; Spyrou, K.; Alcaraz, P.E. Match Demands of Female Team Sports: A Scoping Review. Biol. Sport. 2024, 41, 175. [Google Scholar] [CrossRef] [PubMed]
  3. Gomez-Bruton, A.; Marin-Puyalto, J.; Muniz-Pardos, B.; Matute-Llorente, A.; Del Coso, J.; Gomez-Cabello, A.; Vicente-Rodriguez, G.; Casajus, J.A.; Lozano-Berges, G. Does Acute Caffeine Supplementation Improve Physical Performance in Female Team-Sport Athletes? Evidence from a Systematic Review and Meta-Analysis. Nutrients 2021, 13, 3663. [Google Scholar] [CrossRef]
  4. Taylor, J.B.; Wright, A.A.; Dischiavi, S.L.; Townsend, M.A.; Marmon, A.R. Activity Demands During Multi-Directional Team Sports: A Systematic Review. Sports Med. 2017, 47, 2533–2551. [Google Scholar] [CrossRef]
  5. Torres-Ronda, L.; Beanland, E.; Whitehead, S.; Sweeting, A.; Clubb, J. Tracking Systems in Team Sports: A Narrative Review of Applications of the Data and Sport Specific Analysis. Sports Med. Open 2022, 8, 15. [Google Scholar] [CrossRef] [PubMed]
  6. Scott, M.T.U.; Scott, T.J.; Kelly, V.G. The Validity and Reliability of Global Positioning Systems in Team Sport: A Brief Review. J. Strength. Cond. Res. 2016, 30, 1470–1490. [Google Scholar] [CrossRef]
  7. Luteberget, L.S.; Gilgien, M. Validation Methods for Global and Local Positioning-Based Athlete Monitoring Systems in Team Sports: A Scoping Review. BMJ Open Sport—Exerc. Med. 2020, 6, e000794. [Google Scholar] [CrossRef]
  8. Alonso, E.; Portes, R.; Gómez, M.Á.; Parmar, N.; Lorenzo, A.; Jiménez Sáiz, S.L. A Narrative Review of the Most Demanding Scenarios in Basketball: Current Trends and Future Directions. J. Hum. Kinet. 2023, 89, 231–245. [Google Scholar] [CrossRef]
  9. García-Sánchez, C.; Navarro, R.M.; Karcher, C.; de la Rubia, A. Physical Demands during Official Competitions in Elite Handball: A Systematic Review. Int. J. Environ. Res. Public Health 2023, 20, 3353. [Google Scholar] [CrossRef]
  10. Delves, R.I.M.; Aughey, R.J.; Ball, K.; Duthie, G.M. The Quantification of Acceleration Events in Elite Team Sport: A Systematic Review. Sports Med. Open 2021, 7, 45. [Google Scholar] [CrossRef]
  11. Harper, D.J.; Carling, C.; Kiely, J. High-Intensity Acceleration and Deceleration Demands in Elite Team Sports Competitive Match Play: A Systematic Review and Meta-Analysis of Observational Studies. Sports Med. 2019, 49, 1923–1947. [Google Scholar] [CrossRef] [PubMed]
  12. Clemente, F.M.; Ramirez-Campillo, R.; Beato, M.; Moran, J.; Kawczynski, A.; Makar, P.; Sarmento, H.; Afonso, J. Arbitrary Absolute vs. Individualized Running Speed Thresholds in Team Sports: A Scoping Review with Evidence Gap Map. Biol. Sport. 2023, 40, 919. [Google Scholar] [CrossRef] [PubMed]
  13. Ball, S.; Halaki, M.; Orr, R. Movement Demands of Rugby Sevens in Men and Women: A Systematic Review and Meta-Analysis. J. Strength. Cond. Res. 2019, 33, 3475–3490. [Google Scholar] [CrossRef] [PubMed]
  14. Cummins, C.; Charlton, G.; Paul, D.; Buxton, S.; Murphy, A. How Fast Is Fast? Defining Velocity Zones in Women’s Rugby League. Sci. Med. Footb. 2023, 7, 165–170. [Google Scholar] [CrossRef]
  15. Nyman, D.L.E.; Spriet, L.L. External Training Demands in Women’s Varsity Rugby Union Players Quantified by Wearable Microtechnology with Individualized Speed Thresholds. J. Strength. Cond. Res. 2022, 36, 3151–3158. [Google Scholar] [CrossRef]
  16. Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med. 2009, 6, e1000097. [Google Scholar] [CrossRef]
  17. McKay, G.D.; Goldie, P.A.; Payne, W.R.; Oakes, B.W.; Watson, L.F. A Prospective Study of Injuries in Basketball: A Total Profile and Comparison by Gender and Standard of Competition. J. Sci. Med. Sport. 2001, 4, 196–211. [Google Scholar] [CrossRef]
  18. Hughes, M.D.; Bartlett, R.M. The use of performance indicators in performance analysis. J. Sports Sci. 2002, 20, 739–754. [Google Scholar] [CrossRef]
  19. von Elm, E.; Altman, D.G.; Egger, M.; Pocock, S.J.; Gøtzsche, P.C.; Vandenbroucke, J.P. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for Reporting Observational Studies. Int. J. Surg. 2014, 12, 1495–1499. [Google Scholar] [CrossRef]
  20. Baptista, I.; Winther, A.K.; Johansen, D.; Randers, M.B.; Pedersen, S.; Pettersen, S.A. The Variability of Physical Match Demands in Elite Women’s Football. Sci. Med. Footb. 2022, 6, 559–565. [Google Scholar] [CrossRef]
  21. Baptista, I.; Winther, A.K.; Johansen, D.; Pettersen, S.A. Analysis of Peak Locomotor Demands in Women’s Football–the Influence of Different Epoch Lengths. PLoS ONE 2024, 19, 2–10. [Google Scholar] [CrossRef] [PubMed]
  22. Bohner, J.D.; Hoffman, J.R.; McCormack, W.P.; Scanlon, T.C.; Townsend, J.R.; Stout, J.R.; Fragala, M.S.; Fukuda, D.H. Moderate Altitude Affects High Intensity Running Performance in a Collegiate Women’s Soccer Game. J. Hum. Kinet. 2015, 47, 147–154. [Google Scholar] [CrossRef]
  23. Bozzini, B.N.; McFadden, B.A.; Walker, A.J.; Arent, S.M. Varying Demands and Quality of Play Between In-Conference and Out-of-Conference Games in Division I Collegiate Women’s Soccer. J. Strength. Cond. Res. 2020, 34, 3364–3368. [Google Scholar] [CrossRef] [PubMed]
  24. Bradley, E.J.; Board, L.; Hogg, B.; Archer, D.T. Quantification of Movement Characteristics in Women’s English Premier Elite Domestic Rugby Union. J. Hum. Kinet. 2020, 72, 185–194. [Google Scholar] [CrossRef]
  25. Bradley, E.; Roberts, J.; Archer, D. Determining Female-specific High-intensity Activity GPS Thresholds in Women’s Rugby Union: Use of Current Use of Male-derived Absolute Speed Thresholds Underestimates True Levels. Eur. J. Sport. Sci. 2024, 24, 1079–1085. [Google Scholar] [CrossRef] [PubMed]
  26. Brosnan, R.J.; Visentin, D.; Watson, G.; Twentyman, C.; Stuart, W.; Schmidt, M. Match-Play Movement Demands of International and Domestic Women’s Rugby Sevens Players in an Elite Dual-Level Tournament. Sci. Med. Footb. 2024, 8, 84–93. [Google Scholar] [CrossRef]
  27. Clarke, A.C.; Ryan, S.; Couvalias, G.; Dascombe, B.J.; Coutts, A.J.; Kempton, T. Physical Demands and Technical Performance in Australian Football League Women’s (AFLW) Competition Match-Play. J. Sci. Med. Sport. 2018, 21, 748–752. [Google Scholar] [CrossRef] [PubMed]
  28. Clarke, A.C.; Couvalias, G.; Kempton, T.; Dascombe, B. Comparison of the Match Running Demands of Elite and Sub-Elite Women’s Australian Football. Sci. Med. Footb. 2019, 3, 70–76. [Google Scholar] [CrossRef]
  29. Clarke, A.C.; Whitaker, M.; Sullivan, C. Evolving Peak Period, Match Movement, and Performance Demands in Elite Women’s Australian Football. J. Sci. Med. Sport. 2021, 24, 683–688. [Google Scholar] [CrossRef]
  30. Conte, D.; Guerriero, A.; Lupo, C.; Arruda, A.F.S.; Kamarauskas, P. Influence of Congested Match Schedules, Pre-Match Well-Being and Level of Opponents on Match Loads during World Rugby Women’s Sevens Series. Int. J. Environ. Res. Public Health 2021, 18, 12132. [Google Scholar] [CrossRef]
  31. Conte, D.; Arruda, A.F.S.; Clemente, F.M.; Castillo, D.; Kamarauskas, P.; Guerriero, A. Assessing the Relationship Between External and Internal Match Loads in Elite Women’s Rugby Sevens. Int. J. Sports Physiol. Perform. 2022, 17, 634–639. [Google Scholar] [CrossRef] [PubMed]
  32. Curran, O.; Neville, R.D.; Passmore, D.; MacNamara, Á. Variability in Locomotor Activity in a Female Junior International Hockey Team. J. Sci. Med. Sport. 2022, 25, 586–592. [Google Scholar] [CrossRef] [PubMed]
  33. Datson, N.; Dello Iacono, A.; Doncaster, G.; Page, R.M.; McKeown, A.; Unnithan, V.B. Peak Physical Demands of Elite Women’s Soccer: Assessing Playing Position and Post-Goal Locomotor Patterns. Int. J. Sports Sci. Coach. 2023, 19, 999–1010. [Google Scholar] [CrossRef]
  34. Junior, M.N.S.d.O.; Veneroso, C.E.; Ramos, G.P.; Johnson, K.E.; Guilkey, J.P.; Sena, A.F.d.C.; Cabido, C.E.T.; Cholewa, J.M. Distance and Intensity Profiles in Division i Women’s Soccer Matches across a Competitive Season. Sports 2021, 9, 63. [Google Scholar] [CrossRef]
  35. Devine, N.F.; Hegedus, E.J.; Nguyen, A.; Ford, K.R.; Taylor, J.B. External Match Load in Women’ s Collegiate Lacrosse. J. Strength Cond. Res. 2021, 36, 503–507. [Google Scholar] [CrossRef]
  36. DeWitt, J.K.; Gonzales, M.; Laughlin, M.S.; Amonette, W.E. External Loading Is Dependent upon Game State and Varies by Position in Professional Women’s Soccer. Sci. Med. Footb. 2018, 2, 225–230. [Google Scholar] [CrossRef]
  37. Diaz-Seradilla, E.; Rodríguez-Fernández, A.; Rodríguez-Marroyo, J.A.; Castillo, D.; Raya-González, J.; Vicente, J.G.V. Inter- and Intra-Microcycle External Load Analysis in Female Professional Soccer Players: A Playing Position Approach. PLoS ONE 2022, 17, e0264908. [Google Scholar] [CrossRef]
  38. Doeven, S.H.; Brink, M.S.; Huijgen, B.C.H.; de Jong, J.; Lemmink, K.A.P.M. High Match Load’s Relation to Decreased Well-Being during an Elite Women’s Rugby Sevens Tournament. Int. J. Sports Physiol. Perform. 2019, 14, 1036–1042. [Google Scholar] [CrossRef]
  39. Fernandes, R.; Martins, A.D.; Clemente, F.M.; Brito, J.P.; Nobari, H.; Reis, V.; Oliveira, R. Variations of Distance and Accelerometry-Based GPS Measures and Their Influence on Body Composition in Professional Women Soccer Players. Proc. Inst. Mech. Eng. P. J. Sport. Eng. Technol. 2022, 239, 20–28. [Google Scholar] [CrossRef]
  40. Gabbett, T.J. GPS Analysis of Elite Women’s Field Hockey Training and Competition. J. Strength. Cond. Res. 2010, 24, 1321–1324. [Google Scholar] [CrossRef]
  41. García-Sánchez, C.; Karcher, C.; Navarro, R.M.; Nieto-Acevedo, R.; Cañadas-García, E.; de la Rubia, A. Same Training for Everyone? Effects of Playing Positions on Physical Demands During Official Matches in Women’s Handball. Montenegrin J. Sports Sci. Med. 2024, 20, 11–18. [Google Scholar] [CrossRef]
  42. García-Sánchez, C.; Navarro, R.M.; Mon-López, D.; Nieto-Acevedo, R.; Cañadas-García, E.; de la Rubia, A. Do All Matches Require the Same Effort? Influence of Contextual Factors on Physical Demands during Official Female Handball Competitions. Biol. Sport. 2024, 41, 145–154. [Google Scholar] [CrossRef]
  43. García-Sánchez, C.; Navarro, R.M.; Nieto-Acevedo, R.; de la Rubia, A. Are Fluctuations in Physical Performance Affected by Contextual Factors in Women’s Handball Matches? An Analysis Using Five-Minute Fixed Phases. Biol. Sport. 2024, 42, 113–121. [Google Scholar] [CrossRef]
  44. García-Sánchez, C.; Navarro, R.M.; Nieto-acevedo, R.; de la Rubia, A. De Does the Final Score Influence the Physical Demands of Women’ s Handball Matches? Montenegrin J. Sports Sci. Med. 2024, 13, 21–27. [Google Scholar] [CrossRef]
  45. García-Sánchez, C.; Navarro, R.M.; Nieto-Acevedo, R.; De La Rubia, A. Is Match Playing Time a Potential Tool for Managing Load in Women’s Handball? J. Strength. Cond. Res. 2024, 38, e769–e775. [Google Scholar] [CrossRef] [PubMed]
  46. Gonçalves, L.; Clemente, F.M.; Barrera, J.I.; Sarmento, H.; González-Fernández, F.T.; Vieira, L.H.P.; Figueiredo, A.J.; Clark, C.C.T.; Carral, J.M.C. Relationships between Fitness Status and Match Running Performance in Adult Women Soccer Players: A Cohort Study. Medicina 2021, 57, 617. [Google Scholar] [CrossRef]
  47. Goodale, T.L.; Gabbett, T.J.; Tsai, M.C.; Stellingwerff, T.; Sheppard, J. The Effect of Contextual Factors on Physiological and Activity Profiles in International Women’s Rugby Sevens. Int. J. Sports Physiol. Perform. 2017, 12, 370–376. [Google Scholar] [CrossRef]
  48. Griffin, J.; Newans, T.; Horan, S.; Keogh, J.; Andreatta, M.; Minahan, C. Acceleration and High-Speed Running Profiles of Women’s International and Domestic Football Matches. Front. Sports Act. Living 2021, 3, 604605. [Google Scholar] [CrossRef]
  49. Harkness-Armstrong, A.; Till, K.; Datson, N.; Emmonds, S. Whole and Peak Physical Characteristics of Elite Youth Female Soccer Match-Play. J. Sports Sci. 2021, 39, 1320–1329. [Google Scholar] [CrossRef]
  50. Hauer, R.; Tessitore, A.; Hauer, K.; Tschan, H. Activity Profile of International Female Lacrosse Players. J. Strength. Cond. Res. 2021, 35, 3207–3212. [Google Scholar] [CrossRef]
  51. Ishida, A.; Kyle Travis, S.; Draper, G.; White, J.B.; Stone, M.H. Player Position Affects Relationship Between Internal and External Training Loads During Division I Collegiate Female Soccer Season. J. Strength. Cond. Res. 2022, 36, 513–517. [Google Scholar] [CrossRef] [PubMed]
  52. Kapteijns, J.A.; Caen, K.; Lievens, M.; Bourgois, J.G.; Boone, J. Positional Match Running Performance and Performance Profiles of Elite Female Field Hockey. Int. J. Sports Physiol. Perform. 2021, 16, 1295–1302. [Google Scholar] [CrossRef] [PubMed]
  53. Kim, T.; Cha, J.H.; Park, J.C. Association between In-Game Performance Parameters Recorded via Global Positioning System and Sports Injuries to the Lower Extremities in Elite Female Field Hockey Players. Clust. Comput. 2016, 21, 1069–1078. [Google Scholar] [CrossRef]
  54. Leal Cussaría, J.A.; Ortega Gálvez, M.J.; Porras Alvarez, J.; Galvez Gonzalez, J. Physical and Physiological Demands in Women’s Field Hockey: Differences between Play Times. Retos 2019, 35, 274–277. [Google Scholar]
  55. Mäkiniemi, J.K.; Savolainen, E.H.J.; Finni, T.; Ihalainen, J.K. Position Specific Physical Demands in Different Phases of Competitive Matches in National Level Women’s Football. Biol. Sport. 2023, 40, 629–637. [Google Scholar] [CrossRef]
  56. Malone, S.; Earls, M.; Shovlin, A.; Eddy, A.; Winkelman, N. Match-Play Running Performance and Exercise Intensity in Elite International Women’s Rugby Sevens. J. Strength Cond. Res. 2020, 34, 1741–1749. [Google Scholar] [CrossRef]
  57. Malone, S.; McGuinness, A.; Duggan, J.D.; Talty, P.F.; O’Connor, C.; Collins, K. Establishing the Locomotor Performance Profile of Elite Ladies Gaelic Football across Position and Quarters. Appl. Sci. 2024, 14, 7145. [Google Scholar] [CrossRef]
  58. McGuinness, A.; Malone, S.; Hughes, B.; Collins, K.; Passmore, D. Physical Activity and Physiological Profiles of Elite International Female Field Hockey Players Across the Quarters of Competitive Match Play. J. Strength. Cond. Res. 2019, 33, 2513–2522. [Google Scholar] [CrossRef] [PubMed]
  59. McGuinness, A.; Malone, S.; Petrakos, G.; Collins, K. Physical and Physiological Demands of Elite International Female Field Hockey Players During Competitive Match Play. J. Strength. Cond. Res. 2019, 33, 3105–3113. [Google Scholar] [CrossRef]
  60. McGuinness, A.; McMahon, G.; Malone, S.; Kenna, D.; Passmore, D.; Collins, K. Monitoring Wellness, Training Load, and Running Performance during a Major International Female Field Hockey Tournament. J. Strength Cond. Res. 2020, 34, 2312–2320. [Google Scholar] [CrossRef]
  61. McGuinness, A.; Kenna, D.; Grainger, A.; Collins, K. Investigating the Effect of Individual Rotations on the Physical and Physiological Performance in Elite Female Field Hockey Players. Appl. Sci. 2021, 11, 1022. [Google Scholar] [CrossRef]
  62. McGuinness, A.; Passmore, D.; Malone, S.; Collins, K. Peak Running Intensity of Elite Female Field Hockey Players during Competitive Match Play. J. Strength. Cond. Res. 2022, 36, 1064–1070. [Google Scholar] [CrossRef]
  63. McMahon, G.E.; Kennedy, R.A. Changes in Player Activity Profiles after the 2015 Fih Rule Changes in Elite Women’s Hockey. J. Strength. Cond. Res. 2019, 33, 3114–3122. [Google Scholar] [CrossRef] [PubMed]
  64. Mesa, M.F.; Stout, J.R.; Fukuda, D.H.; Redd, M.J.; Wells, A.J. High-Risk Environmental Conditions Attenuates Performance Efficiency Index in NCAA DI Female Soccer Players. Int. J. Exerc. Sci. 2022, 15, 442–454. [Google Scholar]
  65. Misseldine, N.D.; Blagrove, R.C.; Goodwin, J.E. Speed Demands of Women’s Rugby Sevens Match Play. J. Strength. Cond. Res. 2021, 35, 183–189. [Google Scholar] [CrossRef] [PubMed]
  66. Mohr, M.; Fatouros, I.G.; Jamurtas, A.Z.; Draganidis, D.; Thomassen, M.; Ørntoft, C.; Ermidis, G.; Loules, G.; Batsilas, D.; Poulios, A.; et al. Skeletal Muscle Phenotype and Game Performance in Elite Women Football Players. Scand. J. Med. Sci. Sports 2021, 32, 39–53. [Google Scholar] [CrossRef] [PubMed]
  67. Morencos, E.; Casamichana, D.; Torres, L.; Haro, X.; Rodas, G. Demandas Cinemáticas de Competición Internacional En El Hockey Sobre Hierba Femenino. Apunt. Educ. Física Deportes 2019, 35, 56–70. [Google Scholar] [CrossRef]
  68. Newans, T.; Bellinger, P.; Buxton, S.; Quinn, K.; Minahan, C. Movement Patterns and Match Statistics in the National Rugby League Women’s (NRLW) Premiership. Front. Sports Act. Living 2021, 3, 618913. [Google Scholar] [CrossRef]
  69. Panduro, J.; Ermidis, G.; Røddik, L.; Vigh-Larsen, J.F.; Madsen, E.E.; Larsen, M.N.; Pettersen, S.A.; Krustrup, P.; Randers, M.B. Physical Performance and Loading for Six Playing Positions in Elite Female Football: Full-Game, End-Game, and Peak Periods. Scand. J. Med. Sci. Sports 2022, 32, 115–126. [Google Scholar] [CrossRef]
  70. Pedersen, S.; Welde, B.; Sagelv, E.H.; Heitmann, K.A.; BRanders, M.; Johansen, D.; Pettersen, S.A. Associations between Maximal Strength, Sprint, and Jump Height and Match Physical Performance in High- Level Female Football Players. Scand. J. Med. Sci. Sports 2022, 32, 54–61. [Google Scholar] [CrossRef]
  71. Portes-Sánchez, R.; Navarro Barragán, R.M.; Calleja-González, J.; Gómez-Ruano, M.Á.; Jiménez Sáiz, S.L. Physical Persistency across Game Quarters and during Consecutive Games in Elite Junior Basketball Players. Int. J. Environ. Res. Public Health 2022, 19, 5658. [Google Scholar] [CrossRef]
  72. Portillo, J.; González-Ravé, J.M.; Juárez, D.; García, J.M.; Suárez-Arrones, L.; Newton, R.U. Comparison of Running Characteristics and Heart Rate Response of International and National Female Rugby Sevens Players during Competitive Matches. J. Strength. Cond. Res. 2014, 28, 2281–2289. [Google Scholar] [CrossRef] [PubMed]
  73. Ramos, G.P.; Nakamura, F.Y.; Penna, E.M.; Wilke, C.F.; Pereira, L.A.; Loturco, I.; Capelli, L.; Mahseredjian, F.; Silami-Garcia, E.; Coimbra, C.C. Activity Profiles in U17, U20, and Senior Women’s Brazilian National Soccer Teams during International Competitions:Are There Meaningful Differences? J. Strength. Cond. Res. 2017, 33, 3314–3322. [Google Scholar] [CrossRef]
  74. Ramos, G.P.; Nakamura, F.Y.; Pereira, L.A.; Junior, W.B.; Mahseredjian, F.; Wilke, C.F.; Garcia, E.S.; Coimbra, C.C. Movement Patterns of a U-20 National Women’s Soccer Team during Competitive Matches: Influence of Playing Position and Performance in the First Half. Int. J. Sports Med. 2017, 38, 747–754. [Google Scholar] [CrossRef]
  75. Reina, M.; García-rubio, J.; Ibáñez, S.J. Activity Demands and Speed Profile of Young Female Basketball Players Using Ultra-Wide Band Technology. Int. J. Environ. Res. Public Health 2020, 17, 1477. [Google Scholar] [CrossRef]
  76. Reina, M.; García-Rubio, J.; Esteves, P.T.; Ibáñez, S.J. How External Load of Youth Basketball Players Varies According to Playing Position, Game Period and Playing Time. Int. J. Perform. Anal. Sport. 2020, 20, 917–930. [Google Scholar] [CrossRef]
  77. Reyneke, J.; Hansen, K.; Cronin, J.B.; Macadam, P. An Investigation into the Influence of Score Differential on the Physical Demands of International Women’s Rugby Sevens Match Play. Int. J. Perform. Anal. Sport. 2018, 18, 523–531. [Google Scholar] [CrossRef]
  78. Riboli, A.; Francini, L.; Rossi, E.; Caronti, A.; Boldrini, L.; Mazzoni, S. Top-Class Women’s Soccer Performance: Peak Demands and Distribution of the Match Activities Relative to Maximal Intensities during Official Matches. Biol. Sport. 2024, 41, 207–215. [Google Scholar] [CrossRef]
  79. Romero-Moraleda, B.; Nedergaard, N.J.; Morencos, E.; Casamichana, D.; Ramirez-Campillo, R.; Vanrenterghem, J. External and Internal Loads during the Competitive Season in Professional Female Soccer Players According to Their Playing Position: Differences between Training and Competition. Res. Sports Med. 2021, 29, 449–461. [Google Scholar] [CrossRef]
  80. Sánchez-Abselam, O.; González-Fernández, F.T.; Figueiredo, A.; Castillo-Rodríguez, A.; Onetti-Onetti, W. Effect of the Role, Playing Position and the Body Characteristics on Physical Performance in Female Soccer Players. Heliyon 2024, 10, e29240. [Google Scholar] [CrossRef]
  81. Sausaman, R.W.; Sams, M.L.; Mizuguchi, S.; DeWeese, B.H.; Stone, M.H. The Physical Demands of NCAA Division I Women’s College Soccer. Func. Morphol. Kinesiol. 2019, 4, 73. [Google Scholar] [CrossRef]
  82. Savolainen, E.H.J.; Vänttinen, T.; Peltonen, J.; Ihalainen, J.K.; Walker, S. Average Demands and Most Demanding Passages of National-Level Female Soccer Matches: Do Small- and Large-Sided Games Replicate Match Demands? Front. Sports Act. Living 2023, 5, 1236112. [Google Scholar] [CrossRef] [PubMed]
  83. Scott, D.; Haigh, J.; Lovell, R. Physical Characteristics and Match Performances in Women’s International versus Domestic-Level Football Players: A 2-Year, League-Wide Study. Sci. Med. Footb. 2020, 4, 211–215. [Google Scholar] [CrossRef]
  84. Sheppy, E.; Hills, S.P.; Russell, M.; Chambers, R.; Cunningham, D.J.; Shearer, D.; Heffernan, S.; Waldron, M.; McNarry, M.; Kilduff, L.P. Assessing the Whole-Match and Worst-Case Scenario Locomotor Demands of International Women’s Rugby Union Match-Play. J. Sci. Med. Sport. 2020, 23, 609–614. [Google Scholar] [CrossRef] [PubMed]
  85. Sparks, M. The Influence of Substitution Strategies on the Physical Match Performance of Elite Female Field Hockey Players. Int. J. Perform. Anal. Sport. 2024, 25, 162–173. [Google Scholar] [CrossRef]
  86. Suarez-Arrones, L.; Nuñez, F.J.; Portillo, J.; Mendez-Villanueva, A. Match Running Performance and Exercise Intensity in Elite Female Rugby Sevens. J. Strength. Cond. Res. 2012, 26, 1858–1862. [Google Scholar] [CrossRef]
  87. Suarez-Arrones, L.; Portillo, J.; Pareja-Blanco, F.; Sáez de Villareal, E.; Sánchez-Medina, L.; Munguía-Izquierdo, D. Match-play activity profile in elite women’s rugby. J. Strength. Cond. Res. 2014, 28, 452–458. [Google Scholar] [CrossRef] [PubMed]
  88. Sydney, M.G.; Wollin, M.; Chapman, D.W.; Ball, N.; Mara, J.K. Impaired Pre-Competition Wellbeing Measures Can Negatively Impact Running Performance in Developmental Youth Female Soccer Players. Biol. Sport. 2024, 41, 145–152. [Google Scholar] [CrossRef]
  89. Thornton, H.R.; Armstrong, C.R.; Gamble, T.; Rigby, A.; Johnston, R.D.; Duthie, G.M. Quantifying the Movement Characteristics of Australian Football League Women’s Competition. J. Strength. Cond. Res. 2022, 36, 3415–3421. [Google Scholar] [CrossRef]
  90. Vescovi, J.D.; Favero, T.G. Motion Characteristics of Women’s College Soccer Matches: Female Athletes in Motion (Faim) Study. Int. J. Sports Physiol. Perform. 2014, 9, 405–414. [Google Scholar] [CrossRef]
  91. Vescovi, J.D.; Devon, H.F. Motion Characteristics of Division I College Field Hockey: Female Athletes in Motion (FAiM) Study. Hum. Kinet. 2015, 10, 476–481. [Google Scholar] [CrossRef]
  92. Vescovi, J.D.; Goodale, T. Physical Demands of Women’s Rugby Sevens Matches: Female Athletes in Motion (FAiM) Study. Int. J. Sports Med. 2015, 36, 887–892. [Google Scholar] [CrossRef]
  93. Vescovi, J.D. Motion characteristics of youth women soccer matches: Female athletes in motion (FAiM) study. Int. J. Sports Med. 2014, 35, 110–117. [Google Scholar] [CrossRef]
  94. Vescovi, J.D. Locomotor, Heart-Rate, and Metabolic Power Characteristics of Youth Women’s Field Hockey: Female Athletes in Motion (FAiM) Study. Res. Q. Exerc. Sport. 2016, 87, 68–77. [Google Scholar] [CrossRef] [PubMed]
  95. Villaseca-Vicuña, R.; Perez-Contreras, J.; Zabaloy, S.; Merino-Muñoz, P.; Valenzuela, L.; Burboa, J.; Gonzalez-Jurado, J.A. Comparison of Match Load and Wellness between Friendly and World Cup Matches in Elite Female Soccer Players. Appl. Sci. 2023, 13, 1612. [Google Scholar] [CrossRef]
  96. Wells, A.J.; Hoffman, J.R.; Beyer, K.S.; Hoffman, M.W.; Jajtner, A.R.; Fukuda, D.H.; Stout, J.R. Regular- and Post-Season Comparisons of Playing Time and Measures of Running Performance in Ncaa Division i Women Soccer Players. Appl. Physiol. Nutr. Metab. 2015, 40, 907–917. [Google Scholar] [CrossRef] [PubMed]
  97. White, A.D.; MacFarlane, N.G. Contextual Effects on Activity Profiles of Domestic Field Hockey during Competition and Training. Hum. Mov. Sci. 2015, 40, 422–431. [Google Scholar] [CrossRef] [PubMed]
  98. Winther, A.K.; Baptista, I.; Pedersen, S.; Randers, M.B.; Johansen, D.; Krustrup, P.; Pettersen, S.A. Position Specific Physical Performance and Running Intensity Fluctuations in Elite Women’s Football. Scand. J. Med. Sci. Sports 2022, 32, 105–114. [Google Scholar] [CrossRef]
  99. Woodhouse, L.N.; Tallent, J.; Stephen, D.P.; Waldron, W. Elite International Female Rugby Union Physical Match Demands: A Five-Year Longitudinal Analysis by Position and Opposition Quality. J. Sci. Med. Sport. 2021, 24, 1173–1179. [Google Scholar] [CrossRef]
  100. Yousefian, F.; Huttemann, H.; Borjesson, M.; Ekblom, P.; Mohr, M.; Fransson, D. Physical Workload and Fatigue Pattern Characterization in a Top-Class Women’s Football National Team: A Case Study of the 2019 FIFAWomen’s World Cup. J. Sports Med. Phys. Fit. 2021, 61, 1081–1090. [Google Scholar] [CrossRef]
  101. Zapardiel, J.C.; Asín-Izquierdo, I.; Manchado, C.; Marcos-Jorquera, D.; Gilart-Iglesias, V.; Lozano, D. Competitive Profile Analysis According to Playing Positions of Female Handball Players during the European Championship 2020. Int. J. Perform. Anal. Sport. 2023, 24, 568–586. [Google Scholar] [CrossRef]
  102. McKay, A.K.A.; Stellingwerff, T.; Smith, E.S.; Martin, D.T.; Mujika, I.; Goosey-Tolfrey, V.L.; Sheppard, J.; Burke, L.M. Defining Training and Performance Caliber: A Participant Classification Framework. Int. J. Sports Physiol. Perform. 2021, 17, 317–331. [Google Scholar] [CrossRef]
  103. Manchado, C.; Martínez, J.T.; Pueo, B.; Tormo, J.M.C.; Vila, H.; Ferragut, C.; Sánchez, F.S.; Busquier, S.; Amat, S.; Ríos, L.J.C. High-Performance Handball Player’s Time-Motion Analysis by Playing Positions. Int. J. Environ. Res. Public Health 2020, 17, 6768. [Google Scholar] [CrossRef] [PubMed]
  104. Manchado, C.; Pueo, B.; Chirosa-Rios, L.J.; Tortosa-Martínez, J. Time–Motion Analysis by Playing Positions of Male Handball Players during the European Championship 2020. Int. J. Environ. Res. Public Health 2021, 18, 2787. [Google Scholar] [CrossRef] [PubMed]
  105. Bassek, M.; Raabe, D.; Memmert, D.; Rein, R. Analysis of Motion Characteristics and Metabolic Power in Elite Male Handball Players. J. Sports Sci. Med. 2023, 22, 310–316. [Google Scholar] [CrossRef] [PubMed]
  106. Font, R.; Karcher, C.; Reche, X.; Carmona, G.; Tremps, V.; Irurtia, A. Monitoring External Load in Elite Male Handball Players Depending on Playing Positions. Biol. Sport. 2021, 38, 475–481. [Google Scholar] [CrossRef]
  107. Font, R.; Karcher, C.; Loscos-Fàbregas, E.; Altarriba-Bartés, A.; Peña, J.; Vicens-Bordas, J.; Mesas, J.A.; Irurtia, A. The Effect of Training Schedule and Playing Positions on Training Loads and Game Demands in Professional Handball Players. Biol. Sport. 2023, 40, 857. [Google Scholar] [CrossRef]
  108. García, F.; Fernández, D.; Illa, J.; Reche, X.; Font, R.; Guitart, M.; Pla, F.; Tarragó, J.R.; Guerrero-Vázquez, J. Comparing the Most Demanding Scenarios of Official Matches across Five Different Professional Team Sports in the Same Club. Apunt. Sports Med. 2022, 57, 100390. [Google Scholar] [CrossRef]
  109. Vázquez-Guerrero, J.; Ayala, F.; Garcia, F.; Sampaio, J. The Most Demanding Scenarios of Play in Basketball Competition From Elite Under-18 Teams. Front. Psychol. 2020, 11, 552. [Google Scholar] [CrossRef]
  110. Vázquez-Guerrero, J.; Suarez-Arrones, L.; Gómez, D.C.; Rodas, G. Comparing External Total Load, Acceleration and Deceleration Outputs in Elite Basketball Players across Positions during Match Play. Kinesiology 2018, 50, 228–234. [Google Scholar] [CrossRef]
  111. Garcia, F.; Fernandez, D.; Illa, J.; Reche, X.; Vazquez-Guerrero, J. The Distribution of Match Physical Activities Relative to the Most Demanding Scenarios in Professional Basketball Players. J. Hum. Kinet. 2022, 83, 207–221. [Google Scholar] [CrossRef]
  112. Sosa, C.; Lorenzo, A.; Trapero, J.; Ribas, C.; Alonso, E.; Jimenez, S.L. Specific Absolute Velocity Thresholds during Male Basketball Games Using Local Positional System; Differences between Age Categories. Appl. Sci. 2021, 11, 4390. [Google Scholar] [CrossRef]
  113. Alonso, E.; Miranda, N.; Zhang, S.; Sosa, C.; Trapero, J.; Lorenzo, J.; Lorenzo, A. Peak Match Demands in Young Basketball Players: Approach and Applications. Int. J. Environ. Res. Public Health 2020, 17, 2256. [Google Scholar] [CrossRef] [PubMed]
  114. Alonso Pérez-Chao, E.; Ribas, C.; Gómez, M.A.; Porte, R.; Jiménez, S.L.; Lorenzo, A. Should We Train as We Compete? Games Might Be the Best Scenario to Reach the Internal Peak Demands in Professional Basketball Players. Med. Dello Sport. 2022, 75, 45–58. [Google Scholar] [CrossRef]
  115. Cheuvront, S.N.; Carter, R.; Deruisseau, K.C.; Moffatt, R.J. Running Performance Differences between Men and Women:An Update. Sports Med. 2005, 35, 1017–1024. [Google Scholar] [CrossRef] [PubMed]
  116. Hallam, L.C.; Amorim, F.T. Expanding the Gap: An Updated Look Into Sex Differences in Running Performance. Front. Physiol. 2021, 12, 804149. [Google Scholar] [CrossRef]
  117. Sunderland, C.D.; Edwards, P.L. Activity Profile and Between-Match Variation in Elite Male Field Hockey. J. Strength. Cond. Res. 2017, 31, 758–764. [Google Scholar] [CrossRef]
  118. Hausler, J.; Halaki, M.; Orr, R. Application of Global Positioning System and Microsensor Technology in Competitive Rugby League Match-Play: A Systematic Review and Meta-Analysis. Sports Med. 2016, 46, 559–588. [Google Scholar] [CrossRef]
  119. Haugen, T.; Seiler, S.; Sandbakk, Ø.; Tønnessen, E. The Training and Development of Elite Sprint Performance: An Integration of Scientific and Best Practice Literature. Sports Med.-Open 2019, 5, 44. [Google Scholar] [CrossRef]
  120. Gualtieri, A.; Rampinini, E.; Dello Iacono, A.; Beato, M. High-Speed Running and Sprinting in Professional Adult Soccer: Current Thresholds Definition, Match Demands and Training Strategies. A Systematic Review. Front. Sports Act. Living 2023, 5, 1116293. [Google Scholar] [CrossRef]
Applsci 15 05497 g001
Figure 1. PRISMA flow diagram of the search and selection process.
Figure 1. PRISMA flow diagram of the search and selection process.
Applsci 15 05497 g001
Applsci 15 05497 g002
Figure 2. Absolute and relative frequencies of studies published by year.
Figure 2. Absolute and relative frequencies of studies published by year.
Applsci 15 05497 g002
Applsci 15 05497 g003
Figure 3. Lower velocity, high-speed running, and sprint thresholds for female players in Australian football, basketball, and field hockey, expressed in km·h−1 [27,28,29,32,40,52,53,54,58,59,60,61,62,63,67,71,75,76,85,89,91,94,97].
Figure 3. Lower velocity, high-speed running, and sprint thresholds for female players in Australian football, basketball, and field hockey, expressed in km·h−1 [27,28,29,32,40,52,53,54,58,59,60,61,62,63,67,71,75,76,85,89,91,94,97].
Applsci 15 05497 g003
Applsci 15 05497 g004
Figure 4. Lower velocity, high-speed running, and sprint thresholds for female players in soccer, expressed in km·h−1 [20,21,22,23,33,34,36,37,39,46,48,49,51,55,64,66,69,70,73,74,78,79,80,81,82,83,88,90,93,95,96,98,100].
Figure 4. Lower velocity, high-speed running, and sprint thresholds for female players in soccer, expressed in km·h−1 [20,21,22,23,33,34,36,37,39,46,48,49,51,55,64,66,69,70,73,74,78,79,80,81,82,83,88,90,93,95,96,98,100].
Applsci 15 05497 g004
Applsci 15 05497 g005
Figure 5. Lower velocity, high-speed running, and sprint thresholds for female players in handball, Gaelic football, lacrosse, rugby league, rugby seven, and rugby union, expressed in km·h−1 [24,25,26,30,31,35,38,41,42,43,44,45,47,50,56,57,65,68,72,77,84,86,87,92,99,101].
Figure 5. Lower velocity, high-speed running, and sprint thresholds for female players in handball, Gaelic football, lacrosse, rugby league, rugby seven, and rugby union, expressed in km·h−1 [24,25,26,30,31,35,38,41,42,43,44,45,47,50,56,57,65,68,72,77,84,86,87,92,99,101].
Applsci 15 05497 g005
Table 1. Summary of studies accompanied by the year, sport, competition level, number of participants, matches recorded and number of GPS/LPS samples.
Table 1. Summary of studies accompanied by the year, sport, competition level, number of participants, matches recorded and number of GPS/LPS samples.
ReferenceYearSportCompetition LevelParticipantsMatchesGPS/LPS Samples
Baptista et al. [20]2022SoccerNational10860393
Baptista et al. [21]2024SoccerNational1001531615–1650
Bohner et al. [22]2015SoccerNational62N.A.
Bozzini et al. [23]2020SoccerNationalN.A.11N.A.
Bradley et al. [24]2020Rugby unionNational12914N.A.
Bradley et al. [25]2024Rugby unionNational5818178
Brosnan et al. [26]2024Rugby sevenInternational2433367
Clarke et al. [27]2018Australian footballNational267143
Clarke et al. [28]2019Australian footballNational5246N.A.
Clarke et al. [29]2021Australian footballNational4421211
Conte et al. [30]2021Rugby sevenInternational111273
Conte et al. [31]2022Rugby sevenInternational1012110
Curran et al. [32]2022Field hockeyInternational3334289
Datson et al. [33]2023SoccerNational1914133
de Oliveira Junior et al. [34]2021SoccerNational1813N.A.
Devine et al. [35]2021LacrosseNational1819N.A.
DeWitt et al. [36]2018SoccerNational18N.A.N.A.
Diaz-Serradilla et al. [37]2022SoccerNational1720N.A.
Doeven et al. [38]2019Rugby sevenInternational205N.A.
Fernandes et al. [39]2022SoccerNational1013N.A.
Gabbett [40]2010Field hockeyNational1432N.A.
García-Sánchez et al. [41]2024HandballNational2213153
García-Sánchez et al. [42]2024HandballNational2213153
García-Sánchez et al. [43]2024HandballNational2213153
García-Sánchez et al. [44]2024HandballNational2213153
García-Sánchez et al. [45]2024HandballNational2213153
Gonçalves et al. [46]2021SoccerNational22N.A.N.A.
Goodale et al. [47]2017Rugby sevenInternational205191
Griffin et al. [48]2021SoccerInternational1536182
Harkness-Armstrong et al. [49]2021SoccerNational20150431
Hauer et al. [50]2021LacrosseInternational104N.A.
Ishida et al. [51]2022SoccerNational1719273
Kapteijns et al. [52]2021Field hockeyInternational2026N.A.
Kim et al. [53]2018Field hockeyInternational3220N.A.
Leal-Cussaria et al. [54]2019Field hockeyNational18119
Mäkiniemi et al. [55]2023SoccerNational8568340
Malone et al. [56]2020Rugby sevenInternational2736250
Malone et al. [57]2024Gaelic footballNational3018145
McGuinness et al. [58]2019Field hockeyInternational2715308
McGuinness et al. [59]2019Field hockeyInternational3830N.A.
McGuinness et al. [60]2020Field hockeyInternational167N.A.
McGuinness et al. [61]2021Field hockeyWorld class2827395
McGuinness et al. [62]2022Field hockeyInternational2322360
McMahon et al. [63]2019Field hockeyInternational1912400
Mesa et al. [64]2022SoccerNational89N.A.
Misseldine et al. [65]2021Rugby sevenInternational12659
Mohr et al. [66]2022SoccerNational171N.A.
Morencos et al. [67]2019Field hockeyInternational16550
Newans et al. [68]2021Rugby leagueNational117430370
Panduro et al. [69]2022SoccerNational94N.A.108
Pedersen et al. [70]2022SoccerNational372N.A.
Portes et al. [71]2022BasketballTrained486133
Portillo et al. [72]2014Rugby sevenInternational208N.A.
Ramos et al. [73]2017SoccerInternational127N.A.
Ramos et al. [74]2019SoccerWorld class147N.A.
Reina et al. [75]2020BasketballTrained486144
Reina et al. [76]2020BasketballTrained486144
Reyneke et al. [77]2018Rugby sevenInternational1515N.A.
Riboli et al. [78]2024SoccerNational2838277
Romero-Moraleda et al. [79]2021SoccerNational18N.A.94
Sánchez-Abselam et al. [80]2024SoccerNational45N.A.82
Sausaman et al. [81]2019SoccerNational23N.A.375
Savolainen et al. [82]2023SoccerNational3729249
Scott et al. [83]2020SoccerNational220N.A.3268
Sheppy et al. [84]2020Rugby unionInternational298110
Sparks [85]2024Field hockeyInternational2619286
Suárez-Arrones et al. [86]2012Rugby sevenInternational125N.A.
Suárez-Arrones et al. [87]2014Rugby unionInternational818
Sydney et al. [88]2024SoccerNational1211165
Thornton et al. [89]2022Australian footballNational287140
Vescovi and Favero [90]2014SoccerNational171N.A.89
Vescovi and Frayne [91]2015Field hockeyNational11320N.A.
Vescovi and Goodale [92]2015Rugby sevenInternational68N.A.68
Vescovi [93]2014SoccerNational295N.A.
Vescovi [94]2016Field hockeyInternational444N.A.
Villaseca-Vicuña et al. [95]2023SoccerInternational106N.A.
Wells et al. [96]2015SoccerNational921N.A.
White et al. [97]2015Field hockeyNational108N.A.186
Winther et al. [98]2022SoccerNational5460393
Woodhouse et al. [99]2021Rugby unionInternational7853969
Yousefian et al. [100]2021SoccerInternational21747
Zapardiel et al. [101]2024HandballInternational23147N.A.
Notes: GPS = global positioning system; LPS = local positioning system; N.A. = not available.
Table 2. The study quality analysis (“STROBE” checklist).
Table 2. The study quality analysis (“STROBE” checklist).
ReferenceTitle and AbstractIntroductionMethodsResultsDiscussionOther InformationStrobe Points
12345678910111213141516171819202122
Baptista et al. [20]111111111011111111111121
Baptista et al. [21]111111111011111111111121
Bohner et al. [22]111111110011111111111019
Bozzini et al. [23]111111110011111111111019
Bradley et al. [24]111111110011111111111120
Bradley et al. [25]111111110011111111111120
Brosnan et al. [26]111111111011111111111121
Clarke et al. [27]111111110011111111111120
Clarke et al. [28]111111111011111111111020
Clarke et al. [29]111111110011111111111120
Conte et al. [30]111111111011111111111121
Conte et al. [31]111111111011111111111020
Curran et al. [32]111111111011111111111121
Datson et al. [33]111111111011111111111121
de Oliveira Junior et al. [34]111111111011111111111121
Devine et al. [35]111111111011111111111020
DeWitt et al. [36]111111111011111111111121
Diaz-Serradilla et al. [37]111111111011111111111121
Doeven et al. [38]111111111011111111111020
Fernandes et al. [39]111111111111111111111122
Gabbett [40]111111111011111111000017
García-Sánchez et al. [41]111111111011111111111020
García-Sánchez et al. [42]111111111011111111111020
García-Sánchez et al. [43]111111111011111111111020
García-Sánchez et al. [44]111111111011111111111020
García-Sánchez et al. [45]111111111011111111111020
Gonçalves et al. [46]111111111011111111111121
Goodale et al. [47]111111111011111111010018
Griffin et al. [48]111111111011111111111020
Harkness-Armstrong et al. [49]111111111011111111111020
Hauer et al. [50]111111111011111111111121
Ishida et al. [51]111111111111111111111021
Kapteijns et al. [52]111111111011111111111020
Kim et al. [53]111111111011111111010119
Leal-Cussaria et al. [54]111111111011111111010018
Mäkiniemi et al. [55]111111111011111111111020
Malone et al. [56]111111111011111111111020
Malone et al. [57]111111111011111111111121
McGuinness et al. [58]111111111011111111111020
McGuinness et al. [59]111111111011111111111020
McGuinness et al. [60]111111111011111111111121
McGuinness et al. [61]111111111011111111111121
McGuinness et al. [62]111111111011111111111020
McMahon et al. [63]111111111011111111010018
Mesa et al. [64]111111111011111111111020
Misseldine et al. [65]111111111011111111111020
Mohr et al. [66]111111111111111111111122
Morencos et al. [67]111111111011111111111020
Newans et al. [68]111111111011111111111121
Panduro et al. [69]111111111011111111111121
Pedersen et al. [70]111111111011111111111121
Portes et al. [71]111111111011111111111121
Portillo et al. [72]111111111011111111111020
Ramos et al. [73]111111111011111111010018
Ramos et al. [74]111111111011111111010018
Reina et al. [75]111111111011111111111121
Reina et al. [76]111111111011111111010119
Reyneke et al. [77]111111111011111111111020
Riboli et al. [78]111111111011111111111020
Romero-Moraleda et al. [79]111111111011111111111020
Sánchez-Abselam et al. [80]111111111011111111111121
Sausaman et al. [81]111111111011111111111121
Savolainen et al. [82]111111111011111111111121
Scott et al. [83]111111111011111111010018
Sheppy et al. [84]111111111011111111111020
Sparks [85]111111111011111111111020
Suárez-Arrones et al. [86]111111111011111111010018
Suárez-Arrones et al. [87]111111111011111111111020
Sydney et al. [88]111111111011111111111020
Thornton et al. [89]111111111011111111010018
Vescovi and Favero [90]111111111011111111111020
Vescovi and Frayne [91]111111111011111111111020
Vescovi and Goodale [92]111111111011111111111020
Vescovi [93]111111111011111111111121
Vescovi [94]111111111011111111010119
Villaseca-Vicuña et al. [95]111111111111111111111122
Wells et al. [96]111111111011111111111020
White et al. [97]111111111011111111111020
Winther et al. [98]111111111011111111111121
Woodhouse et al. [99]111111111011111111111121
Yousefian et al. [100]111111111011111111111121
Zapardiel et al. [101]111111111011111111111121
Table 3. Descriptive data of high-speed running (HSR) and sprint thresholds according to sport and expressed in km·h−1.
Table 3. Descriptive data of high-speed running (HSR) and sprint thresholds according to sport and expressed in km·h−1.
Sport HSR Sprint
NMean
(95% CI)		SDModeMinMaxNMean
(95% CI)		SDModeMinMax
Australian football414.40
(14.40–14.40)		0.0014.4014.4014.40422.50
(14.54–30.45)		5.0020.0020.0030.00
Basketball314.26
(13.69–14.84)		0.2314.4014.0014.40121.00
(N.A.–N.A.)		N.A.21.0021.0021.00
Field hockey1616.08
(15.19–16.97)		1.6716.0011.1018.00921.05
(19.49–22.62)		2.0420.0019.0025.00
Soccer3315.80
(15.20–16.90)		1.6915.0012.5019.002820.99
(20.30–21.70)		1.8120.0018.0025.00
Gaelic football115.84
(N.A.–N.A.)		N.A.15.8415.8415.840N.A.N.A.N.A.N.A.N.A.
Handball617.64
(16.71–18.56)		0.8818.0015.8418.00221.12
(19.59–22.64)		0.1721.0021.0021.24
Lacrosse215.00
(15.00–15.00)		0.0015.0015.0015.00219.50
(13.15–25.85)		0.7119.0019.0020.00
Rugby league112.00
(N.A.–N.A.)		N.A.12.0012.0012.000N.A.N.A.N.A.N.A.N.A.
Rugby seven1116.58
(14.72–18.44)		2.7618.0012.5021.601021.19
(19.51–22.87)		2.3520.0019.8027.00
Rugby union516.84
(13.42–20.27)		2.7518.0012.6019.80318.66
(10.68–26.65)		3.2115.0015.0021.00
Total8215.96
(15.54–16.39)		1.9418.0011.1021.605920.97
(20.38–21.57)		2.2620.0015.0030.00
Notes: HSR = high-speed running; N = number of studies; SD = standard deviation; Min = minimum; Max = maximum; CI = confidence interval; N.A. = not available.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Nieto-Acevedo, R.; de la Rubia, A.; Alonso-Pérez-Chao, E.; Marquina Nieto, M.; García-Sánchez, C. High-Speed Running and Sprinting Thresholds in Elite Female Team Sports: A Systematic Review. Appl. Sci. 2025, 15, 5497. https://doi.org/10.3390/app15105497

AMA Style

Nieto-Acevedo R, de la Rubia A, Alonso-Pérez-Chao E, Marquina Nieto M, García-Sánchez C. High-Speed Running and Sprinting Thresholds in Elite Female Team Sports: A Systematic Review. Applied Sciences. 2025; 15(10):5497. https://doi.org/10.3390/app15105497

Chicago/Turabian Style

Nieto-Acevedo, Raúl, Alfonso de la Rubia, Enrique Alonso-Pérez-Chao, Moisés Marquina Nieto, and Carlos García-Sánchez. 2025. "High-Speed Running and Sprinting Thresholds in Elite Female Team Sports: A Systematic Review" Applied Sciences 15, no. 10: 5497. https://doi.org/10.3390/app15105497

APA Style

Nieto-Acevedo, R., de la Rubia, A., Alonso-Pérez-Chao, E., Marquina Nieto, M., & García-Sánchez, C. (2025). High-Speed Running and Sprinting Thresholds in Elite Female Team Sports: A Systematic Review. Applied Sciences, 15(10), 5497. https://doi.org/10.3390/app15105497

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop