You are currently viewing a new version of our website. To view the old version click .
MDPIMDPI
Search all articles
Journal of Functional Morphology and Kinesiology
Download PDF
  • Review
  • Open Access

16 June 2025

Kinetic Variables as Indicators of Lower Limb Indirect Injury Risk in Professional Soccer: A Systematic Review

,
,
,
,
,
,
,
,
and
1
Escuela de Doctorado de La Universidad de Las Palmas de Gran Canaria (EDULPGC), 35016 Las Palmas, Spain
2
Escuela de Ciencias del Deporte y Actividad Física, Facultad de Salud, Universidad Santo Tomas, Santiago 8370003, Chile
3
Departamento de Ciencias Clínicas, Universidad de Las Palmas de Gran Canaria, 35016 Las Palmas, Spain
4
Departamento de Educação Física, Instituto de Ciências da Vida, Universidade Federal de Juiz de Fora, Governador Valadares 35010-180, Brazil
J. Funct. Morphol. Kinesiol.2025, 10(2), 228;https://doi.org/10.3390/jfmk10020228
This article belongs to the Special Issue Biomechanical Analysis in Physical Activity and Sports—2nd Edition
Version Notes
Order Reprints
Review Reports

Abstract

Background: The high demands of professional soccer predispose players to musculoskeletal injuries. The primary challenge for identifying potential risk factors lies in determining the appropriate assessment methods and indicators to consider. Kinetic variables have been identified as potential indicators of injury risk. Objectives: To conduct a systematic review of the literature analyzing the relationship between kinetic variables and the risk of indirect musculoskeletal injuries of the lower limb in professional soccer players. Methods: A search was conducted on Web of Science, PubMed, and Scopus following the PRISMA guidelines. The search included articles that link kinetic variables assessed through dynamometry to indirect lower limb injuries. Sample characteristics, assessments, injury follow-ups, and statistical results were extracted for qualitative synthesis. Results: A total of 1096 studies were initially identified, of which 380 duplicates were removed. After screening 716 articles by title and abstract, 631 were excluded. Subsequently, 85 full-text articles were examined, resulting in 11 studies being included. Of the included articles, 10 used isokinetic dynamometry and the Nordic hamstring curl test to assess lower limb strength. Conclusions: The results of this review indicate that kinetic variables, particularly isokinetic strength measures at different angular velocities, are consistently associated with indirect musculoskeletal injury risk in professional soccer players. The most relevant indicators include eccentric hamstring force and concentric quadriceps torque, which help identify strength deficits and muscular disequilibrium. Monitoring these variables through validated assessments enables the development of targeted prevention strategies. Additionally, injury risk assessment should integrate kinetic data with contextual indicators such as well-being, fatigue, and training load.

1. Introduction

Soccer is an intermittent sport that requires physical and technical efforts at variable intensities over the course of matches. Explosive actions require an optimal physical condition to face competitive demands [1,2,3]. However, the high demands of soccer also increase injury risk, which is influenced both by external factors (number of matches, climate, type of competition) and internal factors (physical condition, health, and training load) [4,5,6]. An injury is defined as any physical trauma sustained by a player as a result of a soccer match or training session, regardless of whether the player requires medical care or must interrupt his training regime [7]. The absence of players in competitions due to injury not only affects team performance [8] but also the financial resources of clubs [9,10]; therefore, injury prevention becomes key in sports environments.
Muscle injuries can be classified as direct and indirect. The first is caused by external impact—e.g., contusions and lacerations—while the latter affects the musculoskeletal system either functionally or structurally [11]. Some functional injuries result from overexertion—e.g., type 1A muscle fatigue or type 1B delayed onset muscle soreness—whereas others are associated with neuromuscular dysfunction that may be caused by spinal disorders or abnormalities (type 2A) or muscle-specific conditions (type 2B). Conversely, structural injuries involve damage to tissue and can be categorized into partial tears (type 3A and 3B) or full tears and tendon avulsions (type 4), which can greatly impair muscle function. This classification aids in the diagnosis, treatment, and prevention of sports injuries [12,13].
Several authors have analyzed the epidemiology of sports injuries in different leagues, genders, age groups, and league divisions [4,8,14,15]. In professional soccer, muscle injuries have been found to account for one-third of injuries in high-performance athletes; of these, 92% are indirect injuries that affect the main four muscle groups of the lower limbs, these being the hamstrings (37%), adductors (23%), quadriceps (19%), and calf muscles (13%) [16]. In addition, Waldén et al. [17] found that 14% of injuries during a season in a professional soccer team occurred in the inguinal and hip areas, and 63% were related to the adductor muscles. A higher incidence of muscle injuries has also been reported during periods of increased match frequency (or congested schedules) [4,18]. One of the main challenges in identifying risk factors for injuries is selecting appropriate tests and indicators for assessment [19]. The evidence suggests that some factors—both modifiable and non-modifiable—can predispose athletes to injuries [20]. Some of the most important indicators include low levels of strength (weakness), fatigue, and asymmetries, which have been widely researched in relation to the incidence of musculoskeletal injuries [21,22,23]. However, there is no consensus on which variables are the most representative for identifying injury risk and how they should be interpreted in practice.
In this context, Pedley et al. [24] conducted a review that revealed that 79% of the studies using drop jump tests identified associations with future injuries, whereas only 8% of the studies with countermovement jump (CMJ) showed a similar relationship. Meanwhile, 57% of unilateral assessments were associated with injury risk, whereas performance-based tests (jump height or distance) showed a weaker association with 30% of cases. Furthermore, assessments that analyzed kinetic and kinematic variables presented a relationship with injuries in 89% of studies [24]. These findings underscore the importance of including advanced biomechanical measures for a more accurate assessment of injury risk.
A key factor for injury prevention is the presence of muscular asymmetries, especially those derived from previous injuries. It has been demonstrated that asymmetries ≥15% in the hamstrings eccentric force and ≥10% in the quadriceps concentric torque significantly increase the risk of muscle injury [25,26]. In addition, kinetic variables during the landing phase of drop jump tests more accurately reflect the injury mechanism, highlighting the importance of assessing not only the magnitude but also the direction and evolution of asymmetries throughout the rehabilitation process [27].
Strength measures have been established as a key tool for injury prevention and sports readaptation [28,29]. However, the selection of the method for calculating the asymmetry remains a point of debate, as different formulas can yield variable results [27]. Recent research suggests that dominant and non-dominant limbs may exhibit different asymmetry levels in jump tests, emphasizing the need for further exploration of their impact on injury risk in sports [30,31]. In this sense, using more standardized methodologies and integrated assessment tools will enhance the identification of players at risk while supporting the development of more effective preventive strategies.
Although kinetic variables are frequently used in performance assessments, their utility in predicting non-contact injuries, particularly in professional soccer, remains unclear. This knowledge gap highlights the need to better understand their role in injury surveillance and prevention.
Given the relevance of kinetic variables in injury prevention and performance monitoring, this systematic review aims to analyze the relationship between kinetic variables and the risk of non-contact musculoskeletal injuries of the lower limb in professional soccer players. By synthesizing the available evidence, this study seeks to identify trends, methodological limitations, and knowledge gaps that may inform injury prevention strategies in this specific context. This review specifically aimed to systematically examine the role of kinetic variables in predicting non-contact lower limb injuries in professional soccer.

2. Materials and Methods

The study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [32]. The review protocol was registered in International Prospective Register of Systematic Reviews (PROSPERO) website on 20 May 2024 (ID 538044).

2.1. Eligibility and Exclusion Criteria

The articles included in the review were selected following the PICO (Population, Intervention, Comparison, and Outcomes) methodology. The inclusion and exclusion criteria are detailed in Table 1.
Table 1. Criteria for inclusion and exclusion.

2.2. Electronic Data Search

The systematic search was conducted in the following databases: Web of Science, PubMed and Scopus, including articles published between 1 January 2010 and 14 November 2023. The period selected allowed the analysis to focus on more recent and potentially relevant evidence, primarily due to the accelerated development of accessibility to high-quality technology in the context of professional soccer. To access these databases, the institutional credentials of Universidad de Las Palmas de Gran Canaria, Spain, were used.
The search strategy was a combination of controlled vocabulary (MeSH), specific free-text terms, intersection Boolean operators (AND), and union (OR) and truncation (*) Boolean operators. The search equation for WOS and Scopus was as follows: (“soccer” OR “football*”) AND (“Kinetic*” OR “strength*” OR “force*” OR “power*” OR “rate of force development” OR “imbalance*” OR “asymmetr*”) AND ((“Ruptur*” OR “Strain*” OR “tear*” OR “fatigue”) AND (“Lower Extremit*” OR “Lower Limb*” OR “Quadricep*” OR “Hamstring*” OR “adductor*” OR “tendon”)) AND (“Risk Factor*” OR “relation*” OR “associat*” OR “Correlation*”). For PubMed, the following search equation was used: (“soccer” OR “football*”) AND (“Kinetic*” OR “strength*” OR “force*” OR “power*” OR “rate of force development” OR “imbalance*” OR “asymmetr*”) AND ((“Ruptur*” OR “Strain*” OR “tear*” OR “fatigue”) AND (“Lower Extremity”[Mesh] OR “Lower Extremit*” OR “Lower Limb*” OR “Quadricep*” OR “Hamstring*” OR “adductor*” OR “tendon”)) AND (“Risk Factors”[Mesh] OR “Risk Factor*” OR “relation*” OR “associat*” OR “Correlation*”)

2.3. Study Selection

To process the results, the guidelines proposed by Rico-González et al. [34] were followed. A CSV was downloaded from each database to then copy the data onto an Excel spreadsheet. A coding system was employed to select the articles, in which 1 = included, 2 = duplicated, and 3 = excluded. The elimination of duplicated articles and initial coding was conducted separately by two reviewers (J.P.-C. and F.I.-R.), who analyzed titles and abstracts. Once the process was completed, the results were compared, and studies were selected for the following stage.

2.4. Data Collection Process

Three reviewers (J.P.-C., F.I.-R., and P.M.-M.) independently recorded the characteristics of the studies in an Excel spreadsheet, including details about samples, follow-up of musculoskeletal injuries, measured kinetic variables, assessment instruments, and results.

2.5. Risk of Bias

Two reviewers (F.I.-R. and P.M.-M.) independently assessed the risk of bias in the studies; when there were discrepancies, a third reviewer (J.P.-C) was consulted and resolved the disagreements. For this purpose, the Downs and Black checklist [35] was employed, of which only item 27 (power) was modified by assigning 1 point if a power analysis had been conducted and 0 points if this had not been conducted or was deemed inappropriate. Based on their scores, the studies were classified into the following categories [36]: excellent (26–28), good (20–25), fair (15–19), and poor (14 or below). To measure the level of agreement among the reviewers, Kohen’s kappa was analyzed, considering the categories of agreement (>0.81) almost perfect; (0.61 to 0.80), substantial; (0.41 to 0.60) moderate; (0.21 to 0.40) regular, (0.01 to 0.20) slight, and (<0.00) poor [37].

3. Results

3.1. Search Results

The initial search yielded 1096 results, of which 380 duplicated items were removed, with a total of 716 potentially relevant articles. During the initial coding, 631 articles were excluded upon the analysis of their title and abstracts. The full text of the 85 remaining articles was inspected based on the inclusion and exclusion criteria. Eleven articles were included in the review [25,26,38,39,40,41,42,43,44,45,46]. The process is presented in Figure 1.
Figure 1. Flow diagram of item selection.

3.2. Characteristics of the Studies

The characteristics of the population and indirect injury follow-up are summarized in Table 2 and Table 3, respectively. Of the 11 studies included, 10 have a prospective cohort design, and only 1 is retrospective [40]. All the studies included male soccer players, as no studies with a female population were found. Considering all the articles included, 2403 individuals were analyzed, of which 517 presented indirect injuries of the lower limb, and 1886 had no injuries. All the studies recorded indirect injuries to the hamstrings. Regarding other affected muscles, Fousekis et al. [25] and Liporaci et al. [26] reported on quadriceps on rectus femoris and hip adductor muscle injuries, respectively. The minimum follow-up time was one season [25,26,38,39,40,41,46], but some studies covered two [43,44] and others four [42,45].
Table 2. Characteristics of population for the studies selected.
Table 3. Characteristics of injury follow-up for selected studies.

3.3. Results of Risk of Bias

Regarding the methodology quality assessment conducted using the Downs and Black checklist for the included studies, reviewer agreement was substantial (Cohen’s Kappa = 0.673). Two articles obtained the score required to be classified as “good” [25,42], while all the other studies were categorized as “fair”, as shown in Table 4. Items 8, 13, 14, 15, 23, and 24 showed the most notable methodological shortcomings, mainly attributable to the observational design of the included studies and to a notable absence of experimental studies.
Table 4. Methodology quality assessment. Modified Downs and Black checklist [34].

3.4. Strength Tests

Ten of the articles included used isokinetic dynamometry to assess lower limb strength [25,26,38,39,40,41,43,44,45,46], and two employed the Nordic hamstring curl test [42,44]. Detailed information about these tests—e.g., analyzed variables and outcomes—is presented in Table 5 and Table 6 for studies that included isokinetic dynamometry and the Nordic hamstring curl, respectively.
Table 5. Glossary.
Table 6. Strength evaluation by isokinetic dynamometry.

3.4.1. Strength Assessment Using Isokinetic Dynamometer

The isokinetic evaluation protocols involved both concentric and eccentric testing for knee flexors but only concentric protocols for knee extensors. Repetition angular velocities ranged from 60°/s to 300°/s for concentric contractions of both knee flexors and extensors. For eccentric knee flexor contractions, velocities ranged from 30°/s to 180°/s. While peak isokinetic torque was the primary outcome variable, its behavior was analyzed across multiple dimensions. A glossary detailing these dimensions is provided in Table 5.

3.4.2. Strength Assessment Using the Nordic Hamstring Curl Test

Two distinct evaluation protocols were identified for the Nordic hamstring flexion test: eccentric and isometric. The eccentric protocol, consistently applied across both studies [42,44], required participants to kneel on a padded board and descend in a controlled manner, striving to maintain a neutral trunk and hip position. Conversely, the isometric protocol utilized the same kneeling position with the knees extended, where participants performed a maximal isometric contraction for 5 s [42].
The primary findings from these studies focused on eccentric force production and eccentric torque [42]. Specifically, an absolute eccentric force below 337 N and a relative eccentric force below 4.35 N/kg were associated with relative risks of 4.4 and 2.5, respectively, for future injury. Similarly, an eccentric torque threshold of 145 N·m and a relative torque threshold of 1.86 N·m corresponded to relative risks of 3.6 and 2.9, respectively. Isometric strength variables [42] and maximum strength imbalance [44] between limbs did not show significant results, as shown in Table 6 and Table 7.
Table 7. Strength evaluation by Nordic hamstring curl.

4. Discussion

Optimal physical fitness is key to facing the demands of professional soccer, as it also plays a crucial role in injury risk prevention, especially muscle injuries, which account for one-third of injuries in this sport [16]. Internal factors such as strength, fatigue, and asymmetries, together with kinetic variables associated with neuromuscular fatigue, have been proposed as risk indicators, allowing for the determination of thresholds that link physical performance to injury probability [52,53]. The purpose of this study was to conduct a systematic review of the literature to analyze the relationship between kinetic variables and the risk of indirect musculoskeletal injuries of the lower limb in professional soccer.

4.1. Strength Assessment Using Isokinetic Dynamometer

The results show a wide range of torque variables (type of contraction and execution speed) generated by the knee flexor–extensor musculature as possible risk factors. According to van Dyk et al. [45], a higher risk rate for tear injuries is associated with a deficit in the maximum torque production of the quadriceps during concentric movements at 60°/s, normalized by body mass (N·m/kg) (OR = 1.41; IC 95% 1.03–1.92; p = 0.03), as well as a deficit in the maximum eccentric torque production of the hamstring at 60°/s, normalized by body mass (N·m/kg) (OR = 1.37; IC 95% 1.01–1.85; p = 0.04). Nevertheless, both variables have lower probabilities as predictors of hamstring tears. Another study using a multiple linear regression model discovered that the concentric torque at 240°/s of the dominant leg’s hamstrings influenced the hamstring injury rate (β = 0.01 ± 0.01) [46]. However, the clinical magnitude is considerably small compared to other factors in the model, such as age, hamstring injury history, and the results of the Nordic hamstring curl test.
An interesting analysis involves determining cut-off points to classify dichotomous variables as risk factors. When analyzing the concentric torque of the quadriceps at 300°/s, van Dyk et al. [44] found that an increase of one standard deviation above the mean in the maximum concentric torque of the quadriceps, normalized by body mass, increased the risk of hamstring tears (HR = 2.06; 95% CI 1.21–3.51), with a small to moderate prevalence [54]. In turn, Lee et al. [41] discovered that values below 2.4 N·m/kg for the hamstring eccentric torque peak at 30°/s indicate a large effect size for the risk of tears (Adjusted OR = 5.59; IC 95% 2.20–12.92; p < 0.001). Finally, van Dyk et al. [43] studied the rate of torque development (RTD) at 30 ms, 50 ms, and 100 ms without significant findings. These results are likely influenced by the lower reliability of early RTD (0 to 100 ms) compared to the late RTD of the knee extensors (150 to 250 ms) [55]; however, the authors did not report the reliability of the early RTD of the knee flexor–extensors. Therefore, early RTD may preliminarily be an appropriate risk factor for hamstring tears; nevertheless, further research is required on late RTD, as this has demonstrated more reliability between sessions.

4.2. Ratios and Asymmetries Derived from Isokinetic Strength Assessments

Using ratios in the assessment of isokinetic strength is a common practice. Although the hamstring/quadriceps (H:Q) ratio is the most popular, the hamstring/hamstring (H:H) ratio and quadriceps/quadriceps (Q:Q) ratio were also employed. To calculate them, different torque combinations are used, considering contraction type, execution speed and limb dominance. The most critical findings are related to concentric H:Q at 60°/s as a possible risk factor for hamstrings. Lee et al. [41] found that the absolute value of concentric H:Q at 60°/s could be considered a protective factor for hamstring tears; however, when that same variable is conditioned to a risk threshold, if the concentric H:Q at 60°/s is under 50.5%, it then becomes a risk factor for this phenomenon (OR = 3.14; 95% CI 1.37 to 7.22; p = 0.01). In addition, Liporaci et al. [26] discovered that the concentric H:Q at 60°/s increases the risk rate for indirect injury (OR = 6.72; 95% CI 1.32–34.31; p = 0.02). This ratio seems to be the most promising one, as it is a strength-related risk factor that increases the likelihood of hamstring tears.
The threshold values used to define outcomes not only influence the results but are often arbitrarily chosen, representing a potential limitation of the analysis. Regarding this, Dauty et al. [38] studied the influence of setting three thresholds for diverse H:Q and H:H torque ratios. However, no significant results were obtained for any of the selected thresholds. Therefore, conducting future studies to develop objective criteria for determining risk thresholds for isokinetic strength is a priority.
With respect to the results, the strength disequilibrium of the hamstrings at 30°/s is associated with higher injury risk rates (OR = 1.05; IC 95% 1.00–1.10; p = 0.03); nevertheless, the magnitude of this association is small. Fousekis et al. [25] emphasize that asymmetries in hamstring eccentric strength, differences in leg length, and previous injury records are key factors for predicting the risk of muscle strain in hamstrings and quadriceps. In particular, asymmetries ≥ 15% between the eccentric strength at 60 or 180°/s of both legs’ hamstrings are associated with a significantly higher risk of tears (OR = 3.88; CI 95% 1.13–12.23); it is important to note that this achievement is supported by the good methodological quality of the study. In turn, Liporaci et al. [26] found that asymmetries ≥ 10% in the concentric torque peak at 60°/s of the quadriceps (OR = 7.49; CI 95% 1.51 to 37.26) and hamstrings (OR = 46.94; CI 95% 4.16–530) can increase the risk of hamstring tears. However, the wide confidence interval of the hamstring eccentric torque peak should be interpreted with caution.
It appears that both force asymmetry thresholds could be used as a criterion to indicate hamstring injury risk. However, based on methodological quality and confidence intervals on the magnitude of the findings, the asymmetry threshold ≥ 15% for excentric force at 60 or 180°/s of the hamstrings between limbs seems to be the most appropriate as a risk factor. Furthermore, the angular velocity of 180°/s may be more appropriate based on the speed of technical kicking actions during a soccer match [56]. Therefore, maintaining a balanced force generation between limbs seems to be essential, both in the knee extensor muscles.

4.3. Strength Assessment Using the Nordic Hamstring Curl Test

Hamstring strength disequilibrium, whether due to bilateral asymmetry or a disequilibrium relationship with quadriceps strength, is a modifiable risk factor associated with muscle tears in this area [57]. Hamstring injuries, common in sports like soccer [58], often occur due to excessive strain during eccentric contraction, with eccentric strength playing a crucial role in the prevention of these injuries [16]. Factors such as previous contraction speed, elongation speed, and activation time determine the severity of the injury [59]. Hamstring injuries are classified into two types according to their mechanism: those provoked by stretching, associated with movements such as kicks that combine hip flexion and knee extension, and those caused by sprints, which occur during high-speed races. While the former involves longer muscle lengths, the latter occurs within the muscle’s functional range [57].
In line with our results, Timmins et al. [42] underscore the importance of assessing knee flexor eccentric strength and torque, as they are key indicators of injuries from hamstring strains in professional soccer players. The authors identified critical thresholds based on the optimal contraction range. Specifically, the values of absolute 337 N and relative 4.35 N/kg eccentric force were determined, as well as those of absolute 145 N·m and relative 1.86 N·m/kg eccentric torque; the values were associated with higher injury risk. On the other hand, the absence of beeches by van Dyk et al. [44] could be partly explained by the quality of the methodology and the variables selected for the study since they did not consider in their analysis a displacement component, which is a crucial phenomenon in the evaluation of dynamic force. These findings emphasize the need for specific monitoring and strengthening strategies to improve the eccentric capacity of the hamstring muscles, using standardized protocols and precise tools to identify athletes at higher risk of injury. They also highlight the importance of including these strategies in preventive programs under professional supervision [60].
The relationship between hamstring strength disequilibrium and the risk of muscle tear injury remains unclear. Therefore, there is a need to explore the theoretical aspects of this phenomenon and adopt a multifactorial perspective that goes beyond strength as the sole factor [59]. Factors such as fatigue and exposure, both preseason and throughout the season, are decisive in increasing injury risk; this risk progressively rises with each match half and is reflected in the occurrence of overuse injuries [12,16]. Therefore, implementing continuous load monitoring is essential to better understand the factors that influence injury occurrence and to design more effective preventive strategies.

4.4. Limitations of This Study

This review has several limitations. Firstly, all included studies exclusively involved male professional soccer players, which limits the generalizability of our findings to female professional athletes. Secondly, the focus on high-level professional players means these results may not be applicable to amateur soccer players or those in sports training programs. Lastly, by concentrating on kinetic variables, this review did not consider other intrinsic factors as indicators of lower-body indirect injury risk.
Regarding the quality of the primary studies, we observed substantial methodological heterogeneity. This was particularly evident in the selection and processing of kinetic variables for both isokinetic strength assessments and the Nordic hamstring curl test. Although isokinetic evaluation protocols for knee flexor–extensors were largely consistent (e.g., contraction type and execution speed), the variables chosen for analysis varied significantly. A great diversity is observed in the ratios analyzed (based on quadriceps and hamstring strength), along with differing cut-off points for asymmetry and ratio values used to determine injury risk and even the dichotomization between dominant and non-dominant legs. Similarly, protocols and variables for the Nordic hamstring curl test differed among studies.
An important limitation concerns the use of arbitrary thresholds, such as ≥10% asymmetry or an H:Q ratio < 50%, which have not been validated through diagnostic accuracy analyses. It is recommended that future research examine these cut-off points using the receiver operating characteristic (ROC) curves and metrics such as sensitivity, specificity, and the area under the curve (AUC) in order to establish more robust and generalizable criteria. Furthermore, a key limitation identified in the primary studies is the scarcity of experimental designs, an issue that will be further addressed in the projections section.

4.5. Projections

Despite prevalent methodological limitations within the selected studies, this largely stems from a scarcity of experimental research in professional soccer. Implementing such designs presents considerable challenges due to potential risks for players and clubs. Consequently, prospective studies appear to be the most suitable approach for identifying indirect injury risk factors in this population. However, future research should explore the feasibility of experimental designs with amateur soccer players to more conclusively determine the relevance of clinical variables and the risk of indirect injuries.
Future research should consider other factors that may increase the risk of injury, such as age, previous injuries, and aerobic performance, among others [28,53]. For these multivariate analyses, such as machine learning algorithms (logistic regression, algorithms based on trees or neural networks) could help researchers or teams to identify variables and models that predict the probability of injury and the variables that are most important for this task [61]. Also, it should address other relevant variables, such as the rate of force development, the rate of torque development, and the integral or area under the force curve, as these metrics can provide a more comprehensive view of muscle performance under different conditions.
Although all the articles included only represented the male population, one study in the female population was identified that did not meet the selection criteria, due to the lack of formal statistical analysis between kinetic variables and injury risk [62]. Due to the growth of women’s soccer and the increased availability of resources, future studies should be conducted on a female cohort.
Another interesting point is the speed of execution of the isokinetic tests; although most of the beeches were at low speed (60°/s), this corresponds to a considerably lower speed than that achieved in technical actions such as ball kicking, where angular velocities of up to 1625°/s can be reached [56]. Therefore, it would be interesting for future studies to develop protocols with a higher contraction velocity that could have a greater ecological validity. Additionally, it would be necessary to include ecological tests involving different types of jumps performed on force platforms, as this would allow for the assessment of strength in more representative real-world performance settings. It is recommended to apply unidimensional analysis to the force’s curves using statistical parametric mapping, which could facilitate the identification of specific patterns in the dynamics of force production and help optimize training approaches [63] should also be considered relevant for a greater understanding of force patterns and their relation to injury risk.

4.6. Practical Applications

Implementing regular assessments at the beginning and throughout the season is key to designing comprehensive prevention and rehabilitation programs. However, conducting these analyses with caution and under the supervision of specialized professionals is fundamental to ensure proper data interpretation and the effective application of prevention strategies that benefit teams.
Permanent monitoring is essential, as well as effective communication between the interdisciplinary team, to anticipate and promptly manage injuries. Implementing these approaches will improve injury prevention and performance in professional soccer. Specifically, the maximum values for quadriceps concentric torque and hamstring eccentric torque at 60°/s, normalized by body mass, have been shown to be key predictors of hamstring tear risk. In addition, a value of less than 50.5% and greater than 64% of the H:Q concentric ratio and asymmetry ≥ 15% hamstring eccentric force at 60 or 180°/s between limbs have demonstrated a stronger association with the injury risk of this muscle group. Therefore, it is recommended that practitioners use assessment protocols that include the measurement of concentric quadriceps and hamstring strength at 60°/s, and eccentric hamstring strength at 60 and 180°/s in order to monitor indicators of hamstring injury risk without the need to subject athletes to overly extensive or intensive testing protocols.

5. Conclusions

Based on the results of this review, kinetic variables, particularly isokinetic torque and inter-limb asymmetries, are consistently associated with the risk of indirect musculoskeletal injuries in professional soccer players. Tests using isokinetic machines, especially at different angular velocities, have been the most reliable indicators, allowing for accurate assessments of strength deficits and muscle disequilibrium. Monitoring these variables can help identify players at higher risk, enabling the development of specific strengthening and injury prevention strategies.
This review highlights the importance of assessing muscle strength as a relevant predictor of injury risk, along with other established risk factors. For coaching and medical staff, it is essential to define risk thresholds based on these indicators, select validated tests, and apply rigorous data analysis methods. Additionally, injury risk assessment should incorporate multifactorial elements, such as well-being, fatigue, and external/internal load measures.

Author Contributions

Conceptualization, J.P.-C., J.F.L.-F., F.I.-R. and E.A.-M.; methodology, J.P.-C., J.F.L.-F., E.A.-M., F.I.-R. and P.M.-M.; validation, F.H.-P. and D.A.T.; formal analysis, A.B.G. and P.M.-M.; investigation, C.J.B. and G.C.-R.; data curation, A.B.G. and F.M.-H.; writing—original draft preparation, J.P.-C., F.I.-R., P.M.-M. and E.A.-M.; writing—review and editing, J.F.L.-F., E.A.-M., C.J.B. and G.C.-R.; visualization, A.B.G. and F.H.-P.; supervision, J.P.-C. and D.A.T.; project administration, J.P.-C. and F.M.-H. 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.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Bangsbo, J.; Mohr, M.; Krustrup, P. Physical and metabolic demands of training and match-play in the elite football player. J. Sports Sci. 2006, 24, 665–674. [Google Scholar] [CrossRef] [PubMed]
  2. Dolci, F.; Hart, N.H.; Kilding, A.E.; Chivers, P.; Piggott, B.; Spiteri, T. Physical and energetic demand of soccer: A brief review. Strength Cond. J. 2020, 42, 70–77. [Google Scholar] [CrossRef]
  3. Rites, A.; Viana, D.; Merino-Muñoz, P.; Miarka, B.; Aedomuñoz, E.; Perez-Contreras, J.; Salerno, V.P. Do contextual factors, tournament level, and location affect external match load in elite Brazilian youth soccer players? J. Phys. Educ. Sport 2022, 22, 2898–2903. [Google Scholar]
  4. Bengtsson, H.; Ekstrand, J.; Waldén, M.; Hägglund, M. Muscle injury rate in professional football is higher in matches played within 5 days since the previous match: A 14-year prospective study with more than 130,000 match observations. Br. J. Sports Med. 2018, 52, 1116–1122. [Google Scholar] [CrossRef]
  5. de Albuquerque Freire, L.; Brito, M.A.; Merino Muñoz, P.; Valenzuela Pérez, D.I.; Cerda Kohler, H.; Aedo-Muñoz, E.A.; Slimani, M.; José Brito, C.; Bragazzi, N.L.; Znazen, H. Match Running Performance of Brazilian Professional Soccer Players according to Tournament Types. Montenegrin J. Sports Sci. Med. 2022, 11, 53–58. [Google Scholar] [CrossRef]
  6. Silva, J.R.; Rumpf, M.; Hertzog, M.; Castagna, C.; Farooq, A.; Girard, O.; Hader, K. Acute and residual soccer match-related fatigue: A systematic review and meta-analysis. Sports Med. 2018, 48, 539–583. [Google Scholar] [CrossRef]
  7. Olson, D.; Sikka, R.S.; Labounty, A.; Christensen, T. Injuries in professional football: Current concepts. Curr. Sports Med. Rep. 2013, 12, 381–390. [Google Scholar] [CrossRef]
  8. Hägglund, M.; Waldén, M.; Magnusson, H.; Kristenson, K.; Bengtsson, H.; Ekstrand, J. Injuries affect team performance negatively in professional football: An 11-year follow-up of the UEFA Champions League injury study. Br. J. Sports Med. 2013, 47, 738–742. [Google Scholar] [CrossRef]
  9. Ekstrand, J. Preventing injuries in professional football: Thinking bigger and working together. Br. J. Sports Med. 2016, 50, 709. [Google Scholar] [CrossRef]
  10. Fuller, C.W.; Ekstrand, J.; Junge, A.; Andersen, T.E.; Bahr, R.; Dvorak, J.; Hägglund, M.; McCrory, P.; Meeuwisse, W.H. Consensus statement on injury definitions and data collection procedures in studies of football (soccer) injuries. Br. J. Sports Med. 2006, 40, 193. [Google Scholar] [CrossRef]
  11. Ekstrand, J. Keeping your top players on the pitch: The key to football medicine at a professional level. Br. J. Sports Med. 2013, 47, 723. [Google Scholar] [CrossRef]
  12. Huygaerts, S.; Cos, F.; Cohen, D.D.; Calleja-González, J.; Guitart, M.; Blazevich, A.J.; Alcaraz, P.E. Mechanisms of Hamstring Strain Injury: Interactions between Fatigue, Muscle Activation and Function. Sports 2020, 8, 65. [Google Scholar] [CrossRef] [PubMed]
  13. Mueller-Wohlfahrt, H.-W.; Haensel, L.; Mithoefer, K.; Ekstrand, J.; English, B.; McNally, S.; Orchard, J.; van Dijk, C.N.; Kerkhoffs, G.M.; Schamasch, P.; et al. Terminology and classification of muscle injuries in sport: The Munich consensus statement. Br. J. Sports Med. 2013, 47, 342. [Google Scholar] [CrossRef] [PubMed]
  14. Klein, C.; Henke, T.; Platen, P. Injuries in football (soccer)—A systematic review of epidemiology and aetiological aspects. Ger. J. Exerc. Sport Res. 2018, 48, 309–322. [Google Scholar] [CrossRef]
  15. Larruskain, J.; Lekue, J.A.; Diaz, N.; Odriozola, A.; Gil, S.M. A comparison of injuries in elite male and female football players: A five-season prospective study. Scand. J. Med. Sci. Sports 2018, 28, 237–245. [Google Scholar] [CrossRef]
  16. Ekstrand, J.; Hägglund, M.; Waldén, M. Epidemiology of Muscle Injuries in Professional Football (Soccer). Am. J. Sports Med. 2011, 39, 1226–1232. [Google Scholar] [CrossRef]
  17. Waldén, M.; Hägglund, M.; Ekstrand, J. The epidemiology of groin injury in senior football: A systematic review of prospective studies. Br. J. Sports Med. 2015, 49, 792. [Google Scholar] [CrossRef]
  18. Harøy, J.; Clarsen, B.; Thorborg, K.; Hölmich, P.; Bahr, R.; Andersen, T.E. Groin Problems in Male Soccer Players Are More Common Than Previously Reported. Am. J. Sports Med. 2017, 45, 1304–1308. [Google Scholar] [CrossRef]
  19. Pérez-Contreras, J.; Loro-Ferrer, J.F.; Merino-Muñoz, P.; Hermosilla-Palma, F.; Miranda-Lorca, B.; Bustamante-Garrido, A.; Inostroza-Ríos, F.; Brito, C.J.; Aedo-Muñoz, E. Intra and Inter-Test Reliability of Isometric Hip Adduction Strength Test with Force Plates in Professional Soccer Players. J. Funct. Morphol. Kinesiol. 2024, 9, 270. [Google Scholar] [CrossRef]
  20. Owoeye, O.B.A.; VanderWey, M.J.; Pike, I. Reducing Injuries in Soccer (Football): An Umbrella Review of Best Evidence Across the Epidemiological Framework for Prevention. Sports Med. Open 2020, 6, 46. [Google Scholar] [CrossRef]
  21. Delextrat, A.; Piquet, J.; Matthews, M.J.; Cohen, D.D. Strength-Endurance Training Reduces the Hamstrings Strength Decline Following Simulated Football Competition in Female Players. Front. Physiol. 2018, 9, 1059. [Google Scholar] [CrossRef] [PubMed]
  22. Hughes, S.; Warmenhoven, J.; Haff, G.G.; Chapman, D.W.; Nimphius, S. Countermovement Jump and Squat Jump Force-Time Curve Analysis in Control and Fatigue Conditions. J. Strength Cond. Res. 2022, 36, 2752–2761. [Google Scholar] [CrossRef]
  23. Lovell, G.A.; Blanch, P.D.; Barnes, C.J. EMG of the hip adductor muscles in six clinical examination tests. Phys. Ther. Sport 2012, 13, 134–140. [Google Scholar] [CrossRef] [PubMed]
  24. Pedley, J.S.; Lloyd, R.S.; Read, P.J.; Moore, I.S.; De Ste Croix, M.; Myer, G.D.; Oliver, J.L. Utility of Kinetic and Kinematic Jumping and Landing Variables as Predictors of Injury Risk: A Systematic Review. J. Sci. Sport Exerc. 2020, 2, 287–304. [Google Scholar] [CrossRef]
  25. Fousekis, K.; Tsepis, E.; Poulmedis, P.; Athanasopoulos, S.; Vagenas, G. Intrinsic risk factors of non-contact quadriceps and hamstring strains in soccer: A prospective study of 100 professional players. Br. J. Sports Med. 2011, 45, 709. [Google Scholar] [CrossRef]
  26. Liporaci, R.F.; Saad, M.; Grossi, D.B.; Riberto, M. Clinical Features and isokinetic Parameters in Assessing Injury Risk in elite Football Players. Int. J. Sports Med. 2019, 40, 903–908. [Google Scholar] [CrossRef]
  27. Bishop, C.; Turner, A.; Gonzalo-Skok, O.; Read, P. Inter-limb asymmetry during rehabilitation understanding formulas and monitoring the “magnitude” and “direction”. Aspetar Sports Med. J. 2020, 9, 18–22. [Google Scholar]
  28. Engebretsen, A.H.; Myklebust, G.; Holme, I.; Engebretsen, L.; Bahr, R. Intrinsic Risk Factors for Groin Injuries among Male Soccer Players: A Prospective Cohort Study. Am. J. Sports Med. 2010, 38, 2051–2057. [Google Scholar] [CrossRef]
  29. Helme, M.; Tee, J.; Emmonds, S.; Low, C. Does lower-limb asymmetry increase injury risk in sport? A systematic review. Phys. Ther. Sport 2021, 49, 204–213. [Google Scholar] [CrossRef]
  30. Bishop, C.; Lake, J.; Loturco, I.; Papadopoulos, K.; Turner, A.; Read, P. Interlimb Asymmetries: The Need for an Individual Approach to Data Analysis. J. Strength Cond. Res. 2021, 35, 695–701. [Google Scholar] [CrossRef]
  31. Maloney, S.J. The Relationship Between Asymmetry and Athletic Performance: A Critical Review. J. Strength Cond. Res. 2019, 33, 2579–2593. [Google Scholar] [CrossRef] [PubMed]
  32. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ 2021, 372, n71. [Google Scholar] [CrossRef]
  33. 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. 2022, 17, 317–331. [Google Scholar] [CrossRef] [PubMed]
  34. Rico-González, M.; Pino-Ortega, J.; Clemente, F.; Los Arcos, A. Guidelines for performing systematic reviews in sports science. Biol. Sport 2022, 39, 463–471. [Google Scholar] [CrossRef]
  35. Downs, S.H.; Black, N. The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions. J. Epidemiol. Community Health 1998, 52, 377. [Google Scholar] [CrossRef]
  36. Hooper, P.; Jutai, J.W.; Strong, G.; Russell-Minda, E. Age-related macular degeneration and low-vision rehabilitation: A systematic review. Can. J. Ophthalmol. 2008, 43, 180–187. [Google Scholar] [CrossRef]
  37. Landis, J.R.; Koch, G.G. The Measurement of Observer Agreement for Categorical Data. Biometrics 1977, 33, 159–174. [Google Scholar] [CrossRef]
  38. Dauty, M.; Menu, P.; Fouasson-Chailloux, A. Cutoffs of isokinetic strength ratio and hamstring strain prediction in professional soccer players. Scand. J. Med. Sci. Sports 2018, 28, 276–281. [Google Scholar] [CrossRef]
  39. Dauty, M.; Menu, P.; Fouasson-Chailloux, A. Hamstring Muscle Injury Prediction by Isokinetic Ratios Depends on the Method Used. Clin. J. Sport Med. 2020, 30, 40–45. [Google Scholar] [CrossRef]
  40. Grygorowicz, M.; Michałowska, M.; Walczak, T.; Owen, A.; Grabski, J.K.; Pyda, A.; Piontek, T.; Kotwicki, T. Discussion about different cut-off values of conventional hamstring-to-quadriceps ratio used in hamstring injury prediction among professional male football players. PLoS ONE 2017, 12, e0188974. [Google Scholar] [CrossRef]
  41. Lee, J.W.Y.; Mok, K.-M.; Chan, H.C.K.; Yung, P.S.H.; Chan, K.-M. Eccentric hamstring strength deficit and poor hamstring-to-quadriceps ratio are risk factors for hamstring strain injury in football: A prospective study of 146 professional players. J. Sci. Med. Sport 2018, 21, 789–793. [Google Scholar] [CrossRef] [PubMed]
  42. Timmins, R.G.; Bourne, M.N.; Shield, A.J.; Williams, M.D.; Lorenzen, C.; Opar, D.A. Short biceps femoris fascicles and eccentric knee flexor weakness increase the risk of hamstring injury in elite football (soccer): A prospective cohort study. Br. J. Sports Med. 2016, 50, 1524. [Google Scholar] [CrossRef] [PubMed]
  43. van Dyk, N.; Bahr, R.; Burnett, A.F.; Verhagen, E.; von Tiggelen, D.; Witvrouw, E. No association between rate of torque development and onset of muscle activity with increased risk of hamstring injury in elite football. Scand. J. Med. Sci. Sports 2018, 28, 2153–2163. [Google Scholar] [CrossRef] [PubMed]
  44. van Dyk, N.; Bahr, R.; Burnett, A.F.; Whiteley, R.; Bakken, A.; Mosler, A.; Farooq, A.; Witvrouw, E. A comprehensive strength testing protocol offers no clinical value in predicting risk of hamstring injury: A prospective cohort study of 413 professional football players. Br. J. Sports Med. 2017, 51, 1695. [Google Scholar] [CrossRef]
  45. van Dyk, N.; Bahr, R.; Whiteley, R.; Tol, J.L.; Kumar, B.D.; Hamilton, B.; Farooq, A.; Witvrouw, E. Hamstring and Quadriceps Isokinetic Strength Deficits Are Weak Risk Factors for Hamstring Strain Injuries: A 4-Year Cohort Study. Am. J. Sports Med. 2016, 44, 1789–1795. [Google Scholar] [CrossRef]
  46. Shalaj, I.; Gjaka, M.; Bachl, N.; Wessner, B.; Tschan, H.; Tishukaj, F. Potential prognostic factors for hamstring muscle injury in elite male soccer players: A prospective study. PLoS ONE 2020, 15, e0241127. [Google Scholar] [CrossRef]
  47. Boccia, G.; Brustio, P.R.; Salvaggio, F.; Grossio, L.; Calcagno, E.; Pintore, A.; Rainoldi, A.; Samozino, P. The Rate of Torque Development as a Determinant of the Torque–Velocity Relationship. Scand. J. Med. Sci. Sports 2025, 35, e70035. [Google Scholar] [CrossRef]
  48. Guan, Y.; Bredin, S.S.D.; Taunton, J.; Jiang, Q.; Wu, N.; Warburton, D.E.R. Association between Inter-Limb Asymmetries in Lower-Limb Functional Performance and Sport Injury: A Systematic Review of Prospective Cohort Studies. J. Clin. Med. 2022, 11, 360. [Google Scholar] [CrossRef]
  49. Coombs, R.; Garbutt, G. Developments in the use of the hamstring/quadriceps ratio for the assessment of muscle balance. J. Sports Sci. Med. 2002, 1, 56–62. [Google Scholar]
  50. Hole, C.D.; Smith, G.H.; Hammond, J.; Kumar, A.; Saxton, J.; Cochrane, T. Dynamic control and conventional strength ratios of the quadriceps and hamstrings in subjects with anterior cruciate ligament deficiency. Ergonomics 2000, 43, 1603–1609. [Google Scholar] [CrossRef]
  51. Mrzygłód, S.; Pietraszewski, P.; Golas, A.; Jarosz, J.; Matusiński, A.; Krzysztofik, M. Changes in Muscle Activity Imbalance of the Lower Limbs Following 3 Weeks of Supplementary Body-Weight Unilateral Training. Appl. Sci. 2021, 11, 1494. [Google Scholar] [CrossRef]
  52. Bishop, C. Interlimb Asymmetries: Are Thresholds a Usable Concept? Strength Cond. J. 2021, 43, 32–36. [Google Scholar] [CrossRef]
  53. Read, P.J.; Oliver, J.L.; De Ste Croix, M.B.A.; Myer, G.D.; Lloyd, R.S. A prospective investigation to evaluate risk factors for lower extremity injury risk in male youth soccer players. Scand. J. Med. Sci. Sports 2018, 28, 1244–1251. [Google Scholar] [CrossRef] [PubMed]
  54. Maher, J.M.; Markey, J.C.; Ebert-May, D. The other half of the story: Effect size analysis in quantitative research. CBE Life Sci. Educ. 2013, 12, 345–351. [Google Scholar] [CrossRef]
  55. Grindstaff, T.L.; Palimenio, M.R.; Franco, M.; Anderson, D.; Bagwell, J.J.; Katsavelis, D. Optimizing Between-Session Reliability for Quadriceps Peak Torque and Rate of Torque Development Measures. J. Strength Cond. Res. 2019, 33, 1840–1847. [Google Scholar] [CrossRef]
  56. Aedo-Muñoz, E.; Abarca-Reyes, V.; Torres-Moreno, M.-J.; Bascuñan-Mosqueira, R.; Brito, C.J.; Miarka, B.; Caro-San Juan, J.; Sánchez-Ramírez, C.; Poblete-Gálvez, C. Proposal of a Technical Model of Soccer Kicking: A Systematic Review of Kinematic and Kinetic Variables. MHSalud Rev. Cienc. Mov. Hum. Salud 2020, 17, 1–26. [Google Scholar] [CrossRef]
  57. Henderson, G.; Barnes, C.A.; Portas, M.D. Factors associated with increased propensity for hamstring injury in English Premier League soccer players. J. Sci. Med. Sport 2010, 13, 397–402. [Google Scholar] [CrossRef]
  58. Heiderscheit, B.C.; Sherry, M.A.; Silder, A.; Chumanov, E.S.; Thelen, D.G. Hamstring strain injuries: Recommendations for diagnosis, rehabilitation, and injury prevention. J. Orthop. Sports Phys. Ther. 2010, 40, 67–81. [Google Scholar] [CrossRef]
  59. Liu, H.; Garrett, W.E.; Moorman, C.T.; Yu, B. Injury rate, mechanism, and risk factors of hamstring strain injuries in sports: A review of the literature. J. Sport Health Sci. 2012, 1, 92–101. [Google Scholar] [CrossRef]
  60. Askling, C.; Karlsson, J.; Thorstensson, A. Hamstring injury occurrence in elite soccer players after preseason strength training with eccentric overload. Scand. J. Med. Sci. Sports 2003, 13, 244–250. [Google Scholar] [CrossRef]
  61. Majumdar, A.; Bakirov, R.; Hodges, D.; Scott, S.; Rees, T. Machine Learning for Understanding and Predicting Injuries in Football. Sports Med. Open 2022, 8, 73. [Google Scholar] [CrossRef] [PubMed]
  62. Zebis, M.K.; Andersen, L.L.; Ellingsgaard, H.; Aagaard, P. Rapid hamstring/quadriceps force capacity in male vs. female elite soccer players. J. Strength Cond. Res. 2011, 25, 1989–1993. [Google Scholar] [CrossRef] [PubMed]
  63. Pataky, T.C. Generalized n-dimensional biomechanical field analysis using statistical parametric mapping. J. Biomech. 2010, 43, 1976–1982. [Google Scholar] [CrossRef] [PubMed]
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.

Article Metrics

Citations

Article Access Statistics

Journal Statistics
Multiple requests from the same IP address are counted as one view.
Download PDF
Effects of a 5-Day Back Squat Overreaching Protocol on Strength Performance, Perceived Recovery and Wellness Responses: A Pilot Trial
Previous
Short-Term, Significant Gains from a 10-Day Field-Based Multi-Modal Outdoor Activity Camp with Time-Restricted Feeding Dissipate at Three-Month Follow-Up
Next