Effects of the FIFA 11 + neuromuscular warm-up program on Move2Perform injury risk classification in youth amateur soccer players: a randomized controlled trial

Abstract

Background

Lower extremity injuries are a major concern in youth soccer, where multifactorial risk factors interact and isolated screening tools have demonstrated limited predictive accuracy. Neuromuscular warm-up programs such as the FIFA 11 + have shown efficacy in reducing injury incidence, yet limited evidence exists on their effect when combined with multifactorial risk-classification frameworks in amateur youth populations. The present study aimed to evaluate the effects of an eight-week FIFA 11 + neuromuscular warm-up program on injury risk profiles-classified by the Move2Perform algorithm-and on functional performance and injury incidence in youth amateur male soccer players.

Methods

In this parallel-group, single-blinded randomized controlled trial, 44 male amateur soccer players aged 15–18 years competing in a regional amateur league were randomly allocated, using computer-generated block randomization, to an experimental group (n = 22) or a control group (n = 22). Injury risk was classified using the Move2Perform algorithm, which integrates demographic data, injury history, the Functional Movement Screen (FMS), and the Lower Quarter Y-Balance Test (YBT-LQ). Additional outcomes included jump performance and isometric quadriceps and hamstring strength. The experimental group performed the FIFA 11 + program three times per week for eight weeks under the supervision of a certified physiotherapist, while the control group continued their routine warm-up. Time-loss injuries were recorded prospectively during the eight-week period. A mixed-design ANOVA was used to assess Group × Time interactions.

Results

The experimental group showed significant improvements in YBT-LQ composite scores, FMS total scores, jump test performance, and quadriceps strength (p < 0.05), with significant Group × Time interactions favoring the FIFA 11 + group. Move2Perform risk classification shifted favorably in the experimental group: athletes initially categorized as Moderate Risk showed the most pronounced improvement, transitioning to Slight Risk, and three athletes initially classified as Substantial Risk moved to the Slight Risk category (descriptively notable, but not reaching statistical significance for this subgroup). The experimental group experienced significantly fewer time-loss injuries (n = 2) than the control group (n = 8) over the eight-week period (p = 0.009), with significantly lower incidences of ankle sprains (p = 0.038) and hamstring strains (p = 0.041). Athletes classified as high risk by the Move2Perform algorithm sustained approximately a threefold increase in injury occurrence compared with their lower-risk counterparts.

Conclusions

An eight-week, supervised FIFA 11 + neuromuscular warm-up program produced favorable shifts in Move2Perform injury risk classification and reduced time-loss injury incidence in youth amateur soccer players. Combining multifactorial injury risk classification with structured neuromuscular warm-up appears to be a practical and effective strategy for reducing lower extremity injury risk in this population, supporting the integration of preseason group-based prevention with individualized corrective approaches.

Trial registration

ClinicalTrials.gov, NCT07713004. Registered on 17 July 2026. Retrospectively registered.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s13102-026-01919-y.

Introduction

Injury prevention remains a cornerstone of sports science, as injuries impair athletic performance and impose financial and strategic burdens on teams. Each year, millions of athletes sustain injuries, with non-contact injuries accounting for a considerable proportion, estimated between 26–59% [1]. Recurrent injuries, particularly of the same type and location, constitute nearly 20–25% of cases, often leading to extended recovery times and a heightened risk of re-injury [2]. In youth amateur soccer, this burden is amplified by limited access to dedicated medical and conditioning staff, making structured prevention programs particularly valuable.

One of the most widely implemented prevention interventions is the FIFA 11 + program, designed by the Fédération Internationale de Football Association (FIFA) as a structured warm-up routine focusing on neuromuscular control, dynamic stability, and muscle activation. Systematic reviews demonstrate that FIFA 11 + significantly reduces lower extremity (LE) injury incidence, particularly among soccer players, when performed at least twice per week [3, 4]. Its effectiveness is attributed to improvements in neuromuscular coordination and biomechanical efficiency [5]. However, evidence suggests that while FIFA 11 + is effective for injury prevention, its effects on sprinting and agility performance compared with alternative dynamic warm-up routines remain less consistent, raising questions about its universal applicability [3].

In parallel, accurate injury risk prediction remains challenging because injury risk is multifactorial. Screening tools such as the Functional Movement Screen (FMS) and the Lower Quarter Y-Balance Test (YBT-LQ) are widely used to evaluate movement limitations, asymmetries, and dynamic balance. Although several studies have suggested associations between low FMS scores and increased injury risk, recent evidence indicates that predictive accuracy improves only when FMS is combined with additional parameters such as training load, fitness status, and movement asymmetry [6]. Similarly, although the YBT-LQ has been extensively used in risk assessments, its standalone predictive validity has been inconsistent. Reach asymmetries exceeding 4 cm have been linked to greater LE injury risk in some cohorts [7], but recent meta-analyses conclude that the YBT-LQ alone cannot reliably predict injuries, emphasizing its limited discriminant value when used in isolation [8].

To address these limitations, multifactorial prediction models have been developed. The Move2Perform algorithm integrates demographic variables, injury history, FMS scores, and YBT-LQ results to generate individualized risk profiles, offering a more comprehensive approach to identifying at-risk athletes. Such integrated methods align with broader predictive modeling research, which demonstrates that multifactorial approaches substantially outperform single-variable screening in musculoskeletal injury prediction [9]. Crucially, the FIFA 11 + program and the Move2Perform algorithm are conceptually complementary: the algorithm identifies the athletes most likely to benefit from intervention and the specific deficits to be targeted, while FIFA 11 + provides a standardized, time-efficient intervention that addresses the neuromuscular, balance, and core-stability components captured by the algorithm. Deficits in core strength and neuromuscular control have been linked to impaired movement patterns and injury susceptibility [10], and the FIFA 11 + program directly targets these elements through its dynamic stability and trunk-control exercises, providing a plausible mechanistic basis for risk-profile improvements within this framework.

Despite this conceptual alignment, the combined application of multifactorial risk classification and structured neuromuscular warm-up has been evaluated mainly in collegiate and elite cohorts. Youth amateur soccer players competing in regional leagues-a population with high participation rates, limited medical resources, and elevated developmental injury risk-remain underrepresented in this literature. The present study addresses this gap by evaluating, within a randomized controlled trial, how an eight-week FIFA 11 + program affects Move2Perform risk classification, functional performance, and time-loss injury incidence in youth amateur male soccer players aged 15–18 years.

We hypothesized that, compared with a routine warm-up control, the FIFA 11 + program would (i) produce a favorable shift in Move2Perform injury risk categories, (ii) improve dynamic balance, functional movement, jump performance, and lower extremity strength, and (iii) reduce time-loss injury incidence over the eight-week intervention period.

Methods

Study design

This study was conducted as a parallel-group, single-blinded randomized controlled trial (RCT) comparing an eight-week FIFA 11 + neuromuscular warm-up program with a routine warm-up control in youth amateur male soccer players. Outcome assessments were performed at baseline and after the eight-week intervention. Testing took place on the natural grass field on which the athletes regularly trained, under standard training conditions. The study was conducted in accordance with the principles of the Declaration of Helsinki. This study is reported in accordance with the Consolidated Standards of Reporting Trials (CONSORT) guidelines. A completed CONSORT checklist is provided as Additional file 1.

Participants

Forty-four male amateur soccer players competing in the Muğla Regional Amateur League voluntarily participated in this study. All participants had at least one year of competitive experience. Inclusion criteria were: (1) male athletes aged 15–18 years; (2) absence of any diagnosed systemic disease; and (3) a minimum of one year of competitive experience in amateur soccer leagues. Athletes were excluded if they (1) reported pain at the time of assessment, (2) had sustained an injury within the six months preceding the study, or (3) incurred an injury during the study period that prevented full participation in training or testing procedures.

Prior to enrolment, each participant and their parent or legal guardian was informed about the potential risks and discomforts associated with the research. Because all participants were minors (under 18 years), written informed consent was obtained from a parent or legal guardian, and written assent was obtained from each participant, in accordance with ethical guidelines for research involving minors. Ethical approval was granted by the Pamukkale University Faculty of Medicine Non-Interventional Clinical Research Ethics Committee (Approval Date: 12.08.2024; Decision No: 564538).

The mean age, height, and body mass index (BMI) of the participants were 16.75 ± 1.15 years, 174.85 ± 5.95 cm, and 22.2 ± 1.95 kg/m2, respectively. Anthropometric measurements, including height, body weight, and leg length, were collected for all participants on the first test day.

Sample size

An a priori power analysis was conducted using G*Power 3.1 for an F-test (ANOVA: repeated measures, within-between interaction) to detect a moderate effect (f = 0.25, equivalent to η2p ≈ 0.06) for the Group × Time interaction. With α = 0.05, power (1-β) = 0.80, two groups, two measurements, and an assumed within-subject correlation of 0.5, the analysis indicated a minimum total sample size of 34 participants. The final enrolled sample of 44 participants (22 per group) therefore provided adequate statistical power to detect the hypothesized Group × Time interaction effects.

Randomization and blinding

After baseline assessment, participants were randomly allocated to the experimental (FIFA 11 +) group (n = 22) or the control group (n = 22) using computer-generated block randomization with a block size of four, to ensure balanced group sizes throughout enrolment. The allocation sequence was prepared by an independent researcher who was not involved in data collection or analysis, and assignments were concealed from the recruiting investigator until after baseline testing. The investigators who administered the FMS, YBT-LQ, jump tests, and strength assessments at baseline and post-intervention were blinded to group allocation. Due to the nature of the intervention, neither participants nor the supervising physiotherapist could be blinded to group assignment. Data were de-identified prior to statistical analysis.

Move2Perform algorithm

Athlete data were analyzed using the Move2Perform (Move2Perform LLC, Evansville, Indiana, USA) injury risk classification system. The algorithm assesses injury risk based on multiple parameters, including demographic data, injury history, and results from functional movement assessments. The inputs used in the algorithm in the present study were the Lower Quarter Y-Balance Test (YBT-LQ) composite score, the Functional Movement Screen (FMS) total score, jump test performance, and isometric lower extremity strength values. Based on the algorithm’s integrated output, athletes were classified into four risk categories: Slight, Moderate, Substantial, or High Risk. This injury prediction system has previously been validated and shown to provide reliable classification of injury risk [11].

Outcome measures

Lower Quarter Y-Balance Test (YBT-LQ)

The YBT-LQ is a validated screening tool that assesses single-leg dynamic balance by measuring reach distances in the anterior, posteromedial, and posterolateral directions. Each participant performed the test barefoot under the supervision of trained evaluators. The composite score was calculated as the average reach distance across all three directions, normalized to leg length.

Functional Movement Screen (FMS)

The FMS was used to evaluate fundamental movement patterns and to identify movement limitations and asymmetries that may contribute to injury risk. The screen consists of seven fundamental movement tests, with a composite score derived from the sum of individual test scores (range 0–21).

Jump test

Jump performance was assessed using a standardized protocol. Athletes performed three consecutive double-leg horizontal jumps, with the total distance covered recorded as the final score. The test was then repeated using single-leg jumps for both the right and left legs.

Muscle strength test

Isometric muscle strength of the quadriceps and hamstrings was assessed using a handheld dynamometer (Powertrak, JTech Medical, Utah, USA). Participants performed maximal voluntary contractions, and the highest recorded value was used for analysis.

Injury surveillance

Time-loss injuries were prospectively recorded throughout the eight-week intervention period. An injury was defined, in accordance with international consensus definitions for football, as any physical complaint sustained during training or match play that resulted in the player being unable to take a full part in future training or match play for at least 24 h (time-loss injury definition).

FIFA 11 + exercise program

The experimental group followed the FIFA 11 + injury prevention program, developed by FIFA in collaboration with the Oslo Sports Trauma Research Center and the Santa Monica Orthopedic and Sports Medicine Research Foundation. The program comprises three sequential parts performed as a complete warm-up: an initial running-based warm-up; a central section of strength, plyometric, and balance exercises designed to improve neuromuscular control and core stability and progressed across three levels of difficulty; and a final part consisting of higher-speed running drills incorporating planting and cutting movements. The full program was performed three times per week prior to regular training sessions for eight weeks, with each session lasting approximately 20 min. All FIFA 11 + sessions were supervised by a certified physiotherapist trained in the program, who monitored technical execution, progressed exercise difficulty when criteria were met, and provided real-time correction to ensure intervention fidelity. The control group continued their routine pre-training warm-up over the same period.

Statistical methods

All collected data were analyzed using IBM SPSS Statistics 22.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics, including means and standard deviations (M ± SD), were calculated for all study variables. The normality of the data distribution was assessed using the Shapiro–Wilk test. Given that the data followed a normal distribution, paired t-tests were employed for within-group comparisons. A mixed-design (2 × 2) ANOVA was conducted to determine the interaction effects between time (pre-test vs. post-test) and group (experimental vs. control). Effect sizes were calculated using Cohen’s d for paired comparisons and partial eta-squared (η2p) for ANOVA tests, in order to estimate the magnitude of the observed differences. Post hoc analyses with Bonferroni corrections were applied to adjust for multiple comparisons when significant main effects were found. The relative risk of injury between groups was calculated with 95% confidence intervals, and between-group injury incidence was compared using Fisher’s exact test where appropriate. The statistical significance level was set at p < 0.05.

Results

Table 1 summarizes the baseline demographic characteristics of the experimental and control groups, including age, height, body weight, and body mass index (BMI). Statistical analyses revealed no significant differences between the two groups regarding these variables (p > 0.05). This indicates that the experimental and control groups had similar physical characteristics at the beginning of the study and were homogeneously distributed.

Table 1.

Participant characteristics

Variable	Experimental Group (n = 22)	Control Group (n = 22)	p-value
Age (years)	16.8 ± 1.1	16.7 ± 1.2	0.812
Height (cm)	175.2 ± 5.8	174.5 ± 6.1	0.734
Weight (kg)	68.3 ± 6.5	67.9 ± 7.0	0.852
BMI (kg/m2)	22.3 ± 1.9	22.1 ± 2.0	0.921

Values are presented as mean ± standard deviation (SD)

BMI Body Mass Index

Table 2 illustrates the changes in performance and injury risk markers before and after the eight-week training program. In the experimental group, statistically significant improvements were recorded in the Lower Quarter Y-Balance Test (YBT-LQ) composite score, Functional Movement Screen (FMS) total score, jump test distance, and quadriceps strength values compared with baseline (p < 0.05). Conversely, no significant changes were observed in any of these parameters within the control group (p > 0.05). Furthermore, the Time × Group interaction was significant for all measured variables, demonstrating that the FIFA 11 + based neuromuscular warm-up program was substantially more effective in enhancing performance and reducing injury risk than the control condition.

Table 2.

Changes in performance and injury risk markers following intervention with within-group analysis

Variable	Pre-Test (Exp)	Post-Test (Exp)	p-value (Pre-Post Exp)	Pre-Test (Control)	Post-Test (Control)	p-value (Pre-Post Control)	p-value (Time × Group)	Effect Size (η2)
YBT-LQ Composite Score (%)	94.5 ± 2.6	97.8 ± 2.3	0.001	94.8 ± 2.5	95.1 ± 2.7	0.512	0.003	0.372
FMS Total Score	15.6 ± 1.9	17.2 ± 1.8	0.001	15.8 ± 2.0	15.9 ± 2.2	0.789	0.017	0.256
Jump Test (cm)	32.1 ± 3.5	35.3 ± 3.2	0.002	32.3 ± 3.4	33.1 ± 3.6	0.245	0.021	0.210
Quadriceps Strength (N)	330 ± 25	352 ± 27	0.005	328 ± 26	334 ± 29	0.198	0.042	0.189

Values are presented as mean ± SD. Bolded p-values indicate statistical significance (p < 0.05)

Exp Experimental Group, Control Control Group, YBT-LQ Lower Quadrant Y-Balance Test, FMS Functional Movement Screen, η2 partial eta-squared

Move2Perform risk classification also shifted favorably in the experimental group following the intervention. Athletes initially classified as Moderate Risk showed the most pronounced improvement, transitioning to the Slight Risk category. In addition, three athletes initially classified as Substantial Risk moved to the Slight Risk category; although this change was descriptively notable, it did not reach statistical significance for this subgroup, likely due to the small number of athletes in that category at baseline.

Table 3 presents the distribution of injury incidents and the relative risk analysis for both groups over the eight-week study period. Regarding total injury incidence, the experimental group experienced significantly fewer injuries (2 cases) than the control group (8 cases) (p = 0.009). When examining specific injury types, the occurrences of ankle sprains (p = 0.038) and hamstring strains (p = 0.041) were significantly lower in the experimental group. For other injury types, such as anterior cruciate ligament (ACL) tears and quadriceps strains, no statistically significant differences were detected between the groups due to the low number of events (p > 0.05). Consistent with prior literature, athletes initially classified as high risk by the Move2Perform algorithm demonstrated approximately a threefold increase in injury occurrence compared with their lower-risk counterparts.

Table 3.

Injury incidence during the eight-week study period with relative risk analysis

Variables	Experimental Group	Control Group	Relative Risk (95% CI)	p-value
Ankle Sprains	1	3	0.33 (0.04—3.09)	0.038
Hamstring Strains	0	2	-	0.041
Quadriceps Strains	1	2	0.50 (0.05—5.02)	0.092
ACL Tears	0	1	-	0.128
Total Injury Incidence	2	8	0.25 (0.08—0.81)	0.009

Data represent the count of injuries. Statistical significance determined using Fisher’s Exact Test for individual injury types and Chi-Square test for total incidence. Bolded p-values indicate statistical significance (p < 0.05)

ACL Anterior Cruciate Ligament

Discussion

Effectiveness of the FIFA 11 + program in injury prevention

The findings of this study align with extensive research demonstrating the efficacy of the FIFA 11 + program in reducing injuries among soccer players. A meta-analysis reported that teams implementing the FIFA 11 + program experienced a 30% reduction in overall injuries, with a relative risk of 0.70 (95% CI, 0.52–0.93; p = 0.01) [12]. This injury reduction is particularly significant for lower extremity injuries, including anterior cruciate ligament (ACL) tears. The program’s effectiveness extends across various demographics: studies have shown substantial decreases in injury rates among both male and female players who consistently perform the FIFA 11 + exercises [13]. For instance, adolescent female players adhering to the program at least twice weekly experienced up to a 50% reduction in injuries [14], and male collegiate players demonstrated a significant decrease in injury incidence following regular implementation of the program [15]; injury reductions have likewise been reported in older recreational male players in a randomized controlled trial [16].

Despite these benefits, the adoption of the FIFA 11 + program remains suboptimal. A global survey revealed that less than half of professional and semi-professional soccer players and coaches were aware of the program, and among those, approximately 83.8% implemented it in their routines [17]. Barriers to implementation include lack of awareness, insufficient training on proper execution, and perceived time constraints during practice sessions [17, 18]. In the present study, players consistently performing the FIFA 11 + program over an eight-week period sustained markedly fewer injuries than those in the control group (2 vs. 8 injuries). This pattern is consistent with previous findings; the relatively large between-group difference observed in our cohort may be attributable to the supervised delivery by a certified physiotherapist, the relatively short follow-up window with high compliance, and the characteristics of the youth amateur cohort.

In addition to overall injury reduction, the FIFA 11 + program has been associated with decreased incidence of specific injuries. A meta-analysis demonstrated a 46% reduction in knee injuries among soccer players implementing the program [19], and another study reported a significant decrease in head and neck injuries [20]. The program’s multifaceted approach-incorporating strength, balance, and agility exercises-contributes to its effectiveness. Such comprehensive warm-up routines enhance neuromuscular control, which is crucial for mitigating injury risk [21]. Furthermore, consistent application has been linked to improved performance metrics, including increased agility and jump performance, which may indirectly contribute to injury prevention [15]. However, the program’s efficacy is closely tied to adherence levels: teams with high compliance rates experience more pronounced reductions in injury incidence than those with lower adherence [22, 23].

Multifactorial injury risk assessment using Move2Perform

The integration of the Move2Perform algorithm in this study provided a comprehensive and data-driven approach to injury risk assessment. This tool synthesizes information from the FMS, YBT-LQ, and individual injury history to categorize athletes based on their injury susceptibility. Prior research has confirmed the algorithm’s predictive validity, demonstrating that athletes classified as high risk are significantly more likely to sustain non-contact lower extremity injuries than those in lower-risk categories [24]. Our findings support these earlier studies, as high-risk athletes in our sample exhibited approximately a threefold increase in injury occurrence compared with their lower-risk counterparts.

To provide greater clinical depth, the movement deficits most prevalent among athletes who sustained injuries in our cohort included asymmetries in the anterior reach component of the YBT-LQ (commonly exceeding the 4 cm threshold previously linked to elevated LE injury risk) and low scores on the deep squat and in-line lunge components of the FMS. These deficits reflect impairments in dynamic single-leg stability, ankle dorsiflexion mobility, and frontal-plane control-movement qualities that are heavily loaded during the cutting, decelerating, and landing demands of soccer. This pattern is consistent with the rationale of the Move2Perform algorithm, which weights such deficits when assigning risk categories, and helps explain why simple cut-offs on any single test underperform a multifactorial classification framework [25].

The Move2Perform algorithm has been implemented across various athletic populations, including collegiate sports teams and military training programs, due to its ability to identify movement deficiencies and predict injury likelihood [26, 27]. The effectiveness of such models lies in their ability to guide targeted interventions by pinpointing specific weaknesses in an athlete’s movement patterns. However, while multifactorial screening models enhance injury risk prediction, their effectiveness depends on the accuracy of data collection and the consistency of their application. Variations in evaluator experience, test administration, and athlete effort can introduce inconsistencies that may affect risk categorization. Additionally, these models primarily focus on biomechanical and neuromuscular factors and do not account for external variables such as training load, fatigue, and psychological stress [28]. Future research should explore how integrating workload monitoring tools, physiological stress markers, and movement quality assessments can further refine such predictive models.

Dynamic balance, core stability, and injury prevention

Dynamic balance is a critical component in maintaining athletic performance and preventing injuries. The YBT-LQ serves as a reliable measure of dynamic balance capabilities. Athletes with anterior reach asymmetries greater than 4 cm have been shown to be at increased risk of lower extremity injuries [29], a finding corroborated by Smith et al. [30], who reported that anterior reach asymmetry exceeding 4 cm was associated with a higher likelihood of non-contact injuries among collegiate athletes.

In our study, participants who completed the FIFA 11 + program showed significant improvements in YBT-LQ scores, indicating enhanced dynamic balance. The dynamic-stability components of the FIFA 11 + program-particularly the single-leg balance, eccentric Nordic hamstring exercises, plyometric jumps, and bench/side-plank exercises in the central section-directly target neuromuscular control of the hip, knee, and ankle during single-leg loading. In amateur youth players, who frequently present with side-to-side asymmetries due to limb dominance and uneven exposure to corrective conditioning, these exercises plausibly drive the observed improvements in YBT-LQ composite scores and the reduction in reach asymmetry that underlies the favorable shifts in Move2Perform risk categories. This interpretation is consistent with research showing that the FIFA 11 + program significantly improves dynamic balance and lower extremity strength in soccer players over six- to eight-week intervention periods [31]. Comparable findings have been reported in adolescent athletes from other team sports: in young basketball players aged 15–17 years, an eight-week plyometric-focused training program produced significant improvements in balance, vertical jump, agility, and sprint performance, supporting the role of plyometric and balance-oriented work in concurrently developing balance and lower-extremity power during this developmental window [32].

Core stability is similarly relevant, as a strong core provides a foundation for efficient movement and force transfer, and core deficits can lead to compensatory movement patterns that increase injury susceptibility. While our study did not directly measure core strength or endurance, the FIFA 11 + exercises target trunk control and dynamic stabilization through bench, side-plank, and single-leg balance tasks, which likely contributed to the observed reductions in injury rates. Previous research has shown that the FIFA 11 + program leads to significant improvements in core muscle endurance, sprint performance, and balance among under-21 football players [33]. Because core stability was not directly assessed in the present trial, any direct contribution of core function to our findings remains a plausible but speculative mechanism that should be confirmed by future trials using dedicated core stability measures.

Limitations and future directions

This study has several limitations that should be acknowledged. First, biological maturation status (e.g., Peak Height Velocity) was not assessed in our cohort. Because participants were in the 15–18 age range, inter-individual differences in maturation could meaningfully influence both injury risk and neuromuscular performance, and unmeasured maturation may have contributed to between-participant variability in outcomes. Future studies should incorporate maturity-offset estimation when working with this age group.

Second, exposure time (cumulative hours of training and match play) was not formally quantified between groups. Although both groups continued their regular team training and match schedule, any imbalance in actual exposure-particularly more match minutes in the control group-could have partially accounted for the higher injury rate observed in that group, independent of the intervention. Future trials should record individual exposure to express injury rates per 1,000 h of training and match exposure, in line with consensus reporting standards in football.

Third, the eight-week intervention period, while sufficient to detect the hypothesized changes, limits inferences regarding the durability of the observed effects. Longer follow-up periods are needed to evaluate whether the favorable shifts in Move2Perform risk classification and the reductions in injury incidence persist throughout a full competitive season, or whether a “wash-out” effect emerges once supervised delivery is reduced. Long-term studies tracking athletes across an entire season are therefore warranted.

Finally, external variables such as training load monitoring, psychological readiness, and game intensity were not directly captured. Future research integrating workload monitoring and psychosocial measures into multifactorial injury risk models could enhance both prediction accuracy and the targeting of preventive interventions.

Conclusion

The present randomized controlled trial demonstrates that an eight-week, supervised FIFA 11 + neuromuscular warm-up program produced a favorable shift in Move2Perform injury risk classification and a significant reduction in time-loss injury incidence in youth amateur male soccer players aged 15–18 years. Athletes initially classified as high risk by the Move2Perform algorithm sustained substantially more injuries than their lower-risk counterparts, supporting the predictive utility of the multifactorial risk-classification approach in this population.

The primary contribution of this study lies in showing that combining a multifactorial injury risk assessment framework with a structured, supervised neuromuscular warm-up program is feasible and effective in a youth amateur cohort with limited access to dedicated medical and conditioning resources. While core stability was not directly measured, its contribution to the present findings remains a plausible mechanism rather than an established result of this trial and should be examined directly in future work. Overall, multifactorial screening combined with the FIFA 11 + program offers a practical pathway for reducing injury burden in youth amateur soccer.

Practical application

The findings of this study support the routine integration of the FIFA 11 + neuromuscular warm-up program into youth amateur soccer training to reduce injury risk and enhance lower extremity functional performance. Consistent implementation-performed at least two to three times per week, with attention to proper technical execution-appears critical to maximize benefits, and coaches, medical staff, and players should be educated on the long-term advantages of adherence.

Beyond risk screening at preseason, the Move2Perform algorithm can be used as a periodic monitoring tool to assess the ongoing effectiveness of the prevention program. We suggest that practitioners re-classify athletes at mid-season to verify that risk profiles remain stable or continue to improve; athletes whose category worsens can then be flagged for an individualized corrective block, while athletes whose category improves can be progressed to higher-intensity FIFA 11 + levels. This use of the algorithm as both a screening and monitoring instrument complements its role at baseline and helps practitioners adjust the prevention strategy throughout the competitive season.

A holistic approach that combines structured warm-up programs, multifactorial injury screening, and individualized adaptations is recommended for minimizing injury risk in youth amateur soccer. Long-term adherence, supported by education and engagement of athletes and staff, will be central to sustaining these benefits.

Authors’ contributions

Conceptualisation: E.G.A., A.Y.; Supervision: E.G.A., A.Y.; Materials acquisition: E.G.A., Y.E.B.; Data collection and processing: E.G.A.; Formal analysis and interpretation: E.G.A., A.Y., Y.E.B.; Writing – original draft: E.G.A., A.Y.; Writing – review and editing: E.G.A., A.Y. All authors read and approved the final manuscript.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Data availability

The datasets generated and analysed during the current study are not publicly available due to the involvement of minors as participants, but are available from the corresponding author on reasonable request subject to applicable ethical restrictions.

Declarations

Ethics approval and consent to participate

This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. Ethical approval was obtained from the Pamukkale University Non-Interventional Clinical Research Ethics Committee (Approval Date: 12.08.2024; Decision No: 564538). Because all participants were minors (aged 15–18 years), written informed consent was obtained from a parent or legal guardian, and written assent was obtained from each participant, prior to inclusion in the study.

Consent for publication

This manuscript does not include any individually identifiable personal data requiring specific consent for publication.

Competing interests

The authors declare no competing interests.