Weekly Heart Rate Variability and Training Zone Analysis in U-15 Soccer Players: The Predictive Value of Combined Warm-up Protocols for Optimizing Cardiovascular Monitoring

Abstract

Background:

Warm-up protocols play a crucial role in optimizing athletic performance and cardiovascular readiness in youth soccer players. This study aimed to compare the effects of six warm-up strategies on heart rate (HR) parameters and exertion levels in under-15 (U-15) soccer athletes.

Materials and Methods:

Seventy-two male participants were randomly (concealed participant allocation) assigned to six groups: Dynamic Warm-up (DWU), Analytical Warm-up (AWU), Analytical + Dynamic Warm-up (ADWU), Small-Sided Games Warm-up (SSGWU), Integrated Warm-up (IWU), and Small-Sided Games + Integrated Warm-up (SIWU). This randomized parallel study lasted 8 weeks, with pre- and post-tests measuring resting HR, maximal HR (MHR), average HR (AHR), RR intervals, HR variability (HRV), session rating of perceived exertion (sRPE), and HR zone distributions.

Results:

Significant improvements (P < 0.001) were observed in resting, maximum, and average heart rates, RR intervals, HRV, and session RPE in most groups, especially DWU, SSGWU, and SIWU, indicating better cardiovascular function and reduced exertion. HR zone analysis showed significant shifts in all zones for IWU and SIWU (P < 0.001). Mixed repeated measures analysis of variance revealed significant between-group differences in post-test values for maximum HR, RR intervals, HRV, and sRPE change scores (P < 0.05).

Conclusions:

These findings highlight the differential impact of warm-up protocols on cardiovascular outcomes and perceived exertion. Integrated and small-sided games warm-ups showed superior benefits, suggesting their incorporation into youth soccer training could optimize physiological preparedness and performance.

INTRODUCTION

The heart rate monitor (HRM) has become an essential component and a key criterion in both sports science and medical research, providing valuable insights into cardiovascular function, physical fitness, and training adaptation. Most importantly, it is a strong predictor of cardiac health.[1,2,3] HRM is a simple, noninvasive, and widely accessible tool that reflects the body’s physiological responses during physical activity. It provides valuable insights that can help optimize training programs, monitor recovery, and assess overall health status.[3,4,5] In sports, tracking heart rate (HR) accurately is vital. It guides athletes to train at the optimal intensity, protects them from overtraining syndrome, and directly fuels better performance outcomes. It is about training effectively and staying healthy.[6,7]

In soccer, a high-intensity, intermittent sport that requires a combination of aerobic and anaerobic capacities, HRM holds exceptional importance.[8] Soccer players experience rapid HR fluctuations due to the game’s dynamic nature, which involves sprints, decelerations, and directional changes interspersed with sustained intermittent efforts throughout 90 min of play.[9,10] For youth and adolescent soccer players, this importance is amplified as their developing cardiovascular systems require careful monitoring to optimize performance while ensuring long-term health.[5]

Studies have shown that HR variability (HRV) and resting HR (RHR) in young athletes are closely linked to their training loads, recovery needs, and potential risks of overtraining or injury.[11,12,13] From a medical perspective, HR monitoring serves as a predictive tool for assessing cardiovascular health and training load requirements.[14] This information is crucial for designing personalized training plans that help athletes stay healthy while performing at their best.[15]

Tracking HR every week has become a crucial aspect of modern soccer training.[10] It provides coaches with valuable guidance into how players’ bodies respond to training loads, their recovery levels, and overall cardiovascular health.[10,16] Soccer, as a sport, involves short bursts of intense activity followed by periods of lower intensity, placing unique demands on players’ cardiovascular systems. Regular HR monitoring helps coaches evaluate the effectiveness of training sessions and ensure players stay within their ideal training zones, balancing performance improvement with physiological safety.[1,17] For young soccer players, keeping track of HR every week is especially important because their bodies are going through significant changes as they grow and develop.[18,19] During this time, adolescents experience noticeable shifts in how their cardiovascular systems respond to training, which can affect both their performance and their overall health in the long run.[12] Research has shown that HRV and maximum HR in young athletes are strongly connected to how much training they are doing, how well they are recovering, and even early signs of fatigue or overtraining.[11,20] By regularly monitoring HR, coaches can get a clear picture of these changes and adjust the intensity and length of training sessions to match the players’ needs.[21,22] This helps prevent burnout, reduces the risk of injuries, and ensures that the players stay healthy while improving their performance.[22,23]

Warm-up exercises are essential for athletes to prepare their bodies and minds for the demands of training or competition, improving performance and possibly reducing injury risks.[24] A good warm-up boosts blood flow, enhances flexibility, and improves coordination, ensuring a smooth transition into intense activity.[24,25] Recent studies emphasize the importance of HRM during warm-ups to maximize its effectiveness.[26,27,28,29] HRM is important to ensure athletes stay within their target zones. However, the typical warm-up is not designed to develop aerobic or anaerobic capacity; only the latter, more specific strength and conditioning phases serve that purpose.[30] HRM also helps coaches identify when players are overexerting or underperforming, enabling immediate adjustments for safer and more effective warm-ups.[13,28] Ultimately, warm-ups set the tone for the session or game, and skipping or doing them incorrectly increases the risk of injuries like strains or sprains. Combining HR tracking with structured warm-up routines provides athletes with the best preparation for peak performance.[5,22,31,32]

A study by Taylor et al. demonstrated that dynamic warm-up routines, when paired with HR monitoring, significantly improved players’ readiness for high-intensity activities.[33] Similarly, research by Villaseca-Vicuña et al. emphasized the importance warming up load, in tailoring warm-up exercises for soccer players.[34] Rabbani et al. studied the reliability and validity of a submaximal warm-up test for monitoring training status in professional soccer players.[35] Yilmaz et al. investigated how different warm-up durations (8 min, 15 min, and 25 min) affect performance in 4 v 4 small-sided soccer games. The study analyzed both internal factors, such as HR and perceived exertion, and external factors, including technical skills and movement patterns. Their findings offer practical guidance for coaches to tailor warm-up strategies in soccer, ensuring players are optimally prepared for both physical and technical demands.[3] These findings underscore the necessity of incorporating HRM into warm-up protocols to ensure that the intensity aligns with their physiological capacities.[34,36]

Warm-up routines are essential in youth soccer as they prepare players physically and mentally while reducing injury risks. Various approaches have been studied, including static stretching,[37,38] dynamic stretching,[39,40] sport-specific drills,[41,42] and combined protocols[43,44] like the FIFA 11+ program.[45,46,47] Research suggests that static stretching improves flexibility but may temporarily reduce muscle strength.[48] In contrast, dynamic stretching enhances sprint speed, agility, and explosive power while lowering injury risks.[49] Sport-specific drills and combined approaches, such as the FIFA 11+ protocol, offer the most comprehensive benefits by improving neuromuscular control, balance, and coordination, and significantly reducing injury rates.[50] Studies comparing these methods highlight the superiority of dynamic stretching and combined protocols in optimizing player readiness and safety.[37,51,52,53,54,55]

There are limited studies on HRM during warm-up exercises, and even fewer include studies examining and comparing these protocols in their combined and integrated forms.[36,56,57,58] The key innovation of this study lies in its detailed examination of six distinct warm-up protocols, including two that were combinations of similar methods. Over an 8-week period, adolescent soccer players were closely monitored, with weekly HR data collected to ensure a thorough and well-rounded analysis of the protocols’ effectiveness.

This study aims to analyze different warm-up protocols, with a particular focus on HRM and training zones. It also seeks to provide practical recommendations for combining protocols in ways that optimize HR tracking and variability, offering valuable insights for coaches and sports practitioners. By connecting sports science with real-world applications, this research contributes to the development of evidence-based warm-up strategies tailored to adolescent football players.

METHODS

Experimental approach to the problem

This randomized parallel study was designed to examine, compare, and monitor health rate during warm-up exercises across six distinct protocols in U-15 players from a soccer club competing in the grassroots leagues of Isfahan Province, Iran. Convenience sampling was used to recruit the players. The study design is schematically shown in [Figure 1]. Context data collection was carried out over an 8-week period, from June 23, 2024 to August 15, 2024. The data were gathered on odd days of the week—Sunday, Tuesday, and Thursday—immediately after the pre-season training sessions of the 2024–2025 grassroots football leagues in Isfahan Province. In total, 24 training sessions were analyzed during this period.

Figurer 1.

Schematic of study design

Participants

Seventy-two U15 Trained/Developmental[59] male players from Nesf-e-Jahan Soccer Team (Isfahan’s grassroots league) joined the study with parental and club consent. Players had at least 3 years of experience competing and participating in grassroots leagues. Randomization was done by the club principal, who used a draw system to assign players (72 total) into intervention and control groups while balancing skill levels. The club principal, an individual independent of the study, concealed participant allocation by shaking a bag containing all 72 players from three teams before baseline testing. Five players from each team were randomly assigned to the intervention group, while the remaining players were placed in the control group. This method ensured that each group had an equal chance of being assigned to the intervention condition while maintaining a proper balance of player grades across the two groups. Sessions were held on hybrid turf under consistent conditions (15°C–25°C, 50%–70% humidity), with lifestyle factors like sleep and nutrition monitored. Warm-up protocols were tested daily (17:00–19:00) as the sole variable, and players avoided intense exercise 48 h before baseline testing.

Inclusion/exclusion criteria

The inclusion criteria required players to be present for all warm-up protocol sessions and to remain healthy and free of injury throughout the study. Eligible participants had no history of nutritional supplement use, had completed at least 3 years of consistent training and competition, and had no diagnosed cardiovascular or musculoskeletal conditions. Players were excluded if they missed more than 20% of training sessions, sustained injuries causing absences longer than three days, or showed declines of 15% or more in two baseline performance tests as these conditions were considered to potentially skew the study’s results.

Sample size

A priori power analysis using G*Power 3.1.9.4 accounted for the study’s six-group repeated-measures design and multiple outcomes. Based on prior warm-up literature,[56,60] researchers estimated a moderate multivariate effect size (η² = 0.15), with α = 0.05, power = 0.80, and five dependent variables, yielding a required sample of 66 (n = 11). To mitigate attrition risks and ensure robust univariate follow-ups for significant results, the sample was increased to 72 (n = 12). This adjustment strengthened methodological rigor, aligning with best practices for longitudinal sports science research.

Warm-up protocols

This study included 24 warm-up sessions, conducted over 8 weeks with three sessions per week, each lasting 20 min at the start of training. The analyzed warm-up protocols were designed to target various aspects of athletic preparation, each offering distinct benefits:

1. Dynamic Warm-Up (DWU): Adapted from Taylor et al., this protocol consists of 16 consecutive movements with active rest periods between exercises, enhancing dynamic readiness and physical activation [Table 1]

2. Analytical Warm-Up (AWU): Based on Coledam et al., it incorporates 12 controlled dynamic drills to refine motor skills and improve coordination [Table 2]

3. Small-Sided Games Warm-Up (SSGW): Inspired by Redd et al., this protocol adds a competitive element with one defender facing five attackers in a 7 × 7-meter square, promoting agility and tactical awareness [Figure 2a]

4. Integrated Warm-Up (IWU): Building on the SSG format, this protocol features two 10-min small-sided games with two mini goals of 1 m × 1 m on a 20 m × 28-m pitch with modified rules, such as midfield restarts and unlimited touches, conducted without verbal cues to focus on intensity and gameplay dynamics. The game was supervised by the physical trainer of the club, who was also in charge of quickly repositioning another ball in order to maintain the intensity of the game. Once the game began, no verbal stimulation was administered, with the aim of preventing any external influence on the intensity of the execution. The game modification rules were as follows: There were no throw-ins or corner kicks; when the ball left the game zone, the game was resumed from the center of the field; there were no limits for the number of contacts per player; to consider a goal valid, the entire attacking team had to be in the opponent’s half of the field [Figure 2b].

Table 1.

Dynamic warm-up protocol

n		Exercise		Description		Biomechanical focus		Soccer-specific relevance
1		High knee		Alternating knee raises synchronized with arm motion. 3 × 20 m		Hip flexor activation, core stability		Enhances sprint mechanics and stride frequency
2		Butt flicks		Controlled flicking motion of heels toward glutes. 3 × 20 m (15–20 reps)		Hamstring activation, short-foot contact		Optimizes recovery in high-frequency sprints
3		Carioca		Lateral crossover steps over 3 × 20m each side		Lateral hip mobility, coordination		Improves agility and quick directional changes
4		Dynamic hamstring swings		Controlled leg swings to full range of motion. 3 × 10 reps per leg		Eccentric hamstring loading, hip control		Prevents hamstring strains; improves backswing
5		Dynamic groin swings		Controlled leg swings targeting groin muscles. 3 × 10 reps per leg		Hip adductor activation, flexibility		Enhances inside-foot passes and defensive pivots
6		Arm swings (forward/back)		Controlled arm swings in both directions. 3 × 10 reps per direction		Shoulder mobility, coordination		Improves upper-body coordination in movement
7		Faster high knee		High-speed alternating knee raises over 4 × 10 m		Hip flexor strength, power generation		Boosts acceleration phase in counterattacks
8		Swerving		Controlled swerving motion over 2 × 30 m at 70% max pace		Lateral agility, multidirectional speed		Mimics directional changes in matches
9		Side stepping		Lateral steps over 2 × 30m at 80% max pace		Lateral glute strength, frontal plane agility		Defensive shuffling and quick transitions
10		Spiderman walks		Controlled walking motion with wide strides. 1 × 20 m (10 reps per side)		Hip mobility, eccentric strength		Improves deceleration and lateral movement control
11		Sideways low squat walks		Squat walk in a sideways motion × 10 steps each direction		Quad-glute engagement, lateral stability		Enhances low defensive positioning
12		Upper body rotations		Controlled rotations of the upper body × 10 reps per direction		Core stability, trunk mobility		Improves rotational movement for passing/shooting
13		Vertical jump		Explosive jumps × 5 reps (progressive effort 60% → 90%)		Quad-glute power, stretch-shortening cycle		Builds explosive power for jumping headers
14		Run through		Sprint intervals: 2 × 20 m (70%), 2 × 20 m (80%), 1 × 20 m (90%)		Acceleration, speed endurance		Enhances sprint mechanics for counterattacks
15		Countermovement jump +5 m Sprint		Explosive jump followed by 5m sprint (90% × 2, 95% × 1)		Reactive strength, sprint mechanics		Enhances transition speed for reactive play
16		Sprint + countermovement jump		Sprint for 5m followed by explosive jump × 2 sets		Reactive agility, power generation		Mimics defensive recovery movements

Table 2.

Analytical warm-up protocol

n		Exercise		Description		Biomechanical focus		Soccer-specific relevance
1		High knee skipping		The player jogs while lifting their knees toward the chest. Support is on the forefoot, with alternating arm movements for balance. Approximately 12–15 knee lifts per leg every 10 s (around 180 total repetitions)		Jogging with high knees, emphasizing forefoot stance and opposite arm swing to activate hip flexors and enhance core stability		Improves sprint mechanics and stride frequency by gradually activating hip flexors and core with minimal exertion
2		Dynamic hamstrings swing		The player jogs with alternating arm movements, lifting one extended leg forward before returning to the starting position and repeating with the other leg. 10–12 swings per leg every 10 s (around 120 total swings)		Jogging with straight-leg swings to enhance hamstring strength and hip motion control		Prevents hamstring strains and improves kicking control through eccentric loading and controlled warm-up movements
3		Squat and run		The player performs a squat, immediately followed by a short burst of running. 8–10 squat-run cycles (depending on intensity)		Bodyweight squat into explosive run to boost quad-glute power and activate the stretch-shortening cycle		Develops explosive power for jumps and sprints, preparing the body for dynamic movements
4		Inward hip circumduction		The player jogs with alternating arm movements, performing an inward circular motion with one hip before returning to the starting position and repeating with the other leg. 10–12 inward hip rotations per leg every 10 s (around 120 total rotations).		Jogging with circular hip rotations to enhance internal rotation and adductor flexibility		Essential for inside-foot plays and cutting, emphasizing flexibility and hip rotation for soccer movements
5		Outward hip circumduction		The player jogs with alternating arm movements, performing an outward circular motion with one hip before returning to the starting position and repeating with the other leg. 10–12 outward hip rotations per leg every 10 s (around 120 total rotations).		Jogging with outward hip rotations to improve external rotation and activate the gluteus medius		Enhances hip stability for crosses and outside-foot kicks, balancing internal and external rotation with glute activation
6		Lateral side to side jog with left leg		The player moves laterally to the left, leading with the left leg. Feet do not cross, and arms stay open for balance. 8–10 lateral movements to the left and back in each 10-second interval (around 80-100 total).		Sideways movement with open arms improves lateral glute strength and frontal plane agility, critical for directional changes		Enhances lateral agility and quick transitions for effective defensive shuffling during 1v1 duels
7		Lateral side to side with right leg		The player moves laterally to the right, leading with the right leg. Feet do not cross, and arms stay open for balance. 8–10 lateral movements to the right and back in each 10-second interval (around 80–100 total).		Mirror of #6. Symmetrical development of lateral movement control		Balanced agility for bidirectional defending Ensures symmetrical movement development for agility
8		Lunge walk		The player walks forward, performing alternating lunges with each leg. The trunk stays upright, and the arms swing naturally for balance. 8–10 lunges per leg every 10 s (around 80–100 total lunges)		Forward walking with alternating deep lunges. Trunk vertical, arms oscillating. Quad/hamstring eccentric strength, hip stability		Improves deceleration control and shooting stability Focuses on eccentric quad/hamstring strength and deceleration control
9		Butt flicks		The player quickly moves the heels toward the gluteus, while the trunk remains straight, with arms oscillation 2 sets of 20 s		Rapid heel-to-gluteus touches while jogging. Hamstring recruitment, short-foot contact		Optimizes back-kick recovery during high-frequency sprints Engages hamstrings for quick recovery during sprints
10		Backward running		The player performs a reverse running, so that he travels in the direction his back is facing rather than his front 2 sets of 20 s		Running in reverse direction. Proprioception, posterior chain engagement		Develops spatial awareness for tracking balls over the shoulder Develops posterior chain and spatial awareness for soccer movements
11		Fast skipping		The player performs a knee raise while advancing. Frequency and range of motion should be considered. The trunk should remain slightly tilted, alternating the arms 2 sets of 20 s		High-frequency knee drives with slight forward trunk lean. Power generation, arm-leg coordination		Boosts acceleration phase in counterattacks Boosts acceleration and coordination for counterattacks
12		Backward running with turn and sprint		The player performs a half-reverse run, then turns and performs a frontal sprint 2 sets of 20 s		Backward run followed by 180° turn into maximal sprint. Reactive agility, transition speed		Mimics recovery runs after defensive retreats Mimics reactive agility and transition speed during gameplay

Figure 2.

SSGWU protocols. (a) SSGWU Redd et al. (2021); (b) IWU Villaseca-Vicuña et al. (2024); (c) SSGWU+ IWU. SSGWU = Small-sided games warm-up, IWU = Integrated warm-up

Additionally, the study explored combined protocols:

• 5. DWU + AWU: This combination merges the dynamic and analytical phases to enhance neuromuscular activation and motor performance [Table 3]

• 6. SSGW + IWU: Sequential 10-min phases of SSGW and IWU were integrated to synergize their physiological and technical benefits while preserving the integrity of their original structures [Figure 2c].

Table 3.

Dynamic and analytical warm-up protocol

Resource		Exercise		Description		Biomechanical focus		Soccer-specific relevance
DWU		High knee		Alternating knee raises synchronized with arm movement over 3×20 m		Hip flexor activation, core stability		Enhances sprint mechanics and stride frequency. Activates lower limbs and core while preparing for higher zones; widely recognized as an essential warm-up exercise for soccer
ADW		Butt flicks		Controlled flicking motion of heels toward glutes over 3×20 m		Hamstring activation, short-foot contact		Optimizes recovery in high-frequency sprints Improve sprint recovery and hamstring activation; critical for sprint mechanics in soccer
DWU		Carioca		Lateral crossover steps performed at increasing speed over 3×20 m		Lateral hip mobility, coordination		Improves agility and quick directional changes Enhances lateral agility and coordination, critical for defensive shuffling and quick transitions in soccer
DWU		Dynamic hamstring swings		Controlled leg swings targeting hamstrings and hip range of motion		Eccentric hamstring loading, hip control		Prevents hamstring strains; improves backswing Improves hamstring flexibility and reduces injury risk; essential for dynamic
ADW		Side-stepping		Rapid lateral steps performed over 3×20 m		Lateral glute activation, agility		Defensive shuffling and quick transitions Lateral movement control and agility; mimics match scenarios for defenders
DWU		Spiderman walks		Controlled forward lunges with wide strides over 2×20 m		Hip mobility, eccentric strength		Improves deceleration and lateral movement control Builds flexibility and control; effective for multidirectional soccer movements
ADW		Skater jumps		Lateral jumps with controlled landings over 3×10 reps		Glute activation, knee stability		Enhances lateral power and balance Improves reactive lateral power and joint stability; ideal for soccer-specific agility
DWU		Vertical jump		Explosive jumps×5 reps (progressive effort 60% → 90%)		Quad-glute power, stretch-shortening cycle		Builds explosive power for jumping headers Develops explosive power and jump mechanics, critical for aerial duels in soccer matches
ADW		Sprint intervals		Sprint intervals: 3×20 m (70%, 80%, 90%)		Acceleration, speed endurance		Enhances sprint mechanics for counterattacks enhance speed endurance and acceleration, key for soccer counterattacks
DWU		Countermovement jump + sprint		Explosive jump followed by 5 m sprint×3 reps		Reactive strength, sprint mechanics		Enhances transition speed for reactive play Combines explosive power with reactive sprinting; simulates game-like reactive scenarios
ADW		Sprint + countermovement jump		Sprint for 5m followed by explosive jump×3 sets		Reactive agility, power generation		Mimics defensive recovery movements Combines speed and explosive power, critical for transitions in high-intensity match situations
DWU		Run through		Progressive sprint intervals over 2×30 m (80%, 90%)		Acceleration, speed endurance		Boosts acceleration phase in counterattacks Peak effort sprint intervals mimic match demands, enhancing acceleration and endurance

DWU=Dynamic warm-up, AWU=Analytical warm-up

Heart rate monitor and motion analysis system

Player HR was monitored in real time using a Polar H10 Heart Rate Monitor (Polar Electro Oy, Finland), capturing data at one-second intervals with wrist-based pulse detection. This system simultaneously tracks distance covered while offering versatile connectivity via Bluetooth, ANT+, and 5 kHz transmission, supporting dual Bluetooth connections. All metrics were analyzed through Polar Team Pro software, enabling: (1) Simultaneous monitoring of all players; (2) Training intensity assessment via speed/distance metrics; (3) Sprint frequency quantification; Cross-session performance comparison and recovery status evaluation based on cumulative training load. This integrated approach will optimize workload management and activity–rest balance. The Polar H10 heart rate monitor (HRM) and Polar Team Pro software are well-recognized tools for sports performance analysis. The Polar H10, validated against electrocardiograph (ECG) (the gold standard for HR measurement), has demonstrated high accuracy with correlation coefficients exceeding 0.90 in various studies conducted during both rest and exercise conditions. For instance, Gilgen-Ammann et al. reported minimal bias and strong agreement between Polar H10 and ECG recordings, highlighting its reliability for HRV assessment during physical activity.[61] Similarly, the Polar Team Pro software is reliable for tracking distance, sprint frequency, and workload metrics, with research confirming its precision in team sports settings.

This integrated system provides coaches and sports scientists with a robust platform for real-time monitoring and workload optimization. By combining accurate HR data and detailed movement metrics, the system supports informed decision-making to improve training intensity, prevent overtraining, and enhance performance recovery. Moreover, the inclusion of personalized HR zones, based on either maximal HR (MHR) tests or validated formulas such as 211-0.64 × age, ensures individualized monitoring tailored to each player’s physiological profile, thereby maximizing the efficacy of training and recovery strategies.

The 8-week training program

This study leveraged Polar Team Pro’s advanced wearable technology to quantify both physical and physiological demands in athletes. The system tracked physical performance measures, including sprint score, acceleration profile, total distance covered, distance per minute, peak/average speed, and session duration, alongside physiological markers such as MHR, average HR, R-R interval dynamics, HRV, and time spent in training zones (Zones 1–5). Training load was calculated using Polar’s proprietary algorithm, which synthesizes these multimodal datasets into actionable insights for coaches.[62,63] The Polar Team Pro’s chest-strap design integrates a 10 Hz GPS, 200 Hz accelerometer, and medical-grade ECG sensors to capture HR via electrical cardiac signals-a method validated against gold-standard electrocardiograms in peer-reviewed studies.[61,64] Positioned at the xiphoid process, the strap minimizes motion artifacts while maintaining athlete comfort during dynamic movements.[65] Particularly, its 10 Hz MEMS motion sensor provides granular tracking of multidirectional accelerations, critical for analyzing sport-specific agility. To ensure data consistency, athletes were assigned the same sensor throughout the study, a protocol shown to reduce inter-device variability in team-sport settings.[66]

Athletes attended three weekly training sessions at the sports club (on Sundays, Tuesdays, and Thursdays) to follow their structured regimen, culminating in a competitive match at the end of each week. Six distinct warm-up protocols were implemented across an artificial turf field segmented into sections, with players assigned to three teams training on adjacent artificial and natural turf fields within a stadium. The fields, separated by mesh fences and spaced less than 5 m apart, operated under uniform conditions, with strict control over the first 20 min of each 90-min session to isolate warm-up protocols as the sole variable. Coaching staff, excluding head coaches, were randomized across teams during sessions, with three coaches per field overseeing execution. For ball-inclusive warm-ups, ten Mikasa V300W size-5 balls (Thai-manufactured) were positioned near training areas, managed by three dedicated crew members to minimize disruptions. Each protocol zone included one coordinator coach and two supervisors stationed strategically to ensure adherence. Time loss due to ball retrieval was mitigated by assigning club crew to handle scatter, preserving intervention integrity.

To minimize environmental variability, researchers administered standardized weekly assessments on artificial turf at fixed times. Warm-ups replicated test conditions, and HRV was monitored continuously during sessions. Players’ RHR, reported weekly under parental supervision, and training behaviors were systematically tracked. Internal training load was quantified via the session–session rating of perceived exertion (sRPE) method.[67]

Statistical analysis

Data were analyzed using IBM’s SPSS Statistics, version 27.0 (IBM Corp., Armonk, New York, United States), a leading software in sports science research, to ensure rigorous statistical evaluation. Results are reported as mean ± standard deviation (SD), a standard measure showing average values alongside variation within the dataset. Initial analysis employed descriptive statistics to summarize trends across all metrics. To validate the statistical approach, the Shapiro–Wilk test was first applied, confirming that the data followed a normal distribution—a critical step before selecting follow-up tests. Following normalization confirmation, a mixed repeated measures analysis of variance (ANOVA) was conducted to examine the primary research questions. This analytical approach was specifically chosen because our study design included both between-subjects factors (the six different warm-up groups) and within-subjects factors (measurements taken before and after the intervention). The mixed repeated measures ANOVA allowed us to simultaneously investigate three key questions: first, whether HR indicators changed significantly from pre- to postintervention across all participants (main effect of time); second, whether the six warm-up protocols produced different overall effects on cardiovascular responses (main effect of group); and most importantly, whether the effectiveness of different warm-up protocols varied depending on the specific HR metric being measured (time × group interaction). For each of the seven HR monitoring indices including rest HR (RHR), MHR, average HR (AHR), average RR interval (ARR), maximum RR interval (MRR), HRV, and sRPE, separate analyses were performed to ensure precision and avoid statistical complications associated with multiple dependent variables. When significant main effects or interactions were detected, post hoc analyses using Bonferroni correction were applied to identify specific group differences while controlling for multiple comparisons. This conservative approach helps prevent false discoveries when conducting numerous statistical tests. Statistical significance was set at P < 0.05 for all analyses, ensuring a 95% confidence level in our conclusions.

Normality test of data

Prior to conducting parametric statistical analyses, we evaluated the normality of data distribution using the Shapiro–Wilk test, which is widely recognized as the most appropriate normality test for sample sizes under 50 per group. We applied this test to all seven HR monitoring variables (RHR, MHR, AHR, ARR, MRR, HRV, and sRPE) across both pre- and postintervention time points for each of the six warm-up protocol groups. Our results demonstrated that all variables successfully met the normality assumption across all groups and time points (all P > 0.05), confirming that the data followed a normal distribution pattern. This finding provided strong validation for using parametric statistical procedures in subsequent analyses, including our planned mixed repeated measures ANOVA.

RESULTS

Demographic characteristics

Table 4 shows the mean and SD of demographic characteristics of players U-15 based on six groups and types of warm-up protocols. The mean and SD of the demographic data across the six groups were as follows: age (14.34 ± 0.19 years), height (161.96 ± 6.13 cm), weight (54.97 ± 4.09 kg), and body mass index (20.92 ± 1.00).

Table 4.

Demographics of players

Group		Mean±SD
		Age (years)		Height (cm)		Body mass (kg)		BMI (kg/m2)
DWU		14.40±0.17		159.29±6.62		54.09±5.96		21.25±1.15
AWU		14.37±0.20		162.56±5.79		56.25±4.18		21.27±0.91
ADWU		14.34±0.19		160.25±7.41		51.31±6.01		19.91±1.05
SSGWU		14.38±0.22		162.94±5.89		55.40±3.75		20.85±0.65
IWU		14.24±0.10		163.09±5.60		55.43±4.02		20.82±0.89
SIWU		14.32±0.20		163.61±5.23		57.36±3.62		21.41±0.59

DWU=Dynamic warm-up, AWU=Analytical warm-up, ADWU=Analytical + dynamic warm-up, SSGWU=Small side games warm-up, IWU=Integrated warm-up, SIWU: SSG+integrated warm-up, BMI=Body mass index, SD=Standard deviation

Descriptive overview of cardiovascular adaptations before and after the intervention

Table 5 provides a detailed summary of the cardiovascular adaptations observed among the U-15 soccer players after 8 weeks of structured warm-up protocols. The descriptive statistics, including mean ± SD, along with additional measures such as P values, ηp², and the calculated differences in mean values, offer valuable insights into the efficacy of each warm-up strategy.

Table 5.

Descriptive statistics for heart rate measures

Variable		Group		Mean±SD						P		ηp2
				Preintervention (week 1)		Postintervention (week 8)		Difference mean
Rest heart rate (beats/min)		DWU		70.17±1.26		67.16±0.83		−3.00±1.27		<0.001		0.857
		AWU		68.76±1.60		66.50±0.67		−2.25±1.35		<0.001		0.750
		ADWU		67.58±2.31		66.41±1.37		−2.16±1.52		<0.001		0.687
		SSGWU		69.83±2.03		66.50±1.08		−3.41±1.83		<0.001		0.749
		IWU		69.83±1.94		66.41±0.66		−3.33±2.01		<0.001		0.791
		SIWU		69.50±2.15		64.33±0.49		−5.16±1.89		<0.001		0.890
Maximal heart rate (beats/min)		DWU		194.91±3.93		188.83±3.73		−6.08±2.19		<0.001		0.894
		AWU		192.00±3.93		184.33±4.05		−7.66±0.98		<0.001		0.985
		ADWU		197.00±3.54		195.66±5.01		−1.33±3.05		0.159		0.172
		SSGWU		197.33±1.77		192.66±5.26		−4.66±3.77		0.001		0.625
		IWU		198.25±0.86		197.58±1.16		−0.66±1.07		0.054		0.296
		SIWU		199.08±1.44		190.91±3.05		−8.16±1.64		<0.001		0.964
Average heart rate (beats/min)		DWU		152.83±2.94		146.16±3.48		−6.66±1.87		<0.001		0.932
		AWU		156.00±3.93		148.25±4.30		−7.75±0.96		<0.001		0.986
		ADWU		134.75±1.21		131.41±2.02		−3.33±1.15		<0.001		0.901
		SSGWU		159.23±3.28		153.50±5.56		−5.73±2.77		<0.001		0.823
		IWU		160.15±2.45		154.50±10.44		−5.65±9.78		0.071		0.267
		SIWU		173.75±1.28		164.91±4.98		−8.83±3.80		<0.001		0.854
Average RR interval (ms)		DWU		397.60±11.55		419.84±16.93		22.24±5.79		<0.001		0.941
		AWU		388.74±10.73		409.73±13.19		20.99±3.38		<0.001		0.977
		ADWU		409.50±25.85		427.72±29.85		18.21±5.21		<0.001		0.930
		SSGWU		384.56±8.36		405.15±17.88		20.58±11.02		<0.001		0.792
		IWU		382.14±6.13		389.35±11.37		7.21±9.79		0.027		0.372
		SIWU		354.57±2.56		373.90±12.83		19.33±10.41		<0.001		0.790
Maximum RR interval (ms)		DWU		445.41±14.09		471.93±22.63		26.51±8.83		<0.001		0.908
		AWU		488.30±16.97		524.33±30.87		36.03±14.05		<0.001		0.878
		ADWU		518.19±37.34		548.31±47.68		30.12±11.09		<0.001		0.889
		SSGWU		560.94±29.94		603.14±55.54		42.19±27.23		<0.001		0.724
		IWU		546.66±21.83		551.80±29.81		5.14±19.30		0.376		0.072
		SIWU		608.70±7.42		659.31±37.45		50.60±30.52		<0.001		0.750
HRV (ms)		DWU		52.50±1.70		56.14±2.57		3.36±0.96		<0.001		0.939
		AWU		45.28±2.56		50.40±3.73		5.12±1.25		<0.001		0.948
		ADWU		51.24±5.16		56.61±7.82		5.37±3.22		<0.001		0.751
		SSGWU		54.40±4.36		61.20±5.58		6.79±2.35		<0.001		0.901
		IWU		53.20±3.45		54.46±2.79		1.26±2.64		0127		0.199
		SIWU		62.98±1.18		70.72±4.72		7.73±3.57		<0.001		0.836
sRPE (AU)		DWU		5.91±0.79		3.58±0.51		−2.33±0.88		<0.001		0.883
		AWU		3.41±0.51		3.25±0.62		−0.016±0.38		0.166		0.167
		ADWU		4.91±0.66		3.33±0.65		−1.58±0.79		<0.001		0.813
		SSGWU		6.16±0.38		4.50±0.52		−1.66±0.77		<0.001		0.833
		IWU		5.58±0.51		3.33±0.65		−2.25±0.96		<0.001		0.856
		SIWU		8.16±0.71		6.58±0.51		−1.58±0.79		<0.001		0.813

SD=Standard deviation, ηp²=Partial eta squared, DWU=Dynamic warm-up, AWU=Analytical warm-up, ADWU=Analytical + dynamic warm-up, SSGWU=Small-sided games warm-up, IWU=Integrated warm-up, SIWU=Small-sided games + integrated warm-up

Across all protocols, RHR significantly decreased, indicating improved cardiac efficiency at rest. The SIWU group demonstrated the most pronounced improvement, with RHR dropping from 69.50 ± 2.15 bpm to 64.33 ± 0.49 bpm (P < 0.001, ηp² = 0.890). Other groups, such as IWU and SSGWU, also showed meaningful reductions, reinforcing the cardiovascular benefits of these warm-up routines.

Improvements in exercise efficiency were evident as both MHR and AHR decreased post intervention. The SIWU group experienced the greatest decrease in MHR, dropping from 199.08 ± 1.44 bpm to 190.91 ± 3.05 bpm (P < 0.001, ηp² = 0.964). Similarly, their AHR decreased significantly (173.75 ± 1.28 bpm to 164.91 ± 4.98 bpm, P < 0.001, ηp² = 0.854). These reductions suggest improved cardiovascular fitness, enabling players to perform the same workload with less strain.

The average and maximum RR intervals, indicators of HR recovery, improved across most groups. The SIWU group saw a substantial increase in maximum RR interval from 608.70 ± 7.42 ms to 659.31 ± 37.45 ms (P < 0.001, ηp² = 0.750), highlighting faster and more efficient post-exercise recovery. Similarly, the AWU group recorded significant improvements in their RR intervals (P < 0.001, ηp² =0.878), albeit with slightly smaller effect sizes.

HRV, a critical marker for recovery and autonomic balance, improved significantly in most groups, with the SIWU group again showing the largest increase from 62.98 ± 1.18 to 70.72 ± 4.72 ms (P < 0.001, ηp² = 0.836). The SSGWU group also exhibited a notable rise in HRV (6.79 ± 2.35 ms, P < 0.001, ηp² = 0.901), further highlighting their effectiveness in enhancing recovery capacity.

Players consistently reported lower perceived exertion after 8 weeks of training, with sRPE dropping in nearly all groups. The IWU group, for instance, reduced their sRPE from 5.58 ± 0.51 AU to 3.33 ± 0.65 AU (P < 0.001, ηp² = 0.856). Interestingly, the AWU group showed no significant change in sRPE (P = 0.166), indicating that this protocol may have maintained a consistent level of perceived effort throughout the intervention.

The data suggest that all warm-up protocols positively influenced cardiovascular health and recovery capacity. However, the SIWU and SSGWU groups stood out as the most effective, yielding the largest gains in RHR, HRV, and recovery indicators. These results underline the potential of structured warm-up routines to enhance fitness and performance in young soccer players.

Descriptive overview of heart rate zones adaptations before and after the intervention

The Polar H10 system automatically calculates and tracks these zones for each player based on their age and HRmax. The main difference between the zones is the intensity of physical activity and the corresponding physiological response, ranging from light recovery (Zone 1) to maximal effort (Zone 5). This approach allows for individualized monitoring and training load management according to each player’s cardiovascular capacity. Table 6 presents descriptive statistics for HR zone measures across six warm-up protocols, comparing preintervention (week 1) and postintervention (week 8) values.

Table 6.

Descriptive statistics for heart rate zones measures

Variable		Group		Mean±SD						P		ηp2
				Preintervention (week 1)		Postintervention (week 8)		Difference mean
Zone 1		DWU		0.00±0.00		0.01±0.01		0.01±0.01		0.002		0.614
		AWU		0.01±0.05		0.06±0.28		0.06±0.02		<0.001		0.868
		ADWU		0.01±0.06		0.15±0.07		0.13±0.06		<0.001		0.809
		SSGWU		0.07±0.06		0.03±0.01		0.02±0.01		<0.001		0.888
		IWU		0.06±0.04		0.04±0.01		0.03±0.01		<0.001		0.808
		SIWU		0.01±0.09		0.05±0.04		0.04±0.01		<0.001		0.922
Zone 2		DWU		0.32±0.04		0.30±0.06		−0.02±0.02		0.007		0.504
		AWU		0.17±0.03		0.29±0.01		0.12±0.04		<0.001		0.912
		ADWU		0.21±0.05		0.21±0.07		0.00±0.05		0.913		0.001
		SSGWU		0.04±0.01		0.05±0.02		0.01±0.02		0.025		0.381
		IWU		0.04±0.01		0.15±0.01		0.11±0.00		<0.001		0.989
		SIWU		0.10±0.02		0.04±0.01		−0.05±0.03		<0.001		0.770
Zone 3		DWU		0.35±0.04		0.41±0.02		0.06±0.02		<0.001		0.894
		AWU		0.33±0.12		0.45±0.04		0.11±0.10		0.003		0.572
		ADWU		0.21±0.04		0.27±0.08		0.05±0.10		0.103		0.223
		SSGWU		0.44±0.01		0.40±0.05		−0.04±0.04		0.010		0.468
		IWU		0.43±0.02		0.34±0.02		−0.09±0.00		<0.001		0.996
		SIWU		0.08±0.04		0.38±0.04		0.29±0.04		<0.001		0.978
Zone 4		DWU		0.18±0.00		0.17±0.01		−0.01±0.02		0.111		0.214
		AWU		0.23±0.05		0.09±0.05		−0.14±0.09		<0.001		0.721
		ADWU		0.33±0.05		0.22±0.07		−0.11±0.02		0.001		0.619
		SSGWU		0.07±0.01		0.08±0.03		0.01±0.02		0.225		0.130
		IWU		0.07±0.01		0.05±0.00		−0.02±0.01		<0.001		0.736
		SIWU		0.14±0.01		0.11±0.00		−0.03±0.02		<0.001		0.700
Zone 5		DWU		0.13±0.03		0.10±0.03		−0.03±0.02		<0.001		0.690
		AWU		0.15±0.04		0.11±0.03		−0.04±0.01		<0.001		0.904
		ADWU		0.22±0.01		0.13±0.05		−0.08±0.05		<0.001		0.742
		SSGWU		0.44±0.00		0.42±0.01		−0.01±0.01		<0.001		0.640
		IWU		0.43±0.00		0.41±0.00		−0.02±0.00		<0.001		0.964
		SIWU		0.53±0.01		0.40±0.01		−0.13±0.00		<0.001		0.998

SD=Standard deviation, ηp²=Partial eta squared, DWU=Dynamic warm-up, AWU=Analytical warm-up, ADWU=Analytical + dynamic warm-up, SSGWU=Small-sided games warm-up, IWU=Integrated warm-up, SIWU=Small-sided games + integrated warm-up

Zone 1 measures revealed significant improvements across most protocols, indicating increased time spent in light-intensity activities. The SIWU group experienced a substantial increase from 0.01 ± 0.09 to 0.05 ± 0.04 (difference: 0.04 ± 0.01, P < 0.001, ηp² = 0.922), suggesting enhanced recovery and efficiency in low-intensity zones. Other groups, such as ADWU (difference: 0.13 ± 0.06, P < 0.001, ηp² = 0.809) and AWU (difference: 0.06 ± 0.02, P < 0.001, ηp² = 0.868), also showed significant increases.

For Zone 2, trends varied across protocols. The AWU group demonstrated a considerable increase from 0.17 ± 0.03 to 0.29 ± 0.01 (difference: 0.12 ± 0.04, P < 0.001, ηp² = 0.912), reflecting improved tolerance for moderate-intensity activities. Conversely, the SIWU group showed a decrease from 0.10 ± 0.02 to 0.04 ± 0.01 (difference: −0.05 ± 0.03, P < 0.001, ηp² = 0.770), potentially indicating a shift toward higher efficiency in other zones.

Significant changes were observed in Zone 3, with varying responses across protocols. The SIWU group experienced a dramatic increase from 0.08 ± 0.04 to 0.38 ± 0.04 (difference: 0.29 ± 0.04, P < 0.001, ηp² = 0.978), highlighting a remarkable adaptation to high-intensity activities. In contrast, groups like IWU (difference: -0.09 ± 0.00, P < 0.001, ηp² = 0.996) and SSGWU (difference: -0.04 ± 0.04, P = 0.010, ηp² = 0.468) showed decreases, possibly reflecting improved efficiency and recovery mechanisms.

Zone 4 measures showed decreases across most protocols, suggesting enhanced efficiency at performing high workloads with less strain. For example, the AWU group decreased from 0.23 ± 0.05 to 0.09 ± 0.05 (difference: −0.14 ± 0.09, P < 0.001, ηp² = 0.721), while the SIWU group exhibited a more minor decrease (difference: −0.03 ± 0.02, P < 0.001, ηp² = 0.700). These results highlight adaptations in the ability to manage very high-intensity activities.

In Zone 5, significant reductions were observed across all protocols, indicating improved cardiovascular efficiency during maximal-intensity efforts. The SIWU group showed the most significant decrease from 0.53 ± 0.01 to 0.40 ± 0.01 (difference: −0.13 ± 0.00, P < 0.001, ηp² = 0.998), marking substantial improvements in maximal intensity performance and recovery. Similarly, the IWU group decreased from 0.43 ± 0.00 to 0.41 ± 0.00 (difference: −0.02 ± 0.00, P < 0.001, ηp² = 0.964).

The descriptive statistics highlight significant adaptations in HR zones across all groups, with the SIWU protocol consistently demonstrating the most pronounced improvements across multiple measures. These results underscore the effectiveness of structured warm-up routines in optimizing cardiovascular performance, recovery, and efficiency.

Mixed repeated measures analysis of variance results for heart rate indices

Table 7 presents the results of the mixed repeated measures ANOVA, examining how the different warm-up protocols affected various HR indices over time.

Table 7.

Mixed repeated measures analysis of variance results for heart rate and zone measures

Variable		Time effect						Group effect						Time × group interaction
		F		P		ηp2		F		P		ηp2		F		P		ηp2
RHR (bpm)		266.455		<0.001		0.801		5.238		<0.001		0.284		5.081		<0.001		0.278
MHR (bpm)		295.263		<0.001		0.817		13.898		<0.001		0.513		21.819		<0.001		0.623
AHR (bpm)		139.835		<0.001		0.679		111.905		<0.001		0.894		2.115		0.074		0.138
ARR (msec)		355.524		<0.001		0.843		18.476		<0.001		0.583		5.493		<0.001		0.294
MRR (msec)		178.341		<0.001		0.730		7.192		<0.001		0.353		7.192		<0.001		0.254
HRV (msec)		280.944		<0.001		0.810		29.749		<0.001		0.693		10.062		<0.001		0.433
sRPE (AU)		295.081		<0.001		0.817		112.998		<0.001		0.895		11.643		<0.001		0.469
Zone 1		195.990		<0.001		0.748		27.496		<0.001		0.676		22.132		<0.001		0.626
Zone 2		53.647		<0.001		0.448		109.064		<0.001		0.892		60.243		<0.001		0.820
Zone 3		67.193		<0.001		0.504		39.294		<0.001		0.749		49.522		<0.001		0.790
Zone 4		62.306		<0.001		0.486		96.569		<0.001		0.880		14.057		<0.001		0.516
Zone 5		361.298		<0.001		0.846		49.501		<0.001		0.974		37.581		<0.001		0.740

RHR=Rest heart rate, MHR=Maximal heart rate, AHR=Average heart rate, ARR=Average RR interval, MRR=Maximum RR interval, HRV=Heart rate variability, sRPE=Session rating of perceived exertion

Time effects

All measured variables showed significant changes over time (all P < 0.001), with large effect sizes (ηp² ranging from 0.679 to 0.843). This means that, regardless of the group, the participants’ physiological profiles improved significantly throughout the 8-week intervention. For example, RHR (F = 266.455, P < 0.001, ηp² = 0.801) and MHR (F = 295.263, P < 0.001, ηp² = 0.817) both showed substantial reductions, indicating better cardiovascular efficiency and fitness across all groups.

Group effects

Significant differences were found between the groups in almost all variables (P < 0.001), with substantial effect sizes (ηp² up to 0.895 for AHR and session RPE [sRPE]). This suggests that the type of warm-up protocol played a significant role in shaping the athletes’ HR responses and perceived exertion. For instance, HRV (F = 29.749, P < 0.001, ηp² = 0.693) and AHR (F = 111.905, P < 0.001, ηp² = 0.894) varied significantly depending on the protocol used.

Time × group interactions

There were also significant interactions between time and group for most variables, including RHR (F = 5.081, P < 0.001, ηp² = 0.278), MHR (F = 21.819, P < 0.001, ηp² = 0.623), and sRPE (F = 11.643, P < 0.001, ηp² = 0.469). This means that the degree of improvement over time was not the same for all groups; some protocols led to greater positive changes than others. For example, the impact of each warm-up type on HRV and sRPE differed, showing that specific protocols were especially effective in enhancing cardiac recovery and reducing perceived effort.

Overall, these results highlight that not only did all participants benefit physiologically from the intervention period, but the specific warm-up protocol they followed also made a meaningful difference. The significant interactions further emphasize that some protocols were more effective than others in promoting positive adaptations in HR and exertion levels.

The results for HR zones (Zone 1–5) showed significant changes over time, with all zones demonstrating large effect sizes (ηp² ranging from 0.448 to 0.846, P < 0.001). This indicates that participants experienced notable shifts in the time spent in each HR zone during the intervention. Furthermore, significant group effects (ηp² up to 0.974, P < 0.001) and time × group interactions (ηp² up to 0.820, P < 0.001) revealed that the warm-up protocols influenced the distribution of time spent in these zones differently. For example, Zone 5 had the most significant group effect (ηp² = 0.974), suggesting that specific protocols were particularly effective at increasing high-intensity efforts.

Pairwise comparisons using Bonferroni adjustment revealed several significant differences between the warm-up protocols

Table 8 presents the results of Bonferroni-adjusted pairwise comparisons between selected warm-up protocols.

Table 8.

Pairwise comparisons using Bonferroni adjustment

Comparison		Variable		Mean difference		P		Interpretation
ADWU versus DWU		RHR		−2.16		<0.001		S
		MHR		4.45		0.020		S
		AHR		−16.41		<0.001		S
		ARR		9.88		1.000		NS
		MRR		74.58		<0.001		S
		HRV		−0.38		1.000		NS
		sRPE		−0.62		0.0018		S
ADWU versus AWU		RHR		−1.12		0.456		NS
		MHR		8.16		<0.001		S
		AHR		−19.04		<0.001		S
		ARR		19.37		0.042		S
		MRR		26.93		0.517		NS
		HRV		6.08		0.006		S
		sRPE		0.79		<0.001i		S
SIWU versus SSGWU		RHR		−1.25		0.249		NS
		MHR		0.00		1.000		NS
		AHR		12.96		<0.001		S
		ARR		−30.61		<0.001		S
		MRR		51.96		0.001		S
		HRV		9.05		0.001		S
		sRPE		2.04		0.001		S
SIWU versus IWU		RHR		−1.20		0.306		NS
		MHR		−2.91		0.475		NS
		AHR		12.00		<0.001		S
		ARR		−21.50		0.015		S
		MRR		84.77		<0.001		S
		HRV		13.02		<0.001		S
		sRPE		2.91		0.001		S

Significant differences are indicated by P<0.05. NS=Not significant, DWU=Dynamic warm-up, AWU=Analytical warm-up, ADWU=Analytical + dynamic warm-up, SSGWU=Small-sided games warm-up, IWU=Integrated warm-up, SIWU=Small-sided games + integrated warm-up, RHR=Resting heart rate, MHR=Maximum heart rate, AHR=Average heart rate, ARR=Average RR interval, MRR=Maximum RR interval, HRV=Heart Rate Variability, sRPE=Session rating of perceived exertion

• ADWU versus DWU: The ADWU protocol resulted in significantly lower RHR (mean difference = −2.16, P < 0.001), lower AHR (−16.41, P < 0.001), higher MHR (4.45, P = 0.020), higher MRR (74.58, P < 0.001), and lower sRPE (−0.62, P = 0.002) compared to DWU. No significant differences were found for ARR and HRV (P > 0.05)

• ADWU versus AWU: Compared to AWU, ADWU showed significantly higher MHR (8.16, P < 0.001), lower AHR (−19.04, P < 0.001), higher ARR (19.37, P = 0.042), higher HRV (6.08, P = 0.006), and higher sRPE (0.79, P < 0.001). RHR and MRR did not differ significantly between these groups

• SIWU versus SSGWU: The SIWU protocol produced significantly higher AHR (12.96, P < 0.001), lower ARR (−30.61, P < 0.001), higher MRR (51.96, P = 0.001), higher HRV (9.05, P = 0.001), and higher sRPE (2.04, P = 0.001) than SSGWU. No significant differences were observed in RHR or MHR

• SIWU versus IWU: SIWU also showed significantly higher AHR (12.00, P < 0.001), lower ARR (−21.50, P = 0.015), higher MRR (84.77, P < 0.001), higher HRV (13.02, P < 0.001), and higher sRPE (2.91, P = 0.001) than IWU. Differences in RHR and MHR were not significant.

In summary, the ADWU and SIWU protocols consistently led to greater improvements in HR responses, HRV, and perceived exertion compared to the other protocols.

Pairwise comparisons using Bonferroni adjustment revealed several significant differences in heart rate zones between the warm-up protocols

Table 9 summarizes the pairwise comparisons between warm-up protocols across five HR zones using Bonferroni adjustment. Significant differences (marked with *) indicate that the type of warm-up protocol had a notable impact on the time spent in specific HR zones.

Table 9.

Pairwise comparisons using Bonferroni adjustment

Comparison		Variable		Mean difference		P		Interpretation
ADWU versus DWU		Zone 1		0.77		<0.001		S
		Zone 2		−0.09		<0.001		S
		Zone 3		−0.13		<0.001		S
		Zone 4		0.09		<0.001		S
		Zone 5		0.04		<0.001		S
ADWU versus AWU		Zone 1		0.52		0.017		S
		Zone 2		−0.01		1.000		NS
		Zone 3		−0.14		<0.001		S
		Zone 4		0.11		<0.001		S
		Zone 5		0.05		<0.001		S
SIWU versus SSGWU		Zone 1		0.00		1.000		NS
		Zone 2		0.03		0.54		NS
		Zone 3		−0.18		<0.001		S
		Zone 4		0.05		<0.001		S
		Zone 5		0.03		0.009		S
SIWU versus IWU		Zone 1		0.01		1.000		NS
		Zone 2		−0.01		1.000		NS
		Zone 3		−0.15		<0.001		S
		Zone 4		0.06		<0.001		S
		Zone 5		0.03		0.032		S

S=Significance, NS=No significance, DWU=Dynamic warm-up, AWU=Analytical warm-up, ADWU=Analytical + dynamic warm-up, SSGWU=Small-Sided games warm-up, IWU=Integrated warm-up, SIWU=Small-sided games + integrated warm-up

• ADWU versus DWU: Significant differences were observed across all zones (P < 0.001). ADWU showed a higher time spent in Zone 1 and Zone 4, while DWU had greater time in Zones 2 and 3, suggesting distinct intensity profiles between the protocols

• ADWU versus AWU: Significant differences were found in Zones 1, 3, 4, and 5 (P < 0.05), with ADWU leading to more time in Zone 1 and Zone 4. No significant difference was detected in Zone 2 (P = 1.000), indicating similar moderate-intensity effects between the two protocols

• SIWU versus SSGWU: Differences emerged in Zones 3, 4, and 5 (P < 0.05), with SIWU favoring higher intensity efforts (Zone 5) and recovery periods (Zone 4). No significant changes were seen in Zone 1 or Zone 2 (P > 0.05)

• SIWU versus IWU: Significant differences were observed in Zones 3, 4, and 5 (P < 0.05), showing that SIWU promoted higher intensity activity compared to IWU, particularly in Zone 5. No meaningful differences were detected in Zone 1 or Zone 2 (P > 0.05).

DISCUSSION

This study highlights how combining warm-up routines can significantly enhance cardiovascular preparedness in U-15 soccer players. Specifically, protocols like SIWU and ADWU showed significant improvements in MHR and HRV, while also leading to better session-RPE scores. These outcomes reinforce the well-established importance of warm-ups in optimizing the body’s physiological performance. Warm-ups are known for their ability to raise core body temperature and activate muscles specifically needed for competition, which sets the stage for improved athletic results.[26,58] By increasing body temperature and stimulating neural pathways, dynamic movements help muscles become more elastic and improve blood flow, allowing athletes to achieve higher HRs during intense activity, all while avoiding excessive fatigue.[27,68] Moreover, the rise in HRV during rest after training often points to an improved parasympathetic tone, which signals better recovery.[1,69] In this study, the higher HRV values observed following combined warm-ups suggest that these routines may help balance the autonomic nervous system (ANS)—a key indicator of positive adaptation to training stressors.[4,22,70] Diverse warm-up programs like FIFA 11+, which incorporate elements such as running, dynamic stretching, plyometric drills, and agility exercises, have shown long-term benefits in improving skills like jumping, agility, and sprinting while reducing the risk of injuries.[47,50] Our findings imply that similarly diverse warm-ups “prime” young players holistically, resulting in both higher physiological outputs (MHR) and stable subjective effort ratings. This is corroborated by other studies showing that structured warm-ups produce consistent HR patterns and RPE across sessions,[4] and that metrics such as average/maximal HR, time in high-intensity heart-rate zones, and R-R interval (HRV) are strongly correlated with players’ training load and performance indicators.[30] In practical terms, the improved session-RPE responses in our combined protocols may indicate that players felt appropriately prepared yet not overloaded, reflecting an optimal balance of intensity and recovery set by the warm-up.

Dynamic warm-up exercises, such as skill-based drills, small-sided games, and plyometric movements, gradually elevate HR, improving oxygen delivery and metabolic readiness.[39,40,41,42] This process expands stroke volume and shifts the autonomic balance: During activity, sympathetic drive typically increases, but post-exercise parasympathetic rebound occurs faster when muscles are properly prepared beforehand.[70] In this study, the higher HRV observed after combined warm-ups suggests a more substantial parasympathetic influence during rest, which is widely interpreted as an indication of better adaptation and recovery following training.[30,69] For adolescents, this type of response is significant as their cardiovascular systems are undergoing rapid developmental changes. Additionally, raising muscle temperature through active movement facilitates biochemical processes within muscle fibers, improving enzyme efficiency and reducing stiffness in joints and tendons. These effects enable players to reach higher peak HRs (as evidenced by MHR) without extending recovery periods. Beyond the physical benefits, thoughtfully designed warm-ups can also positively influence athletes’ mental states. Many players report feeling more “ready” or “primed” after dynamic routines, which can reduce their perceived effort during the main training session.[4,58] In essence, warm-ups that prepare both the mind and body empower athletes to push themselves harder (reflected in higher MHR) while still finding the effort manageable—a combination that leads to better training outcomes. When comparing different types of warm-up approaches, it becomes clear why combined routines outperformed simpler methods. Analytical warm-ups, which focus solely on isolated techniques or static stretching, were likely less effective at stimulating the cardiovascular system. For example, recent research in youth soccer showed that replacing standard warm-ups with static or ballistic stretching failed to improve key skills like jumping, sprinting, or kicking speed.[37] In contrast, dynamic warm-ups that incorporate active movements and progressively higher intensities are widely recognized for their ability to enhance explosive performance.[4] The dynamic elements in the combined warm-up protocols likely helped steadily raise HRs while mimicking the intermittent bursts of activity seen during real gameplay. Programs that blend ball work or agility drills (like SIWU) likely engaged both neuromuscular and cognitive systems, creating a stimulus similar to match conditions. This combination of elements results in more comprehensive physiological activation. Structured warm-ups such as FIFA 11+ have been shown to improve vertical jump and sprint speed in the short term.[47,50,71] Similarly, the SIWU and ADWU protocols in this study likely combined dynamic exercises with soccer-specific tasks, contributing to superior physiological outcomes. However, it is worth noting that excessively long warm-ups can have adverse effects. For instance, Yanci et al. found that a 25-min warm-up increased RPE scores and even impaired sprint performance compared to shorter routines.[58] The mixed nature and balanced duration of the combined protocols in this study likely hit the “sweet spot,” providing enough intensity to prepare the body without inducing fatigue.

SSGWU deserve special attention, both as effective warm-up tools and as a way to monitor players’ readiness. These games naturally involve constant movement and decision-making, driving HRs to high levels. Coaches frequently use 3v3 or 5v5 games to simulate match-like cardiovascular loads in a time-efficient manner.[72] During warm-ups or training sessions, SSGs can stress players into higher heart-rate zones (e.g., 85%–90% MHR) while simultaneously working on their technical skills.[73]

Tracking HR during SSGWU confirms their intensity: Youth players often spend significant amounts of time above 80% MHR during these drills. The time spent in specific heart-rate zones is an important indicator of training focus and physiological stress. Consistent with this study’s findings, Lechner et al. showed that time spent in the highest heart-rate zones (zones 4–5) strongly correlates with improvements in speed, endurance, and other performance measures.[30] In simpler terms, players who spend more time in high-intensity zones during training tend to show greater improvements overall. By increasing MHR and shifting HR distribution upward, combined warm-ups may help players accumulate more quality time in these zones. This supports the idea of using SSG-style activities early in sessions as they not only effectively prepare players’ cardiovascular systems but also generate measurable data (via heart-rate monitors) that coaches can use to tailor weekly training plans.

The use of HR and HRV monitoring technologies further enhances this approach. Modern systems like Polar Team Pro integrate heart-rate straps with GPS devices, allowing coaches to track both internal loads (HR) and external loads (distance, speed) simultaneously.[72,74] These tools reliably measure average and peak HRs and automatically categorize distances covered at different speeds (e.g., jogging vs. sprinting).[75,76] Utilizing such tools means coaches can track each player’s intensity distribution week-to-week. For instance, a consistent decline in an individual’s HRV at rest might signal accumulating fatigue, prompting a lighter load in upcoming sessions.[70] Likewise, if data reveal that players are seldom entering the higher HR zones in training, the warm-up or practice design can be modified (perhaps adding an extra interval or drill) to elevate intensity. Our results underscore the utility of combining objective and subjective monitoring: RPE alone is informative, but its interpretation is enhanced when cross-referenced with HRV and HR-zone data. The literature advises focusing on individual HRV trends because group averages may mask players who are “high-responders” or “non-responders.”[70,72] In sum, pairing scientifically grounded warm-ups with wearable monitoring technology offers a powerful strategy: The coach has both a mechanism (the warm-up routines) and a feedback system (HRV/HR tracking) to optimize training stimuli and recovery in youth athletes.

Limitations and practical applications

Limitations

While this study offers important insights into the benefits of combined warm-up protocols, there are some limitations that should be kept in mind.

The research was conducted with a small group of U-15 soccer players from a single academy, which means the findings might not apply to all teams or settings. Although we tried to control factors like field conditions, time of day, and season, slight differences in the environment could still have affected the players’ HR and HRV. Even though the warm-up routines were standardized, players’ readiness or familiarity with the exercises might have influenced the outcomes. The SIWU and ADWU protocols are new and unique combinations, and the way drills were ordered or how intensity was managed could have played a role in the results. The routines were tested at fixed intervals, and longer or more frequent warm-ups were not explored. It is also worth noting that players of different ages, genders, or skill levels might respond differently due to changes in their body’s development, hormones, or maturity. So, applying these results to other groups should be done with caution. While HRV was measured under consistent conditions each week, adolescent bodies naturally experience some fluctuations in ANS function, which could add variability to the results.

Additionally, session-RPE scores are based on personal perception, which can be influenced by factors such as mood, motivation, or a player’s level of fatigue on that day. These factors might affect how strong the impact of the warm-up protocols appears. In summary, while the findings are promising, further studies with larger groups, different demographics, and refined measurement methods are needed to confirm and expand on these results fully.

Practical applications

This study offers some down-to-earth tips for coaches and trainers looking to get more out of warm-ups and track their young soccer players’ progress. Mixing things up with dynamic moves, fun game-like drills, and technical exercises can help kids get ready for action. It might even help prevent injuries, especially if you use well-known routines like FIFA 11+ or SIWU/ADWU. It also helps to make warm-ups feel more like the real game; for example, adding short-sided matches or bursts of quick sprints, so players get their HRs up to about 70–80% of their max. This not only preps them for challenging play but also gives you a quick read on their fitness. Using wearables, such as the Polar Team Pro, makes it easier to monitor HR and movement during practice. This way, you can check if players are spending enough time in the right intensity zones, and if not, you can tweak the session—maybe by throwing in some interval drills. Checking HRV, especially in the mornings, can give you a heads-up if someone needs a lighter day or more recovery. It is even better if you look at each player’s numbers instead of just the team average, so you can fine-tune training to what each kid needs. Finally, asking players how tough the session felt (using tools like session-RPE) is still a handy way to gauge effort, but it works best when combined with HR info. If a player says the session felt hard but their HR was not that high, it might be worth checking for things like stress or tiredness. If both are high, it could be time to back off a bit.

All in all, being flexible and paying attention to each player’s unique needs makes for better, safer training. Educate players on the purpose and benefits of combined warm-ups and monitoring systems. Consistent implementation and player buy-in are essential to maximizing the effectiveness of these methods. Share clear goals with players, such as reaching specific HR zones, to keep them motivated and engaged during warm-ups.

CONCLUSIONS

This study highlights the importance of a scientific and structured approach to warm-ups and monitoring in youth soccer. By incorporating dynamic, multifaceted warm-up routines and leveraging objective tools like HR and HRV tracking, coaches can better manage training loads, enhance recovery, and reduce the risk of injuries. Tailoring these strategies to players’ age and developmental stage, while continuously refining methods based on feedback from physiological and performance data, will ensure the best outcomes for young athletes.

Ethics approval and consent to participate

Participants and their legal guardians were fully informed about the study protocol. After providing their approval, legal guardians signed an informed consent form in accordance with ethical guidelines (Declaration of Helsinki, 2000). This project is registered on https://irct.behdasht.gov.ir/ (ID: IRCT20241123063806N1) and has been approved by the Research Ethic Committees of Islamic Azad university-Isfahan (Khorasgan) Branch (IR.IAU.KHUISF. REC.1403.419).

Conflicts of interest

There are no conflicts of interest.

Funding Statement

This work was supported by the Islamic Azad University, Isfahan (Khorasgan) Branch, Faculty of Physical Education and Sports Sciences (Thesis number IR.IAU.KHUISF 162964572/2024). However, no external funding or financial support was allocated to this research. The funder had no role in the study design, data collection, analysis, interpretation, writing of the report, or the decision to submit the paper for publication. All financial responsibilities related to this research, including data collection, analysis, interpretation, and manuscript preparation, were entirely borne by the student.