Effects of Contrast Potentiation on Endurance Performance and Cardiovascular Parameters in Elite Female Soccer Players

Abstract

Background/Objectives: The aim of this study was to investigate the acute effect of isometric and plyometric combined activation prior to the endurance performance assessed with the 30-15 Intermittent Fitness Test (30-15 IFT) and cardiovascular parameters. Methods: In this crossover study the data of 14 elite female soccer players aged 22.1 ± 2.9 years were assessed. The conditioning activity (CA) consisted of three sets of five seconds of maximal mid-thigh pull (IMPT), and peak force was measured, and four countermovement jumps were performed. Contact time, jump height, and reactive strength index (RSI) were assessed. Ninety seconds of rest between the sets was performed. Then, 7 min after the CA, the 30-15 IFT was performed. Results: One-way repeated measures (RM) ANOVA showed that performance during the CA did not decrease; what is more, it improved in RSI (p < 0.01). Further, paired samples t-test showed that the performance in the IFT did not change, whereas training impulse (TRIMP) was increased after CA (p = 0.039, ES = 0.61), thus the Bayesian paired test yielded only anecdotal evidence in favor of the alternative hypothesis (BF₁₀ = 1.92; error = 2%). Conclusions: The improvement in CA suggests potentiation rather than fatigue. However, the unchanged performance alongside a modest TRIMP increase should be interpreted with caution, as TRIMP alone provides a limited assessment of physiological cost. Therefore, while the applied protocol did not enhance endurance performance, further research using multiple physiological markers is needed to clarify its impact on internal load and overall efficacy.

1. Introduction

Female football has experienced rapid growth in recent years, accompanied by increasing physical demands placed on athletes [1]. Among the key determinants of on-field performance is aerobic and intermittent endurance capacity, which underpins repeated high-intensity efforts throughout a match [2]. In this context, methods to optimize acute performance or physiological efficiency during endurance tasks are of particular relevance for elite female athletes [3].

One such method for acute effects is post-activation performance enhancement (PAPE), a phenomenon in which muscular performance is transiently improved following a high-intensity conditioning activity (CA) [4,5,6]. Although traditionally studied in the context of explosive tasks (e.g., jumps, sprints), recent investigations have begun to explore whether PAPE may also benefit endurance-based activities [7,8]. The premise is that an appropriately selected CA may improve neural drive, tendon stiffness, or muscle temperature—potentially enhancing running economy or reducing cardiovascular strain during prolonged efforts [4,9].

Despite the growing interest in PAPE-based warm-up protocols among elite football teams, their use in women’s soccer remains limited and largely unstandardized. A recent randomized controlled trial conducted on highly trained female football players reported no significant acute benefits on sprint or change-of-direction performance following a potentiation warm-up involving jumps and COD drills [10]. These findings underscore that directly translating activation protocols from men’s football may not yield expected results in female athletes, and in some cases may even induce transient fatigue. While PAPE principles are increasingly explored in elite sports, robust evidence supporting their effectiveness in women’s football is still lacking [11].

However, most PAPE studies have focused on short maximal efforts (<10 s). For instance, highly trained boxers performing Wingate tests showed elevated post-test heart rate, perceived exertion, and blood lactate after CA protocols [9], suggesting that cardiovascular parameters are indeed influenced by CA. This raises an important question: can CA improve endurance without imposing undue cardiovascular stress? While PAPE is widely documented for explosive movements, its relevance to endurance performance remains debated. The recent systematic review and meta-analysis by Vasconcelos et al. [12] demonstrated only a very small and inconsistent effect (SMD = 0.15) of PAPE on endurance tasks, with low certainty of evidence, suggesting that its ergogenic potential in this domain is uncertain. Moreover, the mechanisms typically associated with PAPE—such as increased neural drive, transient phosphorylation of the myosin regulatory light chain, and improved tendon stiffness—have not been conclusively linked to enhanced outcomes in endurance tests that predominantly rely on aerobic and anaerobic metabolism [13]. This gap highlights the need for studies exploring whether neuromuscular enhancements induced by CA can translate into improved efficiency during intermittent endurance activities.

The existing literature is also limited regarding female athletes. Most PAPE studies have either excluded women or generalized findings from male-dominated samples, despite evidence that hormonal modulation and muscle fiber composition may influence potentiation responses [14]. Female athletes, particularly those in soccer, present unique physiological profiles that could alter the potentiation–fatigue balance. Consequently, investigating their specific responses to CA is crucial for developing evidence-based warm-up strategies.

Finally, contemporary warm-up practices in elite sports emphasize individualized micro-activation and priming routines to optimize readiness [15]. These strategies integrate both neuromuscular and cardiometabolic stimuli, aligning with the potential benefits sought through CA. However, whether such protocols enhance intermittent endurance while avoiding excessive cardiovascular cost remains unresolved. Therefore, the present study addresses this gap by evaluating the acute effects of a combined isometric–plyometric CA on endurance performance and cardiovascular strain in elite female soccer players.

In endurance contexts, isometric and plyometric exercises are promising candidates; thus, to date, not many studies have verified this, and some data for sprint running were provided [16]. Isometric mid-thigh pull (IMTP) permits high-force output in a fixed position, while plyometrics harness the stretch–shortening cycle and enhance tendon stiffness [17,18]. When combined, these modalities may potentiate both neural activation and elastic mechanics—potentially improving running economy and cardiovascular efficiency during intermittent exertion such as the 30-15 Intermittent Fitness Test (30-15 IFT), a typical assessment of endurance in soccer [19]. Notably, chronic training studies, such as those comparing isometric and plyometric training, have reported improvements in running economy and aerobic performance, although acute cardiovascular responses remain underexplored [9,17]. Assessing cardiovascular parameters—particularly heart rate and training impulse (TRIMP)—is important because an elevated heart rate during or after endurance exercise can indicate increased physiological cost, even when performance remains unchanged [20].

Despite theoretical and mechanistic support, empirical evidence on whether combined isometric and plyometric CA can effectively enhance intermittent endurance performance in elite female soccer players is limited. Furthermore, understanding the trade-off between performance benefits and cardiovascular costs is essential for practical applications. Therefore, the aim of this study was to investigate the acute effects of a combined isometric and plyometric CA on endurance performance (measured via the 30-15 IFT) and cardiovascular strain (via heart rate/TRIMP) in elite female soccer players.

2. Materials and Methods

2.1. Study Design

This investigation employed a randomized crossover design consisting of three sessions separated by a 7-day interval to ensure full recovery and minimize potential carryover effects. The first session included body composition assessment and familiarization with the conditioning activity (CA). The familiarization session consisted of a complete walkthrough of the CA protocol, performance of several submaximal and maximal IMTP trials, and execution of Countermovement Rebound Jump (CMRJ) on the measurement devices. Additionally, the structure of the 30–15 IFT was explained, and players completed a shortened version of the test to ensure they were accustomed to the pacing and turning demands. This familiarization was designed to minimize learning effects and improve measurement reliability. Participants were randomly assigned to two testing sequences (Group A and Group B) using an online randomization tool (www.randomizer.org). Group A completed the 30–15 IFT with the conditioning activity (CA) in the second session and without the CA in the third session, while Group B performed the sessions in the opposite order. This counterbalanced approach was implemented to minimize potential order effects. The experimental sessions were separated by 7 days to ensure full recovery and to reduce the likelihood of carryover effects. The 7 min interval between the CA and the 30–15 IFT was selected based on previous findings indicating that PAPE effects typically occur within a 4–10 min window following activation, depending on the intensity and type of exercise used [21]. This interval was chosen to align with the expected potentiation window while minimizing the risk of residual fatigue. In the second and third sessions, participants completed the 30-15 Intermittent Fitness Test (30-15 IFT): once following the CA protocol and once without it, with the order of conditions reversed between groups.

2.2. Participants

The study sample was selected using a purposive sampling approach to ensure a high level of homogeneity in terms of athletic performance and training background. All participants competed at a similar performance level and were members of the same football club, which minimized potential confounding variables related to differences in coaching methods, training load, or session structure. This approach enhanced the internal consistency of the sample and allowed for more accurate interpretation of the results in the context of the applied experimental protocol. However, this strategy inherently limited the potential sample size from the outset. Considering the exclusion of goalkeepers and the occurrence of injuries, the final sample consisted of 14 field players.

The initial sample included twenty-four female football players aged 16–28 years (mean age: 22 years), all of whom trained at the 1KS Ślęza Wrocław club and competed in the second-tier national league in Poland (Orlen I Liga Kobiet). Each player participated in approximately six training sessions per week: four technical-tactical football sessions and two strength and conditioning sessions supervised by a performance coach. All participants had at least eight years of football experience. Goalkeepers and players with recent or ongoing injuries were excluded (n = 10). Testing occurred during the final phase of preseason preparation. A post hoc sample size analysis for the applied statistical approach, with a power of 0.80 and an alpha level of 0.05, indicated an effect size of 0.58.

2.3. Body Morphology

Stature was measured with a standard anthropometer (Swiss Anthropometer, GPM Anthropological Instruments, DKSH Ltd., Zürich, Switzerland), while body mass was assessed using the InBody230 device (InBody Co., Ltd., Cerritos, CA, USA), which has demonstrated good reliability [22]. Participants stood barefoot, heels together, in an upright posture with their head aligned in the Frankfort horizontal plane. Body height and weight were recorded to the nearest 0.1 cm and 0.1 kg, respectively. Measurements adhered to the protocols established by the International Society for the Advancement of Kinanthropometry (ISAK) [23]. Participants were instructed to refrain from consuming food or engaging in strenuous activity for at least 3 h prior to measurement and to empty their bladders immediately before testing. BMI was calculated using the formula: body mass [kg]/height² [m²].

2.4. Isometric Mid-Thigh Pull (IMTP)

The isometric mid-thigh pull (IMTP) was assessed using the Muscle Meter, a handheld dynamometer (MAT Assessment, UK) designed to measure isometric force production in field-based conditions. The device features a compact force transducer connected via cable to a digital handheld unit, which provides real-time force output and stores peak values. The device was equipped with adjustable straps and handles to ensure standardized testing across subjects and to secure positioning during maximal efforts. Participants performed the test in a standing position, with the dynamometer anchored between the floor and set at mid-thigh level, mimicking a typical pulling posture. The bar height was individually adjusted to maintain sport-specific joint angles at the hip and knee. Lifting straps were used to eliminate grip fatigue and allow force transfer to be focused through the lower and upper limbs. The maximal effort trials consisted of three 5 s pulls. A standardized verbal countdown (“3, 2, 1, pull”) preceded each attempt, and participants received strong verbal encouragement. Pre-tension was allowed solely to remove slack in the system [24]. The device recorded peak isometric force (PF), which was defined as the highest force output displayed during the 5 s maximal effort.

2.5. Countermovement Rebound Jump (CMRJ)

The countermovement rebound jump (CMRJ) was assessed using a validated contact platform (Chronojump, Barcelona, Spain), which recorded flight time and subsequently estimated jump height (JH) using the equation: JH = (9.81 × flight time²)/8. The Chronojump system has demonstrated excellent reliability (α = 1.00; CV = 4.28 ± 1.95%) and sensitivity, with a smallest worthwhile change (SWC) of 1.3 cm and a typical error (TE) of 0.29 cm, resulting in a signal-to-noise ratio of 4.5 [25]. The Chronopic device, operating at a 1000 Hz sampling rate, connected the contact mat to the measurement software. Participants began in an upright position with feet shoulder-width apart and hands on hips. After a rapid countermovement to approximately 90° knee flexion, they performed a maximal vertical jump. Upon landing, they were instructed to immediately execute another jump, aiming for maximum height with minimal ground contact. Each trial consisted of a continuous series of four consecutive jumps. During each jump, participants were required to keep their legs extended in flight and to land simultaneously on both feet.

2.6. Conditioning Activity (CA)

The CA protocol included a 5 s IMTP followed by four repeated CMRJ attempts, focusing on maximal jump height and minimal ground contact time. Three sets were performed with 90 s passive rest intervals between them. Seven minutes post-CA, the 30-15 IFT was initiated. The interval between CA and the endurance test was set at 7 min to coincide with the expected time window where potentiation effects could still be expressed while minimizing the risk of residual fatigue. Previous studies on PAPE protocols have demonstrated that optimal performance responses are often observed within 4–10 min post-activation, depending on the exercise modality and athlete characteristics [21].

2.7. 30-15 Intermittent Fitness Test (30-15 IFT)

All players were previously familiar with the 30-15 IFT, which was conducted as standard during testing protocols. The test involved 30 s shuttle runs interspersed with 15 s recovery intervals. The initial speed was set at 8 km/h and increased by 0.5 km/h every 30 s [19]. Participants ran between two 40 m lines, adjusting pace based on auditory signals. During rest periods, participants walked forward to the nearest line to begin the next stage. The test has shown excellent reliability (ICC = 0.96) [19]. Final running velocity (VIFT) was recorded as the highest fully completed stage.

2.8. Preparation for the 30–15 IFT Test and Its Placement Within the Training Cycle

This study was conducted during the transitional period of the competitive football season, covering two microcycles following an intensive start phase. The 30–15 Intermittent Fitness Test (30–15 IFT) was performed twice: first at the end of the first transitional microcycle (March 30), and again at the end of the second transitional microcycle (April 6). The tests were scheduled after several days of moderate-intensity training sessions to optimize the players’ readiness for high-intensity intermittent exertion and to minimize fatigue-related interference.

The players’ physical preparation included a comprehensive warm-up based on the RAMP model (Raise–Activate–Mobilize–Potentiate), supplemented with an individual preparatory component (“individual prep”). This preparatory block consisted of 1–2 selected exercises targeting three key areas—ankle, knee, and hip/glute region—performed in one set of 6–10 repetitions per side. The “Raise” phase included general movement-based drills such as runs with arm swings, jumps, skips, lateral movements, and lunges. The “Activate” phase involved isometric contractions combined with stretching for the major lower-body muscle groups, while the “Mobilize” phase included dynamic and ballistic stretching exercises. The final “Potentiate” phase comprised speed and reactivity drills such as high-tempo skips, short accelerations, and bounding movements to stimulate neuromuscular readiness for maximal effort.

This comprehensive warm-up protocol was intended not only to raise muscle temperature and activate motor units but also to elicit appropriate neuromuscular stimulation prior to the submaximal and maximal efforts characteristic of the 30–15 IFT.

2.9. Heart Rate Zones and Training Impulse (TRIMP)

Heart rate (HR) was monitored throughout to determine HR maximum, HR mean, and HR minimum. The time spent in specific HR zones was recorded as zone 1: 50–60% HRmax; zone 2: 60–70% HRmax; zone 3: 70–80% HRmax; zone 4: 80–90% HRmax; zone 5: 90–100% HRmax. Training load was quantified using Banister’s TRIMP model [26], which incorporates training duration and HR reserve: TRIMP = t × ΔHR × y, where ΔHR = (HR_avg − HR_rest)/(HR_max − HR_rest), where t is the effort duration (minutes) and y is a sex-specific weighting factor, 0.86 × e^ (1.67 × ΔHR). TRIMP values were expressed in arbitrary units. The used device was Polar H10 (Polar Electro Oy, Kempele, Finland). The device has confirmed validity [27].

2.10. Statistical Analysis

Normality was assessed using the Shapiro–Wilk test. Data were expressed as mean ± SD, with 95% confidence intervals (CI). Homogeneity and sphericity were verified using Levene’s and Mauchly’s tests. A one-way ANOVA repeated measures ANOVA (time) was conducted to verify potentiation effects of conditioning activity. Effect sizes were calculated using partial eta-squared (η²p), interpreted as small (≤0.01), medium (≤0.06), or large (≥0.14) A paired sample t-test was performed to assess the effects of CA on endurance performance, and the within comparison with effect sizes was reported as Cohen’s d (small ≤ 0.2; medium ≤ 0.79; large ≥ 0.8) [28]. Subsequently, a Bayesian paired samples t-test was conducted using a default symmetric Cauchy prior centered at 0 with a scale of r = 0.707, as recommended by Rouder et al. [29]. This prior width balances sensitivity and conservatism in hypothesis testing and is commonly adopted as a default in applied research. A sensitivity analysis across the range r ∈ [0.3; 1.0] was also performed to verify the robustness of conclusions. For clarity, the Bayes factor (BF₁₀) represents the ratio of the likelihood of the data under the alternative hypothesis (H₁) to that under the null hypothesis (H₀). BF₁₀ > 1 indicates evidence favoring H₁, whereas BF₁₀ < 1 supports H₀. Conventionally, values of BF₁₀ between 1 and 3 are interpreted as anecdotal evidence, 3–10 as moderate evidence, 10–30 as strong evidence, and values > 30 as very strong evidence in favor of H₁ [30]. Conversely, BF₁₀ between 0.33 and 1 indicates anecdotal evidence for H₀, 0.1–0.33 moderate evidence, and <0.1 strong evidence supporting H₀. All statistical analyses were performed using Jamovi software (version 2.2.2, Jamovi, Sydney, Australia). A p-value of <0.05 was considered statistically significant.

3. Results

In

Table 1. Descriptive statistics of study participants.

Variable	Mean ± SD (95%CI)
Age [years]	22.1 ± 2.9 (20.5–23.8)
Body height [m]	1.7 ± 0.1 (1.7–1.7)
Body weight [kg]	64.2 ± 5.4 (61–67.3)
BMI [kg/m2]	22.2 ± 1.6 (21.3–23.1)
HR max [beats]	194 ± 5.1 (191.1–196.9)
HR min [beats]	60.9 ± 7 (56.8–64.9)
HRreserve [beats]	132.7 ± 9.3 (127.4–138.1)
Training experience [years]	9.9 ± 1.7 (8.8–10.9)

Abbreviations: SD—standard deviation; 95%CI—confidence interval; BMI—body mass index; HR max—maximum heart rate; HR min—minimum heart rate; HRreserve—heart rate reserve.

descriptive characteristics considering age and training experience, body morphology, and heart rate parameters are presented.

In the first step of the analysis, a one-way (time) repeated measures ANOVA was performed to assess the immediate effect of conditioning activity to assess the fitness status. Results indicated a lack of decrease in ability to force production as well as in jump height (

Table 2. One-way repeated measures ANOVA for isometric mid-thigh pull and jump performance during conditioning activity.

Variable	Set	Mean ± SD (95%CI)	One-Way Repeated Measures ANOVA
Isometric mid-thigh pull [N/kg]	1	101.6 ± 9.8 (96–107.3)	F = 1.32; η2p = 0.09; p = 0.28
	2	104.4 ± 14.1 (96.3–112.6)
	3	106.6 ± 12.4 (99.4–113.8)
Contact time [s]	1	0.212 ± 0.045 (0.186–0.238)	F = 3.07; η2p = 0.19; p = 0.07
	2	0.204 ± 0.04 (0.18–0.227)
	3	0.198 ± 0.03 (0.181–0.216)
Jump height [cm]	1	23.948 ± 4.302 (21.464–26.432)	F = 0.75; η2p = 0.05; p = 0.48
	2	24.608 ± 4.439 (22.045–27.171)
	3	24.629 ± 4.709 (21.91–27.348)
Reactive Strength Index	1	1.164 ± 0.203 (1.047–1.281)	F = 6.25; η2p = 0.32; p < 0.01
	2	1.264 ± 0.274 (1.106–1.422)
	3	1.298 ± 0.274 (1.14–1.456)

). No changes in both parameters were observed (p > 0.05). Moreover, contact time showed a trend to shorten, thus also a lack of significance (p = 0.07); however, the improvement in RSI was identified (p < 0.01).

The post hoc, detailed analysis with Bonferroni correction revealed that the values achieved in the 2nd and 3rd sets in RSI were higher than in the 1st one (p = 0.04; ES = 0.42 and p = 0.03; ES = 0.56, respectively), with a lack of differences between them (p > 0.05).

In the next step of the analysis, the effects of prior CA on the results of 30-15 IFT and cardiovascular parameters were assessed with paired sample t-test and verified with Bayesian paired samples t-test (

Table 3. Results of comparisons, paired samples t-test, and Bayesian paired samples T-Test for 30-15 IFT results and cardiovascular parameters under control and experimental conditions.

Variable	No Conditioning Activity Session (Control)	Conditioning Activity Session (Experimental)	Δ	Paired Samples T-Test		ES	Bayesian Paired Samples T-Test
	Mean ± Sd (95%CI)			t	p		BF10	Error %
VIFT [km/h]	18.04 ± 2.26 (16.73–19.34)	17.96 ± 2.08 (16.76–19.17)	0.07	0.46	0.655	0.12	0.296	0.01
Zone 1 [%]	7.46 ± 2.63 (5.94–8.98)	5.68 ± 3.37 (3.73–7.62)	1.78	1.98	0.069	0.59	1.227	0.02
Zone 2 [%]	15.91 ± 10.94 (9.59–22.23)	14.94 ± 9.48 (9.47–20.41)	0.96	0.37	0.714	0.10	0.287	0.01
Zone 3 [%]	28.82 ± 9.86 (23.12–34.51)	28.2 ± 6.34 (24.54–31.86)	0.61	0.41	0.687	0.11	0.291	0.01
Zone 4 [%]	27.14 ± 7.66 (22.72–31.56)	29.34 ± 7.61 (24.95–33.73)	−2.20	−1.22	0.243	−0.32	0.505	0.01
Zone 5 [%]	20.68 ± 10.46 (14.63–26.72)	21.84 ± 10.38 (15.84–27.83)	−1.16	−1.42	0.179	−0.38	0.619	0.01
TRIMP [a.u.]	29.66 ± 6.33 (26.01–33.32)	32.64 ± 6.57 (28.84–36.43)	−2.97	−2.30	0.039	−0.61	1.925	2.00
HR mean [beats/s]	156.93 ± 11.03 (150.56–163.3)	160.5 ± 8.7 (155.48–165.52)	−3.57	−1.98	0.077	−0.51	1.129	0.02
HR max [beats]	192.29 ± 5.86 (188.9–195.67)	193 ± 5.45 (189.85–196.15)	−0.71	−0.75	0.466	−0.20	0.344	0.01

Abbreviations: VIFT—final running velocity at the 30–15 Intermittent Fitness Test; Zone—heart rate zone; TRIMP—training impulse; HR max—maximum heart rate; HR mean—mean heart rate.

). The only parameter that showed statistically significant change was TRIMP, which was increased under experimental conditions (p = 0.04) with a medium effect size (ES = 0.61). Nevertheless, the Bayesian t-test yielded only anecdotal evidence in favor of the alternative hypothesis (BF₁₀ = 1.92; error = 2%). This Bayes factor indicates that the data are roughly twice as probable under the assumption of an effect than under the null hypothesis, yet the evidential strength remains weak.

4. Discussion

The primary objective of this study was to examine the acute effects of a combined isometric and plyometric conditioning activity (CA) on endurance performance and physiological load in elite female soccer players using the 30-15 Intermittent Fitness Test (30-15 IFT) and TRIMP-based heart rate analysis. Although performance improvements were noted during the CA itself, indicating a transient potentiation effect rather than fatigue, this did not translate into enhanced outcomes during the 30-15 IFT. Instead, the observed increase in TRIMP values may suggest a tendency toward higher cardiovascular demand, although this interpretation is limited by the fact that TRIMP alone does not fully capture physiological strain. This discrepancy indicates that, while the CA protocol was neuromuscular stimulating, its specificity to the metabolic and biomechanical demands of the subsequent endurance task remains uncertain. The absence of measurable performance enhancement in a prolonged, aerobic-dominant test such as the 30-15 IFT may also reflect the limited transfer of acute neuromuscular activation to extended efforts, despite a possible increase in central arousal.

The lack of improvement in the 30-15 IFT after activation with isometric and plyometric exercises is consistent with the findings of the meta-analysis by Vasconcelos et al. [31], including 57 comparisons (432 participants). The authors found that the effect of PAPE on endurance performance is very small, regardless of the PAPE procedure, the type of endurance testing, and the VO₂ max level of the athlete. Research on elite female and male long-distance runners shows that the effect of PAPE on endurance performance may be sex dependent [8]. The PAPE procedure consisted of supplementing the warm-up with a plyometric exercise involving 5 drop jumps from a box of the height accompanied by the highest reactive strength index (RSI) value. While the men ran the 1000 m distance 3 s faster after PAPE compared to the procedure involving only a standard warm-up, the situation was different for the women. Studies on female athletes also report inconsistent or even negative effects of PAPE. For example, in long-distance runners, drop jump–based activation improved male performance but was associated with slower times and higher lactate levels in women, suggesting greater fatigue. Similarly, Zylberberg et al. [10] found no significant benefits of PAPE on sprint or change-of-direction performance in female soccer players. These findings indicate that protocols adapted from male populations may not be optimal for women and highlight the need for lower training volumes and longer recovery periods in female-specific warm-up strategies. The different responses to PAPE in men and women may be due to differences in physique, motor skills (strength, speed, and endurance) [32,33], and the greater performance variability observed in female athletes compared to male athletes [33].

The lack of the PAPE effect found in our study after isometric and plyometric exercises in female soccer players is most likely multi-caused. One of the more important reasons seems to be that endurance performance relies more on aerobic capacity and metabolic factors instead of the neuromuscular potentiation targeted by PAPE. The physiological mechanisms associated with PAPE, including enhanced muscle fiber recruitment and increased muscle contractile properties, primarily support power-based activities rather than prolonged endurance efforts [34,35]. Moreover, the timing and intensity of activation protocols may not sufficiently influence the endurance test performance, as the 30-15 IFT relies on a sustained aerobic and anaerobic energy system rather than acute neuromuscular enhancements [12].

Although activation with isometric and plyometric exercises did not affect the outcome of the endurance test, it caused a significant increase in TRIMP. This suggests that, after activation, the athletes achieved similar performance as after a standard warm-up, potentially at a higher internal load. While this may indicate increased physiological stress, the interpretation remains limited because TRIMP alone does not fully capture the complexity of internal load. Therefore, further studies including additional physiological markers are needed before making firm recommendations regarding the use of this type of activation in female soccer players. Previous research in male football players and endurance runners has shown that higher accumulated TRIMP during training correlates with greater improvements in aerobic capacity [36,37]. However, these findings refer to chronic adaptations, whereas in the present study TRIMP was used only as an acute marker of internal load, which limits direct comparisons. Alternatively, the higher TRIMP observed after CA, although not accompanied by immediate performance benefits, could still be relevant from a training adaptation perspective. Chronic exposure to slightly higher internal loads during repeated warm-up or activation sessions might contribute to long-term improvements in aerobic capacity or fatigue tolerance, as suggested by studies linking accumulated TRIMP with enhanced VO₂ max in athletes [36,37]. Therefore, while the protocol may appear acutely inefficient, its potential role as an additional training stimulus warrants further longitudinal investigation. From a practical perspective, these findings suggest that coaches should be cautious when incorporating isometric–plyometric activation protocols before endurance-dominant tasks in female soccer players. While such activation may transiently stimulate neuromuscular performance, our results do not support its immediate use for improving intermittent endurance performance in match-like conditions. However, the observed increase in internal load could be strategically applied during training to enhance conditioning stimuli, provided it is programmed with adequate recovery and individualized to the athlete’s profile. Coaches may therefore consider using such protocols selectively in training blocks aimed at building tolerance to higher internal loads, while avoiding their application directly before competition until further longitudinal evidence is available. Beyond the findings of the current study, it is important to consider that different CA protocols, varying in intensity, duration, and recovery periods, may elicit different responses in female athletes. Previous research has indicated that lower-volume protocols with longer recovery intervals may be more suitable for women, as they appear to reduce fatigue and optimize the potentiation–fatigue balance [10]. Similarly, adjustments in the type of exercises—such as using submaximal rather than maximal isometric actions or incorporating lower-impact plyometrics—could potentially enhance tolerance and improve outcomes. Future studies should systematically compare various CA configurations in female soccer players to determine protocols that effectively stimulate potentiation without inducing excessive internal load.

Despite the rigorous design and practical relevance of the current study, several limitations must be acknowledged. The limited sample size (n = 14) is a common challenge in research involving elite athletes, where recruitment is constrained by the specificity of the population. Although the crossover design minimized inter-individual variability, the possibility of carryover effects between sessions cannot be completely ruled out, despite the 7-day washout period. Such effects, including residual fatigue or lingering potentiation, could have influenced the outcomes, even though the randomized order of conditions was intended to mitigate this risk. Although a post hoc power analysis indicated that this study was adequately powered (power = 0.80) to detect medium effect sizes (ES = 0.58), the possibility of Type II error cannot be fully excluded, particularly for smaller effects that may have gone undetected. Future studies with larger cohorts or multi-center collaborations would help confirm these findings and improve statistical robustness. The lack of additional physiological markers, such as electromyographic activity (EMG), blood lactate concentration, or muscle oxygenation, limited our ability to fully explain the mechanisms underlying the observed responses. These indicators could have clarified whether the increased TRIMP reflected greater metabolic stress, altered neuromuscular activation, or other factors contributing to internal load. The absence of such data restricts the interpretation of the cardiovascular strain inferred from TRIMP values alone. Future studies should integrate these complementary measurements to provide a more comprehensive understanding of the physiological mechanisms driving responses to CA. Further, hormonal fluctuations related to the menstrual cycle were not controlled for, which may have influenced both performance and physiological responses, given their known effects on neuromuscular function and fatigue resistance. Although many studies report no systematic effects of cycle phase on VO₂ max, heart rate, or lactate response, research suggests that moderate-intensity exercise during the mid-luteal phase can be associated with elevated cardiovascular strain, even if performance outcomes appear unchanged [38]. Furthermore, estrogen fluctuations during the late follicular phase may enhance neuromuscular efficiency and force production, whereas increased progesterone during the luteal phase may contribute to heightened fatigue and slower muscle contraction velocity [39]. Recent reviews also emphasize that the influence of menstrual cycle on strength and endurance performance is highly variable and athlete-dependent [40]. Consequently, the absence of phase tracking in this study introduces variability in physiological response—potentially affecting both potentiation and cardiovascular parameters. Future research should monitor menstrual phases to better isolate hormone-mediated effects in female athletes. Additionally, part of our results was interpreted using Bayesian analysis. While Bayesian methods provide complementary information to traditional null-hypothesis testing, their outcomes are influenced by factors such as the choice of prior distributions and sample size. In small-sample studies, Bayes factors—particularly those indicating only anecdotal evidence—should be interpreted with caution, as they may not provide robust support for or against the tested hypotheses. Future research should address these limitations by increasing biomechanical and physiological monitoring during field-based endurance tests, controlling for menstrual phase. Moreover, longitudinal studies are warranted to assess whether repeated use of PAPE-inducing warm-ups translates into meaningful improvements in aerobic or repeated-sprint performance over time, particularly when tailored to individual athlete profiles [41].

5. Conclusions

The improvement observed during the conditioning activity (CA) suggests the presence of a performance enhancement effect rather than fatigue. However, the absence of performance enhancement during the 30–15 IFT, along with a modest increase in TRIMP, should be interpreted cautiously, as TRIMP alone provides a limited perspective on physiological cost. These findings imply that, while the CA protocol was neuromuscularly stimulating, its specificity to the metabolic and biomechanical demands of the endurance task may have been insufficient. Any potential arousal effect might have been transient or undetectable during the prolonged effort. Further research using additional physiological markers is needed to clarify these responses and optimize CA strategies for endurance contexts.