Effects of post-activation performance enhancement added to general warm-up on jump, sprint, and change-of-direction performance in competitive athletes: a systematic review and meta-analysis

Abstract

Background

Post-activation performance enhancement (PAPE) is commonly used within warm-up routines to acutely enhance explosive performance, but evidence remains inconsistent. This systematic review and meta-analysis examined whether adding a PAPE conditioning activity to a general warm-up improves jump, sprint, and change-of-direction (COD) performance in trained and competitive athletes.

Methods

PubMed, Scopus, Web of Science, Embase, and SPORTDiscus were searched from inception to March 2026. Eligible studies were randomized acute experimental trials in trained or competitive athletes comparing general warm-up plus PAPE with general warm-up alone. Jump performance was the primary outcome; sprint and COD were secondary outcomes. Mean difference (MD) was used for countermovement jump (CMJ) analyses and standardized mean difference (SMD) for conceptually similar outcomes measured with different tests. Risk of bias was assessed with the Cochrane tool.

Results

Thirty-three studies were included qualitatively, and 12 contributed to at least one meta-analysis. In the primary CMJ-only analysis, PAPE significantly improved jump performance (MD = 2.41 cm, 95% CI 1.20 to 3.61; p < 0.0001; I² = 26%; 8 studies/8 effect sizes). The effect remained significant after excluding two influential studies (MD = 1.95 cm, 95% CI 0.69 to 3.21; p = 0.003; I² = 0%) and in an additional SMD-based sensitivity analysis using the same CMJ-only dataset (SMD = 0.52, 95% CI 0.23 to 0.82; p = 0.0005; I² = 0%). In the supplementary all-jump synthesis, PAPE also improved jump-related outcomes (SMD = 0.42, 95% CI 0.17 to 0.68; p = 0.001; I² = 0%). COD performance showed a favourable pooled effect (SMD = -0.75, 95% CI -1.17 to -0.33; p = 0.0005; I² = 0%), but this analysis was based on only 3 studies/3 effect sizes. Sprint performance did not show a significant pooled effect (SMD = 0.29, 95% CI -0.35 to 0.94; p = 0.37; I² = 49%).

Conclusions

Adding a PAPE conditioning activity to a general warm-up appears to acutely enhance jump performance in trained and competitive athletes, and this finding was consistent across MD-based and SMD-based analyses of the CMJ-only dataset. Preliminary and low-certainty evidence suggests possible benefits for COD performance, whereas current evidence does not support a clear sprint benefit. The findings may indicate task-specific responses, but this interpretation remains tentative because the strength of evidence was uneven across outcome domains.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13102-026-01758-x.

Background

Warm-up is an established component of sport preparation because it can influence subsequent performance through temperature-related, metabolic, neuromuscular, and psychological mechanisms [1, 2]. Systematic evidence also indicates that appropriately designed warm-up routines generally improve subsequent physical performance [3]. In applied settings, coaches frequently extend the general warm-up by adding a more intense conditioning activity in an effort to acutely enhance explosive performance.

Post-activation performance enhancement (PAPE) has therefore become a widely used warm-up strategy in sport and exercise settings. In practice, athletes and coaches often add a conditioning activity, such as heavy resistance exercise, plyometric exercise, flywheel exercise, or isometric contractions, to a general warm-up in an attempt to enhance subsequent jumping, sprinting, or change-of-direction (COD) performance. Although postactivation potentiation (PAP) has historically been used to explain such effects, the relationship between warm-up-related performance enhancement and classical PAP remains complex, and PAP should not be assumed to be the sole mechanism underpinning improved post-warm-up performance [4, 5].

Despite the popularity of this approach, the acute performance effects of PAPE remain inconsistent. Some studies have reported meaningful improvements in jump, sprint, or COD performance, whereas others have observed trivial or non-significant effects. These inconsistencies may be attributable to differences in athlete training status, conditioning activity type, exercise intensity and volume, recovery interval, performance test selection, and study design. Earlier meta-analytic work has further suggested that training status, conditioning activity prescription, and especially the rest interval after the conditioning activity can materially influence the magnitude of the response [6, 7]. Another important issue is comparator choice. Many previous studies and reviews have combined studies using passive rest, sham conditions, alternative active controls, or comparisons among different PAPE strategies, making it difficult to determine whether adding a PAPE stimulus truly provides additional value beyond a standard general warm-up.

Recent reviews suggest that the evidence may differ across outcome domains. A prior meta-analysis reported beneficial effects of PAP/PAPE-related interventions on vertical jump performance [8], whereas more recent reviews have shown that the evidence for sprint and COD performance remains mixed and may depend heavily on protocol characteristics and athlete level [9, 10]. In addition, broader recent syntheses in team-sport athletes, combat-sport athletes, and mixed athletic tasks have highlighted that the effects of PAPE vary according to comparator choice, the comprehensiveness of the underlying general warm-up, and the interaction between prescription variables and performance tests [11–13]. This distinction is especially important in sport practice because jump, sprint, and COD are related but distinct performance domains, and it should not be assumed that PAPE affects them equally.

Accordingly, the aim of this systematic review and meta-analysis was to examine the acute effects of adding a PAPE conditioning activity to a general warm-up on jump, sprint, and COD performance in trained and competitive athletes. The primary outcome was jump performance, with a specific emphasis on countermovement jump (CMJ), whereas sprint and COD performance were treated as secondary outcomes. It was hypothesised that PAPE would improve jump performance and may also benefit COD performance, whereas the effects on sprint performance would be less consistent.

Methods

Study design and registration

This study was conducted as a systematic review and meta-analysis of acute experimental studies examining the effects of post-activation performance enhancement (PAPE) strategies in trained and competitive athletes. The review was conducted and reported in accordance with PRISMA 2020 [14, 15]. The protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO; registration number: CRD420261352221).

Search strategy

A comprehensive literature search was performed in five electronic databases: PubMed, Scopus, Web of Science, Embase, and SPORTDiscus. The databases were searched from inception to 14 March 2026. Search terms were developed around the concepts of post-activation performance enhancement, athletes, warm-up, jump performance, sprint performance, and change-of-direction performance. Database-specific syntax was adapted as required. Search, screening, and synthesis procedures were informed by current systematic review guidance. Full database-specific search strategies are provided in Additional file 1.

Eligibility criteria

Eligibility criteria were defined according to the PICOS framework. Studies were eligible if they included healthy trained or competitive athletes of any sex, sport, or competitive level. Eligible interventions were acute PAPE-related conditioning activities performed after a general warm-up. The comparator had to be general warm-up alone, without any additional PAPE-related conditioning activity. The primary outcome was jump performance, especially countermovement jump (CMJ) height; secondary outcomes were sprint performance and COD performance. Only randomized acute experimental studies were included, including randomized crossover trials, randomized repeated-measures studies, and randomized parallel-group controlled trials.

Study selection

All retrieved records were exported into a reference-management software program and deduplicated before screening. Two reviewers (ZLZ and XYG) independently screened titles and abstracts against the predefined eligibility criteria, followed by full-text assessment of potentially relevant reports. Reasons for exclusion at the full-text stage were recorded. Any disagreement between reviewers was resolved through discussion and, when necessary, consultation with the corresponding author (ZQS). The study selection process is presented in the PRISMA flow diagram.

Data extraction

Data extraction was conducted using a predefined standardized form. Two reviewers (ZLZ and XYG) independently extracted study characteristics and outcome data, including first author, publication year, country, sport, participant characteristics, sample size, study design, warm-up protocol, conditioning activity type, conditioning activity load and volume, recovery interval, comparator, measurement device, number of trials, scoring method, selected time point, and outcome measures. For quantitative synthesis, means, standard deviations (SDs), and sample sizes were extracted for the eligible experimental and control conditions. Where necessary, additional calculations were performed to harmonize the data for meta-analysis. Only studies with sufficiently comparable numerical data were entered into the quantitative synthesis. Studies that satisfied the review inclusion criteria but did not provide directly poolable data for the prespecified one-study-one-effect models were retained for qualitative synthesis and narratively summarised. Any discrepancies in extracted data were resolved through discussion and, if required, consultation with the corresponding author (ZQS). Measurement and effect-size selection details for studies included in the quantitative synthesis are provided in Additional file 5.

Effect selection rules for quantitative synthesis

To avoid unit-of-analysis errors and preserve one-study-one-effect models in the primary analyses, we prespecified decision rules for selecting outcome data from studies reporting multiple post-conditioning time points, multiple eligible outcomes, or multiple PAPE conditions. For the CMJ-only primary synthesis, CMJ height was prioritised because it was the most frequently reported and methodologically comparable jump outcome. When multiple post-conditioning time points were available, we prioritised the time point that corresponded to the original study’s primary or recommended post-conditioning assessment, when this was explicitly stated. If the original study did not define a primary time point, the selected time point was chosen according to prespecified comparability criteria: consistency with the most commonly used post-conditioning window across the dataset, completeness of reported mean and SD data, and alignment with the same outcome domain used in the pooled model. Selection was not based on statistical significance or on the largest observed effect.

For the supplementary all-jump synthesis, conceptually similar jump-height outcomes were eligible, but only one effect size per study was retained. When multiple jump tests were reported, the most widely used and methodologically comparable jump-height measure was prioritised. For sprint and COD outcomes, if multiple eligible distances or tests were reported within the same study, the outcome judged to be most directly comparable with the rest of the dataset and most completely reported was selected. When a study included more than one eligible PAPE arm compared with a shared warm-up-only control, the arm selected for the primary synthesis was the one most consistent with the review question and the overall comparator framework, rather than the arm producing the largest effect. Alternative eligible arms or time points were considered qualitatively or in sensitivity analyses when appropriate. A transparent record of the selected outcome, time point, PAPE arm, and reason for selection is provided in Additional file 5.

Risk of bias assessment

Risk of bias was assessed using the Cochrane Collaboration’s risk of bias tool (original seven-domain version [16]). The following domains were evaluated: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other bias. Each domain was judged as low risk, high risk, or unclear risk. Two reviewers (ZLZ and XYG) independently assessed risk of bias, and disagreements were resolved by discussion with the corresponding author (ZQS) (Figs. 2 and 3).

Fig. 2.

Risk of bias graph. Review authors’ judgements about each risk of bias item presented as percentages across the studies included in the quantitative synthesis

Fig. 3.

Risk of bias summary. Review authors’ judgements about each risk of bias item for each study included in the quantitative synthesis

Data synthesis and statistical analysis

Where sufficient clinically and methodologically comparable data were available, formal meta-analysis was performed. Separate syntheses were conducted for jump, sprint, and COD outcomes. For jump performance, the primary quantitative synthesis focused on CMJ outcomes only. Because these studies reported the same outcome on the same scale, mean difference (MD) with 95% confidence intervals (CIs) was retained as the primary effect metric to allow direct interpretation in centimetres. In response to possible differences in measurement devices and testing protocols across CMJ studies, an additional SMD-based sensitivity analysis was conducted using the same CMJ-only dataset. A supplementary analysis pooled all eligible jump-related outcomes using standardized mean difference (SMD) with 95% CIs. For sprint and COD performance, SMD was used because the included studies did not employ identical sprint distances or identical COD tests. Statistical heterogeneity was assessed using the chi-squared test and the I² statistic. According to the predefined analytical framework used in this review, a fixed-effect model was applied when heterogeneity was low (I² < 50% and chi-squared p > 0.10), whereas a random-effects model was used when heterogeneity was substantial or when the outcome measures were more diverse. Formal subgroup analyses or meta-regression were not performed because the number of studies per outcome was small; instead, protocol type, recovery interval, athlete level, and sex were considered through structured narrative comparison.

Reporting Bias Assessment

For outcomes with at least 10 studies, small-study effects were additionally explored using Egger’s regression test. Visual inspection of funnel plots was used to complement the statistical assessment. Because the number of studies was limited for the sprint and COD syntheses, formal tests for reporting bias were not performed for those outcomes and any interpretation of possible publication bias was restricted to the all-jump synthesis.

Certainty of Evidence

The certainty of evidence for the main outcome domains was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. The certainty of evidence was judged across the domains of risk of bias, inconsistency, indirectness, imprecision, and publication bias, and rated as high, moderate, low, or very low. This assessment was performed for the main quantitative syntheses to provide an outcome-level summary of confidence in the pooled estimates. A detailed GRADE evidence profile is provided in Additional file 2.

Outcome Hierarchy

Jump performance was treated as the primary outcome domain of the review, with the CMJ-only synthesis constituting the primary quantitative analysis. The all-jump synthesis was treated as a supplementary analysis because it combined conceptually related but not identical jump-height outcomes. Sensitivity analyses were used to examine the robustness of the CMJ finding, including leave-two-out and SMD-based analyses. Sprint and COD performance were treated as secondary exploratory outcome domains because fewer studies contributed to these syntheses and the underlying tests were less homogeneous.

Results

Study Selection

A total of 1616 records were identified through database searching, including PubMed (n = 240), Scopus (n = 369), Web of Science (n = 512), Embase (n = 227), and SPORTDiscus (n = 268). After removal of 935 duplicate records, 681 records were screened by title and abstract. Of these, 499 records were excluded at the title/abstract stage, and 182 full-text reports were assessed for eligibility. No full-text reports were unavailable for retrieval. After full-text review, 149 reports were excluded, mainly because the comparator or warm-up condition did not meet the predefined eligibility criteria (n = 101). Other reasons for exclusion included non-athlete populations (n = 18), ineligible outcomes (n = 11), ineligible study design (n = 8), chronic interventions (n = 6), duplicate publication (n = 3), and non-English language (n = 2). Ultimately, 33 studies were included in the qualitative synthesis. Of these, 12 provided sufficiently comparable numerical data for at least one quantitative synthesis, whereas 21 were retained for narrative synthesis only. Reasons for non-inclusion in the quantitative synthesis are distinct from full-text exclusion reasons and are summarized in Additional file 6.

The study selection process is shown in Fig. 1.

Fig. 1.

PRISMA 2020 flow diagram of study selection

Study characteristics

The 33 included studies investigated the acute effects of adding a PAPE conditioning activity to a general warm-up in trained or competitive athletes. The 12 studies included in the quantitative synthesis comprised randomized crossover trials, randomized repeated-measures studies, and randomized parallel-group trials. Participants were drawn from a range of sports, including basketball, volleyball, soccer, sprinting, and taekwondo, and most studies assessed explosive lower-limb performance after resistance-based, plyometric, flywheel, isometric, or sport-specific conditioning activities. Conditioning activities represented in the included literature ranged from isoinertial/flywheel half-squats [17–19], isometric squats [20, 21], traditional loaded-squat or load-manipulation protocols [22–24], and unilateral/bilateral drop jumps [25], to depth-jump, plyometric, or mixed PAP/PAPE protocols [26–31]. Detailed study characteristics are presented in Table 1, and measurement-device, trial-number, scoring-method, and effect-size selection details for quantitative studies are provided in Additional file 5.

Table 1.

Characteristics of the studies included in the quantitative synthesis

Study	Participants	Design	Conditioning activity (PAPE)	Comparator	Post-CA assessment	Main outcomes	Outcome(s)	Primary synthesis role
Pavić et al. 2025 [23]	15 elite youth male basketball players; 17.0 ± 1.0 y	Randomized crossover	Flywheel half-squat, 3 × 6 reps, inertia 0.025 kg·m², 2-min rest between sets	Standardized warm-up only	1, 3, and 5 min	CMJ height	Jump	Primary meta
Jarosz et al. 2025 [28]	14 highly trained male volleyball players; 26 ± 4 y	Randomized crossover	Isometric half-back squat: ISO-1 (1 set) and ISO-3 (3 sets), each contraction 3 s	No conditioning activity (CTRL)	3, 6, and 9 min	CMJ height, relative peak power, RSImod, contraction time	Jump	Primary meta
Villalon-Gasch et al. 2020 [30]	11 elite female volleyball players; 22.18 ± 3.37 y	Randomized parallel-group	Back squat at 90% 1RM, 3 reps	Control condition without PAP activity	8 min	CMJ height	Jump	Primary meta
Stieg et al. 2011 [32]	17 collegiate female soccer players; 18.94 ± 0.74 y	Randomized repeated-measures	Depth jumps: 3, 6, 9, or 12 contacts from individualized box height, 10-s interval	0 jump condition	Post-test after intervention	Vertec jump height, relative ground reaction force	Jump	Supplementary only
Petisco et al. 2019 [6]	10 young professional male soccer players; 21.6 ± 3.2 y	Randomized counterbalanced crossover	Half-back squat at 60% 1RM × 10, 80% 1RM × 5, or 100% 1RM × 1	Standardized soccer warm-up only	5–8 min depending on outcome	H3J, SJ, CMJ, COD, RSCOD, 30-m sprint	Jump; Sprint; COD	Primary meta
Ouergui et al. 2022 [11]	27 young taekwondo athletes (14 male, 13 female); 16 ± 1 y	Randomized repeated-measures	Plyometric jumps or repeated kicking activity with different work-to-rest ratios	Standardized warm-up only	10 min	CMJ, taekwondo-specific agility, FSKT-10s, FSKT-mult	Jump; COD	Supplementary only
Biel et al. 2023 [33]	12 semi-professional basketball players; 23 ± 4 y	Randomized crossover	Bilateral or unilateral drop jumps, 3 × 5 reps, 2-min rest	No conditioning activity (CTRL)	5 and 10 min	CMJ variables, 10-m sprint, vastus lateralis stiffness	Jump; Sprint	Primary meta
Filip-Stachnik et al. 2022 [7]	14 semi-professional female volleyball players; 26 ± 3 y	Randomized crossover	Back squat at 80% 1RM performed after caffeine or placebo ingestion	Control condition without supplementation or CA	Every 2 min up to 10 min	CMJ height	Jump	Primary meta
Si et al. 2026 [5]	28 female collegiate basketball players; 20.39 ± 1.40 y	Randomized parallel-group controlled trial	Parallel back squat at 70%, 80%, or 90% 1RM, 3 × 3 reps, 90-s rest	Control group without loading stimulus	4, 8, and 12 min	CMJ, single- and double-leg approach jumps, CMJ power, vGRF, flight time, sEMG	Jump	Primary meta
Andrić et al. 2026 [24]	10 top-level team-sport athletes (3 female, 7 male); 28 ± 9 y	Randomized crossover	Flywheel eccentric-overload half-squat, 3 × 6 reps, inertia 0.025 kg·m², 2-min rest	Control warm-up	0, 3, and 6 min	CMJ, COD5m left/right, IMTP	Jump; COD	Primary meta
Krzysztofik et al. 2024 [12]	32 national-level sprinters (19 male, 13 female); males 21 ± 5 y, females 20 ± 3 y	Randomized single-blind parallel-group	Stiff-legged hops, 3 × 10 reps from 30-cm box, 1-min rest	No conditioning activity (CTRL)	5 and 10 min	CMJ, 50-m sprint	Jump; Sprint	Primary meta
Till and Cooke 2009 [13]	12 male academy soccer players; 18.3 ± 0.72 y	Randomized counterbalanced crossover	Deadlift (5RM × 5), tuck jumps (5 reps), or isometric knee extension MVC	Control warm-up	4–6 min for sprint; 7–9 min for VJ	10-m sprint, 20-m sprint, vertical jump	Jump; Sprint	Supplementary only

Risk of bias

Overall, the methodological quality of the meta-analytic evidence was acceptable, although several domains were judged as unclear because of limited reporting. Random sequence generation was often reported adequately, and outcome assessment was generally judged as low risk because most outcomes were measured using objective performance devices. Missing outcome data were also rarely a major concern. However, allocation concealment was usually unclear, and blinding of participants and personnel was frequently judged as high or unclear risk, which is understandable in acute exercise intervention studies where participants are often aware of the activity being performed.

The overall risk-of-bias summaries are shown in Figs. 2 and 3.

Meta-analysis of jump performance

Primary analysis: CMJ-only

The primary synthesis for jump performance focused on CMJ outcomes only and included 8 studies contributing 8 effect sizes. This analysis showed a significant positive effect of PAPE on CMJ performance compared with control conditions (MD = 2.41 cm, 95% CI [1.20, 3.61], p < 0.0001). Heterogeneity was low to moderate (I² = 26%, χ² p = 0.22), indicating acceptable consistency across studies.

The corresponding forest plot is shown in Fig. 4.

Fig. 4.

Primary meta-analysis of countermovement jump (CMJ) performance

Supplementary analysis: all jump outcomes

A supplementary synthesis pooled all eligible jump outcomes using standardized mean differences. This analysis demonstrated a significant overall positive effect of PAPE on jump performance (SMD = 0.42, 95% CI [0.17, 0.68], p = 0.001), with no observed statistical heterogeneity (I² = 0%, χ² p = 0.62).

The supplementary forest plot is shown in Fig. 5.

Fig. 5.

Supplementary meta-analysis of all jump-related outcomes

Sensitivity analysis

A sensitivity analysis excluding Krzysztofik et al. [28] and Villalon-Gasch et al. [34] showed that the pooled effect remained statistically significant (MD = 1.95 cm, 95% CI [0.69, 3.21], p = 0.003), while heterogeneity decreased to 0% (I² = 0%, χ² p = 0.63). This indicates that the beneficial effect of PAPE on CMJ performance was not solely driven by these studies. In addition, an SMD-based sensitivity analysis using the same 8-study CMJ-only dataset also remained significant and consistent with the MD-based result (SMD = 0.52, 95% CI [0.23, 0.82], Z = 3.47; p = 0.0005; I² = 0%). This analysis was added to examine whether the primary CMJ finding depended on the choice of MD as the effect metric (Additional file 7). In a leave-one-out sensitivity analysis of the supplementary all-jump synthesis, omission of any single study did not materially change the pooled effect (pooled SMD range 0.36 to 0.49), and all recalculated 95% confidence intervals remained above zero, supporting the robustness of the supplementary finding (Additional file 4).

The CMJ sensitivity forest plot is shown in Fig. 6.

Fig. 6.

Sensitivity analysis of countermovement jump (CMJ) performance after exclusion of Krzysztofik et al. [12] and Villalon-Gasch et al. [30]

Publication bias

For the all-jump synthesis (k = 10), visual inspection of the funnel plot did not suggest marked asymmetry. Egger’s regression did not indicate statistically significant small-study effects (Intercept = 3.31, SE = 1.51, t = 2.19, p = 0.060, 95% CI -0.17 to 6.79; the result was borderline and should be interpreted cautiously). Because the number of studies was limited for the sprint and COD syntheses, formal tests for reporting bias were not performed for those outcomes.

The funnel plot is shown in Fig. 7.

Fig. 7.

Funnel plot for all jump-related outcomes

Meta-analysis of sprint performance

Sprint performance was analysed using standardized mean differences because the included studies assessed sprint performance over different distances. This secondary exploratory synthesis included 3 studies contributing 3 effect sizes. The pooled random-effects analysis showed no significant effect of PAPE on sprint performance (SMD = 0.29, 95% CI [-0.35, 0.94], p = 0.37), with borderline moderate heterogeneity (I² = 49%, χ² p = 0.14). Overall, the available evidence did not support a clear acute benefit of PAPE for sprint performance.

The sprint forest plot is shown in Fig. 8.

Fig. 8.

Meta-analysis of sprint performance

Meta-analysis of change-of-direction performance

COD performance was analysed using standardized mean differences because the included studies did not employ identical COD tests. This secondary exploratory synthesis included 3 studies contributing 3 effect sizes. The pooled random-effects analysis demonstrated a favourable effect of PAPE on COD performance (SMD = -0.75, 95% CI [-1.17, -0.33], p = 0.0005), with no observed heterogeneity (I² = 0%, χ² p = 0.67). Because lower times indicate better COD performance, the negative pooled estimate favoured the experimental condition. However, the small evidence base means that this result should be interpreted as preliminary.

The COD forest plot is shown in Fig. 9.

Fig. 9.

Meta-analysis of change-of-direction (COD) performance

Narrative synthesis of studies not included in the meta-analysis

Of the 33 studies included in the qualitative synthesis, 21 were not entered into the quantitative synthesis and were therefore narratively synthesised. These studies were not treated as full-text exclusions; rather, they were retained because they provided relevant evidence on acute PAPE responses but did not provide a sufficiently compatible contrast, outcome, or data structure for the prespecified pooled models. Common reasons for non-inclusion in meta-analysis included repeated sprint ability outcomes that were not pooled with single linear sprint outcomes, sport-specific kicking or swim-start outcomes that were not comparable with the prespecified jump, sprint, or COD syntheses, combined ergogenic strategies or co-interventions that limited direct attribution to PAPE alone, and complex multi-condition designs that were not suitable for the final one-study-one-effect model. A study-level list of these reasons is provided in Additional file 6. Overall, the narrative evidence suggested that acute PAPE responses were protocol-dependent and varied according to the type of conditioning activity, recovery interval, co-interventions, and specificity of the outcome measure.

Summary of quantitative findings

Taken together, the quantitative synthesis showed that PAPE had a significant positive effect on jump performance, both in the CMJ-only primary analysis and in the broader all-jump supplementary analysis. The additional CMJ-only SMD sensitivity analysis supported the same conclusion, indicating that the primary jump finding was not dependent on using MD as the effect metric. COD performance showed a favourable pooled effect but was based on only 3 studies/3 effect sizes and should therefore be interpreted as preliminary. Sprint performance did not show a significant benefit. Thus, the overall pattern supports the clearest acute benefit for jump-related outcomes, with weaker and more exploratory evidence for COD and sprint outcomes.

The main quantitative findings are summarized in Table 2.

Table 2.

Summary of the main quantitative findings, including the number of studies and effect sizes per analysis

Analysis	Role in manuscript	Model	Effect metric	Studies / effect sizes (k/n)	Participants (Exp/Control)	Pooled effect	95% CI	P value	Heterogeneity (I²)
CMJ-only	Primary analysis	Fixed-effect	MD (cm)	8 / 8	110 / 86	2.41	1.20 to 3.61	< 0.0001	26%
CMJ-only (leave-two-out: excluding Krzysztofik [12] and Villalon-Gasch [30])	Sensitivity analysis	Fixed-effect	MD (cm)	6 / 6	85 / 68	1.95	0.69 to 3.21	0.003	0%
CMJ-only (SMD sensitivity analysis)	Sensitivity analysis	Random-effects	SMD	8 / 8	110 / 86	0.52	0.23 to 0.82	0.0005	0%
All jump outcomes	Supplementary analysis	Random-effects	SMD	10 / 10	139 / 115	0.42	0.17 to 0.68	0.001	0%
Sprint	Secondary exploratory analysis	Random-effects	SMD	3 / 3	41 / 35	0.29	-0.35 to 0.94	0.37	49%
Change-of-direction (COD)	Secondary exploratory analysis	Random-effects	SMD	3 / 3	47 / 47	-0.75	-1.17 to -0.33	0.0005	0%

Certainty of evidence

Using the GRADE framework, the certainty of evidence was judged as moderate for the CMJ-only primary synthesis and for the supplementary all-jump synthesis, reflecting generally consistent findings but some limitations related to study reporting and possible small-study effects. The certainty of evidence for COD performance was judged as low because the pooled effect was based on a small number of studies despite low statistical heterogeneity. The certainty of evidence for sprint performance was also judged as low because the pooled estimate was imprecise, the number of included studies was small, and heterogeneity approached a moderate level. A detailed outcome-level GRADE summary is provided in Additional file 2.

Discussion

Principal findings

The main finding of this systematic review and meta-analysis was that adding a PAPE conditioning activity to a general warm-up produced a significant acute improvement in jump performance in competitive and trained athletes. This positive effect was evident both in the primary CMJ-only synthesis and in the supplementary synthesis including all eligible jump outcomes. In contrast, the COD finding should be interpreted as preliminary because it was based on a much smaller evidence base, and sprint performance did not demonstrate a statistically significant benefit. Therefore, the present findings indicate strong support for jump performance, limited support for COD performance, and inconclusive findings for sprint performance.

Interpretation of jump findings

Jump performance was the most consistently supported outcome in the present review. In the CMJ-only analysis, PAPE significantly improved jump height, and this result remained significant after exclusion of potentially influential studies, while heterogeneity decreased to zero. This pattern is plausible because many conditioning activities used in the included studies shared mechanical features with vertical jump tasks. Resistance, flywheel, isometric, and plyometric stimuli may transiently increase motor-unit recruitment, neural drive, muscle-tendon stiffness, and readiness for rapid vertical force production after sufficient recovery. Because CMJ height is closely aligned with these acute neuromuscular changes, jump performance may be more responsive to PAPE than tasks requiring more complex movement coordination. The present findings are broadly consistent with earlier syntheses showing beneficial effects of PAP/PAPE-related interventions on vertical jump performance [7, 8]. They are also compatible with recent broader reviews indicating that jump outcomes are among the most responsive athletic tasks when conditioning activity type and recovery timing are appropriately prescribed [11–13].

Interpretation of COD findings

A favourable pooled effect was observed for COD performance; however, this result should be regarded as preliminary rather than definitive. Only three studies contributed data to this analysis, and the certainty of evidence was judged as low despite the absence of statistical heterogeneity. From a mechanistic perspective, COD tasks may benefit from PAPE because they require rapid braking, force absorption, re-acceleration, and directional reorientation, all of which involve high levels of lower-limb force production. However, COD performance also depends on task-specific technique, approach speed, turning angle, body positioning, and perceptual-motor demands. Therefore, the present finding suggests that PAPE may benefit COD performance under some conditions, but stronger evidence is needed before a consistent COD benefit can be assumed [9, 11, 13].

Why sprint performance did not improve significantly

Unlike jump performance, sprint performance did not show a significant pooled benefit. The confidence interval crossed zero and heterogeneity approached a moderate level, indicating that the acute response of sprint performance to PAPE is more variable and less predictable. This may be because sprinting depends not only on lower-limb force production but also on horizontal force orientation, step frequency, step length, trunk position, inter-limb coordination, stiffness regulation, and technical execution. Residual fatigue after the conditioning activity may also interfere with sprint mechanics when the recovery interval is not appropriate for the athlete or protocol. Therefore, improvements in jump performance should not be assumed to transfer to sprint performance without direct athlete-specific testing. Recent reviews in sprinters likewise suggest that sprint-related responses depend heavily on protocol design, rest interval, and athlete level [6, 7, 10–12].

Relation to the broader evidence base

The present review contributes to the existing literature by applying a stricter and more comparator-specific eligibility framework than many broader PAPE-related reviews. In particular, this review focused on studies comparing general warm-up plus PAPE with general warm-up alone, thereby reducing one major source of interpretive ambiguity. This distinction is important because it moves the question from whether PAPE can work under some conditions to whether adding PAPE to a general warm-up improves performance beyond warm-up alone. This framing also responds to concerns from recent methodological reviews that many PAPE studies do not adequately separate the effects of the conditioning activity from those of the general warm-up itself [12]. This interpretation is also consistent with broader meta-analytic and conceptual literature indicating that acute responses are shaped by conditioning activity mode, load and volume prescription, recovery duration, athlete training status, and the distinction between classical PAP and the broader PAPE construct [5–7, 11–13, 32, 33].

Because the number of studies per outcome was small, the present review could not reliably test athlete level, sex, conditioning activity mode, load, volume, or recovery interval using formal subgroup analysis or meta-regression. However, the included studies suggest that these factors remain central to interpretation. Resistance-based, isometric, plyometric, and flywheel protocols may produce different balances between potentiation and residual fatigue, and the optimal recovery interval appears likely to differ according to the conditioning activity and athlete characteristics. These issues are especially important when applying PAPE outside jump testing, because COD and sprint tasks impose additional technical and biomechanical demands beyond vertical force production.

Findings from studies not entered into the meta-analysis

Of the 33 studies included in the qualitative synthesis, 21 were narratively synthesised only. These studies were retained to provide context for acute PAPE responses but were not pooled because their outcomes, comparator structures, co-interventions, or reporting formats were not sufficiently compatible with the final quantitative models. The revised supplementary table separates these qualitative-only studies from full-text exclusions and provides a study-level reason for non-inclusion in meta-analysis. This distinction is important because exclusion from quantitative synthesis does not imply that a study failed the review eligibility criteria; rather, it reflects limited poolability within the prespecified one-study-one-effect framework.

Methodological considerations

The methodological appraisal showed that the overall quality of the meta-analytic evidence was acceptable, but several limitations in reporting were common. Random sequence generation was often reported adequately, and outcome assessment was generally judged as low risk because most outcomes were measured using objective performance devices. Missing outcome data were also rarely a major concern. However, allocation concealment was usually unclear, and blinding of participants and personnel was frequently judged as high or unclear risk, which is understandable in acute exercise intervention studies where participants are often aware of the activity being performed.

Practical implications

From a practical perspective, the present findings indicate that PAPE strategies should be prioritized when the immediate goal is to enhance jump-related performance, because this was the outcome domain with the strongest and most consistent evidence. The conditioning activity should be selected according to the athlete’s strength level, sport background, and tolerance to fatigue, rather than applied as a uniform warm-up addition. Recovery timing should also be individualized. In the studies included in the quantitative synthesis, post-conditioning assessments were commonly performed after several minutes of recovery, often within approximately 3–10 min, with some protocols extending to 12 min. This suggests that practitioners should identify an athlete-specific timing window through repeated testing rather than relying on a fixed recovery interval. For COD tasks, PAPE may be considered when the target movement involves explosive braking and re-acceleration, but its use should be verified with the specific COD test or sport movement of interest. For sprinting, coaches should avoid assuming that improvements in jump or COD performance will transfer to sprint performance; sprint or acceleration outcomes should be tested directly before using PAPE as a sprint-specific warm-up strategy.

Strengths and limitations

This review has several strengths. First, it used a clearly defined and practically relevant comparator framework centred on general warm-up plus PAPE versus general warm-up alone. Second, it distinguished between primary and supplementary syntheses for jump performance, which improved interpretability. Third, it combined quantitative synthesis with narrative contextualisation of non-pooled studies rather than simply ignoring studies that could not be entered into the meta-analysis. Fourth, sensitivity analyses supported the robustness of the main jump finding, including an additional SMD-based analysis of the CMJ-only dataset. However, several limitations should also be acknowledged. First, the number of studies included in the sprint and COD syntheses was small, limiting statistical precision and reducing confidence in those pooled estimates. Second, the evidence base was uneven across outcomes, with strong support for jump performance, limited support for COD performance, and inconclusive findings for sprint performance. This imbalance constrains the interpretation that PAPE responses are task-specific. Third, the included studies varied in conditioning activity type, athlete characteristics, measurement devices, scoring methods, and post-conditioning assessment timing, which may have contributed to clinical and methodological heterogeneity even when statistical heterogeneity was low. Fourth, although one-study-one-effect decision rules were used to reduce unit-of-analysis errors, some potentially relevant information from alternative time points, outcomes, or PAPE arms could not be incorporated into the primary pooled models. Fifth, formal subgroup analyses and meta-regression were not performed because the number of studies per outcome was too small to support reliable moderator testing. Sixth, methodological reporting was incomplete in several studies, particularly for allocation concealment, selective reporting, and some measurement-protocol details. Finally, publication bias and other small-study effects cannot be excluded, especially for jump-related outcomes.

Future research

Future research should prioritise well-reported randomized trials using clearly defined comparator conditions and standardized reporting of mean values, standard deviations, and sample sizes for all relevant outcomes. Future studies should also report measurement devices, number of trials, scoring method, selected or recommended post-conditioning time point, and complete data for all tested time points. More studies are particularly needed for sprint and COD performance, where the current evidence base remains limited. Researchers should also aim to clarify the influence of conditioning activity type, recovery interval, athlete level, sex, and study design on acute PAPE responses. Future studies should report the content and completeness of the underlying general warm-up more explicitly, because recent methodological reviews have identified poor comparator control and insufficient warm-up reporting as recurring limitations in this area [12]. Future studies should also report the full structure of the warm-up, the exact timing of post-conditioning assessments, and the rationale for individualized recovery windows more transparently, because the wider warm-up, PAP/PAPE, and game-day priming literature indicates that movement specificity, the balance between potentiation and residual fatigue, and competition-context implementation can materially influence acute outcomes [3, 30, 35–39]. More recent syntheses and comparator-focused studies have further clarified terminology, prescription variables, and the role of warm-up comparators in shaping acute responses to PAPE [19, 21, 31, 40–45]. Collectively, these reports reinforce the need for better reporting of conditioning activity content, recovery timing, and task-specific implementation when translating PAPE protocols into applied sport settings [19, 21, 31, 40–45].

Conclusions

In conclusion, adding a PAPE conditioning activity to a general warm-up appears to produce a meaningful acute benefit for jump performance in competitive and trained athletes. Preliminary and low-certainty evidence suggests potential benefits for COD performance, but this finding should be interpreted cautiously because it was based on a small number of studies. In contrast, current evidence does not demonstrate a clear benefit for sprint performance. Overall, the findings suggest possible task-specific effects, although this interpretation remains tentative because the strength of evidence is uneven across performance domains.

Abbreviations

CA

conditioning activity

CMJ

countermovement jump

COD

change of direction

CTRL

control

FSKT

Frequency Speed of Kick Test

H3J

horizontal triple jump

IMTP

isometric mid-thigh pull

RSImod

reactive strength index modified

RSCOD

reactive strength change of direction

sEMG

surface electromyography

SJ

squat jump

vGRF

vertical ground reaction force

VJ

vertical jump

CI

confidence interval

GRADE

Grading of Recommendations Assessment, Development and Evaluation

MD

mean difference

PAP

post-activation potentiation

PAPE

post-activation performance enhancement

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

PROSPERO

International Prospective Register of Systematic Reviews

RoB

risk of bias

SD

standard deviation

SMD

standardized mean difference

Authors’ contributions

ZLZ conceived the review question, performed the literature search, screening, data extraction, data synthesis, and drafted the manuscript. XYG contributed to study screening, interpretation of the findings, and critical revision of the manuscript. ZQS supervised the study, contributed to the interpretation of the results, and critically revised the manuscript. All authors read and approved the final manuscript.

Funding

No specific funding was received for this study.

Data availability

All data analysed during this study are included in this published article and its supplementary information files. Detailed database-specific search strategies are provided in Additional file 1. The GRADE evidence profile is provided in Additional file 2, Egger’s regression output for the all-jump synthesis is provided in Additional file 3, and leave-one-out sensitivity results for the all-jump synthesis are provided in Additional file 4. Additional extracted data supporting the findings of this study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

Not applicable. This study is a systematic review and meta-analysis of previously published studies.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.