Integrating strength, speed, and endurance: a comprehensive training model for 100m and 400m sprints

troduction: Sprint performance in the 100m and 400m events depends on an optimal balance of strength, speed, and endurance. Traditional training often isolates these components, whereas an integrated approach may yield superior performance adaptations. Objective: This study examines the effects of a combined strength, speed, and endurance train- ing model on sprint performance. Methodology: Thirty trained sprinters were randomly assigned to an experimental group, fol- lowing an integrated training regimen, or a control group, adhering to traditional methods. The 12-week intervention incorporated resistance training, sprint drills, and endurance condition- ing. Pre- and post-test assessments evaluated sprint times, acceleration, stride mechanics, and fatigue resistance. Statistical analyses, including normality tests and comparative measures, de- termined performance improvements. Results: The experimental group showed significant improvements in 100m sprint time (mean reduction: 0.23 ± 0.06 s, p < 0.01) and 400m sprint time (mean reduction: 1.12 ± 0.18 s, p < 0.01), alongside enhancements in acceleration (Δvelocity at 10m: +0.27 m/s) and stride fre- quency (+0.18 Hz). Discussion: These findings align with existing research on the benefits of strength and plyome- tric training for sprint mechanics and endurance training for sustaining high-intensity efforts. The integrated approach provides a holistic framework for optimizing sprint performance. Conclusion: Combining strength, speed, and endurance training enhances sprint performance more effectively than traditional methods. Coaches should implement structured periodization models to optimize adaptations. Future research should explore long-term physiological re- sponses and leverage wearable technology for real-time performance monitoring. Keywords Sprint performance, strength training, speed development, endurance training, track and field. Resumen Introducción: El rendimiento en sprint en las pruebas de 100 y 400 m depende de un equilibrio óptimo entre fuerza, velocidad y resistencia. El entrenamiento tradicional suele aislar estos componentes, mientras que un enfoque integrado puede producir adaptaciones superiores del rendimiento. Objetivo: Este estudio examina

performance monitoring. Keywords Sprint performance, strength training, speed development, endurance training, track and field. Resumen Introducción: El rendimiento en sprint en las pruebas de 100 y 400 m depende de un equilibrio óptimo entre fuerza, velocidad y resistencia. El entrenamiento tradicional suele aislar estos componentes, mientras que un enfoque integrado puede producir adaptaciones superiores del rendimiento. Objetivo: Este estudio examina los efectos de un modelo de entrenamiento com- binado de fuerza, velocidad y resistencia en el rendimiento en sprint. Metodología: Treinta sprinters entrenados fueron asignados aleatoriamente a un grupo experimental, siguiendo un régimen de entrenamiento integrado, o a un grupo control, siguiendo métodos tradicionales. La intervención de 12 semanas incorporó entrenamiento de resistencia, ejercicios de sprint y acondicionamiento de resistencia. Las evaluaciones pre y postest evaluaron los tiempos de sprint, la aceleración, la mecánica de la zancada y la resistencia a la fatiga. Los análisis estadís- ticos, que incluyeron pruebas de normalidad y medidas comparativas, determinaron mejoras en el rendimiento. Resultados: El grupo experimental demostró mejoras significativas en los tiempos de sprint, la eficiencia de la aceleración y la capacidad de resistencia en la prueba de 400 m (p < 0,05). El entrenamiento de fuerza aumentó la producción de fuerza y la longitud de zancada, los ejercicios de velocidad refinaron la frecuencia de zancada y el entrenamiento de resistencia mejoró la resistencia a la fatiga. Discusión: Estos hallazgos coinciden con la investi- gación existente sobre los beneficios del entrenamiento de fuerza y pliométrico para la mecá- nica del sprint y el entrenamiento de resistencia para mantener esfuerzos de alta intensidad. El enfoque integrado proporciona un marco holístico para optimizar el rendimiento en el sprint. Conclusión: La combinación de entrenamiento de fuerza, velocidad y resistencia mejora el ren- dimiento en el sprint con mayor eficacia que los métodos tradicionales. Los entrenadores de- berían implementar modelos de periodización estructurados para optimizar las adaptaciones. Las investigaciones futuras deberían explorar las respuestas fisiológicas a largo plazo y apro- vechar la tecnología portátil para la monitorización del rendimiento en tiempo real. Palabras clave Rendimiento de velocidad, entrenamiento de fuerza, desarrollo de velocidad, entrenamiento de resistencia,

sprint con mayor eficacia que los métodos tradicionales. Los entrenadores de- berían implementar modelos de periodización estructurados para optimizar las adaptaciones. Las investigaciones futuras deberían explorar las respuestas fisiológicas a largo plazo y apro- vechar la tecnología portátil para la monitorización del rendimiento en tiempo real. Palabras clave Rendimiento de velocidad, entrenamiento de fuerza, desarrollo de velocidad, entrenamiento de resistencia, atletismo. Integrating strength, speed, and endurance: a comprehensive training model for 100m and 400m sprints Integración de fuerza, velocidad y resistencia: un modelo de entrenamiento integral para carreras de 100 y 400 m

2025 (junio), Retos, 67, 1200-1210 ISSN: 1579-1726, eISSN: 1988-2041 https://recyt.fecyt.es/index.php/retos/index 1201 Introduction The 100-meter (100m) and 400-meter (400m) sprints are fundamental events in track and field, requir- ing an optimal balance of strength, speed, and endurance. The 100m sprint predominantly emphasizes explosive power, acceleration, and maximal velocity, while the 400m event necessitates a combination of anaerobic power and endurance to sustain high-intensity performance throughout the race (Haugen et al., 2019). Given these distinct yet overlapping physiological demands, an effective sprint training program must integrate multiple training components to maximize performance outcomes. Despite the extensive research on sprint performance, existing training methodologies often remain fragmented, focusing on isolated components rather than a holistic integration of strength, speed, and endurance training. Many studies have examined the individual effects of strength training on power output, speed drills on stride mechanics, and endurance conditioning on fatigue resistance (Beattie et al., 2017; Rodríguez-Rosell et al., 2017). However, limited research has explored the longitudinal effects of a fully integrated training model that systematically balances these elements to optimize sprint per- formance. Furthermore, inconsistencies in training protocols, variation in athlete responsiveness, and potential interference effects between concurrent strength and endurance training present challenges in applying an integrated approach effectively (Stewart, 2014). Addressing these gaps, this study seeks to provide a structured and scientifically grounded training model that synthesizes these critical com- ponents. Recent advancements in sports science have catalyzed a shift from traditional, isolated training methods toward integrated training models that concurrently develop strength, speed, and endurance (Almquist et al., 2019). Hybrid training methodologies, incorporating resistance training, sprint drills, and endur- ance conditioning, have been shown to enhance neuromuscular function, sprint mechanics, and meta- bolic efficiency (Beattie et al., 2017). The physiological basis for integrating these elements lies in their complementary benefits: strength training enhances force production and stride length, speed training improves stride frequency and neuromuscular coordination, and endurance training enhances fatigue resistance and metabolic efficiency (Batista et al., 2020). When appropriately structured, this integra- tion optimizes all phases of sprinting—acceleration, maximal velocity, and fatigue resistance—resulting in superior overall performance. Empirical studies underscore the significance of

lies in their complementary benefits: strength training enhances force production and stride length, speed training improves stride frequency and neuromuscular coordination, and endurance training enhances fatigue resistance and metabolic efficiency (Batista et al., 2020). When appropriately structured, this integra- tion optimizes all phases of sprinting—acceleration, maximal velocity, and fatigue resistance—resulting in superior overall performance. Empirical studies underscore the significance of integrating strength, speed, and endurance components for optimizing sprint performance. Loturco et al., (2015) demonstrated that elite 400m sprinters who engaged in concurrent strength and sprint training exhibited significant improvements in maximal speed and fatigue resistance. Similarly, Almquist et al., (2019) reported that combining heavy resistance training with plyometric exercises led to greater improvements in sprint performance compared to tra- ditional sprint-only regimens. Nevertheless, many existing training programs continue to emphasize isolated training components rather than a holistic, structured approach. This underscores the need for a scientifically grounded, integrated training model that optimizes adaptation and performance out- comes. Objectives and Hypotheses This study aims to: 1. Evaluate the impact of an integrated strength, speed, and endurance training model on sprint performance in 100m and 400m athletes, focusing on key performance indicators such as accel- eration, maximal velocity, and fatigue resistance. 2. Analyze the physiological adaptations resulting from the combined training approach, particu- larly improvements in strength, anaerobic power, and endurance capacity. 3. Compare the effectiveness of integrated training against traditional sprint training methods to determine whether a multifaceted approach yields superior performance outcomes. 4. Identify practical implications for sprint coaching, providing evidence-based recommendations for optimizing training regimens in competitive sprinting. Based on the available literature, we hypothesize that:

2025 (junio), Retos, 67, 1200-1210 ISSN: 1579-1726, eISSN: 1988-2041 https://recyt.fecyt.es/index.php/retos/index 1202 • The integrated training model will lead to greater improvements in acceleration, stride effi- ciency, and fatigue resistance compared to traditional methods. • Athletes undergoing integrated training will exhibit superior adaptations in neuromuscular co- ordination, metabolic efficiency, and power output. • The combined training approach will enhance sprint performance across both short (100m) and long sprint (400m) events by optimizing strength, speed, and endurance development in a sys- tematic manner. Method Study Design This study employed a quasi-experimental pre-test and post-test design to examine the effects of an integrated strength, speed, and endurance training model on 100m and 400m sprint performance. A quasi-experimental approach was chosen due to practical constraints in controlling all external training variables while maintaining ecological validity in a competitive setting. The intervention lasted 12 weeks, structured using a progressive periodization framework to optimize physiological and neuro- muscular adaptations. Participants A total of 30 competitive male sprinters, aged 18–25 years, were recruited from national and collegiate- level track and field teams. Participants were stratified by performance level and then randomly as- signed into two groups to ensure homogeneity: • Experimental Group (n = 15): Received an integrated training model incorporating strength, speed, and endurance components. • Control Group (n = 15): Followed a conventional sprint training program focusing primarily on sprint drills and general strength training. Inclusion Criteria • Minimum of three years of structured sprint training experience. • No musculoskeletal injuries in the past six months. • Training frequency of at least five sessions per week before participation. To minimize assessment bias, performance evaluators were blinded to group assignments. Additionally, participants were instructed to maintain consistent sleep patterns and dietary intake. Recovery prac- tices such as hydration and stretching routines were monitored but not strictly controlled, representing a potential limitation. All participants provided written informed consent, and the study was approved by the Institutional Ethics Review Board. Table 1. Descriptive Statistics of Within-Subject Factor Levels (Age, Weight, Height) Variable Group Mean ± SD Min Max Age (years) Experimental 21.3 ± 2.1 18 25 Control 21.1

as hydration and stretching routines were monitored but not strictly controlled, representing a potential limitation. All participants provided written informed consent, and the study was approved by the Institutional Ethics Review Board. Table 1. Descriptive Statistics of Within-Subject Factor Levels (Age, Weight, Height) Variable Group Mean ± SD Min Max Age (years) Experimental 21.3 ± 2.1 18 25 Control 21.1 ± 2.0 18 25 Weight (kg) Experimental 72.5 ± 5.8 65 81 Control 72.8 ± 5.6 66 82 Height (cm) Experimental 178.6 ± 5.9 170 187 Control 177.9 ± 6.1 169 186 The independent t-test showed no significant baseline differences in age, weight, or height between groups (p > 0.05), ensuring comparability before intervention.

2025 (junio), Retos, 67, 1200-1210 ISSN: 1579-1726, eISSN: 1988-2041 https://recyt.fecyt.es/index.php/retos/index 1203 Training Protocol The experimental group followed a structured three-phase training model, integrating strength, speed, and endurance components to optimize sprint performance. Training was conducted five days per week, with one recovery session per week. Table 2. Weekly Training Structure for Experimental Group Phase Weeks Training Focus Sessions/Week Load/Intensity Strength Development 1-4 Squats, Deadlifts, Power Cleans, Bounding, Resisted Sprints 5 3-5 sets, 85-90% 1RM Speed Development 5-8 Sprint Mechanics, Flying Sprints, Contrast Training 5 Maximal Velocity, Explosive Move- ments Endurance Mainte- nance 9-12 Sprint Endurance Work, Lactate Tolerance Training, Ta- pering 5 90-95% Sprint Effort The control group followed a traditional sprint training model that included: • Sprint Drills: Acceleration drills, flying sprints, and tempo runs. • Moderate Resistance Training: Squats, deadlifts, and Olympic lifts at 60–75% 1RM. • General Endurance Runs: 400m–800m repetitions at 70–80% max effort. Testing Procedures Performance and physiological (neuromuscular, metabolic) parameters were measured at baseline and post-intervention using standardized assessment protocols: • Sprint Performance: 100m and 400m sprint times measured with electronic timing gates (ICC = 0.97). • Strength Assessments: 1RM tests for squat, deadlift, and power clean (ICC = 0.94–0.96). • Reactive Strength Index (RSI): Drop-jump test to evaluate plyometric efficiency. • Sprint Kinematics: Stride length, frequency, and ground contact time analyzed via high-speed video tracking (200Hz camera; ICC = 0.92). • Lactate Threshold: Blood lactate concentration post-400m trials to assess endurance adapta- tion. To control for external factors, participants maintained a standardized warm-up routine before all tests and refrained from high-intensity training 48 hours before assessments. Note: ICC (Intraclass Correlation Coefficient) is a statistical measure used to assess the reliability and consistency of measurements. Test of Normality A Shapiro-Wilk test was conducted to assess the normality of key variables before statistical analyses. Table 3. Shapiro-Wilk Normality Test Results Variable Group W Statistic p-value Normal Distribution (p > 0.05) 100m Sprint Time (Pre-Test) Experimental 0.972 0.423 Yes Control 0.968 0.376 Yes 100m Sprint Time (Post-Test) Experimental 0.963 0.321 Yes Control 0.959 0.298 Yes 400m Sprint Time (Pre-Test) Experimental 0.975 0.482 Yes Control 0.970 0.412

assess the normality of key variables before statistical analyses. Table 3. Shapiro-Wilk Normality Test Results Variable Group W Statistic p-value Normal Distribution (p > 0.05) 100m Sprint Time (Pre-Test) Experimental 0.972 0.423 Yes Control 0.968 0.376 Yes 100m Sprint Time (Post-Test) Experimental 0.963 0.321 Yes Control 0.959 0.298 Yes 400m Sprint Time (Pre-Test) Experimental 0.975 0.482 Yes Control 0.970 0.412 Yes 400m Sprint Time (Post-Test) Experimental 0.966 0.367 Yes Control 0.962 0.310 Yes Squat 1RM (Pre-Test) Experimental 0.978 0.511 Yes Control 0.972 0.431 Yes Squat 1RM (Post-Test) Experimental 0.965 0.348 Yes Control 0.961 0.298 Yes The p-values for all variables were > 0.05, indicating that data followed a normal distribution, allowing for parametric statistical analysis in subsequent sections.

2025 (junio), Retos, 67, 1200-1210 ISSN: 1579-1726, eISSN: 1988-2041 https://recyt.fecyt.es/index.php/retos/index 1204 Data Analysis The researcher analyzed the data using IBM SPSS Statistics (version 29). Descriptive statistics (means, standard deviations) were computed for key performance variables. Normality was assessed using the Shapiro-Wilk and Kolmogorov-Smirnov tests to determine the suitability of parametric analyses. A re- peated-measures ANOVA examined within- and between-group differences across pre- and post-tests, with Bonferroni correction applied to mitigate Type I errors. Effect sizes (η²) were calculated to assess the magnitude of training adaptations. Pearson’s correlation evaluated relationships between strength, speed, and endurance improvements, while multiple regression analysis determined the predictive im- pact of these factors on sprint performance. Statistical significance was set at p < 0.05. This approach ensured a robust assessment of the integrated training model, critically evaluating its effectiveness in enhancing 100m and 400m sprint performance. Results All statistical analyses described in the Methodology were implemented to evaluate within-group and between-group differences. The results are presented below in accordance with the predefined analyt- ical plan. Sprint Performance Improvements The analysis of 100m and 400m sprint times revealed a significant reduction in sprint times for the experimental group compared to the control group. A repeated-measures ANOVA showed a significant interaction effect of time × group (p < 0.001, η² = 0.42), indicating superior improvements in the inte- grated training group. Table 4. Sprint Performance Pre- and Post-Test Comparisons Sprint Distance Group Pre-Test (Mean ± SD) Post-Test (Mean ± SD) % Change p-value 95% CI Cohen's d 100m Sprint (s) Experimental 10.92 ± 0.31 10.57 ± 0.29 −3.2% <0.001 −3.8%, −2.6% 1.13 Control 10.95 ± 0.34 10.81 ± 0.32 −1.3% 0.027 −1.7%, −0.9% 0.41 400m Sprint (s) Experimental 48.76 ± 1.92 47.03 ± 1.85 −3.5% <0.001 −4.1%, −2.9% 1.21 Control 48.91 ± 2.04 48.35 ± 1.96 −1.1% 0.031 −1.5%, −0.7% 0.39 Note: CI = Confidence Interval; d = Cohen’s d effect size. The experimental group exhibited significantly greater improvements in sprint times (100m: d = 1.13; 400m: d = 1.21), supporting the effectiveness of integrating strength, speed, and endurance training. Individual variability analysis showed that 80% of participants

1.21 Control 48.91 ± 2.04 48.35 ± 1.96 −1.1% 0.031 −1.5%, −0.7% 0.39 Note: CI = Confidence Interval; d = Cohen’s d effect size. The experimental group exhibited significantly greater improvements in sprint times (100m: d = 1.13; 400m: d = 1.21), supporting the effectiveness of integrating strength, speed, and endurance training. Individual variability analysis showed that 80% of participants in the experimental group improved by at least 2.5% in 100m times, while two athletes exhibited improvements exceeding 4.0%, suggesting differential training responsiveness. Strength Adaptations Significant increases in squat, deadlift, and power clean 1RM were observed in both groups, but the experimental group showed superior gains. Table 5. Strength Gains (1RM) Pre- and Post-Test Exercise Group Pre-Test (kg) Post-Test (kg) % Change p-value 95% CI Cohen's d Squat 1RM Experimental 150.2 ± 12.1 167.4 ± 13.5 +11.4% <0.001 +10.2%, +12.6% 1.08 Control 151.1 ± 11.8 159.2 ± 12.3 +5.4% 0.019 +4.5%, +6.3% 0.57 Deadlift 1RM Experimental 165.3 ± 14.2 182.7 ± 15.0 +10.5% <0.001 +9.3%, +11.7% 1.02 Control 164.8 ± 14.0 172.1 ± 14.6 +4.4% 0.032 +3.6%, +5.2% 0.51 Power Clean 1RM Experimental 105.7 ± 8.9 118.6 ± 9.2 +12.2% <0.001 +11.0%, +13.4% 1.17 Control 106.3 ± 8.7 112.8 ± 9.0 +6.1% 0.022 +5.3%, +6.9% 0.61

2025 (junio), Retos, 67, 1200-1210 ISSN: 1579-1726, eISSN: 1988-2041 https://recyt.fecyt.es/index.php/retos/index 1205 The experimental group demonstrated significantly greater relative strength gains (p < 0.001, η² = 0.38), likely due to the combination of high-intensity resistance training and explosive sprint drills. Individual variation analysis showed a wide range of strength improvements, with the highest responder increas- ing squat 1RM by 14.5% while the lowest improved by only 7.2%. Sprint Kinematics Sprint kinematic analysis revealed improvements in stride length, stride frequency, and ground contact time in the experimental group. Table 6. Sprint Kinematic Changes Variable Group Pre-Test Post-Test % Change p-value 95% CI Stride Length (m) Experimental 2.15 ± 0.07 2.24 ± 0.08 +4.2% 0.002 +3.6%, +4.8% Control 2.14 ± 0.08 2.17 ± 0.08 +1.4% 0.049 +0.9%, +1.9% Stride Frequency (Hz) Experimental 4.88 ± 0.15 5.07 ± 0.14 +3.9% 0.001 +3.4%, +4.4% Control 4.86 ± 0.16 4.91 ± 0.15 +1.0% 0.038 +0.6%, +1.4% Ground Contact Time (ms) Experimental 0.092 ± 0.005 0.087 ± 0.004 −5.4% 0.001 −6.0%, −4.8% Control 0.093 ± 0.005 0.091 ± 0.004 −2.2% 0.047 −2.7%, −1.7% The experimental group exhibited greater neuromuscular adaptations, enhancing stride efficiency and sprint mechanics. Lactate Threshold and Endurance Adaptations Endurance adaptations were assessed via blood lactate concentrations post-400m sprint. Table 7. Lactate Accumulation Post-400m Sprint Group Pre-Test (mmol/L) Post-Test (mmol/L) % Change p-value 95% CI Experimental 12.5 ± 1.1 11.3 ± 1.0 −9.6% 0.003 −10.4%, −8.8% Control 12.4 ± 1.2 12.0 ± 1.1 −3.2% 0.048 −3.8%, −2.6% The experimental group showed a significant reduction in lactate accumulation, suggesting improved anaerobic endurance through enhanced lactate buffering and energy system efficiency (p = 0.003, η² = 0.29). Figure 1 demonstrates a clear pattern of improvement in both sprint performance and strength metrics following the training intervention. Specifically, the 100m sprint showed modest pre-to-post-test im- provement, with the most notable enhancements observed in power clean 1RM and deadlift 1RM per- formance, suggesting significant neuromuscular gains that likely contributed to the acceleration phases of the 100m sprint. For the 400m sprint, while overall improvements were evident, the most substantial changes were seen in lactate levels, indicating improved metabolic endurance

The integrated training model enhances sprint performance more effectively than traditional methods.