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Editorial

Applied Biomechanics and Sports Sciences: Closing Editorial

by
Filipe Conceição
1,2,
Ricardo J. Fernandes
1,2,* and
Pedro Jimenez-Reyes
3
1
Centre of Research, Education, Innovation and Intervention in Sport, CIFI2D, Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
2
Porto Biomechanics Laboratory, LABIOMEP-UP, Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
3
Center for Sport Studies, Rey Juan Carlos University, 28933 Madrid, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(18), 10059; https://doi.org/10.3390/app151810059
Submission received: 9 September 2025 / Accepted: 11 September 2025 / Published: 15 September 2025
(This article belongs to the Special Issue Applied Biomechanics and Sports Sciences)

1. Introduction

The integration of biomechanics and sports sciences has accelerated markedly in recent years largely due to advances in sensor technology, data analytics, and computational modeling. Wearable devices, such as inertial measurement units and portable electromyography systems, have enhanced the capacity to capture real-time data in ecologically valid conditions, supporting both training and rehabilitation practices [1,2]. Parallel to this, artificial intelligence and machine learning approaches are increasingly employed in performance prediction and individualized training design [3,4]. However, substantial gaps remain since translating complex biomechanical findings into practical tools that coaches can apply with confidence continues to be a challenge, while longitudinal multi-level studies are still underrepresented [5]. Furthermore, there is limited integration across biomechanics, physiology and psychology, restricting our ability to holistically model athlete development. This Special Issue sought to highlight research directions that combine methodological rigor with real-world impact, in line with contributions to applied biomechanics, aquatic performance, and sprint profiling.

2. An Overview of Thematic Contributions

The contributions to this Special Issue can be grouped into four thematic clusters that mirror emergent research priorities. The first relates to accessible monitoring technologies, exemplifying the push toward accurate but low-cost tools that broaden the application of biomechanics beyond laboratory settings [6]. This perspective is consistent with our work on affordable and reliable measurement solutions for neuromuscular assessment in applied contexts [7,8]. A second cluster focuses on predictive modeling and longitudinal profiling, a field where advanced statistics and computational models are increasingly applied to monitor training adaptations and forecast record progression [9,10]. This resonates with our extensive contributions to swimming physiology and energetics, where integrative models have been developed to link biomechanics and bioenergetics to performance outcomes [11].
A third theme highlights underrepresented populations and contexts, such as female athletes, youth, and those recovering from injury. Addressing these gaps is essential to closing the persistent imbalance in sex- and age-based data in sport science [12]. The attention to such groups in this Special Issue also reflects the editorial vision of creating inclusive knowledge that informs talent identification and equitable training strategies. Finally, several studies focus on biomechanical variability and asymmetry, with applications in explosive actions and rehabilitation. This line of research reflects the necessity of accounting for functional imbalances when designing interventions [13,14]. Our research on sprint force–velocity profiling also exemplifies this principle, highlighting how individualized mechanical profiles can guide strength and speed training, optimizing performance while reducing risk of injury [8,15].

3. Conclusions and Future Directions

The contributions in this Special Issue illustrate the breadth of contemporary applied biomechanics, spanning validation of new tools, predictive analytics, profiling of youth athletes and clinical rehabilitation. A recurrent theme is that biomechanics must not be considered in isolation, but should be integrated with physiology, psychology, and training methodology to capture the complexity of sport performance. Persistent challenges include the need for standardized approaches across laboratory and field contexts, the greater inclusion of underrepresented populations and the translation of sophisticated methods into user-friendly formats for practitioners [5,16]. Future research should prioritize longitudinal and integrative frameworks that track adaptation over time, advanced computational tools (including artificial intelligence and force–velocity profiling for individualized diagnostics; [17]) and equitable approaches tailored to women, youth, and clinical populations [12]. In addition, scalable wearable technologies must be designed with attention to ethical and practical factors, such as affordability and data privacy [2,18]. Building on the expertise of this Special Issue’s Guest Editors, the future of applied biomechanics should continue to move toward integrated, accessible and impactful applications that benefit both elite sport and broader human performance contexts.

Conflicts of Interest

The authors declare no conflict of interest.

List of Contributions

  • Abelleira-Lamela, T.; Marcos-Pardo, P.J.; Abraldes, J.A.; González-Gálvez, N.; Espeso-García, A.; Esparza-Ros, F.; Vaquero-Cristóbal, R. Comparative Electromyographic Analysis in Leg Press of Traditional Fitness Equipment, Traditional Outdoor Fitness Equipment, and a New Model of Outdoor Fitness Equipment in Trained Young Men. Appl. Sci. 2024, 14, 7390.
  • Costa, M.J.; Quinta-Nova, L.; Ferreira, S.; Costa, A.M.; Santos, C.C. Trend Forecasting in Swimming World Records and in the Age of World Record Holders. Appl. Sci. 2024, 14, 9492.
  • Castaño-Zambudio, A.; Repullo, C.; Jiménez-Reyes, P. Enhancing Acceleration Capabilities in Professional Women’s Football Players: A Comparative Analysis of Game-Based Versus Resisted Sprint Trainings. Appl. Sci. 2024, 14, 10327.
  • Ramasamy, Y.; Wei, Y.M.; Towler, H.; King, M. Intra-Individual Variation in the Jump Smash for Elite Malaysian Male Badminton Players. Appl. Sci. 2025, 15, 844.
  • Delgado-García, G.; Pérez-Castilla, A.; Rojas-Ruiz, F.J.; Navarro-Marchal, I.; Caballero-Villalta, A. Validity of a User-Friendly Spreadsheet Designed for an In-Depth Analysis of Countermovement Bipodal Jumps. Appl. Sci. 2025, 15, 1519.
  • Silva, M.; Antunes, H.D.; Sousa, A.; Nakamura, F.Y.; Sampaio, A.R.; Pimenta, R. Profiling of Physical Qualities of Highly Trained Portuguese Youth Soccer Players. Appl. Sci. 2025, 15, 5414.
  • Romero Padron, M.A.; Jorgensen, A.; Werner, D.M.; Tao, M.A.; Wellsandt, E. Knee Loading Asymmetries During Descent and Ascent Phases of Squatting After ACL Reconstruction. Appl. Sci. 2025, 15, 7780.
  • Noronha, F.; Canossa, S.; Carvalho, D.D.; Monteiro, A.S.; Afonso, J.; Castro, F.; Fernandes, R. Sex and Age Disparities in Water Polo-Related Skills. Appl. Sci. 2025, 15, 9381.

References

  1. Jaén-Carrillo, D.; Pérez-Castilla, A.; García-Pinillos, F. Wearable and Portable Devices in Sport Biomechanics and Training Science. Sensors 2024, 24, 4616. [Google Scholar] [CrossRef] [PubMed]
  2. Van Hooren, B.; Goudsmit, J.; Restrepo, J.; Vos, S. Real-time feedback by wearables in running: Current approaches, challenges and suggestions for improvements. J. Sports Sci. 2020, 38, 214–230. [Google Scholar] [CrossRef] [PubMed]
  3. Claudino, J.G.; Capanema, D.; de Souza, T.V.; Serrão, J.C.; Machado Pereira, A.C.; Nassis, G.P.; Filho, C.A.C. Current approaches to the use of artificial intelligence for injury risk assessment and performance prediction in team sports: A systematic review. Sports Med.–Open 2019, 5. [Google Scholar] [CrossRef]
  4. Jianjun, Q.; Isleem, H.F.; Almoghayer, W.J.K.; Khishe, M. Predictive athlete performance modeling with machine learning and biometric data integration. Sci. Rep. 2025, 15, 16365. [Google Scholar] [CrossRef] [PubMed]
  5. Bishop, D.; Burnett, A.; Farrow, D.; Gabbett, T.; Newton, R. Sports science research: Methodological issues and applications. Sports Med. 2019, 49, 1–16. [Google Scholar] [CrossRef]
  6. Camomilla, V.; Bergamini, E.; Fantozzi, S.; Vannozzi, G. Trends supporting the in-field use of wearable inertial sensors for sport performance evaluation: A systematic review. Sensors 2018, 18, 873. [Google Scholar] [CrossRef] [PubMed]
  7. Balsalobre-Fernández, C.; Glaister, M.; Lockey, R.A. The validity and reliability of an iPhone app for measuring vertical jump performance. J. Sports Sci. 2016, 33, 1574–1579. [Google Scholar] [CrossRef] [PubMed]
  8. Silva, M.P.; Fonseca, P.; Fernandes, R.J.; Conceição, F. Is running technique important to mitigate hamstring injuries in football players? Appl. Sci. 2024, 14, 11643. [Google Scholar] [CrossRef]
  9. Allen, S.V.; Vandenbogaerde, T.J.; Hopkins, W.G. Career performance trajectories of Olympic swimmers: Benchmarks for talent development. Eur. J. Sport Sci. 2014, 14, 643–651. [Google Scholar] [CrossRef]
  10. Romann, M.; Müller, S. Longitudinal performance trajectories of young female 60 m sprinters using linear mixed effects models. Front. Sports Act. Living 2024, 6. [Google Scholar] [CrossRef]
  11. Fernandes, R.J.; Carvalho, D.D.; Figueiredo, P. Training zones in competitive swimming: A biophysical approach. Front. Sports Act. Living 2024, 6, 1363730. [Google Scholar] [CrossRef] [PubMed]
  12. Cowley, E.S.; Olenick, A.A.; McNulty, K.L.; Ross, E.Z. “Invisible sportswomen”: The sex data gap in sport and exercise science research. Women Sport Phys. Act. J. 2021, 29, 146–151. [Google Scholar] [CrossRef]
  13. Morin, J.-B.; Samozino, P. Interpreting power-force-velocity profiles for individualized and specific training. Int. J. Sports Physiol. Perform. 2016, 11, 267–272. [Google Scholar] [CrossRef] [PubMed]
  14. Mendiguchia, J.; Castaño-Zambudio, A.; Jiménez-Reyes, P.; Morin, J.-B.; Edouard, P.; Conceição, F.; Tawiah-Dodoo, J.; Colyer, S.L. Can We Modify Maximal Speed Running Posture? Implications for Performance and Hamstring Injury Management. Int. J. Sports Physiol. Perform. 2022, 17, 374–383. [Google Scholar] [CrossRef] [PubMed]
  15. Jiménez-Reyes, P.; Garcia-Ramos, A.; Párraga-Montilla, J.A.; Morcillo-Losa, J.A.; Cuadrado-Peñafiel, V.; Castaño-Zambudio, A.; Samozino, P.; Morin, J.-B. Seasonal changes in the sprint acceleration force-velocity profile of elite male soccer players. J. Strength Cond. Res. 2022, 36, 70–74. [Google Scholar] [CrossRef] [PubMed]
  16. Windt, J.; Gabbett, T.J. How do training and competition workloads relate to injury? The workload–injury aetiology model. Br. J. Sports Med. 2017, 51, 428–435. [Google Scholar] [CrossRef] [PubMed]
  17. Rojas-Valverde, D.; Gutiérrez-Vargas, R.; Sánchez-Ureña, B.; Crowe, J.; Gutiérrez-Vargas, J.C. Application of machine learning in sports: A bibliometric and content analysis. Appl. Sci. 2022, 12, 3483. [Google Scholar] [CrossRef]
  18. Halson, S.L.; Mujika, I.; Meeusen, R. Monitoring training load: The past, the present, and the future. Int. J. Sports Physiol. Perform. 2019, 14, 2–11. [Google Scholar] [CrossRef]
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MDPI and ACS Style

Conceição, F.; Fernandes, R.J.; Jimenez-Reyes, P. Applied Biomechanics and Sports Sciences: Closing Editorial. Appl. Sci. 2025, 15, 10059. https://doi.org/10.3390/app151810059

AMA Style

Conceição F, Fernandes RJ, Jimenez-Reyes P. Applied Biomechanics and Sports Sciences: Closing Editorial. Applied Sciences. 2025; 15(18):10059. https://doi.org/10.3390/app151810059

Chicago/Turabian Style

Conceição, Filipe, Ricardo J. Fernandes, and Pedro Jimenez-Reyes. 2025. "Applied Biomechanics and Sports Sciences: Closing Editorial" Applied Sciences 15, no. 18: 10059. https://doi.org/10.3390/app151810059

APA Style

Conceição, F., Fernandes, R. J., & Jimenez-Reyes, P. (2025). Applied Biomechanics and Sports Sciences: Closing Editorial. Applied Sciences, 15(18), 10059. https://doi.org/10.3390/app151810059

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