Special Issue “Advances in Performance Analysis and Technology in Sports”

1. Introduction

In recent years, the landscape of sports science has been profoundly transformed by rapid advances in performance analysis and the integration of innovative technologies. From elite competitive environments to grassroots development programs, coaches, scientists, and practitioners increasingly rely on data-driven insights to optimize training, enhance decision-making, and improve athlete performance and safety [1]. The convergence of disciplines such as biomechanics, physiology, data science, and wearable technology has enabled more precise, real-time monitoring and evaluation of athletic output [2]. Tools such as motion capture systems, GPS tracking, inertial measurement units (IMUs), and artificial intelligence-based video analysis have transitioned from research settings to everyday practice in high-performance sport [3]. This digital revolution is not only reshaping how performance is understood and measured but also redefining the roles of sport scientists and practitioners [2]. This Special Issue, “Advances in Performance Analysis and Technology in Sports”, was conceived to provide a platform for cutting-edge research and practical applications that reflect this evolving field. It brings together a diverse set of contributions that explore novel methods, tools, and frameworks for analyzing and improving athletic performance across a range of sports and contexts [4]. The articles selected for this issue highlight both the scientific innovation and applied value that modern performance analysis can offer.

2. Purpose of This Special Issue

The primary aim of this Special Issue was to gather high-quality, interdisciplinary research that reflects the latest developments in sports performance analysis and technology-enhanced training environments. As performance demands continue to rise across all levels of sport, there is an increasing need for scientific approaches that are both innovative and applicable in real-world contexts.

This Special Issue sought to explore how modern technologies—ranging from wearable sensors and video tracking systems to machine learning algorithms and mobile applications—are reshaping the ways in which performance is measured, interpreted, and acted upon. Equally important was the inclusion of studies that critically examine the validity, reliability, and usability of these tools in both laboratory and field settings.

We were particularly interested in contributions that

• Presented new methodologies or validation studies for performance monitoring tools;
• Demonstrated applied case studies in elite or youth sport settings;
• Explored athlete profiling and load management through digital means;
• Integrated multidisciplinary approaches combining physiology, biomechanics, psychology, or data science;
• Addressed ethical, practical, or methodological challenges associated with technology use in sport.

By fostering collaboration across disciplines and bridging the gap between theory and practice, this Special Issue aims to support the advancement of evidence-based performance strategies and to inform future research directions in sports technology and analysis.

3. Overview of the Contributions

The Special Issue opens with a study by Šimenko et al., titled “Exploring the Relationship between Anaerobic and Morphological Characteristics and Competition Success in Young Male Slovenian Judo Athletes”. This cross-sectional research evaluated the anaerobic performance of U18 and U20 Slovenian judokas using the upper body Wingate test and investigated its relationship with body composition and competitive results. Although no significant correlation was found between anaerobic or morphological parameters and competition ranking, the authors identified notable associations between skeletal muscle mass and anaerobic capacity. The findings underscore the multifactorial nature of judo performance and suggest the need for individualized training focused on strength and anaerobic power development in youth athletes. Importantly, the study contributes valuable reference data for normative assessments of young judokas and highlights methodological considerations when comparing youth to senior normative tables [5].

In the second contribution, Hussain et al. present the “RunsGuard Framework: Context Aware Cricket Game Strategy for Field Placement and Score Containment”. This study addresses the growing need for intelligent, data-driven decision-making in cricket by introducing an integrated framework that processes ball-by-ball text commentary, extracts player-specific performance insights, and recommends optimal field placements. Utilizing natural language processing and machine learning techniques, the framework identifies player strengths and weaknesses, contextualizes delivery data, and develops tailored bowling and fielding strategies. Simulations demonstrated the model’s efficacy, showing a reduction in scoring by up to 37.7% in selected innings. The framework bridges the gap between unstructured commentary data and practical tactical planning, offering significant potential for coaches and analysts aiming to optimize in-game decision-making in cricket [6].

The third article, authored by Steff, Badau, and Badau, is titled “Improving Agility and Reactive Agility in Basketball Players U14 and U16 by Implementing Fitlight Technology in the Sports Training Process”. This experimental study evaluates the impact of integrating Fitlight technology into agility training for junior basketball players. Across 18 weeks, U14 and U16 athletes in the experimental group participated in sessions using Fitlight—a tool based on visual stimuli—to enhance coordination, reaction time, and multidirectional movement skills. The authors conducted six standardized and reactive agility tests, both with and without a basketball, and reported significant improvements in the experimental group compared to controls, with large effect sizes (Cohen’s d > 0.8). These results support the efficacy of technology-assisted training in youth sports and provide a replicable methodology for coaches seeking to modernize performance enhancement programs in basketball [7].

The fourth article, “The Effect of Situational Variables on Women’s Rink Hockey Match Outcomes” by Arboix-Alió et al., addresses a notable gap in the literature by focusing on female athletes in a traditionally underrepresented sport. Drawing on data from 840 matches in Spain’s top-tier women’s rink hockey league (OkLiga), the authors developed a predictive logistic model to assess how match outcomes are influenced by five situational variables: match location, team level, opponent level, scoring first, and halftime score. The study found that the most influential predictor was match status at halftime, followed by opponent and team level, with match location exerting a modest effect. Interestingly, scoring the first goal did not significantly impact match outcomes. These findings not only offer a novel model for performance prediction in female team sports but also provide actionable insights for coaches to tailor tactical decisions based on game scenarios [8].

In the fifth article, Jung and Hong investigate the “Effects of Short-Rest Interval Time on Resisted Sprint Performance and Sprint Mechanical Variables in Elite Youth Soccer Players”. Using a randomized crossover design, the authors compared two sprint training protocols—one with traditional 2 min rest intervals (RST2M) and the other with shortened 40 s intervals (RST40S)—involving six 20 m resisted sprints with a 30% velocity decrement load. Despite expectations, there were no statistically significant differences in sprint performance, mechanical variables, or fatigue indices between the two protocols. These findings suggest that elite youth players may maintain sprint quality even under shorter recovery durations, challenging traditional assumptions in sprint training periodization. The study introduces a novel training approach that may offer greater efficiency without compromising sprint mechanics or inducing excessive fatigue, holding practical implications for conditioning coaches in soccer and similar team sports [9].

In the sixth contribution, Tortu and Deliceoglu present a comparative study titled “Comparative Analysis of Energy System Demands and Performance Metrics in Professional Soccer Players: Running vs. Cycling Repeated Sprint Tests”. This investigation aimed to assess the physiological and performance responses of professional soccer players during repeated sprint efforts using both running and cycling modalities. The results revealed that running-based sprints elicited significantly greater total energy expenditure, ATP-PCr system contribution, and energy demand, despite cycling producing higher peak and mean power outputs. Interestingly, the performance variables between modalities were not strongly correlated, suggesting that cycling and running sprint tests cannot be used interchangeably for assessing repeated sprint ability in field sports. The study offers critical insights into test modality selection for performance diagnostics, emphasizing the importance of sport-specificity when evaluating high-intensity intermittent exercise capacity [10].

The seventh article, authored by Spieszny et al., is titled “The Impact of Coordination Training on Psychomotor Abilities in Adolescent Handball Players: A Randomized Controlled Trial”. This study explored the long-term effects of an eight-month coordination training program on a range of psychomotor skills among male adolescent handball players. Using a randomized controlled design with pre-, mid-, and post-intervention assessments, the experimental group demonstrated statistically significant improvements in simple reaction time, visual–motor coordination, spatial orientation, divided attention, and perception orientation compared to a control group following standard training. The program incorporated a diverse array of coordination-focused exercises integrated into regular training sessions, emphasizing variability and progressive difficulty. The findings highlight the effectiveness of targeted coordination training in enhancing key cognitive-motor attributes in youth athletes and support its inclusion in developmental training programs for handball and other team sports [11].

The eighth article, “Kinematic Characteristics of the Non-Throwing Arm During the Completion Phase of the Glide Shot Put in Elite Female Athletes: A Case Study” by Jiao et al., provides a biomechanical exploration of a rarely analyzed component in shot put technique—the non-throwing arm. Using three-dimensional motion capture during a national-level competition, the study focused on the displacement, velocity, and angular motion of the non-throwing arm in a world-class female shot-putter. The results demonstrated that joint velocities and angular changes in the non-throwing arm were significantly correlated with performance indicators such as shot velocity and center of mass displacement. Notably, shoulder movement of the non-throwing arm positively correlated with center of mass velocity, while the elbow and wrist showed negative correlations with the throwing side’s kinematics. These findings suggest that the non-throwing arm actively contributes to rotational mechanics, energy transfer, and postural stability and should be strategically addressed in elite training programs. The study advances our understanding of the kinetic chain in shot put and emphasizes the non-throwing arm as a critical element rather than a passive appendage [12].

In the ninth article, “Beyond Instinct: Data-Driven Decision Trees for Tactical Shot Selection in Professional Padel”, López-Sierra et al. explore how statistical modeling can support tactical decision-making in elite-level racquet sports. By analyzing 878 final shot actions from ten matches of the 2023 World Padel Tour, the authors constructed CHAID decision trees to identify the most effective finishing shots in men’s and women’s professional padel. The results revealed distinct gender-based patterns: men achieved higher success rates with smashes, recovery smashes, and off-court shots, while women were more effective using volleys, bandejas, viboras, and forehand/backhand strokes. Despite men’s greater reliance on power-based shots, both sexes committed more errors than they scored winners. The study not only reinforces the tactical specificity of professional padel by gender but also advocates for integrating decision-tree models into training environments to support more objective, data-informed coaching. The findings offer valuable strategic insights and highlight the need for sex-specific approaches in developing shot selection and error management skills [13].

The tenth article, “Influence of Category and Sex in Game Structure Variables in Young Elite Tennis” by Zurano et al., investigates how age category (U-12 vs. U-14) and sex influence temporal and formal gameplay structures in elite youth tennis. Using a notational analysis of 24 semi-final and final matches from international tournaments, the study evaluated key performance metrics such as match duration, point duration, active time percentage, strokes per point, and stroke frequency. The findings revealed that age category significantly influenced all analyzed variables, with U-12 players exhibiting longer rallies, higher active time, and greater stroke volume compared to their U-14 counterparts. Surprisingly, sex had minimal influence, except for a slightly higher number of strokes per point recorded by males. The study offers strong evidence that category-based differences outweigh sex-based variations in early developmental stages, emphasizing the importance of age-specific training adaptations and providing a comprehensive benchmark for load management and tactical planning in youth tennis [14].

4. Conclusions and Future Directions

Collectively, the articles featured in this Special Issue reflect the dynamic and evolving landscape of performance analysis and sports technology across a diverse range of disciplines, age groups, and methodological approaches. From high-performance training interventions in team sports to advanced analytical frameworks in racquet sports and combat disciplines, each study contributes unique insights into how contemporary tools and data-driven strategies can inform and enhance athletic performance.

Several key themes emerge. First, the integration of technology—whether through wearable devices, reactive stimulus systems, machine learning models, or notational video analysis—has become a cornerstone of modern performance diagnostics and tactical planning. Second, the value of interdisciplinary collaboration is evident, with biomechanics, physiology, psychology, and data science working in concert to refine training methods and improve outcomes. Third, many studies underscore the importance of context: age category, competitive level, and sex-specific differences must all be considered when developing or interpreting performance models.

This Special Issue also highlights areas for future research. While innovative methods are being applied at the elite level, there is a clear need for longitudinal studies that follow athletes through developmental stages. Moreover, ethical considerations regarding data privacy and the practical implementation of complex systems in real-world sport settings require further attention. Cross-validation across sports, broader demographic representation (especially among female and youth athletes), and the inclusion of psychological and sociocultural dimensions are also critical for the next generation of sports science research.

We extend our gratitude to the authors, reviewers, and editorial team for their contributions to this volume. It is our hope that the insights presented here will inspire continued innovation and dialogue within the fields of performance analysis and sports technology, ultimately serving both researchers and practitioners striving for excellence in sport.