Proceedings of the Institution of Mechanical Engineers,Part P: Journal of Sports Engineering and Technology

Optimising trunk posture is critical for improving efficiency in speed skating, as it influences both aerodynamic drag and neuromuscular demands. This study aimed to quantify how incremental changes in sagittal trunk flexion angle affect aerodynamic resistance, muscular load, and overall skating efficiency under race-relevant conditions. Twenty-eight elite male speed skaters performed trials across straight and curved tracks at sagittal trunk flexion angles ranging from 30°to 50°. Trunk kinematics were captured using inertial measurement units, muscular activity was recorded with surface electromyography, and drag coefficients were estimated through computational fluid dynamics simulations. These datasets were integrated within the Real-Time Integrated Trunk–Cd–Efficiency (RITCE) model to evaluate the combined biomechanical and aerodynamic effects. Results showed that efficiency decreased significantly from 82.1% at 30° to 75.3% at 50° (p< 0.001), while drag coefficient increased from 0.241 to 0.276 (p < 0.001) and EMG load rose from 100.2 to 130.9 µV (p < 0.001). Fatigue indices and co-contraction ratios also increased with deeper trunk flexion. Efficiency was consistently lower on curved tracks, with significant sagittal trunk flexion angle–track interactions observed. These findings demonstrate that excessive trunk flexion imposes aerodynamic, neuromuscular, and mechanical penalties, supporting the need for trunk-targeted biomechanical interventions to enhance skating efficiency in elite athlete.

Penalty kicks are key moments in soccer, yet their success depends not only on strategic shot placement but also on a player’s ability to execute accurately under pressure. This study investigates how variability in kicking accuracy affects optimal aim during penalty kicks. Using data from 4299 penalties in Danish youth leagues and 1060 laboratory-measured kicks from academy players, we modeled the bivariate distribution of shot placement and applied Monte Carlo simulations to identify optimal aiming strategies. Results show that while top corners yield the highest scoring percentages on average, players with higher shot variability achieve better outcomes by aiming for more central and lower zones of the goal. Conversely, players with greater consistency can exploit more challenging placements for higher success rates. Additionally, the orientation of shot variability—horizontal versus vertical—affects the location of the optimal aim point. These findings suggest that effective penalty strategies should be individualized, taking into account each player’s performance profile. By bridging statistical models with practical execution data, this study provides actionable insights for players, coaches, and analysts aiming to improve penalty kick outcomes through tailored strategies.

This study introduces DataGoal, an open-source MATLAB-based toolbox designed to process, analyze, and visualize positional data in soccer obtained from Global Positioning System (GPS/GNSS), Local Positioning System (LPS), and video-tracking technologies. The increasing availability of tracking data has created new opportunities for investigating the spatial–temporal dynamics of team sports; however, the complexity of these datasets often limits their effective use. DataGoal addresses this challenge by providing an integrated analytical framework that combines data importation, spatial calibration, preprocessing, metric computation, and graphical visualization within a single workflow. The toolbox implements a comprehensive set of linear and non-linear metrics to quantify individual and collective behaviors, including physical demands, team compactness, spatial organization, and dynamic coordination patterns. Through an interactive graphical user interface, DataGoal enables users to configure analyses and process positional datasets without extensive programming requirements, while its modular MATLAB-based architecture allows users to extend or customize analytical routines. By integrating multiple analytical procedures within a unified environment, DataGoal facilitates reproducible positional-data analyses and supports investigations of collective dynamics in soccer. The framework is suitable for applications in scientific research, performance analysis, and sports science education. As an open-source project, DataGoal is intended to evolve through community contributions and future extensions, contributing to the advancement of data-driven approaches in soccer performance analysis.

Experimental design and optimization of artificial turf playing surfaces is costly and time-consuming. Although contemporary finite element (FE) models can offer insight into design choices, they have not been validated for a wide range of turf design parameters. In the present study, 14 physical turf designs with varying infill composition (different infill mixture ratios), fiber areal density (fibers per square inch), mixture composition (different infill particle diameters), turf height (varying both fiber length and infill depth), infill depth (using the same fiber length), and fiber type (monofilament vs slit film) were constructed. The turfs were tested using the Biocore Elite Athlete Shoe Turf (BEAST) test apparatus under translation and rotation loading, with the results typically showing low sensitivity to variations in turf design parameters (<10% absolute difference for most metrics), except for extreme case, such as 100% sand infill and very low areal fiber density (0.5 fibers/cm²). Corresponding FE models were developed using a recently validated methodology and captured the variation in response under both translational and rotational modes of loading with a CORA objective rating between 0.53 and 0.93 (mean 0.75). The models demonstrated the ability to reproduce the main effects from the experimental tests and to predict the rank order of the effects measured experimentally. Importantly, the model was able to quantify the effect of varying parameters and show potential for use in future turf design and optimization.

Novel technologies that mitigate head impact severity can contribute to reducing TBI risk in helmeted activities. This study evaluated the efficacy of prototype equipment that couples a helmet and shoulder pads during head impacts representative of American football. A custom test fixture accelerated the head, neck, torso, and pelvis of an anthropomorphic test device (ATD) into a second, stationary ATD so that head and neck loading could be assessed for both players involved in an impact. Three equipment configurations were tested, each at 6.7 m/s and 4.4 m/s: (i) both ATDs wore a standard helmet and shoulder pads, (ii) the accelerated ATD wore the prototype while the stationary ATD wore a standard helmet and shoulder pads, and (iii) both ATDs wore the prototype. The prototype yielded significant reductions in peak linear accelerations of the head for both ATDs at 6.7 m/s, but only one ATD at 4.4 m/s. Reductions in angular head kinematics were inconsistent across the different equipment configurations and test conditions. Significant reductions in upper neck loading (both force and moment) were observed in both ATDs as a result of wearing the coupled equipment in all but one scenario.

This study compares minimalist and comprehensive inertial measurement unit (IMU) configurations for monitoring rider posture in equestrian sport. The minimalist setup employed three IMUs positioned at the pelvis, sternum, and saddle, while the comprehensive configuration used 18 sensors distributed across the rider and saddle. Data collected during real riding conditions were processed in MATLAB to evaluate posture angles, symmetry measures, and center of mass (CoM) trajectories. The minimalist system achieved sub-degree accuracy for pelvis and trunk orientations, exhibited no substantial differences in key posture metrics, and required approximately 40% less setup time than the comprehensive system. However, CoM estimation showed greater variability, with an average RMS deviation of 0.185 m compared to the full-body configuration. In addition, the reduced sensor configuration demonstrated improved practicality for field deployment due to lower system complexity and reduced preparation requirements. These results indicate that minimalist IMU systems can provide accurate and field-deployable posture monitoring, while comprehensive configurations remain preferable when high-precision whole-body biomechanical measures, such as CoM estimation, are required.

Understanding team performance in professional football increasingly benefits from network science, which models players as nodes and their interactions as functional links. While Social Network Analysis (SNA) provides valuable structural insights, it often fails to capture the probabilistic nature of possession. This exploratory study introduces an integrated methodological framework that combines static SNA with a Markov-spectral model of ball circulation to analyse the Portuguese National Team across two high-stakes 2025 Nations League finals matches. This approach moves beyond describing who is connected to quantifying how possession flows through the team network. Match event data were obtained via the Wyscout^® platform, with all passing actions by Portugal extracted. The framework combined SNA (using uPATO^®) with Markov-spectral analysis (implemented in MATLAB^®) to compute indices of passing uncertainty, diffusion speed, navigability, and network robustness. The results suggested that (i) SNA identified key players as crucial hubs for ball circulation at the micro level, while indicating a cohesive team structure with adaptable macro-level properties; and (ii) Markov-spectral quantification showed descriptive between-match variations, with the second match displaying higher Entropy (2.84 vs 2.77 bits/pass), suggestive of greater unpredictability, and a larger Spectral Gap (0.53 vs 0.45), indicative of faster potential diffusion of possession. Overall, this integrated approach demonstrates the feasibility of profiling team coordination through both structural configuration and stochastic flow properties. The Markov-spectral framework complements traditional SNA by providing quantifiable indices related to passing variability, network navigability, and structural cohesion, offering a multi-layered, proof-of-concept toolkit for analysing collective performance.

Anthropometric test devices (ATDs) are human surrogate devices that are used in impact testing for the simulation and evaluation of helmet impact performance in American football. However, these ATD’s are often used outside of the scope of their original testing purposes, leading to an increased potential for misinterpretation of laboratory testing data. In this study a computational analysis was conducted of human neck muscular equivalence to that of the Hybrid III neckform using the HYOID OpenSim model scaled to 50th and 95th percentiles of human muscle mechanical properties. Neck bending was simulated in four directions (sagittal, coronal, 45° off-center, and transverse planes) and compared to experimental data on the Hybrid III neckform. In a muscle parameter optimization, maximum isometric force ( F o M ) and passive fiber strain at F o M ( ε o M ) were altered to match the stiffness responses of the HYOID model to the Hybrid III neckform. The Hybrid III sagittal plane flexion response was found to be non-physiologic, requiring a 275% increase in F o M from the HYOID 50th percentile model. The extension response was moderately more physiologic, requiring only a 66% increase in F o M . The Hybrid III neckform was consistently closer to the HYOID 95th percentile model in all planes of motion, suggesting a better match with collegiate/professional populations than the average male. Results from this work can be used as a baseline for future dynamic comparisons to improve the biofidelity of surrogate devices used in the laboratory testing of head protective equipment for American football.

The stretch-shortening cycle (SSC) is critical to explosive movements; recent methods favor fixed relative loading over bodyweight-only depth jumps to better replicate competitive demands. Twenty-four male sprinters performed drop jump tests from five heights (0.20–0.60 m), each with a fixed load equivalent to 10% of their body weight. Three-dimensional kinematic and kinetic data were acquired via a Vicon motion analysis system coupled with force platforms. Key variables included ground reaction force, joint moments and powers, average power output, and reactive strength indices. Repeated-measures ANOVA assessed the effects of height. Drop height significantly affected peak ground reaction force (p = 0.002), hip and ankle moments and powers (p < 0.05), average power output (p = 0.004), RSI (p = 0.002), and RSR (p = 0.003). Most variables peaked or leveled off at ≥0.40 m, with 0.40 m offering the best peak force and contact time optimal trade-off. A 0.40 m drop height with a 10% bodyweight load optimally enhances lower limb explosive strength and reactive power in sprinters. This load–height combination facilitates neuromuscular adaptation while potentially minimizing injury risk. Therefore, this paper is recommended as a targeted prescription for sprint-specific SSC training protocols designed to improve SSC efficiency and explosive performance under controlled loading conditions.

Every strike with an ice tool transmits impulsive shock and vibration to the climber’s hand-arm system while ascending – leading to discomfort. The developed prototype ice tool features a fibre-reinforced polymer shaft with an interleaved viscoelastic layer in a carbon-aramid hybrid laminate, aiming to enhance climbing efficiency through increased damping. By vacuum split moulding the shaft, a 43% weight reduction over aluminium at 50% fibre volume fraction is achieved. The prototype’s damping ratio was then compared with three conventional ice tools. An accelerometer on the back of the hand measured the hand-arm vibration response during and after impact, while a force plate standardised the peak contact force. Lighter ice tools must be accelerated more to achieve the same impact energy. Results indicate that this requirement leads to higher vibration exposure of the hand-arm system. Incorporating rubber foil improved vibration damping and potentially impact attenuation, though performance differences were limited due to the system’s overall high stiffness.

The purpose of this study is to develop an optimized prediction model for Champions League qualification using machine learning and SHAP methods. The research data comprises 14 match statistics from 300 teams over 15 seasons, from the 2009–2010 season to the 2023–2024 season of the English Premier League. The prediction models were evaluated by combining four algorithms with six data balancing techniques, resulting in the evaluation of 24 models. Additionally, the hyperparameters of the top-performing models were tuned to evaluate the optimized models’ performance. Finally, SHAP methodology was applied to assess the importance of variables in the optimized models. The results of this study are as follows. First, the performance of the SMOTE XGBoost model was the highest, followed by the SMOTE-Tomek Gradient Boosting Trees model. Second, the most important variable in the SMOTE XGBoost model was the Shots OT pg, followed by Six Yard Box. These results can contribute not only to predicting team performance in advance but also to improving operational efficiency and can serve as foundational data for teams aiming for long-term success.

Rowing blades (oars) transfer power from athletes to the water to propel a boat forward. The complex nature of fluid forces around a blade has only recently started to be understood with previous studies only investigating blades that are commercially available. The full motion of a blade spoon through water is complex, with motion both longitudinal and perpendicular to the boat motion. This multidisciplinary research uses a combination of computational models with experimental analysis to evaluate how spoon shapes affect the fluid forces on a blade during rowing. The computational model used 3D computational fluid dynamics (CFD) to evaluate the drag and lift forces around four different spoon shapes as they rotate through moving water. Each design had the same surface area, with different positions of maximum depth along their length. Experimental analyses used telemetry to measure blade forces during a series of rowing runs, for two different Concept2 blades, over different stroke rates and blade gearing. The results showed there was a correlation of R² = 0.78 between the location of the spoon’s maximum depth and the lift force generated at the catch. The study also found that, a resultant fluid force change of 47.3 N, at the spoon, can promote a −10.7° ± 1.7° shift in the maximum force angle in the real world. The shift in maximum force angle highlighted how spoon design, especially regarding position of the maximum depth, affected the profile of the rowing stroke.

This study aimed to examine the effects of wearable resistance (WR) training on change of direction ability (CODA), muscle activation patterns, and knee joint stress in athletes. Fifteen healthy male football players participated in a pre- and post-training intervention designed to target the quadriceps, hamstrings, and calf muscles to improve neuromuscular control and joint stability. Surface electromyography (EMG) was used to assess muscle activation, and finite element analysis (FEA) was applied to evaluate stress distribution in the knee joint. Following the WR training program, there was a significant reduction in knee abduction angle during the stance phase (p = 0.001), indicating enhanced joint stability. Strength in the calf muscles increased significantly, while muscle activation levels in the quadriceps (p < 0.001) and hamstrings (p = 0.007) were also elevated. Enhanced co-activation between quadriceps and hamstrings was observed, and FEA demonstrated a significant decrease in the maximal von Mises stress in the anterior cruciate ligament (ACL) and meniscus. These findings suggest that WR training improves CODA and lower limb muscle coordination while reducing internal knee joint stress, potentially lowering the risk of ACL injuries and enhancing athletic performance.

Accurate and reliable performance monitoring is crucial in elite team sports, where wearable technologies, such as GPS systems, are widely utilized. However, the impact of Bluetooth transmission distance between wearable devices and receiver units on measurement quality has received limited attention. This study aimed to evaluate the reliability and validity of running distance data collected using the Polar Team Pro GPS at three different Bluetooth connection distances—20 m, 50 m, and 100 m—during a standardized 20-meter shuttle run test in elite youth football players (n = 20). Participants were randomly assigned to perform the test at each of the specified distances. Reliability was assessed using intraclass correlation coefficients (ICC), coefficient of variation (CV%), standard error of measurement (SEM), smallest worthwhile change (SWC), and minimal detectable change (MDC). Validity was evaluated through Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Square Error (RMSE), and Bland–Altman plots. Results showed that data reliability and validity declined substantially as the Bluetooth distance increased, with the highest ICC (0.73) and lowest measurement error occurring at a distance of 20 m. These findings underscore the importance of maintaining close receiver proximity to ensure the accuracy of GPS-derived data in both research and applied athlete monitoring settings.

As one of the most widely played and watched contact sports in the United States, football presents a significant risk of blunt chest trauma. Thus, effective chest protection is essential to prevent rare but fatal injuries like commotio cordis. Despite the risk of fatal outcomes, current test methods for certifying chest protective equipment fail to account for injury metrics relevant to commotio cordis and neglect body-to-body collisions, common in contact sports such as football. This study presents the development of a method that simulates shoulder-to-chest impacts via a pneumatic linear impactor, and the evaluation of football chest protectors, with the goal of informing cardiac safety. This statistically verified method considers two impact locations vulnerable to commotio cordis at minimum and moderate football tackle testing speeds to evaluate chest forces, rib deflections, and viscous criterion values of seven different football chest protector combinations on a Hybrid III Upper Torso Assembly. Additionally, this study investigates the quasi-static behavior of the chest to evaluate the predictive capability of quasi-static tests for the dynamic performance of these protector combinations. Researchers show that current football chest protectors fail to reduce viscous criterion values below the established 25% risk threshold for commotio cordis risk at moderate football tackle testing speeds. Additionally, researchers observed a moderate trend between quasi-static stiffness and dynamic viscous criterion ( R 2  = 0.580, p = 0.0468, slope = 0.059, 95% CI [0.02, 0.963]). Ultimately, a statistically verified test method was developed that differentiates between protector combinations, locations, and speeds, to inform certification standards for football chest protective equipment.

The understanding of association football head collision mechanics is of interest in the context of increased neurodegenerative disease risk in ex-professional players. This study sought to measure and characterise micromechanical pressure wave propagation from football head collisions; a distinct energy transfer mechanism from, and occurring before the start of, macromechanical gross head kinematics. A surrogate head setup, instrumented with a hydrophone pressure sensor, was exposed to footballs travelling at match realistic velocities. Pressure waves emanating from the region of first contact were measured within the cranial cavity. Their mean peak-to-peak magnitudes were up to 31.0 kPa. Across a range of 20 footballs of different materials, constructions and assembly methods, all of which satisfied the Laws of the Game, a 9.1-fold difference in peak-to-peak pressure and 54.7-fold difference in energy transfer, was observed. A 5-fold increase in peak-to-peak pressure was observed for a 77% increase in ball inbound velocity. Hydrophilic leather ball types demonstrated up to 4.2-fold greater peak-to-peak pressures when tested in wet, compared to dry conditions. These data highlight that pressure wave energy transfer may be influenced by the materials and construction of the ball, with scope to affect this without requiring alteration to the game or its Laws. The influence of these pressure waves on acute and long-term brain health requires further exploration.

Ring size was proved to impact bicycle drivetrain efficiency as larger rings are used to improve this efficiency. However, results from studies focused on sprockets create a gain expectation that is not met when considering ring size at a fixed gear ratio. This study was designed to understand this discrepancy better. Three chainring sizes (58, 60, 62 teeth) and 3 sprocket sizes (13, 16, 24 teeth) were tested on a dedicated testing rig in conditions that were representative for professional time-trial racing (450 W, 100 rpm). Four derailleur pulley combinations (11 teeth for the upper pulley and 11 for the lower, 14–14, 14–18 and 14–19 teeth) were tested as well. Bigger sprockets allow an increased efficiency, as expected based on the literature. However, a slight trend toward a decrease in efficiency was observed when increasing chainring size. If it was to be confirmed, this trend could be explained by the fact that, at a fixed torque, chainring size governs chain tension, on which efficiency depends. Indeed, a bigger chainring lowers chain tension and therefore could decrease efficiency. This finding could explain the moderate gains in efficiency measured for a fixed gear ratio when compared to studies focused on sprocket size. This study did not find any effect from derailleur pulley size. Overall, bigger rings offer better efficiency, as efficiency is mainly governed by the sprocket effect, but this effect could well be reduced by an opposed chainring effect at a fixed gear ratio and torque.

Women’s soccer has grown significantly in popularity, competitiveness, and professionalism. Despite this growth, research on collective spatial organization and its relationship with match outcomes in elite women’s soccer remains limited. This study aimed to investigate differences in spatial organization and technical-tactical performance between winning and losing teams during the FIFA Women’s World Cup 2023. A total of 102 observations from 51 non-drawn matches were analyzed using official FIFA post-match reports. The variables included width, height, depth, total area occupied by the team, and key match actions (shots, completed passes, receptions in the final third, line breaks, and defensive line breaks). Generalized Linear Models were used to compare outcomes. Results showed that winning teams performed better in most technical-tactical actions and recovered possession faster, while applying less defensive pressure. Spatially, they demonstrated greater width, height, and area in the build-up and progression phases, higher positioning in the high and middle blocks, and distinct patterns in the final third and low block. These findings establish a benchmark analysis for elite women’s soccer, showing how the integration of spatial and technical-tactical performance metrics can more accurately inform training and strategic planning.

The purpose of this study was to analyze scoring outcomes according to manufacturer differences in official Taekwondo Protector and Scoring Systems (PSS). To this end, match data were collected from 77 women’s bouts at the 2024 Paris Olympic Games using the D-company PSS and 361 women’s bouts at the 2025 World Taekwondo Championships using the K-company PSS. Due to differences in weight class structures between the two competitions, all data were integrated and analyzed based on the Olympic weight class criteria. The results showed that, across all weight classes, the K-company PSS exhibited a higher proportion of trunk scoring, whereas the D-company PSS demonstrated a relatively higher proportion of head scoring. For both manufacturers, roundhouse kicks were identified as the primary scoring technique; however, statistically significant differences in scoring outcomes were observed between manufacturers even when technically comparable actions and match situations were applied. These differences were particularly pronounced in the lightweight divisions, where a wider range of techniques and competitive situations contributed to scoring, while in the middleweight and heavyweight divisions, differences were more limited and primarily associated with high-scoring techniques.

High-performance cycling ergometers require precise control systems to ensure smooth operation, dynamic stability, and accurate resistance modulation. Traditional control methods for active magnetic bearings (AMBs) often struggle to manage nonlinear system behavior and external disturbances. This study develops and evaluates a reinforcement learning-based control framework for AMBs to improve stability and responsiveness in cycling ergometers under variable loading conditions. A nonlinear dynamic model of the rotor system is formulated, incorporating magnetic force dynamics, shaft deflection, and disturbances such as pedaling force variation and flywheel imbalance. Two control strategies are implemented and compared: a conventional Proportional-Integral-Derivative (PID) controller and a reinforcement learning controller based on Proximal Policy Optimization (PPO). Both controllers are trained in simulation and evaluated under transient and steady-state conditions. Results show that the PPO controller provides superior rotor stability, reduced angular deviation, and more robust performance under shock inputs compared to PID control. Additionally, the PPO controller adapts effectively to varying operational scenarios without manual tuning. These findings demonstrate the potential of reinforcement learning for real-time adaptive control of AMBs, offering a promising approach to enhance the performance, reliability, and user experience of next-generation sports training equipment.