Kyle R Leister, Sara E Burke, Kevin Carroll, Tiago V Barreira
{"title":"Predicting physical activity from self-reported mobility in individuals with transtibial amputation: A validation study.","authors":"Kyle R Leister, Sara E Burke, Kevin Carroll, Tiago V Barreira","doi":"10.1080/02640414.2025.2520109","DOIUrl":"https://doi.org/10.1080/02640414.2025.2520109","url":null,"abstract":"<p><p>Accelerometry-based physical activity monitoring can complement information obtained via patient-reported outcome measures (PROMs) by permitting objective, free-living measurements of mobility. The purpose of this study was to examine the relationship between the Prosthetic Limb User's Survey of Mobility (PLUS-M) PROM and accelerometer-measured steps and to develop and validate an equation for predicting steps. Participants with transtibial amputation completed the PLUS-M and wore an activPAL for seven days. LASSO regression was used to build a prediction model in training data (<i>n</i> = 80), and performance was evaluated in holdout data (<i>n</i> = 26). There was a moderately high correlation (<i>r</i> = 0.77) between model-predicted and actual steps in the holdout data. However, the model overestimated steps (<i>t</i><sub>25</sub>=-2.09, <i>p</i> = 0.046) and failed to meet the predefined equivalence threshold of ± 10% of the actual mean step counts (CI: 0, 968.82 steps; <i>p</i> > 0.05). Additionally, a root mean square error of 1,380 steps was noted between the model and activPAL-measured steps, representing roughly 33% of the mean actual step count. While the moderately high correlation highlights the potential of combining PROMs with accelerometer data to approximate physical activity, these limitations indicate the model is not yet suitable for clinical decision-making. Further refinement is required to improve accuracy and enhance practical application.</p>","PeriodicalId":17066,"journal":{"name":"Journal of Sports Sciences","volume":" ","pages":"1-10"},"PeriodicalIF":2.3,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144310070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Diwei Zhou, Justin W L Keogh, Yingliang Ma, Raymond K Y Tong, Abdul R Khan, Nicholas R Jennings
{"title":"Artificial intelligence in sport: A narrative review of applications, challenges and future trends.","authors":"Diwei Zhou, Justin W L Keogh, Yingliang Ma, Raymond K Y Tong, Abdul R Khan, Nicholas R Jennings","doi":"10.1080/02640414.2025.2518694","DOIUrl":"10.1080/02640414.2025.2518694","url":null,"abstract":"<p><p>This narrative review explores the transformative impact of artificial intelligence (AI) in sport, covering its applications, challenges and future directions across key areas such as biomechanics, performance enhancement, sports medicine, health monitoring, coaching and talent identification. AI can potentially empower athletes to optimise movement, personalise training, improve diagnostics and accelerate rehabilitation. However, integrating AI into sport presents challenges, particularly around data privacy, ethical concerns and adoption within sport organisations. This review also addresses these issues, highlighting strategies for responsible data governance and transparency. Furthermore, the review explores the promising future trends for AI in sport, which suggest a profound impact how sport is practiced and managed globally, pointing towards an era of enhanced performance, health and inclusivity.</p>","PeriodicalId":17066,"journal":{"name":"Journal of Sports Sciences","volume":" ","pages":"1-16"},"PeriodicalIF":2.3,"publicationDate":"2025-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144302354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Miguel Gomes, Afonso Fitas, Paulo Santos, Pedro Pezarat-Correia, Goncalo V Mendonca
{"title":"Effects of concurrent training on maximal and explosive strength in trained individuals: Insights from the load-velocity relationship.","authors":"Miguel Gomes, Afonso Fitas, Paulo Santos, Pedro Pezarat-Correia, Goncalo V Mendonca","doi":"10.1080/02640414.2025.2518827","DOIUrl":"https://doi.org/10.1080/02640414.2025.2518827","url":null,"abstract":"<p><p>This study explored the effects of concurrent-training (CT), resistance-only (R) and endurance-only (E) training on back squat one-repetition maximum (1RM), load-velocity profile (LVP) parameters and countermovement jump (CMJ). Thirty trained males were randomised into three groups (E, R, CT) and trained thrice-weekly for 11-weeks. R and CT groups completed a two-phase resistance training programme: maximal-strength (weeks 1-5) and explosive-strength (weeks 6-11). E and CT groups performed 30-minutes of running within the moderate-to-heavy-intensity domains. CT involved resistance followed by endurance training. LVP parameters (L<sub>0</sub>, V<sub>0</sub>, Slope and A<sub>line</sub>), 1RM and CMJ height were assessed at baseline, mid-training and post-training. Back squat 1RM increased similarly in R and CT groups during the first phase but only in R during the second phase. CMJ height increased throughout both phases for R but only during the second for CT. R increased V<sub>0</sub> and decreased Slope in both phases, while CT exhibited similar changes only during the second phase. A<sub>line</sub> increased in R and CT during the first phase but improved only in R during the second. No significant changes occurred in the E group. CT impaired maximal and explosive strength adaptations compared to R, highlighting the need for tailored programmes to reduce interference effects.</p>","PeriodicalId":17066,"journal":{"name":"Journal of Sports Sciences","volume":" ","pages":"1-21"},"PeriodicalIF":2.3,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144289478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Development and internal validation of machine learning prognostic models of sports injuries using self-reported data in athletics (track and field): The influence of quantity and quality of features.","authors":"Spyridon Iatropoulos, Pierre-Eddy Dandrieux, Pascal Edouard, Laurent Navarro","doi":"10.1080/02640414.2025.2517971","DOIUrl":"10.1080/02640414.2025.2517971","url":null,"abstract":"<p><p>To compare the performance of sports injury prognostic machine learning models when trained on (i) baseline data (i.e. collected once) vs. monitoring data (i.e. collected frequently over a period), (ii) raw monitoring data vs. time-integrating engineered features of the same data, and (iii) different numbers of features. Self-reported data collected during a previous randomised controlled trial in athletics athletes over 39 weeks constituted the dataset for model development. Baseline features, monitoring features, and two time-integrating feature engineering strategies were employed. Seven machine learning algorithms were trained with different groups and numbers of features and validated internally with bootstrapping. The models' discrimination was statistically compared using t-tests or Mann-Whitney tests (α = 0.00026). A dataset of 4537 cases including 149 injuries was derived from 165 athletes. Monitoring features outperformed baseline features in 5 out of 7 algorithms (<i>p</i> < 0.00026). The two feature engineering strategies showed marginal differences (1-8%) in 4 out of 7 algorithms (<i>p</i> < 0.00026). Larger numbers of features showed consistent improvements of performance for 6 out of 7 algorithms. Developing injury prediction ML models based on self-reported data in the sport of athletics seems promising but highly influenced by the quality and quantity of features.</p>","PeriodicalId":17066,"journal":{"name":"Journal of Sports Sciences","volume":" ","pages":"1-15"},"PeriodicalIF":2.3,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144285044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alexandre Schortgen, Thibault Goyallon, Guillaume Saulière, Antoine Muller, Lionel Revéret
{"title":"Monocular markerless position tracking of elite amateur boxing fighters in real combat situation.","authors":"Alexandre Schortgen, Thibault Goyallon, Guillaume Saulière, Antoine Muller, Lionel Revéret","doi":"10.1080/02640414.2025.2510774","DOIUrl":"https://doi.org/10.1080/02640414.2025.2510774","url":null,"abstract":"<p><p>Markerless video analysis represents an opportunity for conducting efficient in-situ motion analysis of athletes during competitions. From monocular video data, we propose a robust end-to-end method to automatically capture the 2D trajectory of athletes' position on planar ground, even in highly occluded contexts. A tracking-by-detection algorithm is first applied on a short sequence to build a specific contextual dataset ('self-supervision'). These data are subsequently used to train a specific person detector. Afterwards, body anatomical features in image coordinates are identified using human pose estimator. Athletes position is extracted as the midpoint between the feet and converted to metric units through homography. The accuracy of our monocular algorithm was evaluated by comparison with a position trajectories calculated from markerless reconstruction of 3D poses using 11 accurately synchronized and calibrated cameras as reference. The average error was 0.3 m over about 130,000 frames at 50 fps. The trajectories of the monocular method and the multiple views reference show an average correlation above 0.9. The robustness of the monocular method was tested in real competition of boxing combats for 18 rounds involving 22 elite fighters. These results open perspectives to provide performance indicators such as ring generalship to the coaching staff with minimal setup.</p>","PeriodicalId":17066,"journal":{"name":"Journal of Sports Sciences","volume":" ","pages":"1-15"},"PeriodicalIF":2.3,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144266482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Massimiliano Ditroilo, Cristian Mesquida, Grant Abt, Daniël Lakens
{"title":"Exploratory research in sport and exercise science: Perceptions, challenges, and recommendations.","authors":"Massimiliano Ditroilo, Cristian Mesquida, Grant Abt, Daniël Lakens","doi":"10.1080/02640414.2025.2486871","DOIUrl":"10.1080/02640414.2025.2486871","url":null,"abstract":"<p><p>Quantitative exploratory research implies a flexible examination of a dataset with the purpose of finding patterns, associations, and interactions between variables to help formulate a hypothesis, which should be severely tested in a future confirmatory study. In many fields, including sport and exercise science, exploratory research is not openly reported, a practice that leads to serious problems. At the same time, exploration is a crucial step in scientific knowledge generation, and a substantial proportion of studies will be exploratory in nature, or include both confirmatory and exploratory analyses. Using a flowchart, we review how data are typically collected and used, and we distinguish exploratory from confirmatory studies by arguing that data-driven analyses, where the Type I and Type II error cannot be controlled, is what characterises exploratory research. We ask which factors increase the quality and value of exploratory analyses, and highlight large sample sizes, uncommon sample compositions, rigorous data collection, widely used measures, observing a logical and coherent pattern across multiple variables, and the potential for generating new research questions as the main factors. Finally, we provide guidelines for carrying out and transparently writing up an exploratory study.</p>","PeriodicalId":17066,"journal":{"name":"Journal of Sports Sciences","volume":" ","pages":"1108-1120"},"PeriodicalIF":2.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143803568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wenjin Wang, Shulin Xu, Marvin Zedler, Yutong Jing, Wolfgang Potthast
{"title":"Tracking of time-dependent changes in concentric and eccentric quadriceps and hamstring torques and powers after a half-marathon.","authors":"Wenjin Wang, Shulin Xu, Marvin Zedler, Yutong Jing, Wolfgang Potthast","doi":"10.1080/02640414.2025.2489857","DOIUrl":"10.1080/02640414.2025.2489857","url":null,"abstract":"<p><p>The increasing participation in running events, particularly half-marathons, has been noteworthy in recent decades. However, the time course of recovery of muscle performance after a half-marathon running remains largely unclear. This study aimed to investigate changes in concentric and eccentric quadriceps and hamstring peak torques and mean powers, as well as hamstring to quadriceps torque and power ratios, after a half-marathon. Thirty-eight recreational runners participated in this study. Isokinetic dynamometry was used to measure peak torque and mean power at four time points: pre (baseline), immediately post (within 5 min), 1 day post and 2 days post half-marathon running. Compared with baseline measurements, reductions were observed in concentric and eccentric quadriceps and hamstring peak torques (<i>p</i> < 0.001) and mean powers (<i>p</i> < 0.001), reductions in eccentric hamstring to concentric quadriceps torque ratios (<i>p</i> < 0.001) and power ratios (<i>p</i> = 0.033). Most measured parameters recovered to baseline within 1 day, except concentric quadriceps peak torques and mean powers, which were restored within 2 days. By the second day, we also observed supercompensation in concentric hamstring and eccentric quadriceps peak torques and mean powers. These findings suggest that recreational runners should avoid high-intensity exercise within 2 days after a half-marathon to minimize injury risk.</p>","PeriodicalId":17066,"journal":{"name":"Journal of Sports Sciences","volume":" ","pages":"1070-1075"},"PeriodicalIF":2.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143788410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Relationships between coordination, strength and performance during initial sprint acceleration.","authors":"Byron Donaldson, Neil Bezodis, Helen Bayne","doi":"10.1080/02640414.2025.2482361","DOIUrl":"https://doi.org/10.1080/02640414.2025.2482361","url":null,"abstract":"<p><p>Despite strong logical and theoretical links, no studies have directly examined the relationship between physical qualities and coordination during sprint acceleration. The aim of this study was to assess the associations between initial acceleration coordination and lower body strength and explore potential interactions between strength and coordination in relation to acceleration performance. Sagittal plane kinematics and velocity-time profiles were obtained for highly trained to world class male sprinters (100 m PB: 9.95-11.17 s). Thigh-thigh and shank-foot coordination was determined for the first four steps using vector coding, and external kinetic parameters derived from a mono-exponential fit to velocity-time profiles. Lower body strength was measured with isometric squat (ISqT), countermovement jump (CMJ), repeated hop (HJ) and Nordic hamstring tests. Large to very large correlations (ρ = 0.59-0.82) existed between ISqT, CMJ, HJ tests and specific coordination features in both step 1 and steps 2-4, and exploratory regression analyses suggested the potential for higher or lower magnitudes of a given strength capacity to modify the relationships between coordination features and acceleration performance. These findings support an individualised approach to technique in sprint training, and consideration of the influence of strength qualities on the adoption and effectiveness of particular movement patterns.</p>","PeriodicalId":17066,"journal":{"name":"Journal of Sports Sciences","volume":"43 12","pages":"1095-1107"},"PeriodicalIF":2.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143978555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using markerless motion analysis to quantify sex and discipline differences in external mechanical work during badminton match play.","authors":"Filippo Santiano, Seb Ison, Julie Emmerson, Steffi Colyer","doi":"10.1080/02640414.2025.2489863","DOIUrl":"https://doi.org/10.1080/02640414.2025.2489863","url":null,"abstract":"<p><p>The high prevalence of overuse injuries in badminton poses a major threat to player development and success, with current training 'load' metrics insufficient for capturing the physical demands. This study quantified the external mechanical work performed during badminton match play across different sexes and disciplines. An eight-camera system captured fourteen male and fourteen female competitive (University to national level) badminton players competing across a total of nine singles and six doubles matches. Markerless pose estimation (HRNet) was used to drive a kinematic model (OpenSim) of each player and compute mass-normalised external mechanical work and power for 30 points per match. A linear mixed effects model found normalised work and power to be greater in men's vs. women's matches (effect size [ES] ± 90% CI = 0.60 ± 0.29 and 1.10 ± 0.48, respectively). Normalised work and power were also greater in singles vs. doubles matches (ES = 0.44 ± 0.29 and 0.47 ± 0.44, respectively). Interestingly, discipline differences were greatest among the most skilled players (e.g. ES = 0.88 ± 0.49 for first-team males). These findings highlight the importance of additional strength training and adequate recovery for elite male players to manage the high physical demands of singles match play.</p>","PeriodicalId":17066,"journal":{"name":"Journal of Sports Sciences","volume":"43 12","pages":"1158-1166"},"PeriodicalIF":2.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144032213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A conceptual framework and review of multi-method approaches for 3D markerless motion capture in sports and exercise.","authors":"Habib Noorbhai, Sanghee Moon, Takashi Fukushima","doi":"10.1080/02640414.2025.2489868","DOIUrl":"10.1080/02640414.2025.2489868","url":null,"abstract":"<p><p>The increasing diversity in motion capture technologies necessitates a structured approach to review and compare different systems. This paper presents a conceptual framework based on a review of existing motion capture methodologies, ranging from single-camera configurations to multi-camera systems enhanced with depth sensing and computer vision technology. The framework encompasses three distinct approaches: 1) single-camera with depth estimation, 2) single-camera with depth sensors, and 3) multiple cameras. Each method is detailed in terms of setup procedures, calibration techniques, advantages and disadvantages, as well as data processing workflows. The paper provides a framework and guide that can be adapted to different research and application contexts for sports and exercise, ensuring accurate and reliable 3D markerless motion capture. This framework aims to assist researchers, analysts and scientists in choosing the most suitable configuration based on their sport, specific requirements and/or constraints. By outlining the processes and considerations for each setup, this paper serves as a methodological guide, facilitating broader adoption and standardisation of advanced 3D motion capture technologies for sports and exercise. Although empirical data is not included in this paper, the focus on procedural guidelines demonstrates methodological rigour and practical implementation for 3D markerless motion capture research in sports and exercise.</p>","PeriodicalId":17066,"journal":{"name":"Journal of Sports Sciences","volume":" ","pages":"1167-1174"},"PeriodicalIF":2.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143803639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}