Identifying combinations of players (that is, lineups) in basketball - and other sports - that perform well when they play together is one of the most important tasks in sports analytics. One of the main challenges associated with this task is the frequent substitutions that occur during a game, which results in highly sparse data. In particular, a National Basketball Association (NBA) team will use more than 600 lineups during a season, which translates to an average lineup having seen the court in approximately 25-30 possessions. Inevitably, any statistics that one collects for these lineups are going to be noisy, with low predictive value. Yet, there is no existing work (in the public at least) that addresses this problem. In this work, we propose a regression-based approach that controls for the opposition faced by each lineup, while it also utilizes information about the players making up the lineups. Our experiments show that L-RAPM provides improved predictive power than the currently used baseline, and this improvement increases as the sample size for the lineups gets smaller.
Anupam Agrawal, Rajesh Mohanty, Shamik Bhattacharjee
et al.
Contextual Bandit (CB) algorithms are widely adopted for personalized recommendations but often struggle in dynamic environments typical of fantasy sports, where rapid changes in user behavior and dramatic shifts in reward distributions due to external influences necessitate frequent retraining. To address these challenges, we propose a Hierarchical Contextual Uplift Bandit framework. Our framework dynamically adjusts contextual granularity from broad, system-wide insights to detailed, user-specific contexts, using contextual similarity to facilitate effective policy transfer and mitigate cold-start issues. Additionally, we integrate uplift modeling principles into our approach. Results from large-scale A/B testing on the Dream11 fantasy sports platform show that our method significantly enhances recommendation quality, achieving a 0.4% revenue improvement while also improving user satisfaction metrics compared to the current production system. We subsequently deployed this system to production as the default catalog personalization system in May 2025 and observed a further 0.5% revenue improvement.
Ines Farah KANFOUD, Ibrahim SERSAR, Meriem BENCHARIF
et al.
Introduction: Adopting good nutritional practices and strategies can be attributed to a better understanding of dietary knowledge and habits, thus promoting good sports performance. This study aimed to assess athletes' nutritional knowledge, eating habits, and adherence to the Mediterranean diet.
Methodology: Cross-sectional survey of 70 adult athletes. Data were collected using a questionnaire assessing their eating habits, nutritional knowledge (Abridged Nutrition for Sport Knowledge Questionnaire, A-NSKQ), and adherence to the Mediterranean diet (Medi-Lite score). Statistical analyses were performed using R software (version 3.0.3), with a significance level set at p < 0.05.
Results: Athletes were young adults (18.9–27.8 years) with an average of 7.5 ± 2.8 years of sports practice. Most participants (77.1%) reported consuming four or more meals per day. No sex differences were observed in the consumption of milk and derivatives, cereals, legumes, or starchy foods. In contrast, men generally consumed other food groups more frequently, except for sweet products, which were consumed more often by women (p < 0.001). Overall nutritional knowledge was low (46.5%), with significantly higher scores for general nutrition compared with sports nutrition (67.3% vs. 36.9%; p < 0.001). Adherence to the Mediterranean diet was moderate (mean score: 7.95), with higher scores in men than women and a large effect size. No significant correlations were observed between length of time in sport and either general nutrition knowledge (r = 0.04) or sports nutrition knowledge (r = 0.03). Likewise, adherence to the Mediterranean diet was not significantly correlated with general nutrition knowledge (r = 0.0001), sports nutrition knowledge (r = 0.0013), or total nutrition knowledge (r = 0.0011).
Conclusion: The present study found no significant correlation between nutritional knowledge and adherence to the Mediterranean diet, with athletes demonstrating low levels of both. These findings underscore the necessity for targeted nutrition education interventions to enhance dietary knowledge and practices.
Nutrition. Foods and food supply, Nutritional diseases. Deficiency diseases
Thomas Gossard, Filip Radovic, Andreas Ziegler
et al.
Motion blur reduces the clarity of fast-moving objects, posing challenges for detection systems, especially in racket sports, where balls often appear as streaks rather than distinct points. Existing labeling conventions mark the ball at the leading edge of the blur, introducing asymmetry and ignoring valuable motion cues correlated with velocity. This paper introduces a new labeling strategy that places the ball at the center of the blur streak and explicitly annotates blur attributes. Using this convention, we release a new table tennis ball detection dataset. We demonstrate that this labeling approach consistently enhances detection performance across various models. Furthermore, we introduce BlurBall, a model that jointly estimates ball position and motion blur attributes. By incorporating attention mechanisms such as Squeeze-and-Excitation over multi-frame inputs, we achieve state-of-the-art results in ball detection. Leveraging blur not only improves detection accuracy but also enables more reliable trajectory prediction, benefiting real-time sports analytics.
Human pose capture is essential for sports analysis, enabling precise evaluation of athletes' movements. While deep learning-based human pose estimation (HPE) models from RGB videos have achieved impressive performance on public datasets, their effectiveness in real-world sports scenarios is often hindered by motion blur, occlusions, and domain shifts across different pose representations. Fine-tuning these models can partially alleviate such challenges but typically requires large-scale annotated data and still struggles to generalize across diverse sports environments. To address these limitations, we propose a 2D pose prior-guided refinement approach based on Neural Distance Fields (NDF). Unlike existing approaches that rely solely on angular representations of human poses, we introduce a polar coordinate-based representation that explicitly incorporates joint connection lengths, enabling a more accurate correction of erroneous pose estimations. Additionally, we define a novel non-geodesic distance metric that separates angular and radial discrepancies, which we demonstrate is better suited for polar representations than traditional geodesic distances. To mitigate data scarcity, we develop a gradient-based batch-projection augmentation strategy, which synthesizes realistic pose samples through iterative refinement. Our method is evaluated on a long jump dataset, demonstrating its ability to improve 2D pose estimation across multiple pose representations, making it robust across different domains. Experimental results show that our approach enhances pose plausibility while requiring only limited training data. Code is available at: https://github.com/QGAN2019/polar-NDF.
Introduction. The problem of the research is connected with the constant change of the life rhythm caused by technocratic innovations. The neeed for new skills is today an integral component of a multifaceted life in a rapidly changing society. In this regard, the issues of continuous education carry a deep meaning of the objective variability of human life in the context of a dynamically changing reality.Materials and methods. The research methodology is based on the use of a set of methods of scientific knowledge: analysis, classification, systematization, comparison, generalization. Dissertation studies on Pedagogy, the title of which contains the category «continuous education», coducted in the period from 2000 to 2022, served as an empirical base.The Research results. Based on the data obtained through scientometric analysis of dissertation studies, the specified semantic units of the studied scientific and pedagogical content have been recorded; thematic clusters containing in the title significant areas of scientific and practice-oriented topics on the problem of continuous education have been determined.Discussion and conclusion. The evolution of the scientific direction «continuous education» has been revealed, quantitative indicators of its state, the degree of development and demand for pedagogical practice have been determined. An objective picture of the development of this scientific direction has been obtained and its prospects as a subject of scientific and pedagogical discourse ahave been determined.
Ksenia A. Blinova, Irina E. Mishina, Galina E. Ivanova
et al.
INTRODUCTION. The use of antitumor therapy in patients with breast cancer has led not only to an increase in their life expectancy, but also to the need to correct various side effects, including manifestations of cardiotoxicity. Rehabilitation of such patients in Russia is currently lacking.
AIM. To search and analyze the literature on the effectiveness of physical training for the prevention of cardiotoxic complications of antitumor therapy.
MATERIALS AND METHODS. Publications from the PubMed, Scopus, Web of Science, PEDro databases over the past 15 years were collected and analyzed 15 years by keywords in Russian and English: “cardiotoxicity”, “exercise”, “breast cancer”. 126 sources were selected, including systematic reviews and a Cochrane review.
RESULTS AND DISCUSSION. Preclinical studies have shown that physical exercise reduces the accumulation of antitumor drugs in the myocardium and increases the proliferation of cardiomyocyte progenitor cells. Conducting physical training during and after anticancer treatment increases cardiorespiratory endurance and reduces the manifestations of anthracycline cardiotoxicity. This rehabilitation intervention leads to less fatigue, decreased depression, improved physical fitness, cognitive functions, and quality of life. The greatest effectiveness during and after anticancer therapy was shown by aerobic and strength exercises of moderate intensity, performed for 30–40 minutes 3–5 times a week, which provide 150 minutes of physical activity per week. The limitation of the use of physical training in patients is due to the impossibility of predicting the training heart rate by age, as well as the need to take into account concomitant diseases and the patient’s condition.
CONCLUSION. The use of physical training can be used in cancer patients to prevent cardiotoxicity of anticancer therapy. Further research is needed to ensure their successful use in patients with different physical fitness and treatment tolerance.
The excessive use of antibiotics in industrial meat production in the U.S. incurs severe health implications for animals, humans, and the environment, thereby threatening the integrated health of the ecosystem and sustainable development. While the consumption of meat, including hot dogs, chicken wings, and hamburgers, is a hallmark of attending professional sports events in North America, the sourcing policies for meat in the realm of professional sports remain relatively obscure. We conducted a content analysis case study on the four major sports leagues in North America, their teams and stadium practices. Our objective was twofold: first, to investigate existing sustainability initiatives at the league, team, and stadium levels; and second, to examine whether there are any food sourcing programs, specifically meat sourcing policies that might encourage the consumption of meat produced without the use of antibiotics, in the sports sector that are designed to mitigate ecological ramifications of meat consumption within sports contexts. Results show that existing sustainability initiatives at the three levels are focused primarily on reducing carbon emissions and waste. There is, however, a notable neglect of food sourcing policies, which is concerning given that industrial animal agriculture is a leading cause of antibiotic resistance and environmental degradation. This suggests that meat sourcing policy is a missing piece in current sustainability initiatives. The major sports leagues should therefore consider incorporating pertinent policies, such as procuring meat-based products produced without the use of antibiotics to help strengthen their existing efforts in achieving their sustainable development goals.
Many works in the domain of artificial intelligence in games focus on board or video games due to the ease of reimplementing their mechanics. Decision-making problems in real-world sports share many similarities to such domains. Nevertheless, not many frameworks on sports games exist. In this paper, we present the tennis match simulation environment \textit{Match Point AI}, in which different agents can compete against real-world data-driven bot strategies. Next to presenting the framework, we highlight its capabilities by illustrating, how MCTS can be used in Match Point AI to optimize the shot direction selection problem in tennis. While the framework will be extended in the future, first experiments already reveal that generated shot-by-shot data of simulated tennis matches show realistic characteristics when compared to real-world data. At the same time, reasonable shot placement strategies emerge, which share similarities to the ones found in real-world tennis matches.
Eduardo Alves Baratela, Felipe Jordão Xavier, Thomas Peron
et al.
Soccer attracts the attention of many researchers and professionals in the sports industry. Therefore, the incorporation of science into the sport is constantly growing, with increasing investments in performance analysis and sports prediction industries. This study aims to (i) highlight the use of complex networks as an alternative tool for predicting soccer match outcomes, and (ii) show how the combination of structural analysis of passing networks with match statistical data can provide deeper insights into the game patterns and strategies used by teams. In order to do so, complex network metrics and match statistics were used to build machine learning models that predict the wins and losses of soccer teams in different leagues. The results showed that models based on passing networks were as effective as ``traditional'' models, which use general match statistics. Another finding was that by combining both approaches, more accurate models were obtained than when they were used separately, demonstrating that the fusion of such approaches can offer a deeper understanding of game patterns, allowing the comprehension of tactics employed by teams relationships between players, their positions, and interactions during matches. It is worth mentioning that both network metrics and match statistics were important and impactful for the mixed model. Furthermore, the use of networks with a lower granularity of temporal evolution (such as creating a network for each half of the match) performed better than a single network for the entire game.
Subhasis Dasgupta, Pratik Satpati, Ishika Choudhary
et al.
In the recent past, there were several works on the prediction of stock price using different methods. Sentiment analysis of news and tweets and relating them to the movement of stock prices have already been explored. But, when we talk about the news, there can be several topics such as politics, markets, sports etc. It was observed that most of the prior analyses dealt with news or comments associated with particular stock prices only or the researchers dealt with overall sentiment scores only. However, it is quite possible that different topics having different levels of impact on the movement of the stock price or an index. The current study focused on bridging this gap by analysing the movement of Nifty 50 index with respect to the sentiments associated with news items related to various different topic such as sports, politics, markets etc. The study established that sentiment scores of news items of different other topics also have a significant impact on the movement of the index.
Large language models hold significant potential for integrating various data types, such as text documents and database records, for advanced analytics. However, blending text and numerical data presents substantial challenges. LLMs need to process and cross-reference entities and numbers, handle data inconsistencies and redundancies, and develop planning capabilities such as building a working memory for managing complex data queries. In this paper, we introduce four novel tasks centered around sports data analytics to evaluate the numerical reasoning and information fusion capabilities of LLMs. These tasks involve providing LLMs with detailed, play-by-play sports game descriptions, then challenging them with adversarial scenarios such as new game rules, longer durations, scrambled narratives, and analyzing key statistics in game summaries. We conduct extensive experiments on NBA and NFL games to assess the performance of LLMs on these tasks. Our benchmark, SportsMetrics, introduces a new mechanism for assessing LLMs' numerical reasoning and fusion skills.
The primary objective of this study was to assess the influence of exercise interventions on cancer-related fatigue (CRF), specifically in breast cancer patients, with the ultimate goal of establishing an optimal exercise prescription for breast cancer patients. A comprehensive search was undertaken across multiple databases, including Embase, PubMed, Cochrane Library, Web of Science, and Scopus, covering data published up to 1 September 2023. A meta-analysis was conducted to calculate the standardized mean difference (SMD) along with its corresponding 95% confidence interval (CI), thereby quantifying the effectiveness of exercise in alleviating CRF in the breast cancer patient population. Twenty-six studies met the inclusion criteria. Aerobic exercise (SMD, −0.17, <i>p</i> = 0.02), resistance exercise (SMD, −0.37, <i>p</i> = 0.0009), and combined exercise (SMD, −0.53, <i>p</i> < 0.0001) significantly improved CRF in breast cancer patients. In addition, exercise intervention conducted ≥3 times per week (SMD, −0.47, <i>p</i> = 0.0001) for >60 min per session (SMD, −0.63, <i>p</i> < 0.0001) and ≥180 min per week (SMD, −0.79, <i>p</i> < 0.0001) had greater effects on improving CRF in breast cancer patients, especially middle-aged patients (SMD, −0.42, <i>p</i> < 0.0001). Exercise is an effective approach to improving CRF in breast cancer patients. When devising an exercise program, the primary consideration should be the incorporation of combined exercise as the principal intervention. This entails ensuring that participants engage in the program at least three times weekly, with each session lasting for more than 60 min. The ultimate aim is to achieve a total weekly exercise duration of 180 min by progressively increasing the frequency of exercise sessions.
Pablo Reis de Moraes, Kauã Felipe Kunz, Maiara Helena Rusch
et al.
Introdução: O joelho é a principal articulação acometida pela osteoatrose (OA), com maior prevalência em mulheres idosas. Exercícios multifuncionais são eficazes no tratamento dessa condição, sendo a dança um exercício tolerável e bem aceito. Entretanto, não está claro qual a melhor modalidade de exercício traz maiores benefícios. Objetivo: Comparar a funcionalidade articular entre mulheres com OA de joelhos que participam de um programa de atividade física monitorada de alongamentos e exercícios resistidos para terceira idade e entre participantes de um grupo de dança recreativa. Materiais e Métodos: Estudo transversal, descritivo e analítico. Foram incluídas 47 mulheres acima de 50 anos com OA de joelho. As participantes foram divididas em 2 grupos, um com 25 mulheres que participavam de um grupo de dança recreativa; outro com 22 mulheres que realizavam um programa monitorado de exercícios resistidos e alongamentos. Todas responderam um questionário sociodemográfico e de saúde; a função articular foi avaliada pelo questionário WOMAC. Resultados: As participantes apresentaram características amostrais similares quanto a características sociodemográficas e de saúde. As participantes do grupo de atividade física apresentaram uma maior pontuação no questionário WOMAC em relação as dimensões dor (p<0,001), rigidez (p<0,001) e função física (p<0,001), quando comparadas às do grupo dança. Conclusão: Os resultados demonstram que mulheres com OA de joelho do grupo de dança recreativa apresentaram menos dor, menor rigidez e melhor função física do joelho, quando comparados com o grupo de atividade física monitorada de alongamentos e de exercícios resistidos para terceira idade.
Abstract Introduction The objective of this study is to investigate how lifestyle changes affect the emergency department (ED) presentations of pediatric patients with acute traumatic injuries during the COVID‐19 pandemic. Methods This retrospective cohort study was conducted in the ED of Akdeniz University Hospital. We analyzed the medical records of pediatric patients who presented to our ED with acute traumatic injury during the 52‐week period after March 16, 2020, which marks the official date when in‐person education was suspended in Turkey due to COVID‐19. These records were compared with those from the 52‐week period prior to March 16, 2020 (pre‐COVID). Patients with nontraumatic presentations or follow‐up visits (e.g., dressing, suture removal, injection, etc.) were excluded from the study. The data was obtained through the Hospital Information System. Results The total number of ED pediatric trauma visits declined by 46%. The overall presentation rates of patients between the ages of 1 and 4 years, home injuries, falls, burns, hospitalizations, and costs per patient increased during COVID‐19. In contrast, the rate of motor vehicle accidents, sports injuries, and injuries that occurred at schools and playgrounds decreased. Conclusions It should be expected that the decrease in the number of acute trauma presentations due to the implementation of distance education and lockdown restrictions will increase after the pandemic. As a result, it is necessary to pay attention to the safety of children in streets, playgrounds, and schools as the pandemic ends, as much as it will continue to be important to create safe environments for children at home. In order to reduce mortality and morbidity due to pediatric traumatic injuries, all authorized people, including the relevant ministries, should take precautions to protect children from injuries, and pediatric trauma should be addressed as a preventable public health problem.
Surgery, Medical emergencies. Critical care. Intensive care. First aid
Akihisa Shitara, Miki Namatame, Sayan Sarcar
et al.
In this study, we design and develop HaptStarter -- a haptic stimulus start system -- to improve the starting performance of the deaf and hard of hearing (DHH) sprinters. A DHH person has a physical ability nearly equivalent to hearing; however, the difficulties in perceiving audio information lead to differences in their performance in sports. Furthermore, the visual reaction time is slower than the auditory reaction time (ART), while the haptic reaction time is equivalent to it. However, a light stimulus start system is increasingly being used in sprint races to aid DHH sprinters. In this study, we design a brand-new haptic stimulus start system for DHH sprinters; we also determine and leverage an optimum haptic stimulus interface. The proposed method has the potential to contribute toward the development of prototypes based on the universal design principle for everyone (DHH, blind and low-vision, and other disabled sprinters with wheelchairs or artificial arms or legs, etc.) by focusing on the overlapping area of sports and disability with human-computer interaction.
Ryota Tanaka, Tomohiro Suzuki, Kazuya Takeda
et al.
Automatic evaluating systems are fundamental issues in sports technologies. In many sports, such as figure skating, automated evaluating methods based on pose estimation have been proposed. However, previous studies have evaluated skaters' skills in 2D analysis. In this paper, we propose an automatic edge error judgment system with a monocular smartphone camera and inertial sensors, which enable us to analyze 3D motions. Edge error is one of the most significant scoring items and is challenging to automatically judge due to its 3D motion. The results show that the model using 3D joint position coordinates estimated from the monocular camera as the input feature had the highest accuracy at 83% for unknown skaters' data. We also analyzed the detailed motion analysis for edge error judgment. These results indicate that the monocular camera can be used to judge edge errors automatically. We will provide the figure skating single Lutz jump dataset, including pre-processed videos and labels, at https://github.com/ryota-takedalab/JudgeAI-LutzEdge.
Daria Waligórska, Monika Frydrychowicz, Katarzyna Adamczyk
et al.
Athletes and their romantic partners may experience physical separation as a result of the frequent athletes’ training camps. Little is known about how such couples experience this separation. To fill this gap, the current interview-based research examined how three pairs of Polish athletes aged 22-30 (M = 23.50, SD = 25.17) experience separation in their relationships. The thematic analysis identified four themes: 1) Perception of separation as an element of the relationship; 2) Emotions during separation; 3) Maintaining contact during separation; and 4) Coping with separation. The findings revealed that athletes and their partners perceived separation as a stage, opportunity, necessity, and natural part of their relationships. Emotions related to separation ranged from negative through mixed to positive. Partners maintained regular contact, which provided closeness and continuity in their relationships despite the distance. Finally, partners coped with separation by accepting its necessity, enhanced by the awareness of the realities of sport life. They also coped with separation through mutual support, self-realization, distraction and being among other people and seeking support from them. This study suggests that physical separation in romantic relationships may be an essential and multifaceted part of the participants’ experiences in the romantic functioning and sports careers.
The aim of the study was to examine the effect of walking football applied to elderly male sedentary individuals on life satisfaction and heart rate variability. 22 male volunteers whose physical activity level was determined by International Physical Activity Questionnaire (IPAQ) were included to this study. Volunteers were divided into 11 exercise groups and 11 control groups by random sampling. While the control group had no activity participation, the exercise group performed a 20-minute warm-up, they played 60 minutes of walking football, and they performed a 10-minute cool down. This was done 2 days a week across an 8-week period. In the study, the Life Satisfaction Scale (LSS) was used in the exercise and control groups, Heart Rate (HR), Heart Rate Variability (HRV), heart-mind coherence, maximum heart-mind coherence measurements were applied with the Heartmath-Inner Balance device. “Paired t test” was used for analyzing pretest-posttest differences in variables while "Independent t test" was used for analyzing differences between the groups. Findings show that there was a significant difference between the exercise group’s HRV, heart-mind coherence, maximum heart-mind coherence, and pre-post test measurements of the LSS results (p<0.05), although there was no significant difference in the HR variable (p>0.05). No significant difference was found between the pre-test and post-tests mean comparison of all variables of the control group (p>0.05). According to the results, it can be concluded that walking football has a positive effect on life satisfaction, HRV, heart-mind coherence, and maximum heart-mind coherence in older adults.