Search Results (46)

Competitive eSports impose substantial cognitive workload, yet performance evaluation still emphasizes post-match statistics without considering players’ cognitive states. We reviewed 30 papers that recorded physiological signals using sensors and utilized machine learning (ML) for predicting cognitive states and/or game performance. Findings showed that cardiovascular monitoring (heart rate variability/HRV) was the most prevalent modality (20/30 studies), followed by oculometry (10), electrodermal activity/EDA (9), and electroencephalogram/EEG (5); however, no standardized protocols (device/pre-processing/feature subset) were observed across HRV studies despite it being the most common measure. The best outcomes per construct (measure, accuracy) were: mental workload (pupillometry, ~82%), stress/arousal (EDA, p < 0.001), cognitive fatigue (pupil diameter/EEG, ~88%), expertise (EEG, ~92%), and tilt (EDA/HRV/eye-tracking, ~82–87%). Notably, current studies used small samples and were gender-imbalanced, while ML studies often lacked cross-validation. Only 2 of 30 studies examined flow state—a mental state of optimal performance characterized by total immersion and effortless execution—and interestingly, HRV showed decreases during stress/workload but increases during flow, suggesting context-dependent autonomic regulation. To address this gap, a new framework for flow detection is presented. This review will be of interest to game developers, eSports players, and coaches, and the reported findings may help towards improving player experience and game performance. Full article

Electronic sport (esport) refers to competition in video games. Injuries in esports have hardly been studied so far. A total of 1229 e-athletes of all levels and genres answered a retrospective questionnaire about injuries and overuse damages that occurred in the course of their careers. The average age of the 1229 participants was 23.8 ± 5.5 years. A total of 198 (16.1%) of the e-athletes take part in competitions. The most common injury location was the trunk/spine (319, 26.0%) followed by the wrist region (225, 18.3%). Degenerative and overuse injuries were in the foreground. Professional athletes were injured more frequently than amateur athletes (p = 0.006). Tactical shooter players have significantly more injuries than sports game players (p = 0.021) and MMO (Massively Multiplayer Online) players (p = 0.042). E-athletes are just as susceptible to injury as athletes in traditional disciplines. The high injury rate is certainly not due to acute injuries but to overloading and overuse injuries, with a focus on the thoracocervical area and the upper extremities. Terms such as “Nintenditis”, “gamer’s thumb” and “PlayStation thumb”, which describe injuries caused by repetitive strain, are becoming increasingly common. Injuries in esports should be taken seriously, as they can cause long-term health problems in the event of overuse injuries. Prevention is a critical and promising approach for such a young patient clientele, especially in a sport that is growing so rapidly and is unknown to the majority. Full article

Modern football requires athletes to make rapid and effective decisions in highly dynamic environments. Although ecological dynamic approaches based on small-sided games have shown advantages over traditional training for decision-making development, the potential contribution of football eSports within integrated training protocols remains insufficiently explored. This study aimed to examine the effects of three training approaches—traditional training, ecological dynamic training with small-sided games, and a hybrid eSport-based protocol—on decision-making and reaction time in youth football players. Sixty-nine youth footballers (47 males and 22 females, mean age = 15.1 ± 0.9 years) were assigned to three groups and completed a 24-week intervention with pre-, mid-, and post-intervention assessments. General, offensive, and defensive decision-making were evaluated using the TacticUP Video Test, while reaction time was assessed through frame-by-frame video analysis. Data were analysed using mixed-design ANOVA (Group × Time) with Bonferroni post-hoc comparisons. Significant Group × Time interactions were observed for all variables, suggesting non-uniform longitudinal performance trends across the three training approaches, including a distinct pattern of change in the hybrid eSport-based group. In contrast, minimal changes were found in the traditional group, while moderate improvements were observed in the ecological dynamic group. Overall, the findings indicate that innovative training approaches are more effective than traditional training in enhancing decision-making and response speed in young footballers, with the hybrid eSport-based protocol showing the most pronounced effects. Full article

Background: Sleep quality and mental health are important concerns for esports competitors. However, epidemiological data regarding sleep quality and psychological distress among high-level esports players remain limited. Objective: This study aimed to examine sleep quality and mental health status among high-level esports competitors in Japan and to identify factors associated with psychological distress. Methods: This cross-sectional study included 275 competitors (269 males, 3 females, and 3 who did not report sex) participating in the 2023 National Prefectural Esports Championship. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), psychological distress using the Kessler Psychological Distress Scale (K6), and depressive symptoms using the Patient Health Questionnaire-9 (PHQ-9). Multivariable logistic regression analyses were performed to identify associated factors. Results: The response rate was 61.8% (275/445). Poor sleep quality (PSQI > cut-off) was observed in 38.5% of competitors. Based on the K6, 24.4% reported psychological distress above the mild threshold, and 29.5% reported mild or greater depressive symptoms according to the PHQ-9. Overall mental health levels were comparable to those reported in previous studies of general populations. Nighttime esports training was significantly associated with psychological distress (adjusted odds ratio 3.80; 95% confidence interval 1.50–9.64; p = 0.005). Conclusions: More than one-third of Japanese esports competitors experience poor sleep quality, and approximately one-quarter report mild or greater psychological distress. Nighttime esports training may be an important factor associated with mental health among competitors. Further longitudinal studies are warranted to clarify temporal relationships and to examine whether reducing nighttime training is associated with improved mental health outcomes among esports competitors. Full article

The rapid expansion of gaming and esports in Saudi Arabia has prompted new interest in understanding how social and regional factors shape digital play. One trend is the variation in gaming preferences and motivations across gender and geographic regions. Previous research on gaming behavior has often centered on Western contexts and cross-national comparisons, overlooking how subcultural variation may shape players’ motivations and genre choices. Through a nationwide survey of gamers in Saudi Arabia, distributed via gaming community platforms, we examined how gender and region relate to gaming motivations, preferred genres, and intention to continue playing. Quantitative data were analyzed using inferential statistical methods, while qualitative responses were examined through thematic analysis to identify recurring patterns and contextual insights. Findings reveal that men are more likely to report performance and competition-driven motivations, while women show stronger preferences for escapism and casual gameplay. These results indicate that regional subcultures within Saudi Arabia shape gaming behavior, challenging generalized assumptions about player preferences. By demonstrating systematic regional differences in gaming motivations and preferences, this study extends games user research and informs the development of culturally responsive game design strategies. Full article

Background/Objectives: The dopaminergic system regulates motivation, executive functions, motor learning, and emotional responses—processes that are key in both sport and esports. Although many studies analyse dopaminergic gene polymorphisms, their impact on psychophysical predispositions remains unclear. This narrative review aims to summarise current knowledge about the mechanisms of dopamine action and genetic determinants that may influence athletic and cognitive performance. Methods: The PubMed, Scopus, and Web of Science databases (publications from January 2010 to December 2025) were searched using keywords related to the DRD1–DRD5, COMT, SLC6A3/DAT1, and TH genes, as well as the terms ‘sport’ and ‘esport.’ Studies of athletes were included in which the relationship between dopaminergic polymorphisms and motivational and personality traits was assessed, and the results of neuroimaging and epigenetic studies were also considered. Results: Dopaminergic polymorphisms are associated with differences in reward processing, cognitive flexibility, motivation, and stress resilience. The most essential critical effects concern the DRD2 and DRD4 variants, which are associated with novelty seeking, reward dependence, and coping with stress. The COMT Val158Met polymorphism affects dopamine levels in the prefrontal cortex, modulating executive functions. The effects of individual polymorphisms are moderate, and conclusions regarding esports remain speculative due to limited research in this area. Conclusions: Dopaminergic predispositions involve interactions among genetics, neural activity, and the environment. However, current evidence is limited by small sample sizes, a predominance of European populations, scarce data on esports players, and difficulties in separating genetic effects from training-related adaptations. Full article

eSports and recreational video gaming are expanding in Peru, yet evidence on gamers’ dietary habits and correlates is scarce. We aimed to identify factors associated with eating habits among Peruvian video gamers and professional eSports players. Quantitative and cross-sectional study (Peru, 2023). A culturally adapted version of the German Sport University Cologne questionnaire (28 items; Cronbach’s α = 0.86) was administered online using non-probability snowball sampling. The primary outcome was eating-habit classification (adequate vs. inadequate) based on the instrument’s scoring. Associations with hypothesized correlates (e.g., gaming-related influences, peer interaction, advertising) were assessed with χ² or Fisher’s exact test (α = 0.05). We analyzed 288 respondents (median age 21 years). Overall, 77.8% exhibited inadequate eating habits. Daily water intake was reported by 72%, whereas daily fruit and vegetable consumption was 21% and 32%, respectively. Peer interaction within the gaming environment (p = 0.037) and the perceived influence of video games (p = 0.031) were significantly associated with poorer eating habits. Sitting time, number of meals per day, daily water intake volume, and weekly gaming hours showed no significant association (all p > 0.05). Most Peruvian gamers report suboptimal diets. Social dynamics in the gamer community and gaming-related influences are linked to poorer eating habits, suggesting that nutrition strategies should be embedded in gamer ecosystems (teams, communities, platforms). Longitudinal and interventional studies are warranted to test targeted behavior-change approaches. Full article

Football-themed eSports, combining entertainment and learning elements, are booming, offering benefits in terms of cognitive and motor skill development. Despite this, with the increasing use of eSports and their impact on cognitive and motor skills, there is still a paucity of empirical studies that systematically explore how cognitive stimulation from eSports can translate into psychomotor performance on the field, particularly with regard to linear speed. The aim of this study was to investigate the effects of an ecological–dynamic training protocol, integrated with football eSports, on the development of linear sprint speed in young soccer players. Thirty-two male youth football players (age range: 12–16 years) participated in the study. Participants were divided into an experimental group, which followed a combined ecological–dynamic training protocol including football eSports, and a control group, which performed standard training sessions. Pre- and post-intervention assessments of 30 m sprint performance were conducted using electronic timing gates. Statistical analysis using repeated-measures ANOVA indicated a marked improvement in 30 m sprint performance within the experimental group, decreasing from 4.908 s to 4.651 s. A significant time × group interaction was observed (F = 74.076, p < 0.001). Moreover, a robust main effect of time emerged (F = 141.12, p < 0.001), confirming consistent gains in linear sprint speed. Post hoc comparisons revealed significant differences across all assessment points (p < 0.001). The findings suggest that embedding football eSports into an ecologically grounded training framework may enhance the development of linear speed in young soccer players. This integrated approach shows potential as an innovative tool for performance enhancement, although further investigations are needed to confirm long-term efficacy and generalizability to other sporting populations. Full article

Background/Objectives: Our aim was to create a new method for analyzing metagenomics data, named the gut microbiome obesity index, using a set of taxa/biological functions that correlated with BMI. Methods: A total of 109 obese patients (73 women and 36 men, median BMI 43.0 kg/m²), 87 healthy control (HC) individuals (39 females and 48 males, median BMI 22.7 kg/m²), and 109 esports players (five females and 104 males, median BMI 23.0 kg/m²) were included in the study. To conduct metagenomic and metabolomic analyses, DNA and selected metabolites were isolated from fecal samples and used for whole-genome shotgun sequencing and gas chromatography/mass spectrometry, respectively. Results: Compared with HCs and esports players, obese patients with a BMI > 40 kg/m² had a significantly higher alpha diversity, as analyzed by the Shannon index, and significant dissimilarities in beta diversity. Both richness and diversity measures were correlated with BMI. Compared with HCs and esports players, 12 differential bacteria were found in the overall obesity group and 42 were found in those with a BMI > 40 kg/m². Most of the altered species belonged to the Lachnospiraceae family. When the logarithmic relationship of the sums of the bacteria correlated with BMI was calculated to establish a taxonomic health index, it better differentiated between the obesity groups than a standard analytical pipeline; however, it did not differentiate between the HC and the BMI < 35 kg/m² obesity group. Therefore, we created a functional index based on BMI-associated biological pathways, which differentiated between all obesity groups. Conclusions: Of the obesity indices used to distinguish between healthy and obese microbiota analyzed in this study, a function-based index was more useful than a taxonomy-based index. We believe that gut microbiome indexes could be useful as part of routine metagenomics evaluations. However, an index developed in one geographical area might not be applicable to individuals in a different region and, therefore, further studies should develop separate indices for different populations or geographical regions rather than relying on a single index. Full article

Esports is a global industry, with coaches widely regarded as having a pivotal role in facilitating player development and enhancing performance. Despite this, limited research has investigated the developmental experiences of esports coaches and how they are valued by diverse stakeholder groups. Consequently, the aim of this research is to explore global stakeholders’ perspectives towards the developmental experiences of esports coaches. Data were collected via a qualitative online survey completed by 98 participants, representing 28 nationalities, across six esports stakeholder groups (head coach, assistant coach, player, team manager, performance staff, analyst). Following a reflexive thematic analysis process, three themes were generated: (1) Speaking the same language: the importance of playing and knowing the game; (2) Walking the walk: the need for coaching experience to demonstrate competency; and (3) Formal professional learning and development: a bone of contention. By understanding how diverse stakeholders value different developmental experiences, the findings offer unique insights into the contested nature of coach development in esports. This research contributes to the esports coaching literature and provides a foundation for future empirical research into this emerging area, with recommendations and implications for esports coach education and practice discussed. Full article

Large-scale match data from esports games like League of Legends are stored in complex JSON files that often exceed the input token limitations of large language models (LLMs), restricting advanced analysis and applications such as automated commentary and strategic insight generation. This paper introduces the League of Legends Match Data Compactor (LoL-MDC), a tool designed to transform extensive match data into a concise and structured format optimized for LLM processing. By systematically summarizing structured match information—including match overviews, player and team statistics, timeline summaries, and algorithmically selected key events—the LoL-MDC significantly reduces the data size from approximately 80,000 tokens to under 2000 tokens while retaining analytical value. This method enables LLMs to generate coherent match summaries, analyze player performances, and identify key momentum shifts more effectively than processing raw JSON files. Additionally, the LoL-MDC integrates a winning probability metric to quantitatively enhance the selection of pivotal game events, ensuring relevance in esports analytics. Experimental evaluations demonstrate that the LoL-MDC improves data processing efficiency while maintaining critical insights. The proposed approach provides a structured and adaptable framework for applying LLMs to esports analytics and can be adapted to other competitive gaming environments, supporting AI-driven applications in match analysis, player performance evaluation, and strategic forecasting. Full article

Objective: This study focused on the effect of γ-aminobutyric acid (GABA) intake on psychological state and game performance during esports gameplay. Methods: A randomized, double-blind, placebo-controlled crossover study was conducted with eight healthy male university students aged 20–24 years who regularly play esports. The participants ingested either 200 mg of GABA or a placebo prior to gameplay and then completed a standardized esports task using the Mobalytics Proving Ground™ (MPG), a perceptual-cognitive task within “League of Legends” designed to train and evaluate player performance. Subjective psychological states were assessed pre- and post-gameplay using the Profile of Mood States 2 (POMS2^®) short version. Esports task performance was evaluated based on MPG scores. Results: GABA intake significantly reduced psychological confusion–bewilderment and fatigue in the POMS 2^® short version during esports gameplay. Furthermore, the game scores were significantly higher in the GABA group compared to the placebo group. Conclusions: These findings suggest that GABA intake may serve as a potential strategy to enhance both the mental state and performance of esports players. Full article

Over the last decade, advancements in machine learning and easier model deployment have led to increased commercial applications. One such use case is esports, where machine learning (ML) is used to understand predictors of success. League of Legends, one of the most popular esports, has been a particular academic focus. Investigations into League are divided into two areas: qualitative analyses of factors such as perseverance and group dynamics and quantitative research to create models to predict match outcomes via either pre-game player information or in-game match data. Few studies have integrated both pre-game and in-game data to improve modeling, often using datasets that may not represent the broader player community. This study investigates the factors influencing the accuracy of match prediction models in League of Legends. Evaluating the effects of training on data that are representative of the actual player on the basis of accuracy and determining whether models that amalgamate pre-game and in-game features yield superior results. By utilizing a dataset derived from the Riot API, this research work introduces a novel “streak” feature and constructs models using logistic regression, random forest, C5.0 Gradient Boost and XGBoost, evaluating model performance against recent literature. The results indicate that employing a dataset that more accurately reflects the general player population leads to a slight decrease in the efficacy of the models compared with those using professional datasets only; however, the models demonstrate potential for greater generalizability across a wider range of ranks. The models that incorporate both pre-game and in-game data outperformed most existing studies that focus solely on one type of data, achieving a peak accuracy of 76.8% for the best-performing model. These findings guide future work on feature engineering via the Riot API and model application for broader player populations in esports. Additionally, these insights can be applied to build and improve tools that provide real-time predictions of match results. Full article

Gamers and esports players encounter distinct health challenges that can affect their well-being and performance. Recognising these needs is crucial for developing effective health interventions. This study explored the barriers and facilitators to adopting a healthy lifestyle among gamers and their views on behaviour change interventions. We conducted semi-structured interviews with esports competitors and gamers, using the COM-B model to explore their perceptions. Participants discussed definitions of a healthy lifestyle, emphasising diet and physical activity. There was no consensus on its attainability, as personal, social, and environmental factors influenced perceptions of ease or difficulty. Participants identified key aspects for effective behaviour change interventions, including where, how, and when to implement them, considering these components can help in the design of interventions that are more effective, accessible, and engaging for the target population. This study highlights the importance of a comprehensive approach that considers the unique traits of gamers and their lifestyle. By tailoring health promotion efforts, policymakers can more effectively support this community in reaching its health and wellness objectives. Full article

Multiplayer Online Battle Arena (MOBA) games, exemplified by titles such as League of Legends and Dota 2, have attained global popularity and have been formally recognized as an official event in the 2022 Hangzhou Asian Games, thus establishing their significance in the esports industry. In this study, we proposed a machine learning-based model for predicting comeback victories by leveraging the object bounty mechanism, a critical yet underexplored aspect of previous research. By closely examining the game environment following the activation of the bounty system, we identified pivotal variables and constructed novel indicators that contribute to successful comebacks. Furthermore, an individualized case analysis based on SHapley Additive exPlanations (SHAP) provides new insights to support strategic in-game decision-making and enhance the player experience. The experimental results demonstrate that the indicators introduced in this study, such as the weighted team champion mastery and similarity in champion mastery among the team’s main champions, significantly influence the likelihood of a comeback victory. By capturing the intrinsic dynamism of MOBA games, the proposed model is expected to improve player engagement and satisfaction. Full article