Search Results (19)

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

This study extends the theory of planned behavior (TPB) to examine behavioral intentions for attending on-site e-sports events during the COVID-19 pandemic, integrating perceived risk, non-pharmaceutical interventions (NPIs), and past behavior as contextual determinants. Specifically, it aims to identify effective strategies for maintaining event attendance intention despite unpredictable external shocks, thereby contributing to the sustainability and resilience of the event tourism industry. Using structural equation modeling, survey data from 415 Chinese League of Legends fans were analyzed to explore how pandemic-specific factors reshape traditional TPB frameworks in a sustainable tourism context. The findings revealed that NPIs (β = 0.368, p < 0.001), perceived behavioral control (β = 0.225, p < 0.001), and prior event attendance (β = 0.404, p < 0.001) were significant predictors of participation intent. In contrast, attitudes and subjective norms showed no significant influence, likely due to the homogeneous enthusiasm of the sampled Generation Z cohort. Notably, heightened perceived COVID-19 risk motivated attendees to adopt NPIs (e.g., masking, sanitization), indirectly bolstering participation intentions by alleviating safety concerns. Furthermore, frequent past attendance fostered habitual engagement, reducing reliance on deliberate decision-making. These insights advance the TPB and offer actionable strategies for event managers seeking sustainable solutions for maintaining participant engagement and economic resilience amid external disruptions. 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

Research on the stress and burnout experienced by athletes in the esports field remains limited, necessitating an approach that considers the unique environment and circumstances of esports athletes. This study aims to explore the conceptualization of burnout experiences among professional esports athletes. The participants included 88 athletes from the League of Legends Championship Korea (LCK). Among these, in-depth interviews were conducted with 7 athletes who had experience in international tournaments (the World Championship), while an open-ended survey was completed by 81 athletes. Data collected through in-depth interviews and an open-ended survey were digitized and utilized for analysis. Through critical review by another author and inductive categorization, the conceptual components of esports athletes’ burnout were derived. Through the analysis of 251 raw datum, it was conceptualized into five conceptual factors: performance, overtraining, interpersonal relationships, physical and psychological exhaustion, and career and motivation. The results of this study confirm that esports athletes, like athletes in other conventional sports, experience burnout during their careers, highlighting issues in their unique environment, particularly in aspects of interpersonal relationships and training and rest conditions. This research can serve as a foundational resource for effective athletes’ psychological health management in the esports field and underscores the need for further research on burnout among esports athletes. Full article

The present study focused on the effects of a physical training program on physical- and psychological-related variables in professional esports players. Five professional League of Legends (LOL) players belonging to the highest national category participated in this study. Data were obtained before and after a 5 h virtual training session (acute), as well as before and after an 8-week intervention period, focused on decreasing the impact of fatigue on players’ health and performance. The results showed that a complete virtual training session influences their performance, decreasing jump height and joint mobility (p < 0.01), as well as increasing perceived physical and cognitive exertion by 76.9% (p < 0.01) and 166.67% on the “Rating of Fatigue” scale (p = 0.002). Moreover, the intervention was able to reduce the impact of fatigue (30.8% and 43.3% reduction in cognitive and overall fatigue, respectively, p < 0.05), improving, at the same time, the amount of muscle mass by 2%, jumping ability by 9.8% to 21%, and strength levels in various exercises by 63% to 173% (p < 0.01). The implementation of a physical training program is capable of reducing the players’ fatigue perception, improving their physical conditioning and health status, and decreasing the injury risk. Full article

Elaborate sound design, including background music, ambient sounds (sounds describing the game world), and character sounds (sounds generated by the character’s actions), plays a pivotal role in modern video games. However, the influence of these different types of sound on the player’s experience has not been extensively researched. This study examines the influence of these sound types on immersion, avatar identification, fun, and perceived competence. In two experiments, participants played League of Legends under four different sound conditions. The first experiment (N₁ = 32) revealed a non-significant trend in the effect of character sounds on avatar identification. Ambient sounds, however, were limited because the task restricted participants’ movement across the game map. Consequently, we adapted the task to allow for a wider variety of ambient sounds in the second experiment (N₂ = 32). Here, a significant impact of character sounds on immersion, avatar identification, and fun was observed, as well as an interaction effect of character sounds and ambient sounds on fun. Furthermore, we observed a trend, though not statistically significant, suggesting that ambient sounds may influence the player’s sense of flow. These findings underline the distinct effects of different sound types, and we discuss implications for the design of sound in video games. Full article

Previous studies have demonstrated that individuals with internet gaming disorder (IGD) display abnormal autonomic activities at rest and during gameplay. Here, we examined whether and how in-game autonomic activity is modulated by human characteristics and behavioral performance of the player. We measured heart rate variability (HRV) in 42 male university student habitual gamers (HGs) when they played a round of League of Legends game online. Short-term HRV indices measured in early, middle and late phases of the game were compared between the players at high risk of developing IGD and those at low risk, as assessed by the revised Chen Internet addiction scale (CIAS-R). Multiple linear regression (MLR) was used to identify significant predictors of HRV measured over the whole gameplay period (WG), among CIAS-R, ranking score, hours of weekly playing and selected in-game performance parameters. The high-risk players showed a significantly higher low-frequency power/high-frequency power ratio (LF/HF) relative to the low-risk players, regardless of game phase. MLR analysis revealed that LF/HF measured in WG was predicted by, and only by, CIAS-R. The HRV indicators of sympathetic activity were found to be predicted only by the number of slain in WG (N_Slain), and the indicators of parasympathetic activity were predicted by both CIAS-R and N_Slain. Collectively, the results demonstrated that risk of developing IGD is associated with dysregulated autonomic balance during gameplay, and in-game autonomic activities are modulated by complex interactions among personal attributes and in-game behavioral performance of the player, as well as situational factors embedded in game mechanics. Full article

Game playing is an accessible leisure activity. Recently, the World Health Organization officially included gaming disorder in the ICD-11, and studies using several bio-signals were conducted to quantitatively determine this. However, most EEG studies regarding internet gaming disorder (IGD) were conducted in the resting state, and the outcomes appeared to be too inconsistent to identify a general trend. Therefore, this study aimed to use a series of statistical processes with all the existing EEG parameters until the most effective ones to identify the difference between IGD subjects IGD and healthy subjects was determined. Thirty subjects were grouped into IGD (n = 15) and healthy (n = 15) subjects by using the Young’s internet addition test (IAT) and the compulsive internet use scale (CIUS). EEG data for 16 channels were collected while the subjects played League of Legends. For the exhaustive search of parameters, 240 parameters were tested in terms of t-test, factor analysis, Pearson correlation, and finally logistic regression analysis. After a series of statistical processes, the parameters from Alpha, sensory motor rhythm (SMR), and MidBeta ranging from the Fp1, C3, C4, and O1 channels were found to be best indicators of IGD symptoms. The accuracy of diagnosis was computed as 63.5–73.1% before cross-validation. The most interesting finding of the study was the dynamics of EEG relative power in the 10–20 Hz band. This EEG crossing phenomenon between IGD and healthy subjects may explain why previous research showed inconsistent outcomes. The outcome of this study could be the referential guide for further investigation to quantitatively assess IGD symptoms. Full article

This study aims to examine firstly the motivations of esports spectators driving them to engage in consumption behaviour, and secondly, two spectator groups (League of Legends, LOL; Hearthstone) to compare the findings of the independence model and the competing model. In recent decades, the concept of esports has emerged as a major component of the sports industry and, therefore, of the global economy. However, the basic functioning of this new sector is relatively poorly understood. This study considers consumer motivations as they relate to esports and aims to assess how selected motivations interact. The motivations chosen in five categories were adopted from the Uses and Gratifications Theory. The independence model (based on Uses and Gratifications Theory (UGT)) and competing model (based on multiple theoretical perspectives) were applied to the LOL and Hearthstone spectator groups. Data (n = 574) were collected via online surveys with cross-validation measured and established between the two groups. The findings showed that social integrative motivations positively impacted consumption behaviour across game genres. Affective motivation partially mediated the relationship between social integrative motivation and consumption behaviour in LOL, and cognitive and personal integrative motivations positively influenced consumption behaviour in Hearthstone. The tension-release motivation had no significant association with consumption behaviour for spectators of either game. The findings can help the commercial interests of different esports game genres to predict why people consume particular esports and thus aid effective marketing strategies. Full article

The decade after World War I has traditionally been defined as an “age of isolation.” The American public’s disillusionment with World War I, highlighted by the dismal failure of President Woodrow Wilson’s efforts to join the League of Nations, led to “A Return to Isolationism,” according to a brief summary of American diplomacy produced by the Department of State. Despite the fact that historian William Appleman Williams attempted to destroy the “legend of isolationism in the 1920s” and other scholars have followed his lead with a string of publications recounting the very active U.S. engagement with the rest of the world following the war, many textbooks continue to describe the 1920s as an age wherein the United States withdrew into a shell of isolation. My article suggests that one way of reconciling these apparently contradictory interpretations of American foreign policy in the decade after World War I is to examine one particular factor that has been largely overlooked: Whether “isolationist” or not, the United States during those years utilized race as a way to simultaneously build walls in and around the American nation as well as construct the ideological foundations for U.S. postwar expansion and engagement. Full article

Recently, the skill to play games has led to the professionalization of the activity in the form of “eSports” (electronic sports). Despite the popularity of eSports, little is known about its professional players from a psychological perspective. Given the importance of the coach-created environment in the athletes’ motivational processes, this study aimed to investigate the key psychological dimensions of the coach-created climate in 75 Brazilian professional players of League of Legends (LoL) considering the Self-Determination Theory (SDT) and Achievement Goal Theory (AGT). Fourteen hypotheses were tested, of which seven were confirmed. The empowering climate was a predictor of basic psychological-needs satisfaction and indirectly influenced autonomous motivation. The need satisfaction had a significant impact on both autonomous motivation and on lack of motivation, which, in turn, explained 56% of the variance in well-being and the intention to keep playing eSports. The disempowering climate was a predictor of psychological-needs thwarting but had no significant impact on autonomous motivation or lack of motivation. The results obtained support SDT and AGT in the context of eSports and were similar to those conducted with athletes from traditional sports, indicating that the empowering-and-disempowering-coaching-climates conceptualization applies not only to traditional sports athletes but also to professional eSports players. Full article

The purpose of this study is to determine heart rate variability (HRV) parameters that can quantitatively characterize game addiction by using electrocardiograms (ECGs). 23 subjects were classified into two groups prior to the experiment, 11 game-addicted subjects, and 12 non-addicted subjects, using questionnaires (CIUS and IAT). Various HRV parameters were tested to identify the addicted subject. The subjects played the League of Legends game for 30–40 min. The experimenter measured ECG during the game at various window sizes and specific events. Moreover, correlation and factor analyses were used to find the most effective parameters. A logistic regression equation was formed to calculate the accuracy in diagnosing addicted and non-addicted subjects. The most accurate set of parameters was found to be pNNI20, RMSSD, and LF in the 30 s after the “being killed” event. The logistic regression analysis provided an accuracy of 69.3% to 70.3%. AUC values in this study ranged from 0.654 to 0.677. This study can be noted as an exploratory step in the quantification of game addiction based on the stress response that could be used as an objective diagnostic method in the future. Full article

The aim of the present study was to analyse the neuroendocrine stress response, psychological anxiety response, and perceived match importance (PMI) between expert and non-expert control gamers in an official competitive context. We analyzed, in 25 expert esports players and 20 control participants, modifications in their somatic anxiety, cognitive anxiety, self-confidence, PMI, and cortisol in a League of Legends competition. We found how expert esports players presented higher cortisol concentrations (Z = 155.5; p = 0.03; Cohen’s d = −0.66), cognitive anxiety (Z = 99.5; p = 0.001), and PMI (Z = 50.5; p < 0.001) before the competition than non-experts participants. We found a greater statistical weight in the cognitive variables than in the physiological ones. The results obtained suggest that real competitive context and player’s expertise were factors associated with an anticipatory stress response. The PMI proved to be a differentiating variable between both groups, highlighting the necessity to include subjective variables that contrast objective measurements. Full article