Expert Players Research Articles

Inverse reinforcement learning methods for linear differential games

In this study, we considered the problem of inverse reinforcement learning or estimating the cost function of expert players in multi-player differential games. We proposed two online data-driven solutions for linear–quadratic games that are applicable to systems that fulfill a specific dimension criterion or whose unknown matrices in the cost function conform to a diagonal condition. The first method, which is partially model-free, utilizes the trajectories of expert agents to solve the problem. The second method is entirely model-free and employs the trajectories of both expert and learner agents. We determined the conditions under which the solutions are applicable and identified the necessary requirements for the collected data. We conducted numerical simulations to establish the effectiveness of the proposed methods.

Influence of Motor Imagery Modality on First-Serve Performance in Tennis Players.

Motor imagery (MI) is frequently used in tennis players. This pilot study aimed to assess whether the MI modality and preference of skilled tennis players could influence their service performance when using MI before serving first balls. Twenty expert players (Mage = 18.6years) completed the movement imagery questionnaire (third version) to assess their MI modality scores (internal visual, external visual, and kinesthetic) and their MI preference. Participants completed 4 experimental counterbalanced sessions spread over 4weeks, each including the completion of 20 first-serve balls in match condition. The sessions included a control condition (i.e.,only physical practice trials) and three MI conditions during which the players had to mentally imagine themselves performing a serve according to one of the imagery modalities, either internal visual, external visual, or kinesthetic, before serving. The percentage of success, the speed of the service balls (measured by a tablet with SWING VISION and a radar gun), and an efficiency score were recorded and then evaluated by experts and served as performance indicators and dependent variables. The results of this study showed that players benefited from MI before serving and that almost a third of the participants achieved a higher percentage of success and efficiency scores when using their preferred MI modality. These results lead us, in an applied way, to suggest to skilled tennis players to determine their MI preference and to have recourse to the mental simulation of a successful serve before serving the first balls in match condition.

Neuromechanical proficiency in elite performance decision-making: An event-related potential (ERP) analysis

This research focuses intensively on the neural mechanisms of action selection responses in elite athletes during high-stakes decision-making. It emphasizes the neuromechanical dimensions of these processes, contrasting the responses of expert and novice players within a theoretical framework of neural information processing in high-performance contexts. Utilizing advanced EEG technologies, including event-related potential (ERP) analysis, the study captures a comprehensive view of both behavioral and neurophysiological data. The central aim is to unravel the intricate neural underpinnings that distinguish elite athletes in their decision-making strategies. Key findings highlight: (1) Enhanced accuracy and swifter reaction times in elite athletes during the action selection phase; (2) Significant neurophysiological differences, marked by pronounced N1 peak amplitudes with prolonged latencies, reduced P2 peak amplitudes with stable latencies, decreased P3 peak amplitudes with reduced latencies, and increased average PSW amplitudes. These discoveries significantly advance our understanding of the neural foundations of expert decision-making in high-performance sports. This study not only sheds light on the cognitive and neural dynamics of elite sports performance but also provides a foundation for developing training and performance enhancement techniques in various high-stakes domains.

Prediction of esports competition outcomes using EEG data from expert players

Considerable efforts have focused on predicting sports event outcomes to enhance spectating, coaching, and betting. However, accurately predicting match results across various competitive scenes is challenging. Many researchers have achieved reasonable prediction accuracy using machine learning (ML) models and static data, such as player statistics up to the last match, to perform binary win/loss classification. However, the inherent uncertainty of sports often leads to unexpected outcomes. For example, narrowing the skill-level gap between players may negatively impact prediction accuracy. Moreover, accurately predicting “upsets,” where lower-skilled players defeat higher-skilled opponents, remains challenging. Conventional win/loss prediction techniques rely on static attributes derived from past match statistics, which fail to capture the player's condition immediately before the match. To address this limitation, this study focused on dynamic information reflecting the pre-match player's condition, particularly electroencephalography (EEG) data, recognized as a potent mental conditioning biomarker. We collected pre-match EEG data from esports experts and trained ML models on these data, aiming to assess the ability of ML techniques trained on EEG data to predict match outcomes, particularly in cases subject to high unpredictability. The findings revealed that the light gradient boosting machine (LightGBM) algorithm trained on EEG data achieved the highest prediction accuracy (80%), with parietal beta activity being the most relevant feature. Furthermore, predictive performance remained consistent even in match scenarios involving similar-level players and upset situations. Hence, this approach extends the applicability of win/loss prediction to traditionally unpredictable sports scenes, enhancing the quality of spectator experiences.

Estimating cost function of expert players in differential games: A model-based method and its data-driven extension

In this paper, we introduce two algorithms for estimating the cost function of expert players engaged in optimal performance within linear continuous-time differential games. Initially, we propose a model-based algorithm, followed by its data-driven model-free extension. Both methods rely on optimal policy gains, obtained by observing Nash equilibrium trajectories of the expert players. The model-free method also utilizes the trajectories of the learner system. This method addresses the limitations found in existing model-free approaches, which may suffer from either high computational costs, limited applicability to specific systems, or both. The effectiveness of the proposed methods is demonstrated through numerical simulations.

The contributions of executive functions to decision-making in sport

ABSTRACT In sports, when the game situations become complex, untypical, and uncertain, making good decisions requires controlled processing, i.e., executive functions to regulate thought and action. The current study aimed at comprehending the effects of three core executive functions on decision-making in sport. In study 1, 86 volleyball players (49 experts and 37 novices) completed a routine blocking decision task as well as three core executive function tasks assessing updating, inhibition and shifting. Results showed that the effects of executive functions on blocking decision accuracy were moderated by sports level, with significant predictivity observed only for experts. In study 2, 32 expert players engaged in a dual-task version of the blocking decision task. In this study, only updating was correlated with decision accuracy. Study 3, involving 26 experts, introduced interference during the decision task. The findings highlighted a closer, albeit not statistically significant, relationship between decision accuracy and inhibition compared to updating. Collectively, these findings demonstrated the nuanced yet crucial roles of executive functions in decision-making in sport, underscoring more efficient cognitive processing among higher-level athletes and the different roles served by each executive function.

Managing Road Risk: The Development of Road Infrastructure Toward Liveable City

A country's economic development and prosperity depend on its cities. This study is conducted due to an effectiveness of road infrastructure are still a key issue that affecting quality of life in urban areas. Traffic jams, accidents and delays not only cause driver frustration and inconvenience, but also have serious economic and environmental impacts. This study attempts to identify the type of road infrastructure, to investigate the risk classification of road infrastructure and to suggest the potential development of road infrastructure in development of rural area. The study focused on the rural development area and this research includes data collection from primary and secondary sources such as interviews. Stakeholders and expert players have been interviewed for this research. The data that we found has been analysis using content analysis which is matrix table. The results of this study have found that there are several issues that exist in implementing of good road infrastructure concept and initiatives and development in rural development area. In conclusion, all respondents gave a positive review on the study and the research shows that good road infrastructure is needed to create our country safer and our cities towards liveable city.

Impacts of Kinematic Information on Action Anticipation and the Related Neurophysiological Associations in Volleyball Experts.

In this study, we investigated the cognitive mechanisms underlying action anticipation in volleyball players, especially concerned with the differences between experts and amateurs. Participants included both expert (male, N = 26) and amateur (male, N = 23) volleyball players, who were asked to predict spiking movements containing high, medium, and low levels of kinematic information while their electrophysiological activities were recorded. The high-information stimuli included the whole spiking action, the medium-information stimuli ended at 120 ms, and the low-information stimuli ended at 160 ms before hand-ball contact. The results showed that experts significantly outperformed amateurs in both prediction accuracy (68% in experts vs. 55% in amateurs) and reaction time (475.09 ms in experts vs. 725.81 ms in amateurs) under the medium-information condition. Analysis of alpha rhythm activity revealed that experts exhibited the strongest desynchronization under the low-information condition, suggesting increased attentional engagement. In contrast, amateurs showed the weakest desynchronization under the medium-information condition. Furthermore, mu rhythm activity analysis showed greater desynchronization in the duration of 100-300 ms before hand-ball contact for experts, correlating with their higher anticipation accuracy. These findings highlight the significant kinematic information-processing abilities of volleyball experts and elucidate the neural mechanisms underlying efficient attentional engagement and mirroring. Therefore, this study provides valuable insights for the development of targeted training programs through which to enhance athletic performance.

Which modality is best for delivering an imagery script? Evidence for desirable difficulty effect

ABSTRACT The aim of this study was to investigate the impact of a brief mental imagery task on immediate and delayed learning performance when participants were instructed about the functioning of a game system in basketball using either a written or an audio script. Expert (N = 88) and novice (N = 88) basketball players were randomly assigned to one of four experimental conditions: (i) written script + no-imagery, (ii) audio script + imagery, (iii) written script + imagery, and (iv) written script + imagery. The main results showed that, regardless of the delivery modality of the script, novice participants derived benefited more from the no-imagery condition compared to the imagery condition in the immediate test. However, this advantage reversed in the delayed test one week following, indicating that mental imagery becomes more advantageous, particularly when delivered in written form. On the other hand, the results demonstrated that expert players performed better in both imagery conditions (in both immediate and delayed tests), particularly when the imagery was delivered in an audio format. These results suggest that the modality used to deliver a mental imagery script can significantly influence learning effectiveness, depending on the level of expertise.

Hemispheric Lateralization in Older Adults Who Habitually Play Darts: A Cross-Sectional Study Using Functional Near-Infrared Spectroscopy.

Exercise training integrating physical and cognitive activities is gaining attention because of its potential benefits for brain health. This study focuses on exercise training using a dart game called Wellness Darts. Wellness Darts is a sport involving throwing darts and walking to pull them out of the board, memorizing the score, and subtracting this from the total score, thus requiring the simultaneous performance of two tasks: exercise and calculation. This is expected to maintain and improve cognitive function, and whether this continual darts training affects brain function is of great interest. Before conducting the longitudinal study revealing its effect on brain function, we aimed to cross-sectionally confirm the difference in hemispheric lateralization between expert and non-expert players. Functional near-infrared spectroscopy (fNIRS) was used to measure brain activity for three groups: an expert older group who practiced darts continually, a non-expert older control group, and a non-expert younger control group. Their brain activity patterns were quantified by the lateralization index (LI) and compared between groups. The results showed that the younger and the expert older groups had significantly higher LI values than the non-expert older group, and there was no difference between the expert older and the younger groups. Our results suggest that the Wellness Darts game possibly promotes hemispheric lateralization.

The role of perception-action coupling in badminton-specific vision training: A narrative review

Background and Study Aim. Badminton is a sport characterized by intense competition and rapid pace, necessitating exceptional hand-eye coordination, mental sharpness, and visual acuity from its players. Rapid interchanges and complex shot combinations highlight the imperative for players to maintain heightened concentration and exhibit quick decision-making capabilities. Given these demands, visual training has emerged as an indispensable tool for enhancing athletic ability in badminton. Aim. The study aims to examine the underlying theories of perception-action coupling, investigates various vision training methods for badminton, and evaluates research on their effects on players’ perception-action coupling. Material and Methods. This study employs a narrative review methodology. We conducted an extensive literature search across diverse sources, using keywords like “badminton,” “perception-action coupling,” and “vision training.” The selection of studies was based on relevance to our research objectives, encompassing various study designs, including primary research, reviews, and expert opinions, facilitating a flexible and coherent synthesis of findings, enabling the exploration of context, significance, and implications within the area of the review while highlighting key insights and emerging trends. Results. Several factors can influence a player’s perception-action coupling abilities in badminton, such as their level of expertise and training background. Expert players exhibit better perception-action coupling abilities than their less skilled counterparts. Additionally, several studies have investigated the impact of vision training techniques on perception-action coupling in badminton, revealing improvements in various visual skills crucial for performance. Conclusions. The study explored the pivotal role of perception-action coupling in the context of vision training tailored for badminton players.

Volleyball serves impact sound intensity and frequency spectrum affect the predictions of the future ball’s landing point according to the level of auditory-motor experience

ABSTRACT In ball sports, such as volleyball or soccer, the impact sound of the ball is used to define the shot length and predict the final ball position on the field. Several studies thoroughly investigated the role of sound intensity in predicting the ball’s landing point, neglecting the equally important contribution of the sound frequency spectrum component. Here, we investigated the contribution of the sound frequency spectrum in defining a volleyball serve’s length (i.e., distance). We recorded the sound of short and long volleyball serves (ecological sound) and changed their frequency spectrum in pink noise, preserving their intensity (noise sound). We then presented both sounds (ecological and noise) to expert volleyball players and measured their performance in short and long-shot classifications. The role of auditory-motor experience in sound classification was also explored by testing soccer players (experience on ball shots but not sport-specific auditory-motor experience) and non-athletes (no auditory-motor experience in sports). We found that hearing ecological sound leads to better sound discrimination performance than noise sound. Concurrently, we found an effect of the specific auditory-motor experience, with volleyball players outperforming non-athletes and soccer players. Interestingly, experts in different sports domains (soccer players) mainly used sound intensity for shot classification. This underlines the importance of specific auditory-motor experience in encoding specific sound frequency spectrum for the sound of action classification.

Henri Cochet's theory of angles in tennis (1933) reveals a new facet of anticipation

In this study, we tested the theory of angles that was proposed almost a century ago by the tennis player Henri Cochet. This theory proposes that expert tennis players should position themselves on the bisector of the angle of the opponent’s possibilities in order to optimize shot return, suggesting a geometric occupation of the court relative to the opponent's affordances; namely what he/she is capable of doing. We tested this hypothesis by analysing player and ball positioning data from professional tennis matches recorded with a Hawk-Eye system. We compared this hypothesis with two alternative computational and probabilistic hypotheses which would consist in positioning oneself on the average or the median of the shots usually played from a given location. The results show that expert tennis players apply the principles of the theory of angles and thus confirm Henri Cochet's intuition. That is, for lateral court positioning, a geometric strategy is deemed optimal by expert players. It also appears that the more experienced the players are, the more precise their application of this strategy becomes.

Data-Driven Inverse Reinforcement Learning Control for Linear Multiplayer Games.

This article proposes a data-driven inverse reinforcement learning (RL) control algorithm for nonzero-sum multiplayer games in linear continuous-time differential dynamical systems. The inverse RL problem in the games is solved by a learner reconstructing the unknown expert players' cost functions from demonstrated expert's optimal state and control input trajectories. The learner, thus, obtains the same control feedback gains and trajectories as the expert, only using data along system trajectories without knowing system dynamics. This article first proposes a model-based inverse RL policy iteration framework that has: 1) policy evaluation step for reconstructing cost matrices using Lyapunov functions; 2) state-reward weight improvement step using inverse optimal control (IOC); and 3) policy improvement step using optimal control. Based on the model-based policy iteration algorithm, this article further develops an online data-driven off-policy inverse RL algorithm without knowing any knowledge of system dynamics or expert control gains. Rigorous convergence and stability analysis of the algorithms are provided. It shows that the off-policy inverse RL algorithm guarantees unbiased solutions while probing noises are added to satisfy the persistence of excitation (PE) condition. Finally, two different simulation examples validate the effectiveness of the proposed algorithms.

Esports experts have a wide gaze distribution and short gaze fixation duration: A focus on League of Legends players.

This study investigated the specific gaze control ability of expert players and low-skill players of League of Legends (LoL). Eleven expert and nine low-skill players were divided according to their official ranking. Then, the gaze movement of each participant when performing each task (e.g., easy task and moderate task) while competing against a computer artificial intelligence system was recorded. Experts were found to have a significantly wide horizontal gaze distribution. Additionally, experts had a consistently short gaze fixation duration during the moderate task. These results suggest that a wide horizontal gaze distribution allows experts to obtain information from a wider area. Additionally, the consistently short fixation duration of the experts indicated that they need only a short period to assess information, which is advantageous because large amounts of information need to be processed within a limited time while playing. This specific gaze control ability could be an important factor that contributes to the superior performance of expert LoL players.

Postural stability assessment in expert versus amateur basketball players during optic flow stimulation

We evaluated the role of visual stimulation on postural muscles and the changes in the center of pressure (CoP) during standing posture in expert and amateur basketball players. Participants were instructed to look at a fixation point presented on a screen during foveal, peripheral, and full field optic flow stimuli. Postural mechanisms and motor strategies were assessed by simultaneous recordings of stabilometric, oculomotor, and electromyographic data during visual stimulation. We found significant differences between experts and amateurs in the orientation of visual attention. Experts oriented attention to the right of their visual field, while amateurs to the bottom-right. The displacement in the CoP mediolateral direction showed that experts had a greater postural sway of the right leg, while amateurs on the left leg. The entropy-based data analysis of the CoP mediolateral direction exhibited a greater value in amateurs than in experts. The root-mean-square and the coactivation index analysis showed that experts activated mainly the right leg while amateurs the left leg. In conclusion, playing sports for years seems to have induced some strong differences in the standing posture between the right and left sides. Even during non-ecological visual stimulation, athletes maintain postural adaptations to counteract the body oscillation.

A comparative analysis for eye movement characteristics between professional and non-professional players in FIFA eSports game

Eye-tracking technology has been widely applied to various kinds of traditional sports research, such as football, basketball and table tennis. eSports is an emerging digital sport, which is currently enjoying rapid development. The previous study primarily focuses on the practical applications of eye movement in eSports, such as game design, visual attention, and performance analysis. However, there is a scientific gap for the specific differences between expert and novice players, the potential of eye-tracking as a biological marker for eSports performance, and the transfer of insights from real sports to eSports through eye-tracking studies. This study aims to uncover disparities in eye movement characteristics between professional players (N = 14, 24.1 ± 2.5 years) and non-professional players (N = 14, 25.2 ± 2.3 years) by employing the expert-novice paradigm. We extracted several key eye movement features, including average fixation counts, average fixation duration, first fixation duration, eye movement trajectory, and visits to areas of interest. The results indicate that professional players exhibit higher fixation counts, shorter first fixation duration, reduced average fixation duration, and employ a more effective visual search strategy. Professional players’ fixation trajectories are characterized by clarity and focus, with a greater number of fixation points concentrated on key areas of interest. In contrast, non-professional players demonstrate relatively random fixation trajectories, lacking distinct focal points. This study not only advances our understanding of eye-tracking in eSports but also provides technical guidance and practical significance for further research in this burgeoning field.

Visual search strategies of performance monitoring used in action anticipation of basketball players.

Numerous studies have found that expert players anticipate better than novices. If more accurate prediction represents performance monitoring of experts, what are the advantages of elite basketball players in identifying and processing available cues? There is still a lack of sufficient evidence. This study examined the visual search in basketball players and explored the performance monitoring of action anticipation, adopting an expert-novice paradigm and eye-movement technology. Forty basketball players were recruited in this study: 20 in the expert group and 20 in the novice group. Participants were asked to predict the outcome of videotaped basketball throws and their accuracy and eye-movement characteristics were record. The accuracy of the expert was significantly higher than that of the novice. The experts were able to instantly search and identify important cues in anticipation, and the gaze area of the experts was concentrated on the area of interest of the body. Additionally, the expert group showed long, repetitive, and rapid visual search of vital information, and improved their performance of the task. The experts could monitor the performance of prediction by grabbing vital shooting information (such as the body of a player). The results suggest the athletes and coaches that if they want to improve the ability of prediction, it may be useful to shift their focus of attention from ball trajectory to body action.

Bridging physical and virtual ecologies of action: giving and following instructions in co-located VR-gaming sessions

Using multimodal conversation analysis, this study examines how communicative practices are adapted to the affordances for interaction in co-located encounters where participants are getting acquainted with VR-technology and games. The analysis focuses on instructional activities and investigates how an expert player guides others in learning how to handle VR equipment and getting to know the game mechanics during the initial moments of starting a new game.
 The data comprises video-recordings of informal social gatherings of 3-4 young adults who take turns in trying out different VR games. The gaming situations were organized in a temporary game lab using consumer-grade VR equipment, a large screen that displayed video feed from the game console and loudspeakers for the game sound.
 The analysis demonstrates how the experienced player who has no direct agency over the virtual world uses verbal and carefully placed tactile means to help novice players (who in turn have restricted access to the material world) navigate the initial stages of entering a game. Their complying actions, on the other hand, are characterized by finely tuned bodily adjustments in interplay with affordances of the technology. The instruction sequences, therefore, represent interactional moments in which the participants mutually attend to asymmetries, orienting to bridging physical and virtual ecologies of action.

Long-term Intensive Soccer Training Induced Dynamic Reconfiguration of Brain Network.

Long-term motor skill learning has been shown to impact the functional plasticity of the brain. Athletes, as a unique population, exhibit remarkable adaptive changes in the static properties of their brain networks. However, studying the differences between expert and novice athletes using a dynamic brain network framework can provide a fresh perspective on how motor skill learning affects the functional organization of the brain. In this study, we investigated the dynamic properties of brain networks in expert and novice soccer players at the whole-brain, network, and region-based levels. Our findings revealed that expert soccer players displayed reduced integration and increased segregation at the whole-brain level. As for network level, experts exhibited increased segregation and reduced flexibility in the visual network, enhanced integration between the visual and ventral attention networks, and decreased integration in the subcortical-sensorimotor and subcortical-cerebellar networks. Additionally, specific brain regions within the visual network exhibited greater recruitment in expert soccer players compared to novices at the nodal level. Furthermore, classification analyses demonstrated the critical role played by the visual network in the classification process. In conclusion, our study provides new insights into the dynamic properties of brain networks in expert and novice soccer players, and suggests that reduced integration and increased segregation in the visual network may be neuroimaging marker that distinguish expert soccer players from novices. Our findings may have implications for the training and development of athletes and advance our understanding of how motor skill learning affects brain functional organization.