Outcome Of Game Research Articles

Illusions of control: A quasi-experiment comparing skill-based and traditional slotmachines.

Electronic gaming machines (EGMs) are a significant source of gambling spend due to their widespread use. Skill-based gambling machines (SGMs) represent an innovative adaptation, merging EGMs' chance-based rewards with video game-like skills. This study aimed to explore the appeal and behavioural consequences of playing SGMs in comparison to traditional reel-based EGMs, particularly focusing on illusions of control, betting behaviour, and the subjective experience of gamblers. Participants (N = 1,260) were recruited online and engaged in an online task simulating either an SGM or a reel-based EGM, with outcomes represented to influence their survey compensation. The study examined the effect of SGMs relative to EGMs on bet size, persistence, enjoyment, illusionsofcontrol, game immersion, and the influence of demographic and gambling problem severity. SGMs particularly appealed to younger adults, regular EGM players, and people with more gambling problems. Despite identical payout structures, people assigned to play SGM showed greater illusions of control, believing in the influence of skill on game outcomes and that practice could improveresults. However, there was no significant difference in overall betting intensity between SGM and EGM players, although specific demographic groups showed faster betting speeds in SGMs. SGMs, despite not inherently encouraging higher betting intensity, attract vulnerable groups and create illusions of control, posing new regulatory challenges. The visual and interactive features of SGMs, while appealing, might contribute to these perceptions, indicating a need for careful regulation and further research on their long-term impacts on gambling behaviour and harm.

Rational Expectations Models with Higher-Order Beliefs

Abstract We develop a method of solving rational expectations models with dispersed information and dynamic strategic complementarities. In these types of models, the equilibrium outcome hinges on an infinite number of higher-order expectations which require an increasing number of state variables to keep track of. Despite this complication, we prove that the equilibrium outcome always admits a finite-state representation when the signals follow finite ARMA processes. We also show that such a finite-state result may not hold with endogenous information aggregation. We further illustrate how to use the method to derive comparative statics, characterize equilibrium outcomes in HANK-type network games, reconcile with empirical evidence on expectations, and integrate incomplete information with bounded rationality in general equilibrium.

Abuzaharen's Challenge: Building Sustainability Competencies through Science-Fiction Narratives and Game-based Learning

This paper presents a case study of the evolution of science-fiction themed game-based learning across two Masters units in a higher education course on sustainable development. The authors created three sustainability games to be played by classes in live workshop settings – a card matching game about urban challenges, a hackathon-style sustainability innovation challenge, and a systemic change analysis game - to build students’ capacity to think about systems, sustainability values, and strategies to advance positive change. The story of a bumbling, but well-intentioned, alien protagonist, Abuzaharen, serves as a dynamic backdrop to the games, which see students ‘transported’ to an alternative reality to complete time-bound challenges in a rigorous yet engaging manner in order to find their way ‘home’ to Earth. This paper documents how each game’s narrative, storytelling, design, and play evolved through multiple iterations over four years, drawing on critical reflection, evidence of engagement and student feedback. The paper also reflects on the affordances of generative artificial intelligence (GenAI) for game-based learning designers. One of the games has integrated GenAI to make Abuzaharen a real-time character in the delivery of the game, including judging student’s innovation pitches and generating live narrative content about game outcomes. The GenAI alien agent subsequently appears in ‘regular’ learning content as a course tutor. Qualitative feedback and educator observations suggest the games increased active class participation, built peer connections, fostered skills in problem-solving, promoted collaboration, and modelled creativity. The games also challenge existing narratives about negative impacts of GenAI on tertiary education by illustrating productive and creative uses of GenAI for students and educators. This paper argues that immersive, narrative-driven approaches, coupled with the strategic use of GenAI, can significantly enrich higher education for sustainability and other educational experiences by scaffolding selected competencies and applying complex concepts to real-world challenges in a light-hearted way. It concludes with practice-led insights and directions for future exploration of interest to sustainability educators, designers of interactive learning, and those experimenting with GenAI in narrative-based games.

The associations between self-rated autistic traits, social camouflaging, and mental health outcomes in Taiwanese anime, comics and games (ACG) doujin creators: an exploratory study

BackgroundDoujin (どうじん) is a Japanese term referring to a circle where people share the same interests, usually something that belongs to the Anime, Comics, and Games (ACG) subculture. Individuals who belong to it and create related works, known as ACG doujin creators, are usually described as socially awkward and at potential risk of isolation. In such a context, they may theoretically exhibit higher autistic traits and manifest camouflaging tendencies, which may consequently be associated with their mental health. Nonetheless, the impact of autistic traits and camouflaging on mental health in this subculture remains significantly underexplored.MethodsWe recruited 183 Taiwanese ACG doujin creators (age ranges from 18 to 41, 146 female and 37 male) via social networking platforms. Participants completed Chinese online surveys assessing socio-demographic information, doujin activities, past psychiatric history, the 35-item Version of Autism-Spectrum Quotient (AQ-35), Chinese version Camouflaging Autistic Traits Questionnaire (CAT-Q-Ch), the General Anxiety Disorder-7 (GAD-7), and the Patient Health Questionnaire-9 (PHQ-9). Linear regression analysis was employed to examine the associations between the aforementioned scales.ResultsOur findings revealed that among ACG doujin creators, descriptively higher level of AQ-35 and CAT-Q-Ch than previous studies were found. Moreover, we observed a positive association between camouflaging behaviours and most AQ-35 subscales, with the exception of the mindreading subscale. Additionally, we identified that both camouflaging and autistic traits were significantly linked to higher PHQ-9 and GAD-7 scores.ConclusionsThrough this study, we gained insight into the distinctive characteristics of autistic traits, camouflaging behaviours, and mental health among Taiwanese ACG doujin creators, as the associations between the factors mentioned above are divergent compared to previous research. This topic demonstrated that camouflaging is also associated with adverse mental health in a subculture group.

Performance Metrics And Game Outcomes In Division I Women's Soccer: A Sport Analytics Case Study

Performance Metrics And Game Outcomes In Division I Women's Soccer: A Sport Analytics Case Study

Design and implementation of audio-visual learning media for volleyball passing and serving techniques in junior high school

One of the main challenges in physical education learning is the limited availability of appropriate and interesting learning media for students. This research aimed to develop audio-visual learning media products in class VIII junior high school PE subjects on specific motion material for variations in upper passing, lower passing variations, upper service variations, and lower service variations in volleyball games. The research was conducted as development research adopted the Borg Gall model: preliminary study, planning stage and initial research product development, expert validity test stage and product revision, small- and large-scale tests, effectiveness test and distribution of learning media products. Validation of learning media development is carried out by learning material experts, learning media experts, and learning media design experts. Following the expert validation of the learning content and material by subject matter experts, the validation of the learning media by media specialists, and the validation of the learning media design, further validation conducted by an online questionnaire to gather further feedback and insights. The results were obtained in the form of audio-visual learning media products that were tested to large groups receiving a validation score of 93% from learning material experts, 94% from learning media experts, and 95% from learning media design experts. For the effectiveness test, pre and post-tests on improving volleyball passing and serving skills has done and obtained the experimental class obtained a gain value of 0.62 and the control class obtained a gain value of 0.28. This research concluded that the use of audio-visual learning media in physical education showed positive results in improving understanding, motivation, and learning outcomes of volleyball games. With the right support, this media can be an effective tool to enrich the learning experience and support the achievement of physical education goals.

Data variables related to wins and losses of game in different scenarios in the WNBA 2023 season

ABSTRACT The research subarea of sports performance analysis on women’s basketball games is relatively scarce. Therefore, this study aims to explore the key variables that influence the game outcomes in the Women’s National Basketball Association (WNBA) during the 2023 season. Firstly, chi-square tests and k-means clustering to control variables were applied to categorise games into four groups (home balanced, home unbalanced, away balanced, and away unbalanced). Secondly, stepwise logistic regression was employed to identify key variables influencing game outcomes in each group. The game statistics variables that were significant in home and away balanced games were the field goals made (FG) (+) and attempted (FGA) (-), free throws made (FT) (+), total rebounds (TRB) (+), steals (STL) (+), turnovers (TOV) (-), and personal fouls (PF) (-). Additionally, 3-point field goals made (3P) were significant in home balanced games and assists (AST) (+) in the away balanced games. And FG (+), FGA (-), offensive rebounds (ORB) (+), STL (+), blocks (BLK) (+), and TOV (-) were significant in the home unbalanced games. In addition, in the away unbalanced group 4 variables included 3P (+), offensive rebound percentage (+), defensive rebound percentage (+), and total rebound percentage (+) were identified as key variables.

An Evolutionary Game-Based Regulatory Path for Algorithmic Price Discrimination in E-Commerce Platforms

With the advent of big data, the swift advancement of diverse algorithmic technologies has enhanced the transaction efficiency of the e-commerce business. Nevertheless, it is crucial to acknowledge that e-commerce platforms might employ algorithmic technology to enforce differential pricing for various consumers with the aim of maximizing profits, thus infringing upon the lawful rights and interests of consumers. This paper focuses on the algorithmic price discrimination commonly observed on e-commerce platforms. To effectively regulate this behavior, the paper utilizes evolutionary game theory (EGT) to analyze the strategies employed by e-commerce platforms, consumers, and market regulators to achieve stability. This research employs a real-life situation and utilizes parametric simulation to visualize and analyze the process and outcomes of the three-party evolutionary game. The results demonstrate the credibility and feasibility of the article’s findings. Based on our research, we have reached the following findings: During the process of evolution, the strategic decisions made by the game participants from the three parties will mutually impact each other, and various elements exert varying degrees of influence on the strategic choices made by the game participants from each party. Collaborative governance can enable consumers and market regulators to regulate the discriminatory pricing behavior of e-commerce platforms effectively. This article offers valuable insights into the governance of violations in the e-commerce sector based on robust data and model research.

The reputation-based reward mechanism promotes the evolution of fairness

In real life, a good reputation generally brings positive returns to individuals. For example, merchants with numerous good reviews usually gain higher profits. Considering this in the ultimatum game, we propose a reputation-based reward mechanism to investigate the evolution of fairness. Specifically, individuals' reputations evolve dynamically based on the outcomes of games. At the same time, we set a reputation threshold in the population. When individuals' reputations exceed the reputation threshold, they are considered excellent. Otherwise, they are ordinary. The excellent individuals can receive extra rewards compared to the ordinary ones. Finally, individuals' total payoffs determine their fitness within the population. Based on these settings, this paper mainly explores how reputation threshold, weight factor and reward strength affect the evolution of fairness. Through a series of simulations, the reputation-based rewards mechanism is proved to effectively promote the fairness in the population. To be specific, we find that higher reputation thresholds and smaller values of weight factor significantly enhance the promotion effect of reward on fairness. Simultaneously, there is a specific correspondence between the reputation threshold and the weight factor. When reward strength is fixed, for different reputation thresholds, the optimal value of weight factor to achieve maximum fairness levels also varies. Additionally, increasing reward strength can significantly promote fairness.

Sexism in esports: How male and female players evaluate each others’ performance and agency

While equality and inclusivity are promoted in the realm of video gaming, most gamer communities remain male-dominated, which may give rise to prejudices against female players and their skill among gamer and the general public. In this study, we conducted two experiments where we measured how participants evaluate players’ performance and agency attributions. We used two distinct experimental manipulations—one utilizing videos of players playing (n = 312) and the other using narrative vignettes (n = 338). We found that performance of male players’, to a limited extent, can be attributed to the gaming outcomes compared pre-existing social preconceptions about them and other variables. Female players’ performance assessment was mostly strongly predicted by pre-existing social sex-related prejudice against females, albeit not directly, but through percieved agency of the female players’. These results contribute to the literature on gaming-related stereotypes by enhancing the understanding of societal prejudices in the evaluation of players’ skills.

The Bradley-Terry Model in Binary Outcome Driven Rankings: An Application in Amateur Hockey

Ranking systems serve critical roles in sport settings, most notably in determining playoff participants and seeding. Many ranking methodologies exist that are flexible enough to incorporate many input measures and produce models that are highly predictive of game outcomes. However, there are circumstances—especially for amateur sport leagues—in which more complex inputs are either unavailable or not desirable, as they may lead to adverse performance incentives. Therefore, the goal of this paper is to highlight a ranking methodology that only considers binary game outcomes, i.e., wins and losses. Specifically, we consider the efficacy of the Bradley-Terry Model to efficiently rank sport teams for playoff consideration. We apply this method as a case study to the New England Prep School Ice Hockey Association (NEPSIHA), and compare the accuracy of their current ranking system to the Bradley-Terry model using simulation methods. We show that Bradley-Terry significantly outperforms NEPSIHA’s current method, especially when teams face unbalanced strengths of schedule. This result holds under various league competitive balance distributions.

How to escape the dilemma of carbon emission reduction policies implementation under Chinese fiscal decentralization?

As the world's largest energy consumer and carbon emitter, China has undertaken a series of low-carbon policies. However, its top-down authoritarian governance, coupled with economic decentralization, challenges policy effectiveness. To facilitate the implementation of incentive-compatible carbon emission reduction policies, this study proposes a tripartite stochastic evolutionary game model involving the central government, local governments, and enterprises. Replicator dynamic equations are then employed to assess how uncertainty shapes participants' behavioral choices. Furthermore, a real-case example validates the theoretical findings and supports subsequent arguments: (1) initial strategy choices by stakeholders influence their transitions but have minimal long-term impact on the final convergence pattern; (2) stakeholders' dedicated efforts, especially central government supervision, shape evolutionary outcomes during policy implementation; (3) the escalation of penalties contributes to policy execution, while transfer payment allocation warrants thorough evaluation as it affects the strategies of both local governments and enterprises; and (4) the incorporation of random elements introduces disruptions in stakeholder evolutionary paths, resulting in deviations and fluctuations from expected patterns. This study not only highlights the importance of resolving the dilemma in implementing emission reduction policies through effective coordination among stakeholders but also reduces uncertainty related to unobserved factors, ensuring a comprehensive range of game outcomes.

MambaNet: A Hybrid Neural Network for Predicting the NBA Playoffs

In this paper, we present MambaNet: a hybrid neural network for predicting the outcomes of Basketball games. Contrary to other studies, which focus primarily on season games, this study investigates playoff games. MambaNet is a hybrid neural network architecture that processes a time series of teams’ and players’ game statistics and generates the probability of a team winning or losing an NBA playoff match. In our approach, we utilize Feature Imitating Networks to provide latent signal-processing feature representations of game statistics to further process with convolutional, recurrent, and dense neural layers. Three experiments using five different datasets are conducted to evaluate the performance and generalizability of our architecture against a wide range of previous studies. Our final method successfully predicted the AUC from 0.72 to 0.82, beating the best-performing baseline models by a considerable margin.

The influence of physical fitness qualities, individual characteristics and contextual factors on youth basketball players' perceived exertion and recovery responses to official games.

This study examined the influence of physical fitness qualities, individual characteristics, and contextual factors on perceived exertion and recovery responses to official games in youth basketball players. Twenty-six males (age: 15.8±1.2 years; 12 guards, 9 forwards, and 5 centers) and 7 females (age: 16.1±0.9 years; 3 guards, 4 forwards) were monitored for an entire basketball season (N.=635 observations). Yo-Yo Intermittent Recovery (level 1) and countermovement jump (CMJ) tests were administered, with players categorized as high and low Yo-Yo and CMJ groups according to test results. Ratings of perceived exertion (RPE) were collected after each official game. Before the game and the day after, the Total Quality of Recovery (scores) were collected, and the difference between post- and pregame TQR was calculated (TQRΔ). Separate linear mixed models evaluated the effects of sex (M; F), fitness qualities (high Yo-Yo; low Yo-Yo) (high CMJ; low CMJ), playing position (guard; forward; center), game outcome (won; loss) and game location (home; away). Male players reported higher RPE (7.0±0.3) than females (5.5±0.4) (P=0.003, effect size [ES]: moderate). Players with high Yo-Yo performance also reported higher RPE (6.7±0.4) than low Yo-Yo (5.8±0.3) (P=0.049, ES: small). TQRΔ was higher in guards (-1.3±0.2) than forwards (-0.8±0.2) (P=0.041, ES: trivial), and lower after lost games (-0.8±0.2) compared to won games (-1.2±0.2) (P=0.002, ES: small). In youth basketball, postgame perceived exertion and recovery responses are influenced by players' sex, intermittent endurance capacity, and game outcome. Current findings can help youth basketball practitioners to better understand their players' performances and perceptual responses.

Distributed and Fair Beacon Power and Beaconing Rate Adaptation Based on Game Theoretic Approach for Connected Vehicles

In vehicular ad hoc networks, vehicles regularly transmit information through beacons to raise awareness among nearby vehicles about their presence. However, as the number of beacons increases, the wireless channel becomes congested, resulting in packet collisions and the loss of numerous beacons. This paper addresses the challenge of optimizing joint beaconing power and rate in VANETs. A joint utility-based beacon power and rate game is formulated, treated both as a non-cooperative and a cooperative game. To compute the desired equilibrium, three distributed and iterative algorithms (Best Response Algorithm, Cooperative Bargaining Algorithm) are introduced. These algorithms simultaneously update the optimal values of beaconing power and rate for each vehicle in each step. Extensive simulations showcase the convergence of the proposed algorithm to equilibrium and offer insights into how variations in game parameters may affect the game's outcome. The results demonstrate that the Cooperative Bargaining Algorithm is the most efficient in converging to equilibrium.

Game-related statistics that discriminate winning from losing in NCAA Division-I men's basketball.

The purpose of the present study was to examine differences in game-related statistics between winning and losing game outcomes and determine which performance parameters have the greatest impact in classifying winning from losing game outcomes at the National Collegiate Athletic Association (NCAA) Division-I men's basketball level of competition. The data scraping technique was used to obtain publicly available data over a 2018-2019 season span. The total number of games examined was 5,147. Independent t-tests were used to examine statistically significant differences between winning and losing game outcomes, while a full model discriminant function analysis was used to determine the relative contribution of each game-related statistic and its ability to classify winning from losing game outcomes (p < 0.05). Alongside scoring a greater number of points at the end of the game, the findings of the present study indicate that winning teams: (a) attempted and made more field goals, three-point, and free-throw shots, (b) accumulated more defensive and total rebounds, assists, steals, and blocks, (c) had fewer turnovers and personal fouls, and (d) secured greater field goal, three-point, and free-throw shooting percentage. Moreover, the top three performance parameters discriminating winning from losing game outcomes were field goal percentage, defensive rebounds, and assists, accounting for 16.8%, 12.2%, and 12.0% of the total percentage of explained variance, respectively (i.e., 41.0% combined). Overall, these findings support the expected roles of offensive and defensive game-related statistics and provide further insight into how they work together to optimize the chances of securing the desired game outcome.

Tactical Situations and Playing Styles as Key Performance Indicators in Soccer.

The game of soccer is complex and unpredictable, demanding multifaceted strategies for success. Performance analysis has evolved, focusing on key performance indicators (KPIs) to determine the factors that most significantly influence a team's success or failure during matches. Traditional performance analysis methods have emphasized quantifiable data like physical exertion and basic play events but often neglected the subtler tactical dimensions that could significantly impact game outcomes. This study aimed to fill the gap in the current literature by creating a comprehensive framework that incorporates tactical situations as KPIs. The objective was to examine whether specific playing styles adopted by teams in various tactical situations and phases of the game could predict the outcome of matches. A dataset comprising all First Division Championship matches from 11 different European countries for the 2021-2022 season was analyzed. Variables representing tactical situations were correlated with match outcomes using a Generalized Estimating Equation framework. The model was specified with a binomial distribution and a logit link function. Statistical significance was determined using Wald χ2 tests with a significance level set at p < 0.05. The study's findings revealed that possession style, counterattacking during offensive transitions, and a balanced aggressive defensive strategy significantly increase a team's chances of victory. It also showed that successful teams tend to focus on central attacks, minimize crossing, and execute strategic plays that lead to final attempts on goal with minimal ball possession. The above findings demonstrate that adopting certain tactical approaches significantly influences soccer match outcomes, highlighting the importance of considering tactical aspects as KPIs.

Positional Differences in Decision-Making Situations during Professional Rugby League Match-Play.

The aim of this study was to explore the types and frequency of decision-making situations of rugby league players during defensive situations and examine whether they were predictive of key performance indicators (KPI). Fifteen elite rugby league matches were coded using notational analysis methods. Specific defensive situations were analysed, including the number of: one-on-one situations with an opposing attacker (1-on-1), two-on-one situations (2-on-1), and combined 1-on-1 and 2-on-1 situations (i.e., total decisions; TDs). There was no relationship between the game outcome and game KPIs for TDs or 1-on-1 decision-making situations. However, successful tackles and missed tackles were predictive of 2-on-1 decision-making situations. Positional differences revealed that back rowers were exposed to the greatest number of decision-making situations, while wingers had the lowest exposure. The total number of decisions and the number of 1-on-1 decisions made by the centres and wingers were significant predictors of line breaks. Additionally, 2-on-1 decisions were significant predictors of line breaks for backrowers. The findings of this study suggest that the type and frequency of decision-making situations in Rugby League are position specific. Practical applications for coaches are discussed to ensure that practice approaches are representative of the various defensive decision-making demands players experience during a game, based on their position.

Skill-Based Matchmaking for Competitive Two-Player Games

Skill-based matchmaking is a crucial component of competitive multiplayer games and it is directly tied to how the players would enjoy the game. We present a simple matchmaking algorithm that aims to achieve a target win rate for all players, making long win/loss streaks less probable. It is based on the estimated skill levels of players. Therefore, we also present a rating estimation for players that does not require any game-specific information and purely relies on game outcomes. Our evaluation shows that our methods are effective in estimating a player's rating, responding to changes in rating, and achieving a desirable win rate that avoids long win/loss streaks in competitive two-player games.

Vertical jump neuromuscular performance of professional female handball players-starters vs. non-starters comparison.

Given the complex nature of the handball as a game, players are required to possess a distinct set of physical and physiological attributes to attain peak performance. With the countermovement vertical jump (CVJ) being widely implemented as a non-invasive and time-efficient testing modality in sports settings, the purpose of the present study was twofold: (a) to establish a CVJ profile of professional female handball players and (b) to examine differences in force-time metrics between starters and non-starters. Forty-two professional female handball players (e.g., SuperLeague) volunteered to participate in this study. Each athlete performed three maximum-effort CVJs with no arm swing while standing on a uni-axial force plate system sampling at 1,000 Hz. Independent t-tests were used to examine differences in each variable between starters and non-starters. The results revealed that starters attained superior performance within the eccentric phase of the CVJ when compared to non-starters, particularly in terms of eccentric peak velocity (-0.957 ± 0.242 vs. -0.794 ± 0.177 m·s-1), eccentric mean power (320.0 ± 77.7 vs. 267.1 ± 75.2 W), and eccentric peak power (929.0 ± 388.1 vs. 684.4 ± 214.2 W). While not reaching the level of statistical significance, moderate-to-large effect sizes were observed for concentric impulse, peak velocity, and mean and peak force and power, all in favor of players included in the starting lineup (g = 0.439-0.655). Overall, these findings suggest that at the top-tier level of handball competition, the ability to secure a spot in a starting lineup may be possibly influenced by the athlete's eccentric performance capabilities. Thus, the development of lower-body eccentric strength and power may positively impact on-court athlete performance and ultimately help the team secure the desired game outcome.