Types Of Players Research Articles

Predicting the winning team in basketball: A novel approach

Predicting the winner of a basketball game is a difficult task, due to the inherent complexity of team sports. All 10 players on the court interact with each other and this intricate web of relationships makes the prediction task difficult, especially if the prediction model aims to account for how different players amplify or inhibit other players. Building our approach on complex systems and prototype heuristics, we identify player types through clustering and use cluster memberships to train prediction models. We achieve a prediction accuracy of ∼76% over a period of five NBA seasons and a prediction accuracy of ∼71% over a season not used for model training. Our best models outperform human experts on prediction accuracy. Our research contributes to the literature by showing that player stereotypes extracted from individual statistics are a valid approach to predict game winners.

Contrastive language and vision learning of general fashion concepts

The steady rise of online shopping goes hand in hand with the development of increasingly complex ML and NLP models. While most use cases are cast as specialized supervised learning problems, we argue that practitioners would greatly benefit from general and transferable representations of products. In this work, we build on recent developments in contrastive learning to train FashionCLIP, a CLIP-like model adapted for the fashion industry. We demonstrate the effectiveness of the representations learned by FashionCLIP with extensive tests across a variety of tasks, datasets and generalization probes. We argue that adaptations of large pre-trained models such as CLIP offer new perspectives in terms of scalability and sustainability for certain types of players in the industry. Finally, we detail the costs and environmental impact of training, and release the model weights and code as open source contribution to the community.

Lisfranc injury: Prevalence and maintaining a high index of suspicion for optimal evaluation

ABSTRACT Objectives To quantify the long-term prevalence of game-related Lisfranc trauma in college football on artificial turf and natural grass. Methods 32 universities were evaluated over 10 competitive seasons across all Football Bowl Subdivision (FBS) conferences. Outcomes of interest included injury severity, injury category, primary type of injury, player and skill position, injury mechanism and situation, elective imaging and surgical procedures, and field conditions. Injury incidence rates (IIR) were calculated using injuries per 10 games = (number of injuries) number of games) × 10. Results Of the 1577 games documented, 783 games (49.7%) were played on a 3-layer artificial turf (≥9.0 lbs/ft2) infill system versus 794 games (50.3%) played on natural grass. In sum, 78 Lisfranc cases were documented with 34 (43.6%) occurring on artificial turf, and 44 (56.4%) on natural grass. MANOVAs indicated significant main effects by injury category (F3,74 = 6.439; P = .001), and injury mechanism (F5,72 = 3.372; P = .009) observed between surfaces, but not by injury severity (F2,75 = 0.720; P = .490), primary type of injury (F4,73 = 0.772; P = .547), overall player (F2,75 = 0.219; P = .804) and skill positions (F8,69 = 0.850; P = .563), injury situation (F10,67 = 1.030; P = .428), elective imaging and surgical procedures (F3,74 = 0.515; P = .673), or field conditions (F2,75 = 0.375; P = .688). Post hoc analyses indicated significantly greater incidences (P < .05) of Lisfranc trauma on natural grass attributed to shoe:surface interaction during noncontact play, and during no contact, foot rotation or planting. Ligament tears (n = 8; 57.1%), with minimal cases of subluxation/dislocations (n = 4; 28.6%) and fractures (n = 2; 14.3%) comprised grade 3 cases across both surfaces. Conclusion In regards to Lisfranc trauma, a 3-layer, heavyweight artificial infill surface is as safe or safer than natural grass. The findings of this study may be generalizable only to this level of football competition.

The first compliance cycle of China’s National Emissions Trading Scheme: insights and implications

China’s national Emissions Trading Scheme (ETS), the largest ETS in terms of the amount of CO2 regulated, was launched on the trading platform operated by the Shanghai Environment and Energy Exchange (SEEE) on July 16th 2021, and has successfully completed its first compliance cycle on December 30th, 2021. During the operation of its first cycle, China’s national ETS differs from other international ETSs in many aspects, including trading products and participants, allowance allocation method, compliance term, and offset mechanism, leading to certain unique trading patterns. Some unique settings are worth noticing including key emitters dominated by state-owned enterprises (SOEs) who also dominate transactions, large-scale power groups’ carbon strategies, allowances for 2 years of 2019 and 2020 being processed in one compliance period and allowed inter-year banking of allowances. All these have led to trading patterns characterized by cyclical demand-driven trading, insufficient trading capabilities of regulated entities, stable allowance price and an increased price of CCER. Nonetheless, the successful running of its first compliance cycle offers invaluable experience for future ETS development in operational mechanism improvement, sector coverage expansion, allocation optimization, and introduction of different types of market players and tradable products, and provides a good reference for future international expansion.

Pre-service Teachers' Player Types and Their Relation to Self-efficacy With Digital Media

Gamification in educational contexts is often used to increase learners’ intrinsic motivation and their self-efficacy beliefs, two constructs which are positively related with each other as well as to scholastic outcomes. As self-efficacy beliefs are conceptualized context-specific, it is important to consider various users’ needs by adapting the learning environment to their corresponding gamification player types (GPT). Studies show that different GPT are characterized by different motivational aspects (intrinsically motivated, extrinsically motivated, disruptive GTP) Therefore, the aim of the present study is the examination of six different GPT according to the HEXAD typology (Tondello et al., 2016) for pre-service teachers regarding their distribution and their relation to self-efficacy with digital media. Altogether N = 75 pre-service teachers were assessed in terms of their GPT and their self-efficacy with digital media. It was hypothesized that the GPT distribution for pre-service teachers is comparable to the distribution reported by Tondello et al. (2016). Additionally, it was exploratively examined to what extent the different types of players differ in their self-efficacy with digital media. Results show that the GPT distribution in the current sample differs significantly from the expected distribution. Pre-service teachers seem to show specific GPT characteristics due to their profession. Concerning self-efficacy with digital media, pre-service teachers show a high subjective perception of their self-efficacy with digital media, but contrarious to the hypothesis no significant relation was found between GPT and self-efficacy with digital media. The results indicate that pre-service teachers feel confident to the use of digital media in class and that pre-service teachers form a group with a specific distribution of player types and therefore have specific needs in gamified learning environments. Due to the reported high amount of intrinsic player types, game design elements which promote intrinsic motivation should be in the focus of prospective analyses.

Analysis of Injury Patterns in Men's Football between the English League and the Spanish League.

Background: Injuries in professional football lead to reduced team performance and large financial losses. The aim of this study was to analyse injuries in the two best team competitions in the world (LaLiga and Premier League), establishing similarities and differences, as well as determining injury causation patterns. Methods: A total of 277 on-field injuries requiring a substitution were analysed (142 in the Spanish league and 135 in the English league). The analysis was performed using traditional statistical tests (frequency analysis, chi-square test) with SPSS 25 and a T-Patterns sequence analysis with THEME 5.0. Results: In the Spanish league, there were a similar number of injuries in the first part of the season as in the second part of the season, while in the English league, they are more frequent in the first part of the season. In the Spanish league, injuries are more frequent in the first half of the match, while in the English league, they are more frequent in the second half. The type of player most frequently injured was the defender. Most of the injuries occurred without the presence of an opponent. The accumulated minutes during the season affect injuries of the muscular type. Conclusions: The most common type of injury in both leagues was a strain, followed by a sprain and a contusion. Although common injury patterns can be established between the two leagues, there are notable differences. One of the factors is determined by the English league calendar (many matches at Christmas). In Spain, there were more muscular injuries that were not caused by the opponent, while in England there were more tackling injuries. Age is a risk factor in the Spanish league. In this league, there is a moderately significant relationship between the number of injuries and the points won.

Strategic investment decisions in an oligopoly with a competitive fringe: An equilibrium problem with equilibrium constraints approach

Modern wholesale electricity markets often have producers who exercise market power. The standard way to model market power in an oligopoly with a competitive fringe is by using Mixed Complementarity Problems (MCPs) and conjectural variations. However, such models can lead to myopic (sub-optimal) behaviour for oligopolists. We first build on existing literature to show that an oligopoly with a competitive fringe where all firms have investment decisions will also lead to myopic behaviour when modelled using MCPs with conjectural variations. To overcome this issue, we develop an Equilibrium Problem with Equilibrium Constraints (EPEC) to model such an electricity market structure. The EPEC models two types of players: price-making firms, who have market power, and price-taking firms, who do not. Our model is the first in the literature to consider an oligopoly with a competitive fringe where all firms have investment decisions. Our results indicate that an EPEC can model investment decisions in an oligopoly with a competitive fringe more credibly and thus overcome the myopic behaviour observed in MCPs. The EPEC found multiple equilibria for investment decisions and firms’ profits. Despite this, market prices and consumer costs were found to remain relatively constant across the equilibria. A further contribution of the modelling approach is that it shows how it may be optimal for price-making firms to accept losses in some time periods in order to disincentivize price-taking firms from investing further into the market. We conclude our paper with a discussion of the computational limitations of our approach.

Experts vs. policymakers in the COVID-19 policy response

We build an evolutionary game-theoretic model of the interaction between policymakers and experts in shaping the policy response to the COVID-19 pandemic. Players’ decisions concern two alternative strategies of pandemic management: a “hard” approach, enforcing potentially unpopular measures such as strict confinement orders, and a “soft” approach, based upon voluntary and short-lived social distancing. Policymakers’ decisions may also rely upon expert advice. Unlike experts, policymakers are sensitive to a public consensus incentive that makes lifting restrictions as soon as possible especially desirable. This incentive may conflict with the overall goal of mitigating the effects of the pandemic, leading to a typical policy dilemma. We show that the selection of strategies may be path-dependent, as their initial distribution is a crucial driver of players’ choices. Contingent on cultural factors and the epidemiological conditions, steady states in which both types of players unanimously endorse the strict strategy can coexist with others where experts and policymakers agree on the soft strategy, depending on the initial conditions. The model can also lead to attractive asymmetric equilibria where experts and policymakers endorse different strategies, or to cyclical dynamics where the shares of adoption of strategies oscillate indefinitely around a mixed strategy equilibrium. This multiplicity of equilibria can explain the coexistence of contrasting pandemic countermeasures observed across countries in the first wave of the outbreak. Our results suggest that cross-country differences in the COVID-19 policy response need not be the effect of poor decision making. Instead, they can endogenously result from the interplay between policymakers and experts incentives under the local social, cultural and epidemiological conditions.

Static and Dynamic Game Theory in Common Oil and Gas Fields: A Literature Review and Bibliometric Analysis

This paper provides a systematic literature review and analysis of game theory to model oil and gas scenarios. We select and review 2514 papers from Scopus, present a complex three-dimensional classification of the selected papers, and analyze the resultant citation network. According to the industry-based classification, the surveyed literature can be classified in common oil and gas supply chain fields. Based on the types of players, the literature can be classified into papers that use government-contractor games, the contractor–contractor games, contractor-subcontractor games, subcontractor–subcontractor games, or games involving other players. Based on the type of games used, papers using normal-form noncooperative games, normal-form cooperative games, extensive-form noncooperative games, or extensive-form cooperative games are present. Also, we show that each of the above classifications plays a role in influencing which papers are likely to cite a particular paper. However, the type-of-game classification exerts the strongest influence. Overall, the citation network in this field is sparse, implying that the authors' awareness of studies by other academics is suboptimal. Our review suggests that game theory is useful for modeling oil and gas scenarios. More work needs to be done on production in this domain and using extensive-form noncooperative games.

Belief and higher‐order belief in the centipede games: An experimental investigation

AbstractThis paper experimentally explores the epistemic conditions behind people's non‐equilibrium behaviour in the centipede games. We propose a novel design of laboratory experiment to elicit people's first‐ and second‐order beliefs regarding their opponents' choices and beliefs. The measured beliefs, together with the choice data, help us to estimate people's level of rationality, belief of rationality and second‐order belief of rationality. To examine how these epistemic variables are affected by the social‐efficiency property of the classic increasing‐sum centipede game, we revisit the constant‐sum centipede and compare the measured epistemic conditions from the constant‐sum with those from the classic centipede. We find that people's non‐backward induction behaviour may be attributed to the diffusion of beliefs and higher‐order beliefs in the increasing‐sum centipede. We consider a behavioural model in which people's preferences for social efficiency are incorporated into the extended utility maximization problem. Our analytical and estimation results indicate that the presence of efficiency‐oriented players and people's belief towards the uncertain portion of such type of players may play a part in the non‐backward‐induction outcomes in experimental centipede games.

Chromatin Ubiquitination Guides DNA Double Strand Break Signaling and Repair.

Chromatin is the context for all DNA-based molecular processes taking place in the cell nucleus. The initial chromatin structure at the site of the DNA damage determines both, lesion generation and subsequent activation of the DNA damage response (DDR) pathway. In turn, proceeding DDR changes the chromatin at the damaged site and across large fractions of the genome. Ubiquitination, besides phosphorylation and methylation, was characterized as an important chromatin post-translational modification (PTM) occurring at the DNA damage site and persisting during the duration of the DDR. Ubiquitination appears to function as a highly versatile “signal-response” network involving several types of players performing various functions. Here we discuss how ubiquitin modifiers fine-tune the DNA damage recognition and response and how the interaction with other chromatin modifications ensures cell survival.

Musculoskeletal Disorders, Pain and Fatigue among String and Wind Music Students

Music students are more likely to get Musculoskeletal Disorders (MSDs), fatigue, and pain. However, limited studies compared MSDs, pain and fatigue between different types of musical instrument players. This study compared MSDs, pain, and fatigue among music students who play wind and string instruments. A cross-sectional study was conducted with a group of music students in one of the universities in Malaysia. No statistical differences in pain and fatigue were found, but more wind players experience MSD at the wrist and hand than string players. Therefore, students who play string instruments should be more watchful with MSD symptoms. Keywords: Musical instruments, pain, fatigue, musculoskeletal disorder eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning &amp; Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v7i20.3457

팀스포츠 선수들의 MBTI 성격유형에 따른 스포츠심리기술과 회복탄력성 차이 검증

The purpose of this study was to investigate the difference in sports psychological skill level and resilience according to the MBTI personality type of team sports players, and to provide basic data for developing a sports psychological support program for each personality type. The subjects of this study were 275 registered student athletes of the Korea Sports Association, and self-reported test papers were used. The collected data were subjected to frequency analysis, exploratory factor analysis, reliability verification, T-test, One-way ANOVA, and Scheffe

The Player Experience and Design Implications of Narrative Games

Narrative games focus on the plot, character interactions, and sometimes have story variations depending on how the player interacts with them. This study adopts user experience approaches, such as interviews, think-aloud protocol, and grounded theory, to examine the player experience of commercial narrative games. We identify four types of players’ interactional patterns that include exploring the story, projecting the story, playing the game, and watching the story. Based on the study of the player experience, we derive a set of principles from these interactional patterns that game designers can draw upon when designing narrative games. These principles include player-avatar dynamic, a strong interactive space for the player to explore, placeholder for projecting an emergent narrative, inclusive game design to enhance accessibility, using an interactive feedback loop to adapt to the players’ playstyle, quick-time events and emotional connection to the characters, and more complex options to romance/relationships in narrative games.

Gamification in Language Teaching at the University Level: Learner Profiles and Attitudes

In instructional settings, the term gamification refers to the use of game-based elements to increase learner motivation and involvement. This study aimed to get insight into how adult learners of English perceive gamified activities incorporated into their English language course, and whether player types as defined by Bartle (1996) – explorers, achievers, socializers, and killers – affect student attitudes to specific gamification elements (rules, time limit, challenges, leaderboard, awards, bonuses, and badges). The results showed a high level of student support (97%) for gamified language instruction. A significant difference was observed between player types regarding their attitudes to certain gamification elements and player types. Challenges were highly rated by the explorers (p = 0.006); leaderboards by the killers (p = 0.049), and time limit by the achievers (p = 0.009). The conclusion is that player types and preferences should be surveyed and considered when designing gamified learning activities.

The Relationship Between Russian Kindergarteners' Play and Executive Functions: Validating the Play Observed Behaviors Scale.

BackgroundYoung children’s play is theorized to develop executive functions, skills strongly predictive of many later advantages. The current study sought to validate a practicably short play behavior survey for kindergarten teachers (N = 18) and compare the reported behaviors to the executive functions (EFs) of their 443 Russian kindergarteners (Mage = 78.6 months; SD = 4.04).Research FindingsThe factor model with satisfactory construct validity and internal consistency included three factors: leadership, play preferences and rule conformity. Analyses provide partial support for Vygotsky’s theory that play supports EF development, but particular behaviors were related to different EF components. However, kindergarteners exhibiting more leadership, preferences and conformity overall rated higher on most EF components.Practice and PolicyThese findings do not support the theory that play skills improve unidirectionally with age and EFs, suggesting particular profiles of types of players and complex changes with age. The play behavior survey may be a practicable way to trace different profiles across the early years.

The role of generalised reciprocity and reciprocal tendencies in the emergence of cooperative group norms

• We examined the emergence of cooperation among small groups of anonymous players. • Behavioural modelling revealed the role of generalised reciprocity on behaviour. • Players differed in their reciprocal tendencies, and can be grouped into four types. • Interactions among different player types resulted in different group dynamics. • Cooperation relies on specific group compositions vis-à-vis reciprocal tendencies. Norms for cooperation are essential for groups to function effectively, yet there are often strong incentives for group members to behave selfishly. Direct and indirect reciprocity can help to discourage such uncooperative behaviour by punishing defectors and rewarding cooperators, but require explicit means for punishment and tally-keeping. What, then, encourages an individual to cooperate with their group when others cannot track the behaviour of others? We adapted the Bargaining Game to examine the emergence and maintenance of cooperation among 20 groups of six anonymous players (N = 120) who interacted amongst themselves over recursive bargaining exchanges. By estimating the expected utility that drives players’ demands in these interactions, we demonstrate that their behaviour on each exchange reflects the demands placed upon them previously. Thus, we highlight the role of generalised reciprocity in such situations; that is, when an individual passes on to another member of their group the behaviour they have received previously. Furthermore, we identify four distinct behavioural types that differ in their expressions of generalised reciprocity: Some players converge quickly on cooperative demands regardless of the behaviour they received from their co-players, and are therefore characterised by low expressions of reciprocity. In contrast, individuals with strong reciprocal tendencies decrease their demands over successive interactions in response to the behaviour of their group. By simulating groups with different compositions of these player types, we reveal the strong influence of individual differences in reciprocal tendencies on the emergence of cooperative group dynamics.

Empirical Study of Adaptive Serious Games in Enhancing Learning Outcome

Use of serious games to teach concepts of various important topics including Cybersecurity is growing. A figure of merit for the serious games could be learning outcome and user experience(UX). With enhanced learning outcome and user experience, the player is likely to favourably rate a game. The organisation supporting such games would also benefit from such efficient training process.We report an empirical comparison of two cybersecurity games namely ; Use of Firewalls for network protection and concepts of Structured Query Language (SQL) injections to get unauthorised access to online databases. We have designed these games in two versions. The version without using adaptive features provide a baseline to compare efficacy of the machine learning based adaptive game while comparing the learning outcomes and user experience (UX). The efficacy of the Machine Learning (ML) agent in providing the adaptability to the game play is based on classification of player to two categories viz. Beginner and Expert using historical player data on three relevant attributes. The game dynamics is modulated based on the player classification to ensure that game challenge is optimally suited to player type and the player continues to experience playful flow in different stages of the game.

Using player types to understand cooperative behaviour under economic and sociocultural heterogeneity in common-pool resources: Evidence from lab experiments and agent-based models.

Rising migration numbers and the resulting increase in economic and sociocultural heterogeneity in societies all over the world are theorised to put pressure on the sustainable use of common-pool resources [CPRs]. Increased heterogeneity is argued to decrease trust and diversify interests between resource users, leading to overuse and decline of natural and man-made CPRs. The aim of this paper is to understand cooperative behaviour under economic and sociocultural heterogeneity in CPRs, through the analyses of experimental data including 344 subjects from the United Kingdom and the Netherlands, and 144 subjects from India. Multilevel regression, ordinal logistic regression, linear conditional-contribution profiles [LCPs] and agent-based models [ABMs] are used to analyse and replicate experimental outcomes on the micro- and macro-level. Results show that the combination of economic and sociocultural heterogeneity affects cooperation negatively when the decision-situation is perceived as unfair, but that neither economic nor sociocultural heterogeneity on themselves affect cooperation negatively. Economic heterogeneity is even found to affect cooperation positively relative to homogeneity. Player type classification based on LCP scores shows that experimental outcomes can be interpreted with player types, and ABM simulations validate the experimental results by replicating the main outcomes.

A VNS-based metaheuristic approach for escape interdiction on transportation networks

Containment of dynamic crimes such as kidnapping, bank robbery, hit-and-run, etc., is a challenging issue for law enforcement agencies as the criminal changes his location with time. This type of scenario is generally modelled as an escape interdiction game. We consider two types of players, namely multiple defenders and a single attacker. The defenders choose a sequence of junctions to protect, while the attacker chooses an escape path and the travel time on distinct edges along the path. Hence, both the defender strategy space and the continuous attacker strategy space suffer an exponential growth. This leads to major challenges in the computation of the optimal solution with respect to each player. We develop a double oracle Variable Neighborhood Search (VNS) based meta-heuristic algorithm for finding near-optimal defender and attacker strategies in a time efficient manner. We test the efficiency of this approach against an established exact algorithm named Escape Interdiction Game Solver (EIGS). We use EIGS to generate the benchmark results to check the performance of our heuristic. We also show that the performance of our approach is reasonably good under strict time limitations, as observed in practice.