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Hatem, Belhouchet, and Khatrouch Ikram. "A Methodology for Selection Starting Line-Up of Football Players in Qatar World Cup 2022." European Journal of Sport Sciences 2, no. 2 (April 14, 2023): 46–51. http://dx.doi.org/10.24018/ejsport.2023.2.2.56.
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The process of player selection in multi-player sports is a complex multi-criteria problem. In Football, the role of a coach is selecting players as the starting line-up that is formed subjectively without regard to various criteria. The decision of the coach can impact team performance. This paper proposes a new model for selection starting line-up integrating criteria in FIFA World Cup 2022.The aim is to use MOORA method in football player selection process. We test the efficiency of the model using France National football team and we demonstrate how the methodology can facilitate decision making by selecting players.
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Ohtsuki, Hisashi. "Evolutionary dynamics of n -player games played by relatives." Philosophical Transactions of the Royal Society B: Biological Sciences 369, no. 1642 (May 19, 2014): 20130359. http://dx.doi.org/10.1098/rstb.2013.0359.
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One of the core concepts in social evolution theory is kin selection. Kin selection provides a perspective to understand how natural selection operates when genetically similar individuals are likely to interact. A family-structured population is an excellent example of this, where relatives are engaged in social interactions. Consequences of such social interactions are often described in game-theoretical frameworks, but there is a growing consensus that a naive inclusive fitness accounting with dyadic relatedness coefficients are of limited use when non-additive fitness effects are essential in those situations. Here, I provide a general framework to analyse multiplayer interactions among relatives. Two important results follow from my analysis. First, it is generally necessary to know the n -tuple genetic association of family members when n individuals are engaged in social interactions. However, as a second result, I found that, for a special class of games, we need only measures of lower-order genetic association to fully describe its evolutionary dynamics. I introduce the concept of degree of the game and show how this degree is related to the degree of genetic association.
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Carrillo, Juan D., and Thomas R. Palfrey. "The Compromise Game: Two-Sided Adverse Selection in the Laboratory." American Economic Journal: Microeconomics 1, no. 1 (January 1, 2009): 151–81. http://dx.doi.org/10.1257/mic.1.1.151.
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We analyze a game of two-sided private information where players have privately known “strengths” and can decide to fight or compromise. If either chooses to fight, the stronger player receives a high payoff and the weaker player receives a low payoff. If both choose to compromise, each player receives an intermediate payoff. The only equilibrium is for players to always fight. In our experiment, we observe frequent compromise, more fighting the lower the compromise payoff and less fighting by first than second movers. We explore several theories of cognitive limitations in an attempt to understand these anomalous findings. (JEL C91, D82)
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Silva, João Vítor Rocha da, and Paulo Canas Rodrigues. "All-NBA Teams’ Selection Based on Unsupervised Learning." Stats 5, no. 1 (February 9, 2022): 154–71. http://dx.doi.org/10.3390/stats5010011.
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All-NBA Teams’ selections have great implications for the players’ and teams’ futures. Since contract extensions are highly related to awards, which can be seen as indexes that measure a players’ production in a year, team selection is of mutual interest for athletes and franchises. In this paper, we are interested in studying the current selection format. In particular, this study aims to: (i) identify the factors that are taken into consideration by voters when choosing the three All-NBA Teams; and (ii) suggest a new selection format to evaluate players’ performances. Average game-related statistics of all active NBA players in regular seasons from 2013-14 to 2018-19, were analyzed using LASSO (Logistic) Regression and Principal Component Analysis (PCA). It was possible: (i) to determine an All-NBA player profile; (ii) to determine that this profile can cause a misrepresentation of players’ modern and versatile gameplay styles; and (iii) to suggest a new way to evaluate and select players, through PCA. As the results of this paper a model is presented that may help not only the NBA to better evaluate players, but any basketball league; it also may be a source to researchers that aim to investigate player performance, development, and their impact over many seasons.
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Pratama, Fabio Fahri, and Youllia Indrawaty Nurhasanah. "PENGGUNAAN METODE PROFILE MATCHING DAN NAÏVE BAYES UNTUK MENENTUKAN STARTING ELEVEN PADA SEPAK BOLA." Jurnal Tekno Insentif 14, no. 2 (August 26, 2020): 59–68. http://dx.doi.org/10.36787/jti.v14i2.268.
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Abstrak - Pemilihan pemain starting eleven atau kesebelasan dan formasi tim dengan komposisi pemain yang tepat dalam olahraga sepak bola merupakan hal yang penting untuk meningkatkan performa permainan sebuah tim. Pelatih terkadang memilih pemain starting eleven tidak secara objektif, dikarenakan dibutuhkan keahlian dan kejelian dalam menilai kemampuan seseorang. Guna memudahkan pemilihan pemain dalam starting eleven maka dibangun sistem untuk membantu pelatih memilih posisi I deal bagi pemain dan memilih pemain secara objektif agar meningkatkan kualitas pemilihan pemain, baik dari penempatan posisi ideal pemain maupun pemilihan pemain sebagai starting. Sistem ini akan menerima input berupa nilai atribut kemampuan dan kondisi pemain yang akan diproses untuk menghasilkan output berupa rekomendasi pemain untuk dijadikan starting eleven. Dalam proses menentukan pemain, nilai atribut kemampuan pemain dilakukan proses Profile Matching (PM) untuk menentukan posisi ideal bagi pemain, dari tiap kelompok posisi dilakukan proses identifikasi menggunakan Naïve Bayes (NB) untuk menentukan pemain yang cocok untuk dijadikan starting eleven. Pengujian rekomendasi posisi dilakukan dengan membandingkan posisi asli pemain dengan posisi hasil rekomendasi dengan hasil akurasi sebesar 65%, sedangkan pengujian pemilihan starting eleven dilakukan menggunakan game Football Manager dengan melakukan pertandingan dengan pemilihan pemain secara default dan pemilihan pemain hasil rekomendasi masing-masing sebanyak sepuluh kali melawan tim dengan komposisi pemain yang sama, hasil dari pertandingan tersebut dihitung selisih (%) dari rata-rata rating pemain. Hasil yang diberikan setelah digunakan perekomendasian pemilihan pemain kenaikan rata-rata rating tim hanya naik sebesar 0.98%.
Abstract - The selection of starting eleven players and team formations with the correct composition of players in soccer is important to improve the performance of a team. Coaches sometimes choose not starting players objectively, because it takes expertise and foresight in assessing one's abilities. In order to facilitate the selection of players in the starting eleven, a system was built to help the coach choose the ideal position for the players and choose players objectively to improve the quality of player selection, both from placing the player's ideal position and selecting players as starting. This system will receive input in the form of the ability and condition attribute values of the player which will be processed to produce output in the form of a player's recommendation to become the starting eleven. In the process of determining the players, the value of the attributes of the player's ability is carried out the Profile Matching (PM) process to determine the ideal position for the players, from each group of positions the identification process is done using Naïve Bayes (NB) to determine the suitable players to be the starting eleven. Position recommendation testing is done by comparing the original position of the player with the position of the recommended results with an accuracy of 65%, while testing the selection of the starting eleven is carried out using the game Football Manager by playing matches by selecting players by default and selecting the results of the recommendation players ten times each against the team with the same player composition, the result of the match is calculated as a difference (%) from the average player rating. The results given after using the player selection recommendation increase the team's average rating to only increase by 0.98%.
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Lindholm, Oliver, Erik Niklasson, John Lind, Daniele A. Cardinale, and Tommy R. Lundberg. "A pilot study on bio-banding in male youth ice hockey: Players’ perceptions and coaches’ selection preferences." PLOS ONE 19, no. 8 (August 12, 2024): e0308676. http://dx.doi.org/10.1371/journal.pone.0308676.
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Classifying athletes based on estimates of biological maturation (i.e., bio-banding) as a supplement to traditional age grouping has been shown to be a potential tool for enriching player development in team sports; however, bio-banding has not yet been evaluated in ice hockey. The primary aim was to investigate player experiences and coaches’ selection preferences in bio-banding versus age-banding in a group of 12-13-year-old (early growth spurt) male elite players (n = 69). We also examined the relationship between somatic maturity, expressed as a % predicted adult height (%PAH), and fitness performance. Bio-banding was assessed using a questionnaire and 29 coaches selected their top players in each game based on age or bio-bands. %PAH correlated with grip strength (r = .57, p>0.001) and jumping power (r = .63, p<0.001), but not with vertical jump height, sprint time or endurance. Players who played against more mature players in bio-bands than in age groups experienced higher demands, while players who played against less mature players were able to utilize their skills to a greater extent. Coaches generally favored later-than-average maturing players who performed better on performance tests and chronologically older players in bio-banding. We conclude that bio-banding in youth ice hockey has some promising effects and warrants further evaluation.
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Wardana, Ari Kusuma, and Andri Arif Kustiawan. "Optimization of U-23 futsal player selection through a simple additive weighting approach." Fizjoterapia Polska 24, no. 4 (October 31, 2024): 407–11. http://dx.doi.org/10.56984/8zg01a8d6e8.
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Futsal playing skills are the main support in successfully achieving the goals of the game. There are several underlying techniques that every player needs to master, including passing, dribbling, controlling, chipping and shooting. This study aims to optimize the selection process for the best futsal players using the Simple Additive Weighting (SAW) method. The SAW method was chosen because of its ability to combine various selection criteria into one composite score, which makes decision-making easier. This research involves analyzing the needs of a futsal group to determine the relevant criteria and weights in selecting a group of players, such as passing, control, dribbling, chipping, and shooting. These indicators provide a more comprehensive picture of the capabilities and potential of the player group. Potential futsal group data are collected and processed using the SAW method with a weighted sum of the performance ratings for each alternative from all attributes. The SAW method requires a matrix normalization process on a scale that can be compared with all existing alternative ratings to produce objective and transparent ratings for the player groups. Based on the results of calculations using the SAW method, the assessment results for the prospective group of futsal players were obtained based on the specified criteria and weights. The highest score was achieved by Banyumas 1 with a score of 0.85. The research results show that the application of the SAW method in the selection process for futsal players increases the efficiency and accuracy of selecting new players. By using this approach, Porprov can more easily identify the best candidates to meet their needs.
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Yu, Kristen K., Matthew Guzdial, and Nathan R. Sturtevant. "Evaluating the Effects of AI Directors for Quest Selection." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 20, no. 1 (November 15, 2024): 245–52. http://dx.doi.org/10.1609/aiide.v20i1.31885.
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Modern commercial games are designed for mass appeal, not for individual players, but there is a unique opportunity in video games to better fit the individual through adapting elements in games. In this paper, we focus on AI Directors, systems which can dynamically modify a game, that attempt to personalize the player experience to a player's preference. AI Directors have in the past provided inconclusive results, so their effect on player experience is currently unknown. In this paper, we take three AI Directors and directly compare them in a human subject study to test their effectiveness on quest selection. Our results show that a non-random AI Director provides a better player experience than a random AI Director.
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Towlson, Christopher, Ed Cope, John L. Perry, David Court, and Nick Levett. "Practitioners’ multi-disciplinary perspectives of soccer talent according to phase of development and playing position." International Journal of Sports Science & Coaching 14, no. 4 (May 2019): 528–40. http://dx.doi.org/10.1177/1747954119845061.
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The study aimed to establish the perceived importance that academy soccer practitioners placed on technical/tactical, physical, psycho-social player attributes during player selection and explore whether perceptions change according to Elite Player Performance Plan phase. Seventy academy practitioners working within Elite Player Performance Plan programs (Category 1: n = 29; Category 2: n = 13 and Category 3: n = 28) completed an online survey. Psychological factors were rated significantly ( p ≤ 0.01) higher than sociological, technical/tactical, and physical factors, with recruitment staff specifically valuing psychological factors significantly ( p ≤ 0.01) more than medical staff. Youth Development phase practitioners valued sociological factors significantly ( p < 0.05) more than in the Foundation phase, which was also true for physical factors. Practitioners indicated significant positional differences for most physical and technical/tactical attributes. There was no playing position effect for relative age effect or maturity. Between playing position variance of outfield players for most technical and physical attributes increased according to advancing Elite Player Performance Plan phase. Attitudes to holistic talent identification criteria likely change according to practitioner role. Therefore, this study provides evidence to suggest that Elite Player Performance Plan practitioners place less perceived importance on enhanced maturity status and relative age of players but does indicate an enhancing and significant positional preference for physical and technical/tactical attributes. Suggesting that practitioners are less likely to (de)select players based on transient, maturity-related attributes and instead place greater emphasis on specialist physical/technical position-specific attributes as players navigate the Elite Player Performance Plan pathway towards professional status.
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Megha Chakole. "Optimal Strategy Formulation for Tic-Tac-Toe Using Minimax Algorithm for Interactive Gaming." Communications on Applied Nonlinear Analysis 31, no. 2s (June 1, 2024): 485–95. http://dx.doi.org/10.52783/cana.v31.662.
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Introduction: This research presents a Python implementation of the classic game Tic Tac Toe utilizing the Tkinter library for the graphical user interface (GUI). The code offers a comprehensive framework for creating an interactive gaming experience, featuring both single-player and multiplayer modes. Key functionalities include mode selection, game board initialization, player moves, win and draw condition checks, and game restart options. The graphical interface provides a visually appealing environment for players to engage with the game, facilitating intuitive interaction through buttons and labels. Notably, the single-player mode incorporates a basic AI component powered by the minimax algorithm, offering players the opportunity to challenge themselves against a computer opponent. Objectives: The main objectives include developing a comprehensive framework for Tic-Tac-Toe, encompassing essential functionalities such as mode selection, initializing the game board, managing player moves, conducting win/draw condition checks, and offering game restart options. Methods: The implementation employs Tkinter to create a user-friendly GUI featuring interactive buttons and visual elements. Game logic is meticulously implemented to regulate player turns, validate moves, and assess win/draw conditions. Additionally, the single-player mode integrates a basic AI component driven by the minimax algorithm for a challenging gaming experience. Results: The resulting implementation boasts a visually appealing interface, complete with dedicated mode selection buttons, interactive game board buttons, thorough win/draw condition checks across rows, columns, and diagonals, and a convenient restart button. The single-player mode successfully emulates human-like gameplay through the AI component. Conclusions: This implementation's simplicity and clarity render it an invaluable resource for beginners delving into GUI development and game programming with Python. Furthermore, the integration of AI functionality caters to advanced users keen on exploring algorithmic game strategies. Ultimately, this paper offers a valuable foundation for learning and comprehending the fundamentals of game development using Python and Tkinter.
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Wang, Yuxuan. "NBA Player Salary Projections Based on Gradient Boost in 2022-23 Season." Transactions on Computer Science and Intelligent Systems Research 5 (August 12, 2024): 236–41. http://dx.doi.org/10.62051/ejy6xc14.
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The National Basketball Association (NBA) game has a high international profile, and the level of NBA players and salary projections can help clubs make the right decisions. This study introduces the research topic of predicting NBA salaries for the 2022-23 season. The proposed method utilizes a gradient boosting algorithm to analyze player performance metrics and historical salary data. The specific process includes data preprocessing, feature selection, model selection and evaluation. The proposed method is evaluated through a large number of experiments, and the gradient boosting model outperforms other methods in terms of Mean-Square Error (MSE) and R-squared values. This study demonstrates the potential of machine learning in predicting the salary of NBA players. The results showed that the gradient boosting model achieved an R-squared value of 0.74, indicating that the model is proficient in capturing the relationship between player performance metrics and salary. Clubs can use the model to rationalize their overall layout by capturing the relationship between player performance metrics and salary.
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Zhang, Hong-Bin, and Hong Wang. "Group preferential selection promotes cooperation in spatial public goods game." International Journal of Modern Physics C 25, no. 11 (October 15, 2014): 1450062. http://dx.doi.org/10.1142/s0129183114500624.
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We study the evolution of cooperation in public goods games on the square lattice, focusing on the co-player learning mechanism based on the preferential selection that are brought about by wealthy information of groups where participants collect and search for potential imitators from those groups. We find that co-player learning mechanism based on the choice of weighted group can lead to the promotion of public cooperation by means of the information of wealthy groups that is obtained by participants, and after that the partial choice of public goods groups is enhanced with the tunable preferential parameter. Our results highlight that the learning interactions is not solely confined to the restricted connection among players, but co-players of wealthy groups have the opportunity to be as a role model in the promotion of cooperative evolution. Moreover, we also find the size of learning affects the choice of distant players, cooperators (defectors) having more paths to exploit the phalanx of opponents to survive when the value of preferential parameter is small. Besides, the extinction thresholds of cooperators and defectors for different values of noise are also investigated.
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Touma, Keisuke, Satoshi Endo, Naruaki Toma, Yuhei Akamine, and andKoji Yamada. "An Influence of Player’s Ballot-Weight Changing in Consultation Algorithm." Journal of Advanced Computational Intelligence and Intelligent Informatics 17, no. 5 (September 20, 2013): 707–14. http://dx.doi.org/10.20965/jaciii.2013.p0707.
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The validity of the consultation algorithm is shown in computer shogi. The consultation algorithm determines a move by votes of computer shogi players. In this research, we discuss a method that changes player vote weights during a game. To change player vote weights, we use the selection history of the move and the evaluation function value. Experimental results suggests the validity of our proposed method.
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Saikia, Hemanta, Dibyojyoti Bhattacharjee, and Unni Krishnan Radhakrishnan. "A New Model for Player Selection in Cricket." International Journal of Performance Analysis in Sport 16, no. 1 (April 2016): 373–88. http://dx.doi.org/10.1080/24748668.2016.11868893.
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Beyer, Kyle S., David H. Fukuda, Michael J. Redd, Jeffrey R. Stout, and Jay R. Hoffman. "Player Selection Bias in National Football League Draftees." Journal of Strength and Conditioning Research 30, no. 11 (November 2016): 2965–71. http://dx.doi.org/10.1519/jsc.0000000000001426.
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唐, 涛. "Selection of Young Basketball Player in International Perspective." Advances in Physical Sciences 06, no. 01 (2018): 8–12. http://dx.doi.org/10.12677/aps.2018.61002.
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Hernandez-Simal, Lander, Julio Calleja-González, Alberto Lorenzo Calvo, and Maite Aurrekoetxea-Casaus. "Birthplace and Birthdate Effect during Talent Process in Professional Soccer Academy Players." Applied Sciences 14, no. 11 (May 22, 2024): 4396. http://dx.doi.org/10.3390/app14114396.
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The main objective of this study was to detect, from among a set of innate, acquired, and contextual factors, those variables that are ascribed to players ultimately promoted to the professional team of a Spanish league club during the earlier selection and development phases. The data were presented in frequencies and correlations and by means of a classificatory cluster model. The variables used for the analyses included date of birth, birthplace density, player position, laterality, academy entry stage, international participation, and debutant status. These variables were related to the talent selection and promotion phases (i.e., academy entry stage and player debut). A dataset of information on 1411 players from the last 30 seasons of the Athletic Club de Bilbao (1993–2021) was used. Regarding the results, first, there was an over-representation of players with respect to their Q1 birth date and K5 density quintile in the selection phase; however, once players joined the academy, their chances of promotion (debut) fell for players in the Q4 birth date and K3 density quintiles. Second, there was a significant correlation between players’ debut and the stage of incorporation (p < 0.01; V = 0.46) and internationalisation (p < 0.01; V = 0.5). Finally, the birthplace density and laterality variables converged as classificatory features of the players.
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Wang, Qi, Yi Yang, Zhengren Li, Na Liu, and Xiaohang Zhang. "Research on the influence of balance patch on players' character preference." Internet Research 30, no. 3 (February 24, 2020): 995–1018. http://dx.doi.org/10.1108/intr-04-2019-0148.
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PurposeThe balance patch is an important but not well studied area to maintain game fairness and improve player entertainment. In this paper, we examine the effect of balance patch on player's character preference and further explore the moderating effect of psychological distance and character selection pattern.Design/methodology/approachIn study 1, a web crawler was used to get server-side data of 40, 974 multi-player online battle arena (MOBA) players through official application programming interfaces (APIs). A paired-T test and a stepwise regression were performed to verify the hypothesis. In study 2, a 2-patch type (buff vs nerf) × 2 psychological distance (near vs distant) × 2 character selection pattern (stable vs variable) between-subjects design was adopted to confirm the empirical conclusions through questionnaire survey design and further explored the mediating effect of patch adjustment perception.FindingsThe analyzed results showed that the buff patch led to an increase in players' character preference, while the nerf patch led to a decrease in players' character preference. Moreover, the main effect was mediated by patch adjustment perception. Furthermore, psychological distance and character selection pattern both moderated the relationship between balance patch and character preference changes. The character preference of the near psychological distance increased more significantly elicited by buff patches and decreased more significantly in an adverse situation. Similarly, players with variable selection pattern of characters were more sensitive to the stimuli, and the character preference of the variable group changed more significantly than that of the stable group caused by balance patch release.Originality/valueThis paper studies the influence of a patch on the balance of character strength on player preference, which expands the research on game balance and fairness. The present results contribute to the theoretical research on consumer behavior of psychological distance and character selection pattern elicited by balance patches. Meanwhile, the results indicate that psychological distance theory can apply to the study of the relationship between players and virtual characters.
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Pelloneová, Natalie. "Measuring the Technical Efficiency of Hockey Players: Empirical Evidence from Czech Hockey Competition." Studia sportiva 16, no. 2 (February 24, 2023): 229–48. http://dx.doi.org/10.5817/sts2022-2-23.
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Ice hockey is a very popular sport in the Czech Republic. Nowadays, hockey player efficiency analysis is a useful tool that helps sports managers with player selection, team composition and team performance evaluation. The literature offers only a limited number of scientific studies that deal with the evaluation of the efficiency of hockey players or clubs. The aim of this research is to use data envelopment analysis to help Czech hockey clubs, managers and coaches to evaluate the efficiency of their players. This research evaluates the technical efficiency of Czech hockey players using three data envelopment analysis models, ranks the best players based on their super-efficiency scores, and then tries to uncover the main sources of player inefficiency. The models are empirically applied to players playing in the Tipsport extraliga in the 2021/22 season. The evaluation used in this paper attempts to incorporate greater objectivity into decision making and thus may be an important step in developing a systematic methodology for evaluating hockey players.
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Mariano, Pedro, and Lu´ıs M. P. Correia. "Partner Selection Using Reputation Information in n-player Cooperative Games." Journal of Telecommunications and Information Technology, no. 4 (December 30, 2014): 53–60. http://dx.doi.org/10.26636/jtit.2014.4.1047.
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To study cooperation evolution in populations, it is common to use games to model the individuals interactions. When these games are n-player it might be difficult to assign defection responsibility to any particular individual. In this paper the authors present an agent based model where each agent maintains reputation information of other agents. This information is used for partner selection before each game. Any agent collects information from the successive games it plays and updates a private reputation estimate of its candidate partners. This approach is integrated with an approach of variable sized population where agents are born, interact, reproduce and die, thus presenting a possibility of extinction. The results now obtained, for cooperation evolution in a population, show an improvement over previous models where partner selection did not use any reputation information. Populations are able to survive longer by selecting partners taking merely into account an estimate of others’ reputations.
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Brown, Tom, Robert Cook, Lewis A. Gough, Irfan Khawaja, Alexander B. T. McAuley, and Adam L. Kelly. "Exploring the Multidimensional Characteristics of Selected and Non-Selected White British and British South Asian Youth Cricketers: An Exploratory Machine Learning Approach." Youth 4, no. 2 (May 23, 2024): 718–34. http://dx.doi.org/10.3390/youth4020048.
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Selection into a County Age Group (CAG; under 10–18) programme is the first step for young aspiring cricketers on their journey to achieving professional status. Recognising that the British South Asian (BSA) community represents 30% of those who play recreational cricket compared to less than 5% of those who are selected to play at the professional level in England and Wales, it is important to better understand the characteristics of selected and non-selected players based on ethnicity to identify potential sociocultural differences during selection. Thus, the purpose of this study was to investigate the multidimensional factors that differentiated between selected and non-selected adolescent male cricketers as well as between White British (WB) and BSA selected players into a CAG programme. A total of 82 male participants aged between 14 and 17 years were included (mean = 15.3 ± 1.1 years: selected n = 33 and non-selected n = 49: WB n = 34, BSA n = 44, Other n = 4). In total, 104 characteristics were measured over nine tests, which were subsequently placed into five overarching factors: (a) physiological and anthropometrical, (b) perceptual–cognitive expertise, (c) psychological, (d) participation history, and (e) socio-cultural influences. A Bayesian binomial regression was performed in rSTAN using a weak normal prior to highlight differentiators in selection as well as differences between WB and BSA selected players. The results highlighted that athleticism, wellbeing and cohesion, the number of older brothers, and being born in birth quarters two and three were positively correlated with player selection into a CAG. Conversely, increases in psychological scores, a greater number of younger brothers and older sisters, as well as antisocial behaviour resulted in a reduced chance of player selection. Finally, several developmental factors (i.e., athleticism, wellbeing and cohesion, psychological distress, and levels of anti-social behaviour) differed based on ethnicity. These exploratory findings serve as a useful opening to highlight there are important differences to consider based on selection and ethnicity in CAG cricket.
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Ali, S. Nageeb, Maximilian Mihm, Lucas Siga, and Chloe Tergiman. "Adverse and Advantageous Selection in the Laboratory." American Economic Review 111, no. 7 (July 1, 2021): 2152–78. http://dx.doi.org/10.1257/aer.20200304.
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We study two-player games where one-sided asymmetric information can lead to either adverse or advantageous selection. We contrast behavior in these games with settings where both players are uninformed. We find stark differences, suggesting that subjects do account for endogenous selection effects. Removing strategic uncertainty increases the fraction of subjects who account for selection. Subjects respond more to adverse than advantageous selection. Using additional treatments where we vary payoff feedback, we connect this difference to learning. We also observe a significant fraction of subjects who appear to understand selection effects but do not apply that knowledge. (JEL C92, D82, D91)
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DE MARCO, GIUSEPPE, and JACQUELINE MORGAN. "FRIENDLINESS AND RECIPROCITY IN EQUILIBRIUM SELECTION." International Game Theory Review 10, no. 01 (March 2008): 53–72. http://dx.doi.org/10.1142/s0219198908001777.
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A concept of altruistic behavior (called friendly behavior) has been defined and used for equilibrium selection in some bargaining models in Rusinowska (2002), "Refinements of Nash Equilibria in view of Jealous and Friendly Behavior of Players", International Game Theory Review, 4, 281–299. In this paper, the situation in which every player has friendly behavior is incorporated into the general context of normal form games by introducing a new refinement concept (called friendliness equilibrium). Existence, properties and connections with another refinement concept, introduced by the authors in a previous paper and which captures an idea of reciprocal altruism, are investigated. Examples and counterexamples are given illustrating concepts, results and links with other classical refinement concepts.
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Heneghan, Jack F., and Michael C. Herron. "Relative age effects in American professional football." Journal of Quantitative Analysis in Sports 15, no. 3 (August 27, 2019): 185–202. http://dx.doi.org/10.1515/jqas-2018-0030.
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Abstract We test for the existence of relative age effects in professional American football. In a sample of 18,898 football players born on or after 1940, there is an excess of January and February births – consistent with a relative age effect associated with calendar year – as well as a slight increase in September births – consistent with the fact that some football players we analyze attended high school in states with fall school cutoff dates. We consider the possibility that relative age effects may affect skilled football positions more than positions relying heavily on player weight, and we find suggestive evidence of this. Lastly, and contrary to what has recently been shown in professional hockey, we find no evidence that misguided preferences for relatively older players lead to selection-based inefficiencies in football player drafting. Our results have implications for evaluating potential football players and speak broadly to the role of physiological factors beyond player control on athletic success.
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Malikov, Davronbek, and Jaeho Kim. "Beyond xG: A Dual Prediction Model for Analyzing Player Performance Through Expected and Actual Goals in European Soccer Leagues." Applied Sciences 14, no. 22 (November 12, 2024): 10390. http://dx.doi.org/10.3390/app142210390.
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Soccer is evolving into a science rather than just a sport, driven by intense competition between professional teams. This transformation requires efforts beyond physical training, including strategic planning, data analysis, and advanced metrics. Coaches and teams increasingly use sophisticated methods and data-driven insights to enhance decision-making. Analyzing team performance is crucial to prepare players and coaches, enabling targeted training and strategic adjustments. Expected goals (xG) analysis plays a key role in assessing team and individual player performance, providing nuanced insights into on-field actions and opportunities. This approach allows coaches to optimize tactics and lineup choices beyond traditional scorelines. However, relying solely on xG might not provide a full picture of player performance, as a higher xG does not always translate into more goals due to the intricacies and variabilities of in-game situations. This paper seeks to refine performance assessments by incorporating predictions for both expected goals (xG) and actual goals (aG). Using this new model, we consider a wider variety of factors to provide a more comprehensive evaluation of players and teams. Another major focus of our study is to present a method for selecting and categorizing players based on their predicted xG and aG performance. Additionally, this paper discusses expected goals and actual goals for each individual game; consequently, we use expected goals per game (xGg) and actual goals per game (aGg) to reflect them. Moreover, we employ regression machine learning models, particularly ridge regression, which demonstrates strong performance in forecasting xGg and aGg, outperforming other models in our comparative assessment. Ridge regression’s ability to handle overlapping and correlated variables makes it an ideal choice for our analysis. This approach improves prediction accuracy and provides actionable insights for coaches and analysts to optimize team performance. By using constructed features from various methods in the dataset, we improve our model’s performance by as much as 12%. These features offer a more detailed understanding of player performance in specific leagues and roles, improving the model’s accuracy from 83% to nearly 95%, as indicated by the R-squared metric. Furthermore, our research introduces a player selection methodology based on their predicted xG and aG, as determined by our proposed model. According to our model’s classification, we categorize top players into two groups: efficient scorers and consistent performers. These precise forecasts can guide strategic decisions, player selection, and training approaches, ultimately enhancing team performance and success.
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EHTAMO, HARRI, SIMO HELIÖVAARA, TIMO KORHONEN, and SIMO HOSTIKKA. "GAME THEORETIC BEST-RESPONSE DYNAMICS FOR EVACUEES' EXIT SELECTION." Advances in Complex Systems 13, no. 01 (February 2010): 113–34. http://dx.doi.org/10.1142/s021952591000244x.
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We present a model for evacuees' exit selection in emergency evacuations. The model is based on the game theoretic concept of best-response dynamics, where each player updates his strategy periodically by reacting optimally to other players' strategies. A fixed point of the system of all players' best-response functions defines a Nash equilibrium (NE) of the game. In the model, the players are the evacuees and the strategies are the possible target exits. We present a mathematical formulation for the model and show that the game has a NE with pure strategies. We also analyze different iterative methods for finding the NE and derive an upper bound for the number of iterations needed to find the equilibrium. Numerical simulations are used to analyze the properties of the model.
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Butler, David, Robert Butler, Justin Doran, and Sean O’Connor. "Explaining international footballer selection through Poisson modelling." Journal of Economic Studies 45, no. 2 (May 14, 2018): 296–306. http://dx.doi.org/10.1108/jes-10-2016-0194.
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Purpose Growing evidence suggests regional economic factors impact on individual outcomes, such as life expectancy and well-being. The purpose of this paper is to investigate the impact that player-specific and regional differences have on the number of senior international appearances football players accumulate over the course of their careers, for six UEFA member countries, from 1993 to 2014. Design/methodology/approach The research employs a Poisson regression model to analyse the impact of individual and regional factors on the number of senior international caps a footballer receives over the course of their career. Findings The results indicate that both individual and regional variables can explain the number of caps a player receives over the course of their career. The authors find that an individual’s career length positively influences the number of international caps accrued. Players born in wealthier and more populous regions accumulate a greater number of international appearances. Distance from the capital has no effect, however, the number of youth academies in the player’s region of birth has a significant positive effect. Research limitations/implications The analysis is limited to regional variations within economically developed states. It would be interesting to test whether the correlation between relative regional development and international success exists in less developed countries. The authors only address mens international football in this study and cannot comment on the generality of the findings across genders or sports. Practical implications The results can provide insights for local football authorities and policy makers concerned with regional characteristics and those interested in the development of elite talent. Originality/value This is the first study to analyse a pan-European data set, using an increasingly adopted econometric method to understanding regional economic development – Poisson modelling.
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Onodera, Keisuke, and Masaki Takeda. "Hand Selection in Dribbling Phases: An Analysis of Non-Dominant Hand Usage and Dribble Change in Basketball." Sports 11, no. 11 (November 14, 2023): 226. http://dx.doi.org/10.3390/sports11110226.
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This study investigates the influence of different dribbling phases on hand selection among basketball players across various categories. A total of 33 guard players, including 11 from high school, college, and NBA teams each, were observed. Video data analysis was utilized to determine the frequency of players using their dominant hands (DHs) and non-dominant hands (NDHs) during in-game dribbling phases. The dribbling phases were classified into three categories: First (the initiation of the dribble), Middle (during the dribble but not in First and Last), and Last (the completion of the dribble). Percentage, means, and standard deviations were computed for each category within the First, Middle, and Last measurements. A two-factor analysis of variance (ANOVA) was conducted, considering player category and dribbling phase as factors. The ANOVA revealed significant main effects of player category (p < 0.01) and dribbling phase (p < 0.01). Post hoc multiple comparisons using Holm’s method indicated that, in the First phase, players exhibited a 6.5% higher preference for using their NDHs (43.4 ± 11.9%) compared to the Middle phase (36.9 ± 13.9%) (p < 0.05). Similarly, in the Last phase, players displayed a 5.3% greater inclination towards using their NDHs (42.2 ± 11.7%) compared to the Middle phase (p < 0.05). These findings provide quantitative evidence that the specific dribbling phase influences hand selection during gameplay. The implications of these results are significant for basketball coaches, as they can design targeted training programs and drills that simulate game scenarios and encourage NDH usage. By understanding the factors influencing hand choice, players can enhance their versatility and adaptability on the court. Furthermore, these findings contribute to player performance, skill development, and strategic decision making in dribbling phases.
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Ahmed, Afzal, Mohammad Tariq Iqbal, and Mohsin Jamil. "A Comparative Analysis of Power Consumption While Using Open-Source and Proprietary Media Players." European Journal of Electrical Engineering and Computer Science 8, no. 5 (September 18, 2024): 1–5. http://dx.doi.org/10.24018/ejece.2024.8.5.649.
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This study investigates the power consumption of various media player software applications, comparing open-source and proprietary options. The experiment measured the average power consumption of CPU, GPU, and memory usage of media players such as Kodi, MPC, MPV, SMP, VLC, Windows Media Player, ACG, ALLPlayer, GOM, KMPlayer, LAPlayer, POTPlayer, and RealPlayer while playing 4K video. The results revealed that proprietary media players generally consume less power compared to their open-source counterparts. Statistical analysis, including descriptive statistics and independent samples t-tests, confirmed these findings. Long-term power consumption projections indicated substantial energy savings with more efficient media players. These findings underscore the importance of considering energy efficiency in software selection for sustainable computing.
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Ross, Travis L., and Andrew J. Weaver. "Shall We Play a Game?" Journal of Media Psychology 24, no. 3 (January 2012): 102–12. http://dx.doi.org/10.1027/1864-1105/a000068.
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Over the course of the last decade, many games have shifted from single player to shared social experiences. Yet, most research examining antisocial behavior has focused on coded content and ignored the influence of other players. This paper examines the influence of the behavior of another player on strategy selection, and the formation of expectations, enjoyment, frustration, and state aggression. It reports an experiment examining antisocial griefing behavior in the multiplayer game Neverwinter Nights, where observational learning, revenge seeking, and expectation formation are tested. The results show that (a) the first encounter that a player has in a game shapes both behavior and expectations; (b) environments that facilitate expectation of cooperation will lead to retaliation against players who grief, whereas environments that facilitate expectations of griefing will increase the frequency of griefing, but not the frequency of retaliation against players who grief; and (c) griefing decreases enjoyment, increases frustration, and increases state aggression for the recipient.
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Grigorescu, Ilie, and Yi-Ching Yao. "Maximizing the variance of the time to ruin in a multiplayer game with selection." Advances in Applied Probability 48, no. 2 (June 2016): 610–30. http://dx.doi.org/10.1017/apr.2016.17.
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Abstract We consider a game with K ≥ 2 players, each having an integer-valued fortune. On each round, a pair (i,j) among the players with nonzero fortunes is chosen to play and the winner is decided by flipping a fair coin (independently of the process up to that time). The winner then receives a unit from the loser. All other players' fortunes remain the same. (Once a player's fortune reaches 0, this player is out of the game.) The game continues until only one player wins all. The choices of pairs represent the control present in the problem. While it is known that the expected time to ruin (i.e. expected duration of the game) is independent of the choices of pairs (i,j) (the strategies), our objective is to find a strategy which maximizes the variance of the time to ruin. We show that the maximum variance is uniquely attained by the (optimal) strategy, which always selects a pair of players who have currently the largest fortunes. An explicit formula for the maximum value function is derived. By constructing a simple martingale, we also provide a short proof of a result of Ross (2009) that the expected time to ruin is independent of the strategies. A brief discussion of the (open) problem of minimizing the variance of the time to ruin is given.
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Tavana, Madjid, Farshad Azizi, Farzad Azizi, and Majid Behzadian. "A fuzzy inference system with application to player selection and team formation in multi-player sports." Sport Management Review 16, no. 1 (February 2013): 97–110. http://dx.doi.org/10.1016/j.smr.2012.06.002.
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Vijayabalaji, Srinivasan, and Parthasarathy Balaji. "Best’11 strategy in cricket using MCDM, rough matrix and assignment model." Journal of Intelligent & Fuzzy Systems 39, no. 5 (November 19, 2020): 7431–47. http://dx.doi.org/10.3233/jifs-200784.
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In 1982, Pawlak set up a fresh approach to deal with uncertainties namely rough set theory, Multiple-Criteria Decision Making (MCDM) first traced by Benjamin Franklin in 17th century. Several researchers did significant contribution to MCDM thereafter. An assignment problem involves what happens to the effective function when each of a number of sources is associated with the same number of destinations. Using MCDM, Rough matrices and Assignment model we are inducing an idea to pick Best’11 in all three formats (Test, One Day Internationals (ODI), Twenty20 International matches (T20I)) in the game of cricket with players from two nationals. Using the existing data, we are providing best batting position for any player to maximize team’s run. In addition, based on the preprocessing of informations, we are bringing some new indices to pick Indian squad for the 2019 World Cup cricket held in England from May 2019 to July 2019. After making a selection from our framework, we will compare the list of selected players by Board of Cricket Control Board in India (BCCI) and giveaway the percentage of similarity between the our selection against BCCI’s selection. We pick 11 players after selecting 15 players from 24 players to formulate the assignment model and offer the best batting order to optimize team’s run.
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Rubajczyk, Krystian, and Andrzej Rokita. "The Relative Age Effect in Poland's Elite Youth Soccer Players." Journal of Human Kinetics 64, no. 1 (October 15, 2018): 265–73. http://dx.doi.org/10.1515/hukin-2017-0200.
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Abstract The relative age effect (RAE) is related to discrimination against youth athletes born in the last quarter of the calendar year. The current study presents research on the RAE in elite youth soccer players in Poland. Players in the Central Junior League (CLJ) finals represent 0.59% of the 25,756 players under 20 years old (U20). This study analyzed the post-game protocols of the CLJ knockout stage from the 2013/2014 and 2014/2015 seasons as well as the U17-U21 teams during 2015, including only players who played on the field for at least one minute (n = 395). The results revealed the existence of RAE in the examined groups ( CLJ 2013/2014, χ23 = 15.441, p < 0.01, CLJ 2014/2015, χ23 = 20.891, p < 0.001 U17-U21, χ23 = 25.110, p < 0.001). In addition, the results differed by monthly birth distribution in the Polish population (PP) between 1995 and 1999. This study is the first to examine the RAE in youth soccer in Poland. The occurrence of the RAE with regard to the most promising youth and national team players suggests that a similar effect exists among younger age categories. To reduce the RAE related to identifying soccer talent, tools should be implemented to optimize the player-selection process, such as those that consider the biological development of a player.
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Shree, Dr Tanu. "City Of Dreams: An Open-World Games." International Scientific Journal of Engineering and Management 03, no. 04 (April 23, 2024): 1–9. http://dx.doi.org/10.55041/isjem01622.
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In recent years, the gaming industry has witnessed a remarkable evolution, with open-world games emerging as a dominant genre that captivates players with expansive virtual worlds, intricate narratives, and immersive gameplay experiences. Among these innovative titles, "City of Dreams" stands out as a pinnacle of open-world game design, offering players a richly detailed urban landscape to explore, inhabit, and shape according to their desires. This research paper provides a comprehensive analysis of "City of Dreams," examining its technical development, player engagement dynamics, societal impact, and broader implications within the gaming industry and digital culture. The technical development of "City of Dreams" is explored in detail, encompassing various aspects such as game engine selection, character animation, environment design, and physics implementation. By delving into the technical intricacies of game development, this research sheds light on the creative processes and technological innovations that underpin the creation of immersive gaming experiences. Furthermore, the paper investigates the player engagement dynamics of "City of Dreams," exploring how its diverse gameplay mechanics, immersive world design, and compelling narrative drive player engagement and immersion. Through an analysis of player behavior, feedback, and interaction patterns, insights are gained into the factors that contribute to the game's success and longevity. Keywords—open-world games, player experience, player behavior, game development, immersive environments, Non-Playable Characters (NPCs).
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Mohanty, B. K., and Mahima Gupta. "Product Selection in E-Commerce Under Fuzzy Environment: A MADM Game Theoretic Model." International Game Theory Review 17, no. 01 (March 2015): 1540008. http://dx.doi.org/10.1142/s0219198915400083.
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This paper introduces a methodology based on fuzzy game theory to determine the buyer's priority of the attributes and select a product in the e-business system. The game theory model developed in our paper considers the prioritization of attributes as strategies for the player (player 1) in one side and selection of the products for the opponent player (player 2). The fuzzy probabilities of the strategies in the game theory are obtained by using the concepts of similarities between the fuzzy numbers. The e-business system devises strategies for the player 1 by attaching appropriate priority levels to product attributes for maximum gain. On the other hand the opponent player 2 select the products as the strategies accordingly. The payoffs obtained in the game theory model as fuzzy numbers are subsequently converted to their equivalent probabilistic mean intervals. This process leads to transform the game theory model into a linear programming problem (LPP) with interval coefficients. The solution to LPP gives us the optimal strategies. These probability of strategies are considered as attributes' weights to determine ranking of the products in e-business system. The methodology is illustrated with the help of a numerical example.
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Fahad Alfarraj, Jaquelin Bousie, Jeremy Witchalls, and Phil Newman. "The Relationship Between Pre-Season Functional Screening Test Performance and Coaches' Perception of Soccer Performance in Adult Male Players." International Journal of Physical Education & Sports Sciences 19, no. 1 (August 31, 2024): 15–21. http://dx.doi.org/10.29070/4pwr3v85.
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Coaches typically play a central role in team performance and player selection, but their assessments can also be valuable for the medical team in injury prevention and recovery. This research aimed to evaluate whether soccer coaches' evaluations of their players' physical abilities align with performance testing during pre-season. The players were rated subjectively by two coaches independently, focusing on various aspects such as technical, tactical, physical, and psychological skills. Ratings were given on a scale of 0 to 100, based on the coaches' perceptions of top players in those positions globally. The mean score of the coaches' ratings was used for each player. The study used the Intra-class Correlation Coefficient (ICC) to measure the reliability of inter-coach ratings, while players' scores on common functional tests were assessed independently by the medical staff. Decision tree analysis was conducted to determine the association between coaches' ratings and functional testing scores, as well as to identify cut-off values for differentiating higher and lower coach ratings. Sixty-three male professional soccer players from the Saudi Professional League participated voluntarily. The ICC values ranged from 0.73 to 0.79, indicating good to excellent agreement between coaches. The analysis showed that functional performance scores and coach ratings agreed in 86% of cases, with 88% precision and 91% recall. The algorithm correctly identified 88.4% of players rated high performers by coaches and 80% of lower-rated players. Cut-off scores were determined based on specific functional test results. For instance, players scoring above certain thresholds on tests like the Y-balance test and triple medial hop were more likely to receive higher coach ratings. The study revealed a solid alignment between coaches' subjective evaluations of physical abilities and objectively measured functional performance tests. These results hold the potential for aiding in player selection, establishing preparation standards, and facilitating players' return to play after injury.
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Gál-Pottyondy, Anna, Bálint Petró, András Czétényi, János Négyesi, Ryoichi Nagatomi, and Rita M. Kiss. "Field Testing Protocols for Talent Identification and Development in Basketball—A Systematic Review." Applied Sciences 11, no. 10 (May 11, 2021): 4340. http://dx.doi.org/10.3390/app11104340.
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Basketball is one of the most popular team sports in the world. A wide variety of athletic skills can be valuable indicators of a talented player. Testing these skills help trainers and scouts to make the best decisions during both youth and adult player selection of different competitive levels and field positions. However, scientific data regarding the association between field tests results and match statistics is sparse. We conducted a systematic review to logically summarize the physical field tests of athletic abilities and anthropometric measures used in basketball in different player positions at different levels, and to determine whether test results may correlate with match statistics. A comprehensive electronic literature search was performed via three electronic databases (PubMed, GoogleScholar, SportDiscus). The CASP checklist was used for checking the quality of reporting for all included articles. Based on 39 studies, it could be supported that the agility, speed and jumping test values seem to be crucial measures for basketball players. Anthropometry appeared to be the strongest discriminative factor between basketball positions, therefore, these values need to be significantly considered during selection. Moreover, the maturity status is also an important influencing factor for U-18 teams. In general, we found that successful players can be identified by their nonplanned agility and reactive power, considering that these factors affect match outcomes the most at the same competitive level.
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Xin, Ling, and Yan-wei Xu. "Application of the Multiple Regression Method in Football Tactical Analysis." Wireless Communications and Mobile Computing 2022 (April 20, 2022): 1–10. http://dx.doi.org/10.1155/2022/3787086.
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Aiming at the unreasonable problem of current football tactical analysis, this paper studies the application method of the multiple regression method in football tactical analysis. Build a football tactical rehearsal model, optimize player information and tactical analysis management functions, and analyze football player status. Using the multiple regression method to choose the appropriate position of the players, make the football attack and defense plan. At the same time, the application of the multiple regression method to the analysis of football tactics can better select the optimal tactical plan, to ensure the rationality of football tactical selection.
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Iwazaki, Hikaru, Takenori Ujigawa, and Shao-Chin Sung. "On Network Structure of Stable Strategies in Local Connection Games." Journal of Advanced Computational Intelligence and Intelligent Informatics 16, no. 3 (May 20, 2012): 420–24. http://dx.doi.org/10.20965/jaciii.2012.p0420.
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We are concerned with a model of network formation games, called local connection games, in which networks are formed based on players’ strategies. Each player may decide to build links to other players by paying a certain cost fixed in advance, and a strategy of each player is a selection of links to be built. Each player determines and/or changes her or his strategy depending on cost for building links and cost of contacting all other players on the entire network, which influence the structure of the entire network. One of the main interests on the study of local connection games is to characterize all the stable strategy profiles. In this paper, we analyze the influences on network structure of stable strategy profiles caused by the cost for building links. For the unit cost case, we provide, in terms of network structure, a necessary and sufficient condition for strategy profiles to be stable. Moreover, we investigate the relationship between integral cost cases and non-integral cost cases as well.
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Conforti, Christian M., Ryan L. Crotin, and Jordan Oseguera. "Major League Draft WARs: An Analysis of Wins Above Replacement in Player Selection." Journal of Sports Analytics 8, no. 1 (March 11, 2022): 77–84. http://dx.doi.org/10.3233/jsa-200586.
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Major League Baseball (MLB) teams have 20 rounds to select players with projectable ability to compete at the MLB level. In this exploratory study, players were evaluated for differences in Wins Above Replacement (WAR) related to draft round, first round pick, educational designation, and by team. It was hypothesized WAR differences exist by round, pick number, educational designation and by team. From 2005–2015, 1,623 players were examined to determine population differences owed to draft selection. First round draftees had greater average career WAR compared to Rounds 2 to 20. Collectively, the first five picks had greater WAR versus picks grouped 16 through 30. High school (HS) draft picks were selected in earlier rounds versus collegiate athletes and HS hitters displayed more WAR in first round versus 4-year college pitchers. WAR outcomes in the first 15 picks offer more success with greater performance of HS hitters versus 4-year college pitchers. These trends may influence the current landscape of scouting and draft selection in the new draft format that has reduced player selection from 40 to 20 rounds.
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Gui, Yong Feng, and Xin Li. "The Research Overview on Pertinence between Badminton Players’ Athletics Standards and Psychological Diathesis." Advanced Materials Research 271-273 (July 2011): 756–59. http://dx.doi.org/10.4028/www.scientific.net/amr.271-273.756.
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In this research paper, the relationship between the athletics standard of a badminton player and his psychological diathesis would be discussed. The purpose of this research paper is to support the psychological selection of a badminton player theoretically. In this research paper, it analyzes 57 players’ spatial memory, movement memory, time reaction, attention distribution, attention concentration, intelligence, and personality through 16 different observation factors. Based on the observation and analysis, it could be concluded that a player’s intelligence and psychological ability are closely connected with partial variable and multiterm variable of attention. Also, a player’s intelligence and psychological ability are closely connected with his athletics level. In another word, if a badminton player has a higher intelligence, and better psychological diathesis, he may have a higher athletics standard.
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Rizzo, Terry L., Paul Bishop, and David Tobar. "Attitudes of Soccer Coaches Toward Youth Players with Mild Mental Retardation: A Pilot Study." Adapted Physical Activity Quarterly 14, no. 3 (July 1997): 238–51. http://dx.doi.org/10.1123/apaq.14.3.238.
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Attitudes and selected attributes of youth soccer coaches (N = 82, 18 women, 63 men, and one person who did not identify his/her gender) toward coaching a player with mild mental retardation (MMR) were assessed by Coaches’ Attitudes Toward Players With Disabilities (CAP-S) survey. Intereorrelations among 11 variables were reported. The highest were r = .72 between belief and attitude, and r = .57 between belief and intention. Results from a stepwise selection multiple regression procedure showed that as perceived soccer coaching competence increased, beliefs about coaching a player with MMR showed greater agreement. Results also indicated that, as perceived soccer coaching competence increased, attitudes and intention toward coaching a player with MMR improved. Perceived soccer coaching competence explained only a small amount of the variance for beliefs, attitudes, and intentions.
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G, Harshitha. "Performance Analysis of a Cricketer by Data Visualization." International Journal for Research in Applied Science and Engineering Technology 10, no. 1 (January 31, 2022): 1800–1807. http://dx.doi.org/10.22214/ijraset.2022.40176.
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Abstract: Indian Premier League is a very competitive tournament where team selection is a very tricky and tedious procedure. Analysis of sports data and Prediction of each player’s performance helps in filtering the best players. A novel method employing the techniques of Data Analytics and Data Visualization is used in this research paper to extract individual player performance from huge statistics and datasets. An application is created to bridge the space between selecting team, coaches, and team management and to give a better interpretation on player steadiness, scoring and further capabilities. In this paper, pandas library is used for data analysis and manipulation tool, Microsoft azure is used for performance prediction and HTML, CSS, flask for the front-end application. Additionally, various machine learning algorithms are applied on the same data to find the best fit. The proposed application can be beneficial for team managements and decision making Keywords: Indian Premier League, Data analytics, Data Visualization, Prediction of player’s Performance, Microsoft Azure
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Wang, Xiao-yuan, Ya-qi Liu, Fang Wang, Zhi-guo Liu, Hai-xia Zhao, and Jun-Feng Xin. "Driver’s lane selection model based on multi-player dynamic game." Advances in Mechanical Engineering 11, no. 1 (January 2019): 168781401881990. http://dx.doi.org/10.1177/1687814018819903.
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With a view to the background of Internet of Things, the vehicle group situation, especially the propensity of different drivers, and the corresponding vehicle types were given a comprehensive consideration on the basis of the factors which influence driving behavior, and the drivers’ lane selection model based on multi-player dynamic game with complete information was built. The drivers’ payoffs under different combination of lane selection strategies were analyzed, and on this basis, the subgame perfect Nash equilibrium solution was solved through backward induction, and the drivers’ optimal lane selection strategy was obtained. Next-Generation Simulation datasets and other data were applied for model calibration and validation. The results showed that the proposed model can objectively reflect the actual operation characteristic of traffic flow on road section. So, it is of great significance to apply the multi-person dynamic game in the field of intelligent transportation. And the theoretical basis of the research on lane selection decision-making can be provided for the command system of intelligent driving especially anthropomorphic driving under the condition of Internet of Things.
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Kim, Sang-Yun, and Kwang-Min Cho. "Narrative inquiry about 2017 National boxing player selection process errors." Korean Journal of Sports Science 27, no. 6 (December 31, 2018): 1–13. http://dx.doi.org/10.35159/kjss.2018.12.27.6.1.
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Fudenberg, Drew, and David K. Levine. "Reputation and Equilibrium Selection in Games with a Patient Player." Econometrica 57, no. 4 (July 1989): 759. http://dx.doi.org/10.2307/1913771.
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Tereshchuk, M. V. "The system of world golf ranking among amateur players - WAGR." Physical education of students 18, no. 6 (December 28, 2014): 69–72. http://dx.doi.org/10.15561/20755279.2014.0613.
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Purpose: justify the particular rating-WAGR and determine its value. Material: More than 40 references, including analysis of 8 protocols of Ukraine competition in golf. Results: The features and significance of the world rankings in golf among amateur players. Displaying ranking tournaments in accordance with the system of WAGR and justified the use of the conversion of the results to determine the specific places the player in the rankings. In Ukraine, held six WAGR-Tournament, the first tournament was held in 2011. Today in the world ranking of amateur players is one player from the Ukraine. Conclusions: It was found that the top-WAGR determines the level of development of the national golf federations and influence in the international arena. For the selection of athletes for the summer Youth Olympic Games is used world-rated golf amateur players (WAGR) among boys and girls.
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Zhao, Changheng, and Jiaying Li. "Equilibrium Selection under the Bayes-Based Strategy Updating Rules." Symmetry 12, no. 5 (May 5, 2020): 739. http://dx.doi.org/10.3390/sym12050739.
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In this paper, first, an evolutionary game model for Bayes-based strategy updating rules was constructed, in which players can only observe a signal that reveals a strategy type instead of the strategy type directly, which deviates from the strategy type of players. Then, the equilibrium selection of populations in the case of the asymmetric game, the Battle of the Sexes (BoS), and the case of a symmetric coordination game was studied where individuals make decisions based on the signals released by each player. Finally, it was concluded that in the BoS game, when the accuracy of the signal is low, the population eventually reaches an incompatible state. If the accuracy of the signal is improved, the population finally reaches a coordinated state. In a coordination game, when the accuracy of the signal is low, the population will eventually choose a payoff-dominated equilibrium. With the improvement of signal accuracy, the equilibrium of the final selection of the population depends on its initial state.
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Nurzahputra, Aldi, Afrizal Rizqi Pranata, and Aji Puwinarko. "Decision Support System for Football Players Lineup Selection using Fuzzy Multiple Attribute Decision Making and K-Means Clustering Methods." Jurnal Teknologi dan Sistem Komputer 5, no. 3 (July 31, 2017): 106–9. http://dx.doi.org/10.14710/jtsiskom.5.3.2017.106-109.
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In football, the selection of players line-up is based on their statistical performance. In this research, the line-up selection can implement the decision support system (DSS) with FMADM SAW method. The criteria were used are goal, assists, saves, clean sheets, yellow cards, red cards, games, and an own goal. Then, the assessment players performance is using K-Means Clustering. There are two clusters: cluster_cukup and cluster_baik. The system used Manchester City player data in Forward, Midfielder, Defender and Goal Keeper position. The purpose of this research is applying the FMADM and K-Means Clustering method to the system. Based on the results, the line-up selection can be processed by FMADM method and the performance assessed by K-Means Clustering method. By using the system, the selection and the assessment can be conducted and give the best decision for football coach objectively.