Success Of Players Research Articles

Research on Quantifying and Evaluating Tennis Match Momentum Based on Comprehensive Analytical Methods

Momentum is crucial in tennis matches, influencing player performance and match outcomes. However, quantifying and evaluating momentum has long been a challenge in sports science research. This study aims to quantify momentum in tennis matches by establishing a hierarchical analysis-based model for momentum flow. The model analyzes factors affecting momentum through five criteria: Service Level, Catch Level, Competition Result, Finishing Ability, and Winning Streak, with respective weights of approximately (0.1, 0.1, 0.2, 0.4, 0.2). Subsequently, the study assigns scores to these criteria based on different actions within a match. By multiplying the weights and scores, the momentum of each player is quantified, and the ratio of the two players' momentum provides a measure of momentum flow during the match. To assess the impact of momentum on match outcomes, the study employs k-means++ clustering analysis, violin plot analysis, and point-biserial correlation analysis. The point-biserial correlation analysis reveals a positive correlation coefficient of 0.66 between a player's momentum and their victory. Similar results are derived from the violin plot and clustering analysis. Therefore, it can be concluded that there is a significant association between the direction of momentum flow and a player's success in a match.

It Takes Two to Negotiate: Modeling Social Exchange in Online Multiplayer Games

Online games are dynamic environments where players interact with each other, which offers a rich setting for understanding how players negotiate their way through the game to an ultimate victory. This work studies online player interactions during the turn-based strategy game, Diplomacy. We annotated a dataset of over 10,000 chat messages for different negotiation strategies and empirically examined their importance in predicting long- and short-term game outcomes. Although negotiation strategies can be predicted reasonably accurately through the linguistic modeling of the chat messages, more is needed for predicting short-term outcomes such as trustworthiness. On the other hand, they are essential in graph-aware reinforcement learning approaches to predict long-term outcomes, such as a player's success, based on their prior negotiation history. We close with a discussion of the implications and impact of our work.

Artificial Intelligence (AI)-Based Self-Deciding Character Development Application in Two-Dimensional Video Games

Artificial Intelligence (AI) technologies, which have started to be used in almost all areas of life, are now also used in games. Especially for bot systems that play the game automatically in many popular video games recently, it has become possible for these bots to defeat the grandmasters of the game with advanced Deep Learning (DL) methods. The purpose of this study is to develop an AI-based two-dimensional video game in Unity 2D Game Engine, which can decide what the game characters will do within their abilities. In the game application, the two-dimensional game character is controlled by the user. This character moves in a two-dimensional game plane that is created using procedural plane generation algorithms. In addition, statistics such as the number of enemies defeated and the level reached in the game are recorded. The game is based on the Unity2D game engine and is written in C#. In the study, 8 different experiments are performed. In these experiments, the player's success time in the game with different equipment defined for the character is measured. This time ranges from 0.54 seconds to 1.88 seconds. Today, AI algorithms are developed to play computer games better or to design better games, and new games are designed to improve AI algorithms. In this context, it is evaluated that this study will contribute to the literature on the use of AI in computer games.

Constructing Expertise: Surmounting Performance Plateaus by Tasks, by Tools, and by Techniques.

Acquiring expertise in a task is often thought of as an automatic process that follows inevitably with practice according to the log-log law (aka: power law) of learning. However, as Ericsson, Chase, and Faloon (1980) showed, this is not true for digit-span experts and, as we show, it is certainly not true for Tetris players at any level of expertise. Although some people may simply "twitch" faster than others, the limit to Tetris expertise is not raw keypress time but the techniques acquired by players that allow them to use the tools provided by the hardware and software to compensate for the game's relentlessly increasing drop speed. Unfortunately, these increases in drop speed between Tetris levels make performance plateaus very short and quickly followed by game death. Hence, a player's success at discovering, exploring, and practicing new techniques for the tasks of board preparation, board maintenance, optimal placement discovery, zoid rotation, lateral movement of zoids, and other tasks important to expertise in Tetris is limited. In this paper, we analyze data collected from 492 Tetris players to reveal the challenges they confronted while constructing expertise via the discovery of new techniques for gameplay at increasingly difficult levels ofTetris.

Analyzing and Comparing Shot Planning Strategies and Their Effects on the Performance of an Augment Reality Based Billiard Training System

The shot planning of a cue after it collides with an object ball determines a player's success in a billiard game. This paper proposes three novel gaming strategies to investigate the effect of cue shots planning on gaming performance. The first algorithm considers the nearest pocket for every selected target object ball, seeking optimal post collision positions. The second algorithm considers all pocket and target object ball combinations during both the pre- and post-collision optimal shot selection processes. The third algorithm considers a multi-objective optimization process for optimal shot planning control. The simulations are conducted based on a collision model considering the restitution effects. An augmented reality training facility is devised to guide users in both aiming and cue repositioning control in a real-world billiard game. Experimental results not only prove the reliability of our training device in selecting a proper shot sequence using the all-pocket optimal shot planning algorithm, but it also proves the consistency with the restitution theory.

Interpersonal coordination tendencies shape 1-vs-1 sub-phase performance outcomes in youth soccer

This study investigated the influence of interpersonal coordination tendencies on performance outcomes of 1-vs-1 sub-phases in youth soccer. Eight male developing soccer players (age: 11.8 ± 0.4 years; training experience: 3.6 ± 1.1 years) performed an in situ simulation of a 1-vs-1 sub-phase of soccer. Data from 82 trials were obtained with motion-analysis techniques, and relative phase used to measure the space-time coordination tendencies of attacker-defender dyads. Approximate entropy (ApEn) was then used to quantify the unpredictability of interpersonal interactions over trials. Results revealed how different modes of interpersonal coordination emerging from attacker-defender dyads influenced the 1-vs-1 performance outcomes. High levels of space-time synchronisation (47%) and unpredictability in interpersonal coordination processes (ApEn: 0.91 ± 0.34) were identified as key features of an attacking player's success. A lead-lag relation attributed to a defending player (34% around −30° values) and a more predictable coordination mode (ApEn: 0.65 ± 0.27, P < 0.001), demonstrated the coordination tendencies underlying the success of defending players in 1-vs-1 sub-phases. These findings revealed how the mutual influence of each player on the behaviour of dyadic systems shaped emergent performance outcomes. More specifically, the findings showed that attacking players should be constrained to exploit the space-time synchrony with defenders in an unpredictable and creative way, while defenders should be encouraged to adopt postures and behaviours that actively constrain the attacker's actions.

Mapping statistics to success on the PGA Tour

PurposeAlthough the PGA Tour provides a wide array of statistics, no single measure has successfully been able to predict a player's success during the season, either in terms of earnings per tournament or weighted average scores. The purpose of this paper is to present a metric that attempts to predict annual player rankings based on these two criteria.Design/methodology/approachThe metric is computed from available statistics and attempts to encapsulate a player's unique strengths and weaknesses in a single number.FindingsDeviations in rankings based on the metric are compared to those based on earnings per event and adjusted scoring averages. The results suggest that in addition to the average annual performance on the greens, the mix of tournaments played and the incidence of heroics or consistency have an important impact on the chances of success on the Tour.Research limitations/implicationsThe metric's predictions can be negatively affected if a golfer makes a large proportion of double eagles or double bogies.Practical implicationsThe KCS (Key Criterion of Success) metric provides a quick route to succinctly summarizing a golfer's unique strengths and weaknesses in a single number.Originality/valuePrevious literature has mentioned the gap between statistics and success in golf. For the first time, possible reasons behind this divergence are identified in this paper.

Spillovers, Complementarities, and Sorting in Labor Markets with an Application to Professional Sports

Spillovers to productivity across workers may exist when workers produce in teams. Under certain conditions, these spillovers may cause a worker's marginal product to differ across different firms. Empirical examination of professional basketball finds significant spillovers to offensive productivity but finds relatively little evidence for market sorting based on spillovers. Thus, while teammate composition is important to a player's success, there is no evidence for complementarity.

Spillovers, Complementarities, and Sorting in Labor Markets with an Application to Professional Sports

Spillovers to productivity across workers may exist when workers produce in teams. Under certain conditions, these spillovers may cause a worker's marginal product to differ across different firms. Empirical examination of professional basketball finds significant spillovers to offensive productivity but finds relatively little evidence for market sorting based on spillovers. Thus, while teammate composition is important to a player's success, there is no evidence for complementarity.

Game Theoretic Approaches to Operating Room Management

All interactions between people can be considered games with rules and outcomes. However, modern business practices demand that the players in the game go beyond traditional game theory and look at new ways to improve the outcome of the game. Choosing the right strategy is important to a player's success. A new business strategy, "co-opetition," can be used to increase the value of the game ("create a bigger pie") through cooperative behavior, whereas competition is used to divided the "pie." By looking at how the players adopt simultaneous roles such as complementor and competitor the stakeholders in the operating room (managers, surgeons, anesthesiologists, and nursing staff) can apply the principles of co-opetition to improve the overall success of their facility. Such stakeholders can utilize knowledge of how populations act in games to enhance cooperative play. Adopting such a perspective may lead to increases in the satisfaction and morale of those involved with the operating rooms. Increased morale should increase productivity and staff retention and reduce recruiting needs.

Strength and weakness in four coalition situations

This study tested four models of coalition behavior in decision making on systems at the group level, in four different games, each of which was played by five individuals. Each game established a different distribution of power among the players. Data for coalition frequencies and for the payoffs of the players when they were included in a particular coalition supported Komorita & Chertkoff s (1973) bargaining theory over Komorita's (1974) weighted probability model and Gamson's (1961) minimum resource theory. When the overall payoffs received by each of the players in each game were used as a measure of the player's success in bargaining, the predictions of the Roth-Shipley and the weighted probability models received mixed support. Finally, the results suggested when the “strength is weakness” phenomenon might be expected to occur. Players with equal Shapley values but different resources within a particular game supported “strength is weakness.” Players with different Shapley values supported a “strength is strength” conclusion. Reports of the players provided a possible explanation of the underlying causes of this phenomenon.