Competitive Balance in Team Sports Games

Nikolakaki, Sofia Maria; Dibie, Ogheneovo; Beirami, Ahmad; Peterson, Nicholas; Aghdaie, Navid; Zaman, Kazi A.

doi:10.1109/cog47356.2020.9231859

Cited by 7 publications

(5 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [9], Santiago and Sousa presented a survey on relevant work, current techniques, and trends in the area of team tracking systems applied to sports. Nikolakaki et al showed that using final score difference provides yet a better prediction metric for competitive balance in 2020 [10]. Wei et al focused on the historical evolution of the dragon boat race and the development of sports nonmaterial cultural heritage in [11].…”

Section: Related Workmentioning

confidence: 99%

Artificial Intelligence‐Based Real‐Time Signal Sample and Analysis of Multiperson Dragon Boat Race in Complex Networks

Liu

2022

Complexity

View full text Add to dashboard Cite

Dragon boat sport is a traditional activity in China. In recent years, dragon boat sport has become more and more popular around the world. In order to face more challenges, it is urgent for athletes to enhance their own strength. Scientific training methods are particularly important for athletes, and accurate training data are the basis to support scientific training. Traditional mathematical statistic methods neither can sample signals accurately nor can they do real-time analysis and feedback the characteristics to each athlete. In this paper, we use the wearable device with a triaxial accelerometer and heart rate sensor builtin to sample the speed signals and heart rate signals of athletes in various stages of men’s 1000m straight race. Based on the complex network theory, we regard the 23 dragon boat athletes in the dragon boat race as 23 nodes so as to establish a network with 23 nodes and reflect the importance of nodes by measuring the impact of node deletion on the results of the race. The neural network multilayer perceptron (MLP) model is used for training to obtain the optimal combined value with speed and heart rate for each race stage. The optimal value will be used in the simulated race as the target value to verify if it can help to improve the training efficiency. Experimental results show that the optimal value obtained by this method has a positive effect on the results of the dragon boat race which is beneficial to sports training and tactics planning.

show abstract

Section: Related Workmentioning

confidence: 99%

Artificial Intelligence‐Based Real‐Time Signal Sample and Analysis of Multiperson Dragon Boat Race in Complex Networks

Liu

2022

Complexity

View full text Add to dashboard Cite

show abstract

“…Matchmaking systems often differ in objectives they pursue for conducting assignments. While some systems focus on player engagement [1] and enjoyment [2], the majority of matchmaking algorithms aim for maintaining competitive balance in matches they create [3]. These algorithms assume that the most pleasant experience happens when the match is optimally balanced, meaning the odds of winning are more or less even for the competing players and teams [4].…”

Section: Related Workmentioning

confidence: 99%

Behavioral Player Rating in Competitive Online Shooter Games

Dehpanah¹,

Ghori²,

Gemmell³

et al. 2022

Preprint

View full text Add to dashboard Cite

Competitive online games use rating systems for matchmaking; progression-based algorithms that estimate the skill level of players with interpretable ratings in terms of the outcome of the games they played. However, the overall experience of players is shaped by factors beyond the sole outcome of their games. In this paper, we engineer several features from in-game statistics to model players and create ratings that accurately represent their behavior and true performance level. We then compare the estimating power of our behavioral ratings against ratings created with three mainstream rating systems by predicting rank of players in four popular game modes from the competitive shooter genre. Our results show that the behavioral ratings present more accurate performance estimations while maintaining the interpretability of the created representations. Considering different aspects of the playing behavior of players and using behavioral ratings for matchmaking can lead to matchups that are more aligned with players' goals and interests, consequently resulting in a more enjoyable gaming experience.

show abstract

“…On the other hand, some systems leverage historical in-game statistics to represent players' skills. Depending on the game's genre, these statistics may include kill to death ratio, distance walked, role, or gold owned among others [5][6][7].…”

Section: Related Workmentioning

confidence: 99%

“…Since the outcome of these games is either win or loss (or draw when possible), the majority of works focused on how accurately the systems classify players and teams into their observed outcome. Accuracy [8][9][10][11], F1 score [5,12], and log likelihood [13,14] are among the metrics commonly used for evaluating these works. In addition, some works focused on how closely the systems predict the ratings and their associated ranks compared to the observed outcomes.…”

Section: Related Workmentioning

confidence: 99%

The Evaluation of Rating Systems in Team-based Battle Royale Games

Dehpanah,

Ghori,

Gemmell

et al. 2021

Preprint

View full text Add to dashboard Cite

Online competitive games have become a mainstream entertainment platform. To create a fair and exciting experience, these games use rating systems to match players with similar skills. While there has been an increasing amount of research on improving the performance of these systems, less attention has been paid to how their performance is evaluated. In this paper, we explore the utility of several metrics for evaluating three popular rating systems on a real-world dataset of over 25,000 team battle royale matches. Our results suggest considerable differences in their evaluation patterns. Some metrics were highly impacted by the inclusion of new players. Many could not capture the real differences between certain groups of players. Among all metrics studied, normalized discounted cumulative gain (NDCG) demonstrated more reliable performance and more flexibility. It alleviated most of the challenges faced by the other metrics while adding the freedom to adjust the focus of the evaluations on different groups of players.

show abstract

Competitive Balance in Team Sports Games

Cited by 7 publications

References 14 publications

Artificial Intelligence‐Based Real‐Time Signal Sample and Analysis of Multiperson Dragon Boat Race in Complex Networks

Artificial Intelligence‐Based Real‐Time Signal Sample and Analysis of Multiperson Dragon Boat Race in Complex Networks

Behavioral Player Rating in Competitive Online Shooter Games

The Evaluation of Rating Systems in Team-based Battle Royale Games

Contact Info

Product

Resources

About