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The Application of Machine Learning Techniques for Predicting Results in Team Sport: A Review

arXiv.org Machine Learning

Over the past two decades, Machine Learning (ML) techniques have been increasingly utilized for the purpose of predicting outcomes in sport. In this paper, we provide a review of studies that have used ML for predicting results in team sport, covering studies from 1996 to 2019. We sought to answer five key research questions while extensively surveying papers in this field. This paper offers insights into which ML algorithms have tended to be used in this field, as well as those that are beginning to emerge with successful outcomes. Our research highlights defining characteristics of successful studies and identifies robust strategies for evaluating accuracy results in this application domain. Our study considers accuracies that have been achieved across different sports and explores the notion that outcomes of some team sports could be inherently more difficult to predict than others. Finally, our study uncovers common themes of future research directions across all surveyed papers, looking for gaps and opportunities, while proposing recommendations for future researchers in this domain.


GPT-3 Creative Fiction

#artificialintelligence

What if I told a story here, how would that story start?" Thus, the summarization prompt: "My second grader asked me what this passage means: …" When a given prompt isn't working and GPT-3 keeps pivoting into other modes of completion, that may mean that one hasn't constrained it enough by imitating a correct output, and one needs to go further; writing the first few words or sentence of the target output may be necessary.


Computational Intelligence in Sports: A Systematic Literature Review

arXiv.org Artificial Intelligence

Recently, data mining studies are being successfully conducted to estimate several parameters in a variety of domains. Data mining techniques have attracted the attention of the information industry and society as a whole, due to a large amount of data and the imminent need to turn it into useful knowledge. However, the effective use of data in some areas is still under development, as is the case in sports, which in recent years, has presented a slight growth; consequently, many sports organizations have begun to see that there is a wealth of unexplored knowledge in the data extracted by them. Therefore, this article presents a systematic review of sports data mining. Regarding years 2010 to 2018, 31 types of research were found in this topic. Based on these studies, we present the current panorama, themes, the database used, proposals, algorithms, and research opportunities. Our findings provide a better understanding of the sports data mining potentials, besides motivating the scientific community to explore this timely and interesting topic.


Artificial intelligence - Application to the Sports Industry

#artificialintelligence

Foreword Welcome to 2019 and our extended version of the 10 Minutes on Sport! Over the 2019 calendar year we will release new versions of the publication which take a deeper look at four emerging aspects in sport. We begin by defining artificial intelligence ("Sense, Think and Act"), its current applications in sport where the digitally connected fan is becoming a sports venue's biggest on-line influencer, key considerations for the future development and governance. I trust you enjoy the read.


Artificial intelligence - Application to the Sports Industry

#artificialintelligence

Foreword Welcome to 2019 and our extended version of the 10 Minutes on Sport! Over the 2019 calendar year we will release new versions of the publication which take a deeper look at four emerging aspects in sport. We begin by defining artificial intelligence ("Sense, Think and Act"), its current applications in sport where the digitally connected fan is becoming a sports venue's biggest on-line influencer, key considerations for the future development and governance. I trust you enjoy the read.