Demand for live betting: An analysis using state-space models

IF 1.3 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Applied Stochastic Models in Business and Industry Pub Date : 2024-01-04 DOI:10.1002/asmb.2836
Marius Ötting, Rouven Michels, Roland Langrock, Christian Deutscher
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Abstract

Sports betting markets have grown very rapidly recently, with the total European gambling market worth 98.6 billion euro in 2019. Considering a high-resolution (1 Hz) data set provided by a large European bookmaker, we investigate the demand for bet placements during matches and in particular the effect of news. Accounting for the general market activity level within a state-space modelling framework, we analyse the market's response to events such as goals (i.e., major news). Our results indicate that markets strongly react to news, but other factors, such as the day of the week and the uncertainty of outcome, also affect the stakes placed. We thus provide insights into the behaviour of bettors during matches, which can be relevant for bookmakers, for example to predict future revenues, but also for more specialised tasks such as fraud detection.

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现场投注需求:利用状态空间模型进行分析
体育博彩市场近来发展迅猛,2019 年欧洲博彩市场总值达 986 亿欧元。考虑到欧洲一家大型博彩公司提供的高分辨率(1 Hz)数据集,我们研究了比赛期间的投注需求,特别是新闻的影响。在状态空间建模框架内考虑到一般市场活动水平,我们分析了市场对进球等事件(即重大新闻)的反应。我们的结果表明,市场对新闻的反应强烈,但其他因素,如星期几和结果的不确定性,也会影响赌注。因此,我们对投注者在比赛期间的行为有了深入的了解,这对博彩公司(例如预测未来收入)以及欺诈检测等更专业的任务都有意义。
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来源期刊
CiteScore
2.70
自引率
0.00%
发文量
67
审稿时长
>12 weeks
期刊介绍: ASMBI - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis) was first published in 1985, publishing contributions in the interface between stochastic modelling, data analysis and their applications in business, finance, insurance, management and production. In 2007 ASMBI became the official journal of the International Society for Business and Industrial Statistics (www.isbis.org). The main objective is to publish papers, both technical and practical, presenting new results which solve real-life problems or have great potential in doing so. Mathematical rigour, innovative stochastic modelling and sound applications are the key ingredients of papers to be published, after a very selective review process. The journal is very open to new ideas, like Data Science and Big Data stemming from problems in business and industry or uncertainty quantification in engineering, as well as more traditional ones, like reliability, quality control, design of experiments, managerial processes, supply chains and inventories, insurance, econometrics, financial modelling (provided the papers are related to real problems). The journal is interested also in papers addressing the effects of business and industrial decisions on the environment, healthcare, social life. State-of-the art computational methods are very welcome as well, when combined with sound applications and innovative models.
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