Profiting from overreaction in soccer betting odds

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS
E. Wheatcroft
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引用次数: 2

Abstract

Abstract Betting odds are generally considered to represent accurate reflections of the underlying probabilities for the outcomes of sporting events. There are, however, known to be a number of inherent biases such as the favorite-longshot bias in which outsiders are generally priced with poorer value odds than favorites. Using data from European soccer matches, this paper demonstrates the existence of another bias in which the match odds overreact to favorable and unfavorable runs of results. A statistic is defined, called the Combined Odds Distribution (COD) statistic, which measures the performance of a team relative to expectations given their odds over previous matches. Teams that overperform expectations tend to have a high COD statistic and those that underperform tend to have a low COD statistic. Using data from twenty different leagues over twelve seasons, it is shown that teams with a low COD statistic tend to be assigned more generous odds by bookmakers. This can be exploited and a sustained and robust profit can be made. It is suggested that the bias in the odds can be explained in the context of the “hot hand fallacy”, in which gamblers overestimate variation in the ability of each team over time.
从足球博彩赔率的过度反应中获利
摘要投注赔率通常被认为是对体育赛事结果的潜在概率的准确反映。然而,已知存在一些固有的偏见,比如最受欢迎的长线偏见,即局外人的估值几率通常低于最受欢迎的人。利用欧洲足球比赛的数据,本文证明了另一种偏差的存在,即比赛赔率对有利和不利的结果反应过度。定义了一个统计数据,称为组合赔率分布(Combined Odds Distribution, COD)统计数据,它根据球队在之前比赛中的赔率来衡量球队的表现。超出预期的团队往往有较高的COD统计数据,而那些表现不佳的团队往往有较低的COD统计数据。使用来自20个不同联赛的12个赛季的数据,结果表明,COD数据较低的球队往往会被博彩公司分配更大的赔率。这一点可以加以利用,从而获得持续而强劲的利润。有人认为,赔率上的偏差可以用“热手谬误”来解释,即赌徒高估了每支球队在一段时间内的能力变化。
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来源期刊
Journal of Quantitative Analysis in Sports
Journal of Quantitative Analysis in Sports SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
2.00
自引率
12.50%
发文量
15
期刊介绍: The Journal of Quantitative Analysis in Sports (JQAS), an official journal of the American Statistical Association, publishes timely, high-quality peer-reviewed research on the quantitative aspects of professional and amateur sports, including collegiate and Olympic competition. The scope of application reflects the increasing demand for novel methods to analyze and understand data in the growing field of sports analytics. Articles come from a wide variety of sports and diverse perspectives, and address topics such as game outcome models, measurement and evaluation of player performance, tournament structure, analysis of rules and adjudication, within-game strategy, analysis of sporting technologies, and player and team ranking methods. JQAS seeks to publish manuscripts that demonstrate original ways of approaching problems, develop cutting edge methods, and apply innovative thinking to solve difficult challenges in sports contexts. JQAS brings together researchers from various disciplines, including statistics, operations research, machine learning, scientific computing, econometrics, and sports management.
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