Beyond crowd judgments: Data-driven estimation of market value in association football

Müller, Oliver; Simons, Alexander; Weinmann, Markus

doi:10.1016/j.ejor.2017.05.005

Cited by 121 publications

(222 citation statements)

References 31 publications

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“…They find a large discrepancy between estimated and real market values, due to the lack of important information such as injury-proneness and commercialization capacity. Müller et al [31] develop a similar approach and use soccer-logs, as well as players' popularity data and market values in the preceding years, to estimate a player transfer fee. They show that for the low-and medium-priced players the estimated market values are comparable to estimations by the crowd, while the latter performs better for the high-priced players.…”

Section: Relations Between Performance and Market Valuementioning

confidence: 99%

PlayeRank

Pappalardo

Cintia

Ferragina

et al. 2019

ACM Trans. Intell. Syst. Technol.

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The problem of evaluating the performance of soccer players is attracting the interest of many companies and the scientific community, thanks to the availability of massive data capturing all the events generated during a match (e.g., tackles, passes, shots, etc.). Unfortunately, there is no consolidated and widely accepted metric for measuring performance quality in all of its facets. In this article, we design and implement PlayeRank, a data-driven framework that offers a principled multi-dimensional and role-aware evaluation of the performance of soccer players. We build our framework by deploying a massive dataset of soccer-logs and consisting of millions of match events pertaining to four seasons of 18 prominent soccer competitions. By comparing PlayeRank to known algorithms for performance evaluation in soccer, and by exploiting a dataset of players' evaluations made by professional soccer scouts, we show that PlayeRank significantly outperforms the competitors. We also explore the ratings produced by PlayeRank and discover interesting patterns about the nature of excellent performances and what distinguishes the top players from the others. At the end, we explore some applications of PlayeRank-i.e. searching players and player versatility-showing its flexibility and efficiency, which makes it worth to be used in the design of a scalable platform for soccer analytics. 59:2 L. Pappalardo et al. INTRODUCTIONRankings of soccer players and data-driven evaluations of their performance are becoming more central in the soccer industry [4,14,15,20,32,34,40,46]. On the one hand, many sports companies, websites, and television broadcasters-such as Opta, WhoScored.com, and Sky, as well as the plethora of online platforms for fantasy football and e-sports-widely use soccer statistics to compare the performance of professional players with the purpose of increasing fan engagement via critical analyses, insights, and scoring patterns. On the other hand, coaches and team managers are interested in analytic tools to support tactical analysis and monitor the quality of their players during individual matches or entire seasons [11,27]. Not least, soccer scouts and performance analysts are continuously looking for data-driven tools to improve the retrieval of talented players with desired characteristics, based on evaluation criteria that take into account the complexity and the multi-dimensional nature of soccer performance. While selecting talents on the entire space of soccer players is unfeasible (if not impossible!) for humans, data-driven performance scores help select a small subset of the best players who meet specific constraints (e.g., age, performance features and trends, roles). This allows scouts and performance analysts to analyze a smaller set of players, thus saving considerable time and economic resources while broadening scouting operations and career opportunities of talented players.The problem of data-driven evaluation of player performance is gaining interest in the scientific community, too, thanks to t...

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Section: Relations Between Performance and Market Valuementioning

confidence: 99%

PlayeRank

Pappalardo

Cintia

Ferragina

et al. 2019

ACM Trans. Intell. Syst. Technol.

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“…12 Herm, Callsen-Bracker, and Kreis (2014) argue and prove that the crowd-based market value closely relates to actual transfer fees, and transfer fees relate closely to player characteristics (Dawson, Dobson, and Gerrard 2000). 13 Recent work by Müller, Simons, and Weinmann (2017) implements a multilevel regression analysis to determine the market value of a player as an alternative to the wisdom of the crowd approach. Although they estimate some differences between their data-based approach and the crowd approach, these differences are small and on average, tend to be closer to the crowd approach.…”

Section: The Modelmentioning

confidence: 99%

“…Table 3 reports Equation (1)'s results considering players that participated in at least five games during the season. The results are robust to alternative choices, including just playing at least one complete game, as suggested by Müller, Simons, and Weinmann (2017). The regression includes season and team fixed effects, a country dummy, and the errors are robust and clustered by team to allow for intrateam correlation.…”

Section: The Datamentioning

confidence: 99%

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Performance, Diversity and National Identity Evidence From Association Football

Tovar

2019

Economic Inquiry

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The increasing national diversity of coworkers has no consensus on its impact on performance. Using a team's predominant nationality as a proxy for national diversity and national identity, there is robust evidence that it affects team and individual performance. Detailed worker‐level data from a highly globalized industry, association football, show a nonlinear relationship between performance and the predominant nationality of a team's roster. As the number of members from the predominant nationality increases, performance declines. However, beyond a threshold level, performance rises. It follows that performance benefits from national diversity when the predominant nationality is small and from national identity when it is large. (JEL M14, Z21, Z22, J15)

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“…Desde os primórdios do futebol no Brasil a modalidade adquiriu várias peculiaridades, passando pela transformação de um esporte elitizado para um fenômeno popular. Tornou-se uma manifestação presente no cotidiano dos brasileiros, abrangendo relações sociais e econômicas (MARTINS, 2016). Portanto, é um esporte com ampla participação popular e uma atividade cujo público demonstra um apego significativo por seus times (SCHARF et al, 2016).…”

Section: Introductionunclassified

Aplicação de Redes Bayesianas para análise de programas sócio torcedor

Dias

Monteiro

Ribeiro

2019

Pensamento Contemporâneo em Administração

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O marketing esportivo trata da comercialização da imagem através do esporte e representa uma opção eficiente de aproximação com o público. Nesse contexto, o Programa Sócio Torcedor (PST) tem um potencial significativo para o Brasil. O artigo objetiva identificar a estrutura de valor percebido por distintas características sociodemográficas em um conjunto de atributos oferecidos pelos PSTs e propor um modelo elaborado com Rede Bayesiana (RB) que identifique o plano ideal para públicos distintos. Os dados foram coletados através de um survey online com população composta por torcedores dos times selecionados. Foram analisados com Análise Conjunta (AC) e RB. Verificou-se que o desconto nos ingressos e os preços são os atributos de maior valor para os torcedores. O trabalho contribuiu com a proposta de um instrumento capaz de descrever a percepção de valor nos PSTs e o modelo proposto com a RB mostrou-se uma ferramenta adequada para complementar a AC.

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Beyond crowd judgments: Data-driven estimation of market value in association football

Cited by 121 publications

References 31 publications

PlayeRank

PlayeRank

Performance, Diversity and National Identity Evidence From Association Football

Aplicação de Redes Bayesianas para análise de programas sócio torcedor

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