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

Ötting M, Michels R, Langrock R, Deutscher C (2024)
Applied Stochastic Models in Business and Industry 40(2).

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Abstract / Bemerkung
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.
Stichworte
live betting; market response; state-space model; stochastic volatility; time series analysis
Erscheinungsjahr
2024
Zeitschriftentitel
Applied Stochastic Models in Business and Industry
Band
40
Ausgabe
2
ISSN
1524-1904
eISSN
1526-4025
Finanzierungs-Informationen
Open-Access-Publikationskosten wurden durch die Universität Bielefeld im Rahmen des DEAL-Vertrags gefördert.
Page URI
https://pub.uni-bielefeld.de/record/2985771

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Ötting M, Michels R, Langrock R, Deutscher C. Demand for live betting: An analysis using state‐space models. Applied Stochastic Models in Business and Industry. 2024;40(2).
Ötting, M., Michels, R., Langrock, R., & Deutscher, C. (2024). Demand for live betting: An analysis using state‐space models. Applied Stochastic Models in Business and Industry, 40(2). https://doi.org/10.1002/asmb.2836
Ötting, Marius, Michels, Rouven, Langrock, Roland, and Deutscher, Christian. 2024. “Demand for live betting: An analysis using state‐space models”. Applied Stochastic Models in Business and Industry 40 (2).
Ötting, M., Michels, R., Langrock, R., and Deutscher, C. (2024). Demand for live betting: An analysis using state‐space models. Applied Stochastic Models in Business and Industry 40.
Ötting, M., et al., 2024. Demand for live betting: An analysis using state‐space models. Applied Stochastic Models in Business and Industry, 40(2).
M. Ötting, et al., “Demand for live betting: An analysis using state‐space models”, Applied Stochastic Models in Business and Industry, vol. 40, 2024.
Ötting, M., Michels, R., Langrock, R., Deutscher, C.: Demand for live betting: An analysis using state‐space models. Applied Stochastic Models in Business and Industry. 40, (2024).
Ötting, Marius, Michels, Rouven, Langrock, Roland, and Deutscher, Christian. “Demand for live betting: An analysis using state‐space models”. Applied Stochastic Models in Business and Industry 40.2 (2024).
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2024-01-08T09:32:37Z
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Material in PUB:
Dissertation, die diesen PUB Eintrag enthält
Statistical Inference for Stochastic Process Models in Sports Analytics
Michels R (2024)
Bielefeld: Universität Bielefeld.
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