Publication: Accumulator bet selection through stochastic diffusion search
Issued Date
2019-04-01
Resource Type
ISSN
13494198
Other identifier(s)
2-s2.0-85067580580
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
International Journal of Innovative Computing, Information and Control. Vol.15, No.2 (2019), 641-652
Suggested Citation
Nassim Dehouche Accumulator bet selection through stochastic diffusion search. International Journal of Innovative Computing, Information and Control. Vol.15, No.2 (2019), 641-652. doi:10.24507/ijicic.15.02.641 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/50636
Research Projects
Organizational Units
Authors
Journal Issue
Thesis
Title
Accumulator bet selection through stochastic diffusion search
Author(s)
Other Contributor(s)
Abstract
© 2019, ICIC International. An accumulator is a bet that presents a rather unique payout structure, in that it combines multiple bets into a wager that can generate a total payout given by the multiplication of the individual odds of its parts. These potentially important returns come however at an increased risk of a loss. Indeed, the presence of a single incorrect bet in this selection would make the whole accumulator lose. The complexity of selecting a set of matches to place an accumulator bet on, as well as the number of opportunities to identify winning combinations have both dramatically increased with the easier access to online and offline bookmakers that bettors have nowadays. We address this relatively under-studied combinatorial aspect of sports betting, and propose a binary optimization model for the problem of selecting the most promising combinations of matches, in terms of their total potential payout and probability of a win, to form an accumulator bet. The results of an ongoing computational experiment, in which our model is applied to real data pertaining to the four main football leagues in the world over a complete season, are presented and compared to those of single bet selection methods.