Modelling association football scores and inefficiencies in the football betting market.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published

Standard

Modelling association football scores and inefficiencies in the football betting market. / Dixon, Mark J.; Coles, Stuart G.
In: Journal of the Royal Statistical Society: Series C (Applied Statistics), Vol. 46, No. 2, 1997, p. 265-280.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Dixon, MJ & Coles, SG 1997, 'Modelling association football scores and inefficiencies in the football betting market.', Journal of the Royal Statistical Society: Series C (Applied Statistics), vol. 46, no. 2, pp. 265-280. https://doi.org/10.1111/1467-9876.00065

APA

Dixon, M. J., & Coles, S. G. (1997). Modelling association football scores and inefficiencies in the football betting market. Journal of the Royal Statistical Society: Series C (Applied Statistics), 46(2), 265-280. https://doi.org/10.1111/1467-9876.00065

Vancouver

Dixon MJ, Coles SG. Modelling association football scores and inefficiencies in the football betting market. Journal of the Royal Statistical Society: Series C (Applied Statistics). 1997;46(2):265-280. doi: 10.1111/1467-9876.00065

Author

Dixon, Mark J. ; Coles, Stuart G. / Modelling association football scores and inefficiencies in the football betting market. In: Journal of the Royal Statistical Society: Series C (Applied Statistics). 1997 ; Vol. 46, No. 2. pp. 265-280.

Bibtex

@article{d16276a2d6e0483ba7081d29663f1992,

title = "Modelling association football scores and inefficiencies in the football betting market.",

abstract = "A parametric model is developed and fitted to English league and cup football data from 1992 to 1995. The model is motivated by an aim to exploit potential inefficiencies in the association football betting market, and this is examined using bookmakers' odds from 1995 to 1996. The technique is based on a Poisson regression model but is complicated by the data structure and the dynamic nature of teams' performances. Maximum likelihood estimates are shown to be computationally obtainable, and the model is shown to have a positive return when used as the basis of a betting strategy.",

keywords = "Betting strategy • Expected return • Football (soccer) • Maximum likelihood • Poisson distribution",

author = "Dixon, {Mark J.} and Coles, {Stuart G.}",

year = "1997",

doi = "10.1111/1467-9876.00065",

language = "English",

volume = "46",

pages = "265--280",

journal = "Journal of the Royal Statistical Society: Series C (Applied Statistics)",

issn = "0035-9254",

publisher = "Wiley-Blackwell",

number = "2",

}

RIS

TY - JOUR

T1 - Modelling association football scores and inefficiencies in the football betting market.

AU - Dixon, Mark J.

AU - Coles, Stuart G.

PY - 1997

Y1 - 1997

N2 - A parametric model is developed and fitted to English league and cup football data from 1992 to 1995. The model is motivated by an aim to exploit potential inefficiencies in the association football betting market, and this is examined using bookmakers' odds from 1995 to 1996. The technique is based on a Poisson regression model but is complicated by the data structure and the dynamic nature of teams' performances. Maximum likelihood estimates are shown to be computationally obtainable, and the model is shown to have a positive return when used as the basis of a betting strategy.

AB - A parametric model is developed and fitted to English league and cup football data from 1992 to 1995. The model is motivated by an aim to exploit potential inefficiencies in the association football betting market, and this is examined using bookmakers' odds from 1995 to 1996. The technique is based on a Poisson regression model but is complicated by the data structure and the dynamic nature of teams' performances. Maximum likelihood estimates are shown to be computationally obtainable, and the model is shown to have a positive return when used as the basis of a betting strategy.

KW - Betting strategy • Expected return • Football (soccer) • Maximum likelihood • Poisson distribution

U2 - 10.1111/1467-9876.00065

DO - 10.1111/1467-9876.00065

M3 - Journal article

VL - 46

SP - 265

EP - 280

JO - Journal of the Royal Statistical Society: Series C (Applied Statistics)

JF - Journal of the Royal Statistical Society: Series C (Applied Statistics)

SN - 0035-9254

IS - 2

ER -

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