2019
DOI: 10.3390/app10010046
|View full text |Cite
|
Sign up to set email alerts
|

Machine Learning in Football Betting: Prediction of Match Results Based on Player Characteristics

Abstract: In recent times, football (soccer) has aroused an increasing amount of attention across continents and entered unexpected dimensions. In this course, the number of bookmakers, who offer the opportunity to bet on the outcome of football games, expanded enormously, which was further strengthened by the development of the world wide web. In this context, one could generate positive returns over time by betting based on a strategy which successfully identifies overvalued betting odds. Due to the large number of ma… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

1
19
0
4

Year Published

2020
2020
2024
2024

Publication Types

Select...
4
1
1

Relationship

1
5

Authors

Journals

citations
Cited by 37 publications
(24 citation statements)
references
References 40 publications
1
19
0
4
Order By: Relevance
“…On the other hand, when applying betting strategies that use only limited amount of information (compared to the odds), one can expect systematic losses over time. This is in line with the results of Stübinger et al (2020), where strategies that use no or little information (random-betting or favoring the home team) never gain any positive returns. However, using todays computation power and data, one can generate an historical information advantage in times where the odds did not reflect that knowledge which results in positive returns for earlier periods.…”
Section: Inefficiencies In Football Oddssupporting
confidence: 89%
See 4 more Smart Citations
“…On the other hand, when applying betting strategies that use only limited amount of information (compared to the odds), one can expect systematic losses over time. This is in line with the results of Stübinger et al (2020), where strategies that use no or little information (random-betting or favoring the home team) never gain any positive returns. However, using todays computation power and data, one can generate an historical information advantage in times where the odds did not reflect that knowledge which results in positive returns for earlier periods.…”
Section: Inefficiencies In Football Oddssupporting
confidence: 89%
“…However, the analysis is based on econometrical models, only, whereas Stübinger et al (2020) cover the application of state-of-the-art machine learning technique with a strong emphasis on the prediction of the correct outcome of a game rather than modeling the mechanics between the influencing factors. Stübinger et al (2020) point out diminishing profitability of Benedikt Mangold, Johannes Stübinger systematic betting approaches over time, which can be explained by improved modeling techniques and the improved availability of processing power and data. In this section, we link the aforementioned results of Stübinger et al (2020) to the efficiency hypothesis.…”
Section: Inefficiencies In Football Oddsmentioning
confidence: 99%
See 3 more Smart Citations