2018
DOI: 10.1007/978-3-319-93713-7_22
|View full text |Cite
|
Sign up to set email alerts
|

Bayesian Based Approach Learning for Outcome Prediction of Soccer Matches

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2018
2018
2021
2021

Publication Types

Select...
2
1

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(1 citation statement)
references
References 12 publications
0
1
0
Order By: Relevance
“…A particular case is soccer tournaments, in which it seems difficult to predict the outcome of a game or who will be the winner in a certain championship, because there are many factors involved, such as those previously exposed (athletes, fields and technical personnel) as well as the presence of the public on the fields, injuries of the players, among others. Various studies have been able to predict winners of tournaments and matches, with different statistical models [10,12,13]. An example of this is the large betting houses that, despite their work being based on "chance", use models to benefit themselves and not the user.…”
Section: Theoretical Frameworkmentioning
confidence: 99%
“…A particular case is soccer tournaments, in which it seems difficult to predict the outcome of a game or who will be the winner in a certain championship, because there are many factors involved, such as those previously exposed (athletes, fields and technical personnel) as well as the presence of the public on the fields, injuries of the players, among others. Various studies have been able to predict winners of tournaments and matches, with different statistical models [10,12,13]. An example of this is the large betting houses that, despite their work being based on "chance", use models to benefit themselves and not the user.…”
Section: Theoretical Frameworkmentioning
confidence: 99%