Vol:.(1234567890)
OPSEARCH (2021) 58:54–70
https://doi.org/10.1007/s12597-020-00470-9
1 3
APPLICATION ARTICLE
Sports result prediction using data mining techniques
in comparison with base line model
Praphula Kumar Jain
1
· Waris Quamer
1
· Rajendra Pamula
1
Accepted: 21 July 2020 / Published online: 3 August 2020
© Operational Research Society of India 2020
Abstract
Sports prediction is one of the recent growing areas of interest entailing good pre-
diction accuracy. Coaches require models in order to assess their players, analyse
opponent teams and formulate winning strategies. Generation of comprehensive
statistical data in sports has enabled data mining (DM) techniques to be applied to
it in order to extract underlying predictive information. In this paper, an approach
based on data mining is proposed for result prediction in sports. The work includes
pre-processing of data, feature extraction, attribute selection and application of DM
algorithms as a learning strategy. To validate our proposed model, a case study
concerning prediction of the results of Indian Premier League (IPL) matches is
illustrated. The constructed models are based on the performance of teams in past
matches, player performance indices, opposition team information and external fac-
tors, and therefore, relevant features are engineered to indicate the same. The best
prediction accuracy was found to be 70.58%.
Keywords Data mining · Sports prediction · IPL · Classifcation · Cricket
1 Introduction
Data mining techniques have been extensively used to extract pattern and knowl-
edge from large datasets and fabricate predictive models on them. Despite the
increased implementation of data mining techniques in almost all domains, there
is a need for more accurate models for prediction in sports. In order to analyze
* Praphula Kumar Jain
praphulajn1@gmail.com
Waris Quamer
mr.warisquamer@gmail.com
Rajendra Pamula
rajendrapamula@gmail.com
1
Department of Computer Science and Engineering, Indian Institute of Technology (ISM),
Dhanbad, Jharkhand 826004, India