Novel method for ranking batsmen in Indian Premier League

Manju, M.K.; Philip, Abin Oommen

doi:10.1016/j.dsm.2023.06.004

Cited by 3 publications

(1 citation statement)

References 15 publications

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“… Wieckowski and Salabun [ 34 ] To examine football players' performance score based on multi-criteria decision analysis Budak and Kara [ 35 ] To propose a multi-objective mathematical model for team harmony and players' performance Agarwalla and Mukhopadhyay [ 36 ] To leverage the particle swarm optimization for an effective player selection strategy Dey et al [ 37 ] To evaluate cricket players' performance via AHP-TOPSIS and AHP-COPRAS. Dezman et al [ 38 ] To develop an expert model system to settle the basketball players in the game Pappalardo et al [ 39 ] To evaluate the performance of soccer players Kizielewicz and Dobryakova [ 40 ] To evaluate sport players' performance based on MCDA Nikjo et al [ 41 ] To examine player selection process Manju and Philip [ 42 ] To construct a new performance index, to cluster players due to their experience …”

Section: Literature Reviewmentioning

confidence: 99%

Player selection in football by integrated SWARA-VIKOR methods under fuzzy environment

Çaloğlu Büyükselçuk,

Badem

2024

Heliyon

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Section: Literature Reviewmentioning

confidence: 99%

Player selection in football by integrated SWARA-VIKOR methods under fuzzy environment

Çaloğlu Büyükselçuk,

Badem

2024

Heliyon

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Using multi-criteria decision-making and machine learning for football player selection and performance prediction: a systematic review

Ati,

Bouchet,

Ben Jeddou

2024

Data Science and Management

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A Systematic Literature Review of Machine Learning Applications for Team Formation Problems

Karataş,

Çakır

2024

Bilişim Teknolojileri Dergisi

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With the development of technology, the variety and number of data held for any process has increased exponentially. By processing and analyzing this data, it is possible to solve many problems. Selection of the most appropriate team member and correct team formation in the activities carried out by the team are the factors that affect the success and result of teamwork. For this reason, the problem of team member selection and team formation has become one of the increasing research topics in recent years. Researchers from different disciplines are trying to develop tools, techniques and methodologies to ensure a successful team building process. Machine Learning (ML) methods have become one of the methods that have started to be used in team formation and team member selection problems in recent years. The successful outcome of this problem depends on the correct collection and processing of data and the selection of appropriate machine learning methods. The aim of this article is to present a systematic literature review of machine learning methods applied in team formation and team member selection problems, and to show which machine learning methods are applied in this field and their performance. Articles on the subject were searched in six scientific databases. In addition to providing fundamental information about ML methods, this review also supports new research efforts on team formation problems.

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Novel method for ranking batsmen in Indian Premier League

Cited by 3 publications

References 15 publications

Player selection in football by integrated SWARA-VIKOR methods under fuzzy environment

Player selection in football by integrated SWARA-VIKOR methods under fuzzy environment

Using multi-criteria decision-making and machine learning for football player selection and performance prediction: a systematic review

A Systematic Literature Review of Machine Learning Applications for Team Formation Problems

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