Predicting the Team Based on Player Performance and Formation in Sports Match by Machine Learning Approach
Abstract
In the field of sports evaluation of player performance and predicting the weight of the player for the formation of a well efficient team is very important. The main aim is to pick the best squad from all the available players. This will help to decide which team of players is the best to play against a particular opponent, perform prediction of the performance of the players in future matches and help team management in preparing the best team. The analysis will involve two factors that is time and data. Time means at this time how the player has performed and data involves the player'’s overall journey till now in all the matches. To implement the proposed model the collected statistical data is processed to numerical value to apply machine learning algorithms. Furthermore, a comparison of different methods and selection of the best method to provide maximum accuracy is been focused.
References
Shai Shalev-Shwartz, Shai Ben-David. Understanding Machine Learning from theory to the algorithm. Cambridge University Press, 2014.
Animul Islam Anik, Sakif Yeaser, A.G.M. Imam Hossain Amitabha Chakrabarty. Player’s Performance Prediction in ODI Cricket Using Machine Learning Algorithms, BRAC University, 66, Mohakhali, Bangladesh. 2018.
Harmandeep Kaur, Sushma Jain, Machine Learning approaches to predict basketball game outcome. Thapar University, 2018.
N. Bhalaji, K.B. Sundhara Kumar and Chithra Selvaraj. Empirical study of feature selection methods over classification algorithms. Int. J. Intelligent Systems Technologies and Applications. Vol. 17, Nos. 1/2, 2018.
E. Deepak, G. Sai Pooja, RNS Jyothi, SV Phani Kumar, KV Kishore. SVM Kernel based Predictive Analytics on Faculty Performance Evaluation, Department of Computer Science & Engineering Vignan’s University. 2015.
