Intelligent Cricket Team Selection by Predicting Individual Players’ Performance using Efficient Machine Learning Technique
Chetan Kapadiya1, Ankit Shah2, Kinjal Adhvaryu3, Pratik Barot4
1Chetan Kapadiya*, PG Student, Computer Engineering Department, SVBIT, Gandhinagar, Gujarat, India.
2Dr. Ankit Shah, Head of Computer Engineering, Information Technology department, SVBIT Gandhinagar, Gujarat, India.
3Dr. Kinjal Adhvaryu, Principal, SVBIT, Gandhinagar, Gujarat, India.
4Pratik Barot, Assistant Professor ,Computer Engineering Department, Government Engineering College, Gandhinagar, Gujarat, India.
Manuscript received on January 26, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 3406-3409 | Volume-9 Issue-3, February 2020. | Retrieval Number: C6339029320 /2020©BEIESP | DOI: 10.35940/ijeat.C6339.029320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In any game, selection of best players in a team plays vital role in overall team performance. The team selection in any sport is the key task to ensure good performance of the team. Players are selected based on different criteria. In game of cricket selection of players should consider parameters like players own performance, ground condition, weather forecasting, opposition strength and weakness etc. Machine learning can play vital role in players’ performance prediction. Machine learning uses historical data of team performance and past performance of individual players to predict overall performance of team. Prediction of individual player performance helps in team building process. Recently many researchers proposed model for prediction of player’s performance for a game of cricket. Researchers’ uses machine learning approach for prediction. However existing studies omits some vital features related to ground and weather in their study which have potential to make huge impact on player’s performance. We performed detailed study and literature survey to propose efficient performance prediction of players for game of cricket. Our model will help in best team selection and thus improves overall team performance.
Keywords: Cricket, Performance Prediction, Machine Learning, Decision Tree, Random Fores