Forecasting the Outcome of the Next ODI Cricket Matches to Be Played
Md. Minhazul Abedin1, Silvy Rahman Urmi2, Md. Towfiqul Islam Mozumder3, Md. Samiur Rahman4, Adnan Firoze5
1Minhazul Abedin*, Electrical & Computer Engineering, North South University, Dhaka, Bangladesh.
2Silvy Rahman Urmi, Electrical & Computer Engineering, North South University, Dhaka, Bangladesh.
3Md. Towfiqul Islam Mozumder, Electrical & Computer Engineering, North South University, Dhaka, Bangladesh.
4Md. Samiur Rahman, Electrical & Computer Engineering, North South University, Dhaka, Bangladesh.
5Adnan Firoze, Electrical & Computer Engineering, North South University, Dhaka, Bangladesh.
Manuscript received on November 12, 2019. | Revised Manuscript received on November 24 2019. | Manuscript published on 30 November, 2019. | PP: 10269-10273 | Volume-8 Issue-4, November 2019. | Retrieval Number: D4505118419/2019©BEIESP | DOI: 10.35940/ijrte.D4505.118419
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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: Cricket is one of the most popular sports in the contemporary world. The ebullience of securing victory in a particular match has motivated the rudimentary part of this research aspect. Winning in Cricket depends on various aspects like weather, track records of the performances of players, performances at a specific venue, match experiences, performance against a specific team and the current form of the team and the player. In this paper the main goal is to estimate a win prediction for ODI (One Day International) cricket match. For purposes of model building, various method has been applied retrospectively to the data that are already obtained from previously played matches. From them, Random Forest has given the best outcome of 92.6%.
Keywords: Cricket, Data Mining, Random Forest, K-Nearest Neighbor, SVM, Decision Tree.
Scope of the Article: Data Mining.