ISSN 2394-5125
 

Research Article 


Constractive analysis of cricket data Using Machine learning algorithm

S.SADIQ ALI, A.RAMA.

Abstract
Player selection is one the most important tasks for any sport and cricket is no exception. The performance of the
players depends on various factors such as the opposition team, the venue, his current form etc. The team management, the
coach and the captain select 11 players for each match from a squad of 15 to 20 players. They analyze different
characteristics and the statistics of the players to select the best playing 11 for each match. This paper attempts to predict the
performance of players as how many runs will each batsman score and how many wickets will each bowler take for both the
teams. Both the problems are targeted as classification problems where number of runs and number of wickets are classified
in different ranges. We used nave bayes, random forest, multiclass SVM and decision tree classifiers to generate the
prediction models for both the problems. Random Forest classifier was found to be the most accurate for both the problems.

Key words: Transmission Time, Delivery Ratio, SVM, Throughput.


 
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Pubmed Style

ALI S, A.RAMA . Constractive analysis of cricket data Using Machine learning algorithm. JCR. 2020; 7(3): 948-951. doi:10.31838/jcr.07.03.163


Web Style

ALI S, A.RAMA . Constractive analysis of cricket data Using Machine learning algorithm. http://www.jcreview.com/?mno=99405 [Access: May 31, 2021]. doi:10.31838/jcr.07.03.163


AMA (American Medical Association) Style

ALI S, A.RAMA . Constractive analysis of cricket data Using Machine learning algorithm. JCR. 2020; 7(3): 948-951. doi:10.31838/jcr.07.03.163



Vancouver/ICMJE Style

ALI S, A.RAMA . Constractive analysis of cricket data Using Machine learning algorithm. JCR. (2020), [cited May 31, 2021]; 7(3): 948-951. doi:10.31838/jcr.07.03.163



Harvard Style

ALI, S. & A.RAMA, . (2020) Constractive analysis of cricket data Using Machine learning algorithm. JCR, 7 (3), 948-951. doi:10.31838/jcr.07.03.163



Turabian Style

ALI, S.SADIQ, and A.RAMA. 2020. Constractive analysis of cricket data Using Machine learning algorithm. Journal of Critical Reviews, 7 (3), 948-951. doi:10.31838/jcr.07.03.163



Chicago Style

ALI, S.SADIQ, and A.RAMA. "Constractive analysis of cricket data Using Machine learning algorithm." Journal of Critical Reviews 7 (2020), 948-951. doi:10.31838/jcr.07.03.163



MLA (The Modern Language Association) Style

ALI, S.SADIQ, and A.RAMA. "Constractive analysis of cricket data Using Machine learning algorithm." Journal of Critical Reviews 7.3 (2020), 948-951. Print. doi:10.31838/jcr.07.03.163



APA (American Psychological Association) Style

ALI, S. & A.RAMA, . (2020) Constractive analysis of cricket data Using Machine learning algorithm. Journal of Critical Reviews, 7 (3), 948-951. doi:10.31838/jcr.07.03.163