India's tour to Bangladesh will include three-match ODI series followed by two-match Test series. Out of these 4 classifier algorithm the random forest classifier produce more accurate result then compared to other classifier and SVM produce least useful result.Team India (IND) is set to tour Bangladesh (BAN) for bilateral ODI and Test series, scheduled to take place near the beginning of December 2022. We exploit 'Decision tree', 'Naive Bayes', 'Random Forest' and 'Multiclass SVM' classifiers which produce the useful model to Predict for these 2 problems. For the prediction model these 2 problem are taken into account as goal as classification problem where the number of 'runs' and number of 'wickets' are classified into dissimilar range using different classifier algorithm. However in the game like cricket it is always important the situation in which it is responsibility of the batsmen to scores at most runs and bowlers to claims wickets.In this project we attempt to predict the performance of the players. Throughout selection process of the players the batsman and bowlers are rated on basis of the batting and bowling average correspondingly. They explore special statistic, records and characteristic of the players to select the finest playing11 for each match. The member of selection board, the coach and the captain of the team is conscientious for player selection. The player's performances depend on numerous factors such as the location where the match being play, past records, his current form, average rate, strike rate, run scored at a particular venue, number of inning played against the opposition teams etc.
Evaluation of individual performance and selection of the players in cricket is most critical job.
The most important and decisive task in any sport is selection of players.
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