World Cup Best-XI Selection with ML

• This project is an attempt to use ideas of ML to predict the best XI players for the 2023 Cricket World Cup given a team, venue and an opponent.
• The data used for this project is ODI records of players from 2023 Cricket World Cup.
• The data was gathered from ESPN Cricinfo using web scraping.

Problem Statements

• How many runs will a player score against a particular opposition in a venue.
• What will be the economy of a player against an opposition in a venue.
• In the next match, how will a player get out (Caught behind, stumped, run out ... etc) against an opposition in a venue.
• Given a new domestic player will he be a X-Factor Bowler like Bumrah, Cummins, Strong middle-order batsman like Shreyas Iyer, K L Rahul or an explosive all rounder like Maxwell or a top class batsman like Kohli.

Where to Start

• The final_data folder contains the data used for this project.
• The predicting_runs.ipynb, predicting_economy.ipynb and predicting_Dismissal.ipynb notebooks contain the ML models used for predicting runs, economy and predicting dismissal respectively.
• The clustering_players.ipynb contains the code to cluster the players into 4 groups, X-Factor Bowlers, Strong Middle Order and Wicket Keeping batsmen, Explosive All Rounders and Top Class Batsmen.
• The post_clustering.ipynb contains the code that classifies a new player into one of the clusters from above!

Team

Team
Ashwin Narayanan S
Sreepadh
Ananya R
Arjun P
Kona Deepak