• In this repository all files are added which are required for the deployment of the webapp.
• If you want to view the deployed model, click on the following link here :https://first-innings-score-predictor.herokuapp.com/

• created a machine learning model for predicting the first inning score of IPL matches.
• optimized features
• data cleaning
• feature engineering
• Exploratory Data Analysis

Packages: pandas, numpy, sklearn, matplotlib, seaborn,pickle,heroku.

• 617 IPL matches -> data/ipl.csv

• mid -> Each match is given a unique number
• date -> When the match happened
• venue -> Stadium where match is being played
• bat_team -> Batting team name
• bowl_team -> Bowling team name
• batsman -> Batsman name who faced that ball
• bowler -> Bowler who bowled that ball
• runs -> Total runs scored by team at that instance
• wickets -> Total wickets fallen at that instance
• overs -> Total overs bowled at that instance
• runs_last_6 -> Total runs scored in last 6 overs
• wickets_last_6 -> Total wickets that fell in last 6 overs
• striker -> max(runs scored by striker, runs scored by non-striker)
• non-striker -> min(runs scored by striker, runs scored by non-striker)
• total -> Total runs scored by batting team after first innings

Linear regression, Decision Tree, Random Forest among these linear_regresion performed well ,so that was taken into the consideration.

• features:{date,venue,bat_team,bowl_team,runs,wickets,overs,runs_last_6, wickets_last_6}
• label:{ total}