IPL First Innings Score Prediction - Flask Deployment

Project Goal

This project is to designed to predict the first innings Score of Indian Premier League using Regression Analysis with PYTHON, FLASK and HTML

Webapp Deployment

The final model is deployed in Heroku and found here

Source code link (Github)

Github Code of Webapp can be found here

Dataset Source

The dataset can be downloaded from Kaggle here.

Dataset Description

• mid: Unique match id.

• date: Date on which the match was played.

• venue: Stadium where match was played.

• battingteam: Batting team name.

• bowlingteam: Bowling team name.

• batsman: Batsman who faced that particular ball.

• bowler: Bowler who bowled that particular ball.

• runs: Runs scored by team till that point of instance.

• wickets: Number of Wickets fallen of the team till that point of instance.

• overs: Number of Overs bowled till that point of instance.

• runslast5: Runs scored in previous 5 overs.

• wicketslast5: Number of Wickets that fell in previous 5 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 at the end of first innings.

Algorithms Used

• Linear Regression
• Ridge Regression
• Lasso Regression
• Decision Tree Regressor
• Random Forest Regression
• Support Vector Machine Regression

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