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A Jupyter Notebook / Google Colab based Machine Learning Notebook for training a model to predict the first inning score of an IPL match using data from matches played between 2008 to 2017.

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thatfreakcoder/IPL-Score-Prediction-with-Machine-Learning

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IPL Score Prediction with Machine Learning

Open in Google Colab
Predict the First Inning score of an Indian Premier League (IPL) Match using machine learning algorithms.

Dataset

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

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

Webapp Deployment

The final model is deployed here
Github Code of Webapp can be found here.

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A Jupyter Notebook / Google Colab based Machine Learning Notebook for training a model to predict the first inning score of an IPL match using data from matches played between 2008 to 2017.

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