Indian Premier League (IPL) Ball-by-Ball Data
@kaggle.jamiewelsh2_ball_by_ball_ipl
@kaggle.jamiewelsh2_ball_by_ball_ipl
IPL match data from 2008-2023 was downloaded from cricsheet.org in JSON format. I used the pandas Python library to transform this data into ball-by-ball data with a number of relevant and useful columns. After this, the data was saved as a csv file.
This dataset was created as part of a project where I created metrics to rank players for T20 Internationals and the Indian Premier League (IPL). In the IPL Data Analysis notebook found below, I perform some exploratory data analysis before creating metrics to rank batters, bowlers and all-rounders based on the Runs Added/Reduced Compared to the Average Player. The entire project materials can be found at https://github.com/jamiewelsh25/Cricket_Data_Project/.
Furthermore, If you are interested in how I used this data to train predictive models for second innings chase success and first innings scores, then check out the notebooks below!
@owid
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