Data Science and ML in Cricket

 Objective of the data science in cricket  - Increate team performance  - Maximiser winning chances  Here's a simplified version: --- The IPL has expanded cricket, increasing the number of matches and the amount of data collected. Modern cricket data analysis involves tracking various factors like player positions, ball movements, shot types, delivery angle, spin, speed, and trajectory, which makes data cleaning and preprocessing more complex. **Dynamic Modeling** In cricket, numerous variables must be tracked, including player actions, ball attributes, and potential outcomes. The complexity of modeling depends on the type of predictive questions asked. Predictive models become especially challenging when analyzing hypothetical scenarios, like how a batsman’s shot might change with different ball angles or speeds. **Predictive Analytics Complexity** Cricket decision-making often relies on queries like "how often does a batsman play a specific shot against a certain b...
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Data prepossessing using python.

 Data preprocessing 



What is data processing (Data preprocessing ) 

Data processing is basically organising the data for further processes like Prediction, Hypothesis, Machine learning, Visualisation, and many more purposes.


What happens in Data processing?

Data processed as Making the data structured from unstructured data  and making it ready to processing for testing and training purposes. 

  • Data processig involvs .
  • Removing error data.
  • Checking for null data.
  • Sorting to the proper data type.
  • Filtering to check the classification.
  • Classifying data.
  • Creating pivot

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