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 Analysis

Data Analysis

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What is Data Analysis ?

 Data analysis is a process of Inspecting ,Cleansing,Modeling and Transforming the data .

Inspecting Data :-

Inspecting is done in data analysis to look for useful information and data to use for decision making and improvement of data. 

Cleansing Data :-

Cleansing means correcting information and looking for inaccurate columns and correcting them

Modeling of Data :-

Modeling is important part of data analysis in modeling many thing are done like Data Visualisation,Data mapping,Data Gathering etc in next part will be discussed.

Transforming Data :-

Transforming data means getting raw data and transforming it in information and useful work.


Data Analytics Tools 

1)Tableau Public

Tableau  is simple data analytics tool intriguing insights through data visualization.it Public’s million row limit

Uses

  • Publish interactive data visualizations to the web 
  • No programing 
  • Can be embed in Web pages and Blogs 

2) OpenRefine (GoogleRefine)

It is simple data cleanup tool that helps to clean up data for analysis.

Uses 

  • Cleaning messy data
  • Data Transformation 
  • Parsing data from websites
  • Adding data to the dataset fetching from web services.
  • OpenRefine could be used for geocoding addresses to geographic coordinates

3)KNIME

Helps to manipulate, analyze, and model data through visual programming.Helps to integrate various components for data mining.and machine learning via its modular data pipelining concept.

Uses 

  • Drop and Drag connection points Between Activities 
  • Supports programming lanauge 
  • Analysis tools like these can be extended to run chemistry data, text mining, python, and R.

4) RapidMiner

Same as KNIME. Poor data visualization.Provides machine learning procedures and data mining including data visualization,processing, statistical modeling, deployment, evaluation, and predictive analytics

it is top 10 Data analytics tool

Uses

  • It provides integrated environment business analytics, predictive analysis, text mining, data mining, and machine learning.
  • Also used for application development, rapid prototyping, training, education, and research.

5) Google Fusion Tables

Google Fusion Tables can be added to business analytics tools list. Ranked among the top 10 Data Analytics tools, Google Fusion Tables is fast gaining popularity.

Uses

  • Visualization of bigger table data online.
  • Filtering and summarizing hundreds of thousands of rows.
  • Combining tables with other data on the web.

Dealing with missing value in python 

  • Mark Missing Values: where we learn how to mark missing values in a dataset.
  • Missing Values Causes Problems: where we see how a machine learning algorithm can fail when it contains missing values.
  • Remove Rows With Missing Values: where we see how to remove rows that contain missing values.
  • Impute Missing Values: where we replace missing values with sensible values.
  • Algorithms that Support Missing Values: where we learn about algorithms that support missing values.


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