Indian Premier League Data Analysis

As a cricket fan and a Data Science enthusiast I decided to perform some Data Analysis on IPL data from 2008 - 2017. Since the 2020 IPL season has been postponed and everyone is getting IPL blues, I decided that it would be a good idea to look at some IPL stats in a different way. The dataset has been sourced from kaggle. The dataset contains IPL match data from 2008 - 2017.

Based on the data, these were the main questions I focused on answering:

What are the biggest margins of victory by runs?
Calculating success of a team (Win/Loss percentage)
Does winning the toss give a big advantage?
Which are the players with the most Man of the Match awards?
Calculating a team's Win/Loss percentage in home and away matches
How many matches has a team played against other teams?
What are the Win/Lose percentages of a team at different grounds?

In this exploratory data analysis, I found out answers to these questions and more with my trusty friend; data.

Code and Resources Used

Python Version : 3.8.2

Libraries Used : pandas, numpy, matplotlib, seaborn

Dataset : kaggle

Findings

Overall Dataset Analysis

What are the biggest margins of victory by runs?

Biggest margins of victory by runs was in 2017 when Mumbai Indians defeated Delhi by 146 runs.

Which are the teams with the most biggest margins of victory by wickets ( between 9-10 )

Teams with the most biggest margins of victory by wickets is unsurprisingly RCB, owing to the explosive combination of Chris Gayle and Virat Kohli

What are the number of matches per season?

Most number of matches is in the 2013 season as 9 teams participated.

Does winning the toss give a big advantage?

We can see that winning the toss only gives a minor advantage contrary to the notion "Win the toss, win the match"

Which are the players with the most Man of the Match awards?

No surprises here with Chris Gayle topping the list.

Team Analysis

Considering Mumbai Indians for demonstration

Calculating success of a team (Win/Loss percentage)

Team with the highest Win percentage is CSK - 60.3% (The MSD effect?)

Calculating a team's Win/Loss percentage in home matches

Calculating a team's Win/Loss percentage in away matches

How many matches has a team played against other teams?

What are the Win/Lose percentages of a team at different grounds?

Usage :

This project is best viewed in a notebook viewer, which can be accessed here. In this notebook, you will find a walk through of the work done and the respective code.

ritik-k/ipl_analysis

Indian Premier League Data Analysis

Based on the data, these were the main questions I focused on answering:

In this exploratory data analysis, I found out answers to these questions and more with my trusty friend; data.

Code and Resources Used

Python Version : 3.8.2

Libraries Used : pandas, numpy, matplotlib, seaborn

Dataset : kaggle

Findings

Overall Dataset Analysis

What are the biggest margins of victory by runs?

Biggest margins of victory by runs was in 2017 when Mumbai Indians defeated Delhi by 146 runs.

Which are the teams with the most biggest margins of victory by wickets ( between 9-10 )

Teams with the most biggest margins of victory by wickets is unsurprisingly RCB, owing to the explosive combination of Chris Gayle and Virat Kohli

What are the number of matches per season?

Most number of matches is in the 2013 season as 9 teams participated.

Does winning the toss give a big advantage?

We can see that winning the toss only gives a minor advantage contrary to the notion "Win the toss, win the match"

Which are the players with the most Man of the Match awards?

No surprises here with Chris Gayle topping the list.

Team Analysis

Considering Mumbai Indians for demonstration

Calculating success of a team (Win/Loss percentage)

Team with the highest Win percentage is CSK - 60.3% (The MSD effect?)

Calculating a team's Win/Loss percentage in home matches

Calculating a team's Win/Loss percentage in away matches

How many matches has a team played against other teams?

What are the Win/Lose percentages of a team at different grounds?

Usage :

This project is best viewed in a notebook viewer, which can be accessed here. In this notebook, you will find a walk through of the work done and the respective code.