In this article, I will take you through how we can predict the IPL winner with machine learning. The Indian Premier League (IPL) is a professional Twenty20 cricket league in India, played in March or April and May of each year by eight teams representing eight different cities in India.

## How We Can Predict IPL Winner with Machine Learning?

This is not a simple task, it’s one of the complex tasks of Machine Learning to predict the winner of a cricket tournament. The worst thing is that it doesn’t matter how much the accuracy rate you get in the process, but sometimes it cannot be predicted by just looking at the data as the sentiments and form or players matters a lot.

So how we can predict the IPL winner with machine learning? We can predict the winner by using the data. The process that I followed to predict the IPL winner 2020 is explained below:

- Given the player’s stats in a machine learning model, the model generates the rating points for that player based on their stats.
- Once the model has generated scores for all IPL players, we choose a team’s best playing XI using an algorithm and add all the points of the best XI players to get the total team score.
- This algorithm then generates the winner of two teams using the team evaluation points out that the machine learning algorithm predicted.
- We call this algorithm for all league stadium games. So after the league stage, the algorithm produces the top four teams that qualify.
- In the qualifying phase, again, the same algorithm is executed between two teams and the top two teams will be selected for the finals.
- In the final phase, we end up with the two best teams. We call the algorithm one last time and it comes out the final winner.

## Dataset

I retrieved the data for the top 100 players from ICC T20 by using the Beautiful Soup package and got the data for batsmen, bowlers and all-rounders separately. You can download the full dataset **here**.

## How to Build a Model to Predict the IPL Winner?

After the data cleansing, processing and necessary transformations, we need to build the machine learning models on this cleansed data. In this task I implemented some powerful algorithms like SGDRegressor, KNN-Regressor, Linear Regression using the Least-Square Estimates, Weighted KNN-Regressor and the compared all the models by using the Scikit learn package. Then at the end, I almost got similar results to the Scikit implementation.

When I started to work on this task I didn’t have the schedule of the matches. Now what is best for you is that you now have the complete schedule of the matches to be played so you can modify the changes to get a better prediction. I didn’t include the complete project in this article as the project is very big to explain here. You can get the full project from below.

The models don’t care much about the schedule of the matches until you miss any combination of matches in your created schedule. So after training the models it predicted that Chennai Super Kings (CSK) will be the winner of IPL-2020.

I hope you liked this article on how we can predict the IPL winner 2020. Feel free to ask your valuable questions in the comments section below.

**Also, Read – When do we need to use Machine Learning.**