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Problem statement

The Big Game is the annual American football championship and one of the most celebrated events in the history of sports. It is not only one of the most-watched sports events across the globe, but also has the reputation of being the second-largest day in terms of food consumption in the US. Every fan eagerly waits for the Game Day to find out if their favorite team wins.

A sports betting firm has utilized the data augmentation technique to synthesize a data set of championship outcome of the Big Game's participants and other data. Your task is to generate a model to determine and classify whether a given team will win the championship or not.

Data set

The dataset consists of certain parameters such as average age of players on the team, level of experience of the head coach, number of players on the team that were first round draft picks, number of injured players in the team, number of wins the team has in the ongoing season, and more.

The benefits of practicing this problem by using Machine Learning techniques are as follows:

  • This challenge will encourage you to apply your Machine Learning skills to build models that can anticipate the winning or losing chances of a given team
  • This challenge will help you enhance your knowledge of classification as it is one of the basic building blocks of Machine Learning

We challenge you to build a model that classifies whether a given team will win or lose on the Game Day.


  • 1st Prize - 250 USD

  • 2nd Prize - 150 USD

  • 3rd Prize - 75 USD


Machine learning is an application of artificial intelligence (AI) that provides systems with the ability to automatically learn and improve from experiences without being explicitly programmed. Machine Learning is a science that determines patterns in data. These patterns provide deeper meaning to problems. First, it helps you to understand the problems better and then solve the same with elegance.

Here is the new HackerEarth Machine Learning Challenge—Who wins the Big Game?

This challenge is designed to help you improve your Machine Learning skills by competing and learning from fellow participants.

Why should you participate?

  • To analyze and implement multiple algorithms and determine which is more appropriate for a problem

  • To get hands-on experience in Machine Learning problems

Who should participate?

  • Working professionals

  • Data science or Machine Learning enthusiasts

  • College students (if you understand the basics of predictive modeling)



  • In order to claim your prizes, your HackerEarth profile must be completed more than 50%
  • Only participants currently residing in the US are eligible for the prize money
  • The prizes will be disbursed in the second week of the following month


  1. Your output will be evaluated only for 50% of the test data while the contest is running. Once the contest is over, output for the remaining 50% of the data will be eval...
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