Predicting FIFA World Cup 2022™ using Machine Learning

With the 2022 FIFA World Cup™ closing in, 32 countries are getting ready to test themselves again at the world’s biggest football showcase. It is only natural for all of us to be interested to find out which team will emerge as the World Champion.
We offer an answer to this curiosity with the help of our FIFA World Cup 2022 predictor, developed by our team to forecast the most likely outcome of this year’s football championship using extensive machine learning and various other indicators.
Learn more about which team will most likely end up taking the trophy home, according to the data.

World Cup 2022 Simulator for prediction

How do we build models?

By using ML algorithms. For this one, we used Logistic Regression, Random Forest and SVM. Ranking is the main input.
The Football World Cup 2022 prediction will use the current rankings of the two teams from a match at that particular time and will be based solely on the outcomes of competitive matches (not friendly) to see who will come out on top.

For example:
The current rankings of Brazil and Argentina in 2022 will be different from the rankings of Brazil and Argentina from 1990. And the same follows for other competing teams.

Make your own prediction

FIFA World Cup 2022™ Predictor

The Goal:

Using Machine Learning to predict who will win the FIFA World Cup 2022™.
Predicting the outcome of individual matches for the entire competition.
Simulating the outcomes of crucial games such as quarterfinals, semi-finals, and finals.
Learning what the knockout stages would look like following the conclusion of the group stages.
See the mapped-out schedules of all matchups.
These goals require solving various Machine Learning tasks, including addressing unique real-world prediction challenges. This World Cup prediction Machine Learning tasks include Data Integration, Feature modelling, and Outcome prediction.

World Cup 2022 Prediction Model

How data is used?

For predicting the Football World Cup 2022, we have utilised data from Kaggle International football results from the year 1870 to the current year 2022. Additionally, as input, we used all the participating teams’ match results throughout history, going back to the inception of the championship in 1930. The algorithm also made use of information from football rankings from 1992 through 2022.

How many algorithms have we built?

For this 2022 FIFA World Cup™ Predictor, we built 3 algorithms in total

Random Forest

A commonly-used machine learning algorithm, which combines the output of multiple decision trees to create a “forest". It predicts by taking the average or mean of the output from various trees. It provides the highest accuracy predictions among all available methods.

SVM

One of the most popular and widely used supervised machine learning algorithms. It uses a technique called the kernel trick to transform your data and then based on these transformations it finds an optimal boundary between the possible outputs.

Logistic Regresion

A basic supervised machine learning algorithm, which estimates the probability of an event occurring based on a given dataset of independent variables.

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