The Data Analytics Blog

Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.

All Posts

Can Data Science Predict The Results Of The FIFA Football World Cup?

June 6, 2018 at 1:03 PM

South African based data analytics company, Principa, will be predicting the results of every match at this year’s FIFA Football World Cup, to once again put theory into play. By applying the same principles used to predict customer behaviour for Principa’s financial services and retail clients, the company’s data scientists are using different algorithms to develop models that can predict the outcome of the matches.

View our Football World Cup Predictions

As the objective of machine learning is to develop models that can retrain themselves to adapt when exposed to new data, the algorithms will be re-trained with the results of each match to improve the accuracy of the following round’s generated prediction.

The purpose is to see how well different predictive analytics techniques used successfully in other areas can outperform the best human-made predictions. The exercise will take place on SuperBru.com.

In 2015, Principa predicted the results of the Rugby World Cup matches, out-predicting 99.68% of humans on sports predictor platform, Superbru.com. The Principa data scientists also experienced success when predicting the outcomes of the 2016 Oscars

“It will be interesting to see how accurate and models are in predicting the outcomes of the football matches. We’re cautiously optimistic after our previous success in predicting the Rugby World Cup, but this is a whole new ballgame,” shares Jaco Rossouw, CEO of Principa. “We’ve never used our skills as data scientists to predict the outcomes of a football game, and unlike with the Rugby World Cup where we were predicting the point margins between the participating teams, this time we’ll be predicting the exact final scores - a significantly more complex challenge! We’re excited to see how the algorithms perform.”

Principa will be posting their teams’ data-driven predictions before every match on their website as well as via their Twitter (@PrincipaD) and Facebook accounts. A record of all predictions and the actual results will also be made available on the company's website.

Principa have also created an overview of some of the more interesting insights discovered during the data preparations: https://wonders.principa.co.za/football-world-cup-2018-statistics 

About Principa: Principa Decisions (Pty) Ltd. work wonders with data science to serve over 150 companies in 30 countries in Africa, Middle East and Europe.

Principa’s data science solutions help customers answer questions about the past and present to anticipate future outcomes. Our data scientists, developers and consultants work together to develop data analytics products and solutions that derive answers, predictions and recommended actions from large and complex data. The data insights derived provide the information and knowledge from which to develop more effective strategies, increase efficiency and profitability and decrease cost and risk.

Latest Posts

Amazon Web Services Vs Microsoft Azure: Which Cloud Provider Should You Host Core Business Systems On?

Deciding on which cloud service to host your core business systems on can be a daunting task. Amazon Web Services (AWS) and Microsoft Azure are two of the biggest players around, while Google Cloud and IBM Cloud are also gaining market-share.

Truth Seeker: How To Avoid Logical Fallacies And Cognitive Biases In Data Science

We have released a new eBook titled Truth Seeker: a guide to avoiding logical fallacies and cognitive biases in data science.

Exploring The Evolution Of Data Science In Banking

We’re looking forward to attending this year’s Evolution of Data Science in Banking conference. The 2019 conference will be held on the 5th and 6th of June at the Indaba Hotel, Fourways, Johannesburg. The event will explore the use of data and analytical techniques to help financial services providers meet regulatory and reporting requirements. Also to be discussed is how running analytics at a product level can provide a more holistic view of customers across their portfolios.