There is no doubt that Football is the world’s most famous sport. There cannot be a bigger sporting event than the FIFA Football World Cup that is conducted every 4 years. This year, the football championship is being held in Russia, where 32 teams are competing to be the winner.
In the past, we saw animals trying to predict the winners of the football World Cup. In 2010, Paul the Octopus could correctly predict the outcomes of 12 matches out of 14, including the winner of the finals, Spain. Later on, other animals such as birds, penguins, donkeys, cats, etc. swung into action to predict the winners of the World Cup matches. While there is no scientific explanation for this phenomenon, many think it is just a marketing gimmick that just adds fun to the proceedings.
AI Does The Work
While the prescient nature of these animals continues to amaze us, this time around, things are different. People are now using artificial intelligence to predict the winner of the 2018 FIFA World Cup. Goldman Sachs has used machine learning to predict that Brazil will win the World Cup in its final match against Germany.
Fig: Brazil Will Win The Finals With An Unrounded Score of 1.70
With the help of 200,000 statistical models and by mining data on team characteristics and individual players, the firm was able to predict the outcome of a game. These models gave a large number of outcomes which were used to forecast the winner. Goldman Sachs then simulated 1 million possible variations of the tournament to calculate the probability of each team progressing through the rounds.
Is The Prediction Reliable?
These predictions are to be taken with a pinch of salt, as football is an extremely unpredictable game. As Goldman Sachs itself said, its forecasts are highly uncertain, even after using complex statistical techniques.
In the coming years, we are going to see more applications of AI in making predictions for businesses. Artificial Intelligence and Predictive Analytics can bring actionable insights, that will help you get ahead of your business competitors.
For example, a machine learning program can whisk through thousands or more of your customers’ sales data, and can show a popular combination of products bought was A, B, C. Also, that 70% of the customers that bought this combination also went on to buy product D. So in future your staffs at the store or your e-commerce site can use this information for effective cross-selling or up-selling.
BigAI To Empower Organisations
Tech Vedika’s BigAI platform is built on specialized Machine Learning Models, that helps companies dig deep into their wealth of data to gain valuable insights on their customers. It empowers organizations to gain hidden insights and make them more competitive.
Know more about our Predictive Analytics offerings.