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AI Case Study

Goldman Sachs unsuccessfully predicted participants of the World Cup 2018 finals by crunching team data with machine learning

Goldman Sachs predicted that Brazil would win the World Cup 2018. Whilst easy to mock part of the challenge is the inevitable headlines focus on the prediction rather than the probabilities involved - but GS were sophisticated enough to know this in advance.

Industry

Consumer Goods And Services

Entertainment And Sports

Project Overview

According to Business Insider: "The firm used machine learning to run 200,000 models, mining data on team and individual player attributes, to help forecast specific match scores. Goldman then simulated 1 million variations of the tournament to calculate the probability of advancement for each squad."

The model predicted the number of goals scored "in each possible iteration of the tournament, based on machine-learning results applied to countless scenarios."

"'We are drawn to machine learning models because they can sift through a large number of possible explanatory variables to produce more accurate forecasts than conventional alternatives,' a group of strategists from Goldman's international research team wrote in a client note."

Reported Results

Goldman Sachs predicted a final match between Brazil and Germany with the former set to win. Neither team progressed beyond the quarter-finals.

Technology

Function

Strategy

Data Science

Background

In the run up to the World Cup Goldman Sachs attempted to garner publicity for its analytical abilities by releasing its prediction for who would win the event.

Benefits

Data

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