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Using analytics to predict the World Cup winner

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World Cup 2014 winner odds

At the beginning of the 2014 World Cup in Brazil, speculations were, as always, intense about who is going to win, this time around. As the most important sporting event in the football world was about to start, the sheer number of global audiences it gathers was bound to lead to a vast array of biased or unbiased predictions for its final outcome. Needless to say, it most definitely did. Among this variety of suppositions and guesses some companies took to analysing big data in order to offer an information driven and unbiased prediction for the eventual winner.

The most prominent was FiveThirtyEight which used a model developed by ESPN, called the Soccer Power Index (SPI), to predict each team’s chances of advancing throughout the stages and ultimately winning the cup. The SPI, detailed in a Nate Silver article, is a rating system that aggregates a team’s overall quality based on historical data from several years regarding team results, as well as all individual players’ performances.

The team at FiveThirtyEight used the forecasting SPI model to run over 10,000 simulations in order to calculate the probability of each team of advancing in the tournament and actually winning the World Cup. Brazil was deemed to have a 45.2% chance of winning the World Cup, with Argentina coming in a distant second place, with 12.8%, and Germany rounding the top tree with 10.9%. The result was not so surprising given the fact that a previous prediction published by Goldman Sachs credited the home country with a 48.5% chance to win the cup.

 World Cup 2014 winner odds

The basis for this for this statistical model is not easy to argue with, as the documentation is very solid and backed up with facts that are made available to the public and presented in the aforementioned article. Nonetheless, giving Brazil a 45.2% chance to win the tournament is at least overly enthusiastic, given the quality of the current crop of Brazilian players selected by Scolari and the crucial fact that Brazil did not participate in the South American qualifiers.

Last night’s semi-final exposed, in my opinion, exactly those particular aspects. Before the game, the FiveThirtyEight model continued to back Brazil with a 65% chance to win the game in their pre-match article in which they even took into consideration the absence of probably the most important players in Brazil’s current team: Thiago Silva and Neymar.

But the reality of football kicked in yesterday and everyone saw probably one of the worst Brazilian sides in recent memory, maybe even history, mulled 7-1 by Germany, whom I consider should have been touted the tournaments’ favourites from the start. Even though the magnitude of the defeat was a shocker for everyone, the fact that Germany surpassed Brazil came to a surprise to no one except probably just Brazilians and FiveThirtyEight.

Even though the SPI model is a clear advancement in terms of measuring the quality of football players and teams, this World Cup, and particularly the game last night, shows that we are still some distance apart from being able to accurately measure aspects of the beautiful game. The actual quality of each individual player, their current form, the cohesiveness of a team as a unit and the number of official matches together played prior to a tournament bear a critical influence on a team’s performance and it is apparent that important strides have to be made for us to be able to adequately quantify a football squad’s quality and make accurate forecasts based on that.

Mihai Toma. Business Research Analyst

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Comments (15)

  • Houda Hedi Baccouche

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    we still can not use analytics to predict the World Cup winner.

    Reply

  • Nada Ahmed

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    We are still some distance apart from being able to accurately measure aspects of the World Cup Winner by using the SPI model.

    Reply

  • munirah almalki

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    we are still some distance apart from being able to accurately measure aspects of the beautiful game.

    Reply

  • Khalid

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    Nowadays, we are trying to apply analytics and BI tools to predict any results and optimize our performance. Mr. Mihai Toma wrote an article about using analytics and SPI specifically, which stands for Soccer Power Index, to predict the world cup winner. Forecasts and SPI ratings are used by FiveThirtyEight, sometimes rendered as 538 which is a business segment and division of The Walt Disney Company. In sum, SPI model failed to predict the world cup winner after the unforgettable loss of Brazil against Germany 7-1 and this was a clear indicator that we are still some distance apart from being able to measure and predict accurate results. However, this article is more than 6 years old so I am sure there are many technological advancements and new tools to predict accurate results, especially since their website is up and running not only in predicting football but also in predicting politics and science. This piqued my curiosity to explore and read more about FiveThirtyEight and SPI and understand how their predictions work. Probably the business analysis technique of root cause analysis – 5 whys will help us identify the root cause of their failure to predict the world cup winner and this prevent the process from recurring failures.

    Reply

  • Reem Alqnayah

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    We trying to apply analytics and BI tools to predict any results and optimize our performance. Mr. Mihai Toma wrote an article about using analytics and SPI specifically, which stands for Soccer Power Index, to predict the world cup winner. Forecasts and SPI ratings are used by FiveThirtyEight, sometimes rendered as 538 which is a business segment and division of The Walt Disney Company.

    Reply

  • Iris Daisy De Jesus

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    We are not at a point where we can use analytics to successfully predict the algorithm of an event. Needless to say even though we may have hard data to make a comparison, it is extremely hard to base an objective based on a lets say suggested pattern for a future result. I think it is better to base a KPI on comparison and not an algorithm.

    Reply

  • Drissa TRAORE

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    L’analyse des données est une étape importance dans un système de mesure de la performance.
    Il est à noter que des entreprises ont utilisées l’analyse du Big Data afin d’offrir une prédiction basée sur l’information impartiale pour le gagnant éventuel lors de la coupe du monde 2014.
    Le plus important était FiveThirtyEight qui utilisait un modèle développé par ESPN, appelé Soccer Power Index (SPI), pour prédire les chances de chaque équipe d’avancer à travers les étapes et de remporter finalement la coupe. Les analyses de FiveThirtyEight ont publié que le Brésil avait 45,2%, l’Argentine 12,8% et l’Allemagne 10,9% de chances de remporter la Coupe du monde.
    Les résultats de cette coupe du monde montrent la délicatesse de mesurer avec précision des aspects du beau Jeu de football avec l’analyse du Big Data.

    Reply

  • Jorge Roman Torres

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    El artículo redactado por M. Toma muestra el análisis presentado por FiveThirtyEight para predecir el equipo vencedor de la Copa Mundial de 2014. El modelo utilizado fue el llamado Soccer Power Index (SPI), desarrollado por ESPN, para predecir las posibilidades de los equipos en avanzar hacia la final y el eventual ganador. Al final de la copa el resultado no coincidió con la predicción. Esto demuestra que estos instrumentos no son infalibles. Por otra parte, el análisis de datos se ha tornado en un aspecto primordial en todos los ámbitos, el deporte, la industria, el comercio y áreas de servicio. El desarrollar métodos de análisis de datos es fundamental para la toma de decisiones.

    Reply

  • Samir MohamedAbdelghafar

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    Analyzing data in order to predict and using modern methods, it may or may not succeed, but what happened in the 2014 World Cup and Brazil’s defeat by Germany with a score of 7-1 was beyond expectations due to the poor condition of all Samba players and luck coinciding with German players

    Reply

  • Raoum

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    We still some distance apart from being able to accurately measure aspects of the World Cup Winner by using the SPI model.

    Reply

  • Msharey

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    We are still some distance apart from being able to accurately measure aspects of the World Cup Winner by using the SPI model.

    Reply

  • Njoud Badah

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    I Totally agree, We may have to find another model ?

    Reply

  • Nada Alomair

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    in my opinion the results of football matches can’t be predictable :)

    Reply

  • Hadeel

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    As this article is about predict based on analytical data over time and tracking the index of data. We are not at a point where we can use analytics to successfully predict the algorithm of an event. Needless to say, even though we may have hard data to make a comparison, it is extremely hard to base an objective based on a suggested pattern for a future result. in my opinion the results of football matches can’t be predictable

    Reply

  • Hanouf

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    Regarding the data analysis, it not just gives us the performance of certain KPI, but it can help us to predict the future performance of the KPIs by following the previous performance, then it helps us to create a predictive model for forecasting future events.

    Reply

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