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How Big Data Can Predict Football’s Rising Stars

Jure Rejec / 3 min read.
May 16, 2016
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Did you know that Big Data can help us predict who the future soccer stars will be? This is precisely what happened in Riyad Mahrezs case, PFA Player of the Year, who has conquered the English Premier League with Leicester City.

During last years Big Data Week Conference in London, Malta-based entrepreneur Valery Bollier correctly foresaw that the Leicester midfielder would be the player to keep an eye on (scroll the video in 17 minutes 41 seconds). ”I’ll give you a prediction for this season: there is a footballer, named (Riyad) Mahrez.

According to our game, he is at the moment the best midfielder in Europe, not just in England,” said Bollier during the presentation about Big Data, sports and online games back in November. ”I bet that at the end of the season his value will be huge.”

Oulala's scoring system

How is it possible that Bollier gave such an accurate prediction? The answer to this question is the power of big data and information, which is collected during football matches. This means that the actions occurring on the field are converted into numbers through the use of mathematics and computing power.

Bollier is the co-founder and CEO of daily fantasy sports operator Oulala.com, which is known for its sophisticated mathematical matrix. Oulalas system includes 70 different criteria dependent on a players position (keeper, defender, midfielder, striker), resulting in a total of 275 ways to gain or lose points (left). These range from the usual goals and assists to the more detailed shots on target and successful tackles, amongst many others, making it as close to football reality as possible.


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Consent

Despite the fact that there were 6 players in total to win the award for the PFA Player of the Year (Riyad Mahrez, N’Golo Kante, Jamie Vardy, Harry Kane, Dimitri Payet and Mesut Ozil), it wasn’t hard to guess who the winner would be: according to Oulala, Mahrez has been the best Premier league player so far with 1161 overall points in 36 appearances, and the sixth best player in Europe only behind Lionel Messi (1677), Neymar (1530), Zlatan Ibrahimovic (1451), Luis Suarez (1334) and Cristiano Ronaldo (1245). In the Premier League, the 25-year-old Algerian is followed by teammate Jamie Vardy who has collected exactly 1000 points in 35 matches.

Kevin de Bruyne 
As you can see in the video above, Bollier further explains that the player who attracted lots of attention last season was Kevin de Bruyne (left), from Wolfsburg (Bundesliga): ”Three, four months after the beginning of the season we usually start seeing unknown players from small teams that start over performing in our game.”

They have more points than they should. Usually at the end of the season these guys are bought by big clubs.”

De Bruyne, the Footballer of the Year 2015 in Germany, was later signed by Manchester City for a transfer fee of 58 million (74 million).

What about Mahrez, who has won the Premier League sensationally with the Foxes? Will he earn himself a move to a ”bigger” club? Despite the fact that he currently has a contract with LCFC that will keep him in the club until June 2019, there is no doubt that his numerous suitors will be making big money offers.

Categories: Big Data
Tags: analytics, big data analytics, big data use case, digital data, Football, insights, prediction

About Jure Rejec

Jure Rejec has a profound understanding of both ends of the media spectrum, having spent seven years as a journalist, and four years as a B2B marketing and public relations professional. He is a contributor to various B2B publications, and an all-rounder for Viberate.com, a global music platform that joins all music professionals and helps them discover one another.

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