Football, that sport that moves masses and awakens passions, has always been linked to statistics. From goals scored to passes completed, every action on the field is recorded and analyzed. However, in recent years, the arrival of Big Data has revolutionized the way this data is interpreted, opening up a new world of possibilities for coaches, fans and sports journalists.
One of the key concepts of Big Data in football is “expected goals” (xG), a metric that measures the quality of scoring chances that a team generates. It is calculated taking into account various factors, such as the position of the shot, the distance to the goal and the presence of defenders. In this way, the number of goals a team scores can be compared to the number they were expected to score based on the quality of their opportunities.
More news about Europe’s leagues
LaLiga: An unexpected champion according to Big Data
In the recently concluded LaLiga, Real Madrid were proclaimed champions after a disputed season. However, according to Big Data, Barcelona would have been the fair winner. The Barça team exceeded expectations by 7.80 points, while Real Madrid did so by 20.16. A fact that invites reflection on the influence of luck and other non-measurable factors on team performance.
Beyond the champion: Girona and Almería, two cases to highlight
Big Data not only reveals who should have been the champion, but also offers valuable insights into each team’s performance in different aspects of the game. In the case of Girona, Big Data highlights their effectiveness in front of goal, since they scored 14 more goals than expected, while conceding 9 fewer. A fact that reflects the defensive solidity of the Catalan team.
On the opposite side, the Unión Deportiva Almería is presented as the great victim of Big Data. The Andalusian team, which was finally relegated, obtained 22.40 points less than expected, an abysmal difference that reflects the difficulties they had in materializing their chances and defending their goal.
Premier League, Bundesliga and Serie A: Big Data also has a voice
Big Data has also yielded surprising results in other European leagues. In the Premier League, Arsenal emerged as champions, surpassing Manchester City in expected goals (14 vs 13) and conceding one goal less than expected. In the Bundesliga, Bayern Munich would have taken the title from Xabi Alonso’s Bayer Leverkusen if he had not conceded 13 more goals than expected.
Finally, in Serie A, Napoli, which finished 10th in the standings, would be positioned as the third team in the table, according to Big Data. A fact that invites reflection on the potential of the Neapolitan team and the opportunities they missed during the season.
In conclusion, Big Data is presented as a valuable tool to analyze the performance of football teams, offering information that goes beyond the simple final result. However, it is important to remember that data is not infallible and that luck and other non-measurable factors also play an important role in football.
Big Data is not an oracle that predicts the future, but rather a compass that helps us navigate the complexity of football with greater precision. Interpreting this data, along with analysis of other factors, can be an invaluable tool for coaches, fans, and sports journalists.
League |
Royal champion |
Champion according to Big Data |
---|---|---|
The league |
real Madrid |
FC Barcelona |
Premier League |
Manchester City |
Arsenal |
Ligue 1 |
PSG |
PSG |
A series |
Inter |
Inter |
Bundesliga |
Bayer Leverkusen |
Bayern Munich |
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