How data analysis and Machine Learning are revolutionizing Football

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Data is becoming the new axis of revolution in many sectors, but in this article I want to focus on the world of sports, where the revolution has already begun and what is to come is very promising.

The beginnings of the idyll of sport with data analytics

Baseball already experienced this change when Oakland Athletics coach Billy Beans revolutionized the nba중계 in the 1990s by being the first to use data intelligence. At that time everything was based on big budgets and having big stars in the team. The signings were achieved based on scouts who went around the different states looking for new talent, but they were based on their intuition and experience nothing more.

The Oakland Athletics had no financial means, and Billy began collaborating with a young economics student named Paul DePodesta on a mathematical system that predicted the most “profitable” players (those who contributed more runs for less money) based on their game statistics.

If you want to delve deeper into this story, I recommend the movie “Money Ball:

Breaking the Rules” (2011) in which you can experience this revolution and listen to mythical phrases such as: “The people who run the teams think about buying players. They should not think about buying players, but wins. And for that, they need to buy races. “The 5 axes on which data analysis is revolutionizing current football

With the aim of ordering all the advances that are being achieved in the world of football thanks to this type of technology, I have organized the information based on 5 axes:

  • Trainer: Improved Strategy
  • Players: Improving technique
  • Fans: Improving the experience
  • Medical Equipment: Improving Injury Prediction
  • Betting: The prediction of match events and results

As you will see below, data is the new gold, and different football clubs and organizations are collecting as much data as possible because they know it will give them a competitive advantage.

Trainer: The improvement of the strategy

A key point where data-based prediction tools can help is in the analysis of the strategy proposed for the match and the prediction of the result.

Many advances are being made in this field, and an example of this is the Disney Research project (yes, Mickey Mouse’s) that uses Deep Learning and the “Data-Driven Ghosting” method to predict the probability of a goal in a play your team’s defense versus how a typical or average team in your league would have defended it.

In this way, you can analyze if the movements of your defense are better or worse than the average in a specific type of play and improve them. The following video explains how (in English): Players: Improving technique.

Game data collection devices have been proliferating in the world of football for some years now.

Known as “wearable ”, they are intelligent electronic devices incorporated into clothing and that allow us to collect medical data (heart rate, breathing, temperature, etc.) and physical data (position, speed, acceleration, etc.) of the player during training and games. matches.

The Oakland Athletics had no financial means, and Billy began collaborating with a young economics student named Paul DePodesta on a mathematical system that predicted the most “profitable” players (those who contributed more runs for less money) based on their game statistics.

By aamritri

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