How Data Science is Shaping Football?
Ten years ago, the data used by football clubs were limited to stats on goals, shots, numbers of corners, possession etc. This data has limited value to coaching staff. Also, the typical stats we see on TV do not, in themselves, help teams win games.
The most important one football data came in the form of on-the-ball event data. Which include x-y coordinates of every pass of the ball, every defensive action, every shot, pass completion etc of every player.
To be able to deal with and analyse event data there is need for some programming, preferably in Python or R. Also the basic statistical modelling knowledge will help to analyse data easier. Expected goals is a logistic regression model. Passing models use either logistic regression or basic neural networks. Algorithms are used to correctly identify the players’ positions and body orientations in real-time along with machine learning & computer vision technologies. Data analysis of these every action by each player on the pitch determines its goal probability or how it affects the team’s chances of scoring. All this makes it possible with the help of a team of data scientists.
How Data Science Use In Football?
- Scouting:
Data analytical scouting tools hold a large database of players to help clubs to identify certain players to match their playing style.
- Performance Analysis:
Football clubs with the support of data, easily understand how a team or player has performed over the course of a match or season. For that Big data analysis helps them to discover counter-intuitive facts about football, upon which the club can build an innovative and winning strategy.
- Player Development:
Data analytics is also growing in importance when it comes to youth development. In player development, data analytics becomes a tool to help predict and cultivate players’ potential.
- Injury prevention and rehabilitation:
Data from GPS tracking system & other tools were analysed. It help to gain better insight into players’ fitness, readiness to perform and fatigue, and improve the quality and efficiency of players
How Big Football Clubs Are Using Data Science To Improve Their Performance?
- Liverpool FC:
Premier league football fans must have remembered the 2019, Liverpool FC season, when LFC ended a 30-year wait to be England’s top-flight champions. Many may not be aware of Data Science is also one of the reasons that help them to qualify for UEFA champions league.
Club management of Liverpool FC was in favour of using data science to improve their performance. So, LFC’s research division evaluates players and sporting trends by crunching numbers. This has enabled the Reds to gain a strong understanding of what’s called “Pitch Control.” Using graphics, such as the images included in this article, the team is able to see how best to utilize the pitch, hence the name “pitch control.” The combination of event data and tracking data is the key to Liverpool’s data success. It helps them understand how each action on the pitch impacts their probability of scoring a goal. There is no need to surprise to know that in 2019 season LFC is the club has conceded at least seven fewer goals than any other Premier League team thanks to data science,
(Liverpool’s pitch control concept considers which areas of the pitch are best to use at any given time, Source: Liverpool FC)
2. Manchester City FC:
Manchester City Fc, (owned by City Football Group) another English premier league team experimenting with technology in a bid to move clear of their rivals. They already have a data science team which is expanding by recruiting more data scientists & experts. One of such expert, is former astrophysicist and Treasury policy adviser Laurie Shaw who is employed in the data science wing of the club as ‘Lead Artificial Scientist’ in January 2021. Also, MCFC partnered with google for artificial intelligence competition which ran until December 2020. It challenged tech enthusiasts to develop artificial intelligence ‘agents’ effectively a player within a match situation and programme them to react to normal in-game situations. All these efforts are showing results, in the current season(2020–2021) Manchester city FC already occupy top spot of points table.
In the modern game, the use of data is all about finding the extra 1%, the detail that can exploit even the slightest weakness in the opposition and make the difference between winning and losing. So not only top clubs like Liverpool, Barcelona FC, Manchester FC are taking advantage of data science but also the majority of clubs are using science to improve their game.
As the use of data & technical analysis is increased the demand for Data experts are also increasing not only in football but in other fields too. India is the second-highest country next to the US to have generated the demand to recruit about 50,000 Data Scientists for 2020–2021. Accenture, Myntra, IBM, TCS, Capgemini are some MNC’s that offer job opportunities for data scientists with packages starting from INR 3.65 LPA. The traditional educational system is not ready to produce qualified data scientists but institutes like TryCatch Classes offer data science training program to help aspiring data scientists.
Conclusion:
Data science has proven to be a decisive factor in the football and sports industry in general. The insights gained from data can make a huge difference in key moments during the game. Football as well as many other industries has evolved with the use of data. If the available data is used appropriately with right technology it has the potential to revolutionize sports and other sectors where data science is applied.
