What was once rightly held as one of the most dynamic games to be ever played, has come under the scanner of numbers.
With technological advancements and the game, itself conforming to such changes, football can now be played as both an active sport as well as a game of numbers. Thanks to data analytics and big data compilation, here is how football is changing for good.
The idea of data compilations and playing with numbers was initially meant for a very niche crowd. Rather than the general populace that enjoys watching a competitive game of football, it was catered to the audience who try to gather more information about the intricacies of the football betting world.
You know, one where numbers, game predictions, hardcore stats carry great meaning. This soon took a turn when the game of numbers reached the wider demographic. Not only did this pave the way for a more analytical sense of the game, but also built ramifications that helped a lot of youngsters get into the limelight.
The world of football has seen a shift in playing styles as much as iconic players. Despite it being a hard pill to swallow, now that the Ronaldo-Messi era is coming to a slow but sure termination point, scouts are in their acumen of vigilance. After all, no young talent should be wasted—and this is where data analytics are being used with purpose. Youngsters are being scouted on the basis of their performances in their respective domestic leagues or otherwise, with ease.
Gone are the days when scouts had to be physically present, witnessing a sombrero during training sessions. Thanks to resourceful data compilation, scouts can pick youngsters based on the numbers and detailed analyses they acquire from their respective clubs. Granted, it is always more beneficial to see the player in action before returning home with intel, but data analytics come in handy when physical distance becomes too insurmountable a barrier.
Small Clubs, Big Minds
Along the lines of intelligent scouting, it is also a known fact that data analytics is a major tool used by small clubs to keep themselves relevant.
How, you might ask? Riyad Mahrez took the world of English football by storm. When the all-time favorites, Chelsea, were dethroned, it took everyone by surprise, and the PFA player of the year (2015-2016) undoubtedly had a major role to play. When he was sold to City for a whopping 60 million, it made “top 6” clubs like Leicester more relevant.
While this is just a microcosm of the entire transfer scenes that commence in the world of football, the role of data analytics cannot be ruled out.
It is only because of data analytics that each player can be marked and studied. Bigger clubs like City tend to focus on these attributes which help them solidify their signings. This, in turn, gives smaller clubs a broader window to play such youngsters for a longer time. As stated before, these help the smaller clubs be more relevant. After all, it is them who are providing shelter to the careers of such marvelous talents, and data analytics is but the catalyst in such reactions.
More Competitive Football
Have you ever wondered how the shift from football playing styles over the past decade has been so overly drastic? How has football become so fast-paced? How do leagues have such competitive teams, which were previously close to nominal, or even irrelevant? Once we have moved beyond the signings, the more obvious impact of data analytics comes into light.
Training sessions are important, work ethic is pivotal, and proper management is significant; however, the concoction of all three pale in comparison to the impact data analytics has played, and here is how.
Clubs have shifted from sharpening their own players in a multifaceted way, to training players according to their next opponent’s weaknesses—it is just the way of modern football. As important it is to develop and work on one’s own skill set, it only makes more sense if you are also aware of your foe’s weaknesses. Since data analytics has placed it all on the table, it is only a matter of curation and creation. Unless you know how your opponent plays, you will only be heading towards a training cul-de-sac.
The Bottomline—What it Means for the Fans
Football fans are erratic, and in a good way. The energy content in the said fanbase is truly remarkable. With the shifting paradigm of what an ideal player or team or match is, so is the idea of debates among fanbases.
Data analytics has given football fans stronger clauses to root for their teams and favorite players. Numbers, stats, figures, everything is just a couple of clicks away. Thanks to data analytics, football fans can now have sound debates that are based on facts than emotions, and while that might make the discourse more mechanical, it certainly solidifies it on pragmatic grounds.