We’re in the midst of a new age of football analysis: no-longer do managers and scouts need to rely on a trusted eye and an experienced mind. As has long been the case in the sport of baseball, football is becoming much more statistics and data-oriented, particularly when it comes to making football predictions.
Along with an increasing fondness for football statistics and analysis, technological advances are being applied to create football data science, which is being utilised across all levels of the sport. While these practices are relatively new as a tool of making football predictions, they have been deployed in the online space of gaming for many years, proving the worth of gaming data science as an efficient way of driving decision-making.
Driven by big data
Much like sports, online gaming is an entertainment industry, and within the industry, success appeared to come down to good judgement and talent. But thanks to the deployment of big data in online gaming as a form of gaming data science, operators of the best mobile gaming platforms are now able to analyse huge amounts of customer data derived from their activity to streamline their service.
Through the artificial intelligence used to analyse as a part of the gaming data science, customer experiences are tracked and transformed into gaming statistics to then predict the best approach to sending notifications and real-time offers as well as know the preferences of the player. This is so that the operator can offer the player promotions that they actually want to use.
But it’s not just when sending promotions and notifications that prove the value of gaming data science as even online gaming platforms analyse data to arrange its front according to user trends and behaviours. By analysing the gaming statistics of where visitors click and what they click on, the website can then adjust their presentation accordingly to offer different platforms better coverage.
Used throughout the levels of football
Football data science isn’t a football statistics analysis tool that’s restricted to the biggest clubs with the biggest budgets: it has been seen deployed even as far down as youth football. At Tanjong Katong Primary School, youth football teams are driven by football data science. However, while online gaming is a digitised space where data can be accumulated with relative ease, football predictions need to be made from data accumulated by more inventive means. The aforementioned primary school use drones to map out key moments of matches, as well as Micro Bits to collect data.
At the highest level, a club’s analysis team is proving to play an increasingly prominent role, with the examples of Philippe Coutinho’s free-kick against Brighton & Hove Albion and Hearts’ seemingly unpredictable 4-0 win over Celtic, both in 2017, being the results of big data-driven football predictions. It has been said that over 1,500 football teams around the world utilise the InStat’s big data system, which provides specialised football statistics on over 400,000 players.
The ability to make football predictions continues to improve as football data science becomes more widely used by clubs.