IT ALL STARTED WITH FORMULA 1 IN THE LATE ’70S
Formula 1 is largely, a data-driven business:
This late ’70s photo shows a Formula 1 car (a Tyrrell F1) equipped with a cassette recorder. Of course, we can say that the cassette was not intended to play the driver’s favourite songs during his race but had many other purposes, useful to the Formula 1 engineers.
We can say that this is the first example of the use of electronic data in sport. The engineers understood that, with the acquisition, storage and analysis of data, they could take the understanding of the dynamics of their cars to a much deeper and more accurate level and could acquire a competitive advantage by improving the performance of their cars.
It is widely acknowledged that Formula 1 was the laboratory for the development of automotive technologies; in reality, this is not the case for many of the complex technologies that surround us today, but perhaps, in one thing it can certainly be said that Formula 1 has been at the forefront since the ’80s.
The use of data:
The collection, transmission, storage and analysis of data, the creation of data analytics, the processing of virtual data and their study with the aim of improving vehicle performance and team competitiveness have always been the main tools with which technologies are developed in Formula 1.
Formula 1, thanks to the increasingly advanced technologies of data gathering, transmission, storage and analytics, has thus become, over time, a “data-driven” business.
A Formula 1 car is able to collect tens or hundreds of MegaBytes of data for every single lap, and, for every race weekend, tens or hundreds of Gigabytes of data are stored and analysed. Today, it would be impossible to think even of starting a car and launching it out in the pit lane without the constant real-time monitoring of data from hundreds of sensors. These data received through telemetry systems keep teams of engineers competing with each other to understand how to extract the best performance from their vehicle or to verify the diagnostics and the correct functioning of all the technical parts of the vehicle.
The world of data today and their use in sport:
In the ’80s, when Formula 1’s competitiveness was already based on the ability to collect and analyse large amounts of data, the Internet had not yet been invented, let alone the Internet of Things (IoT).
An IoT ecosystem consists of a set of smart objects connected to the Internet that, through the use of microprocessors, sensors, protocols and transmission technologies, collects, sends and operates on the data acquired from their environments. Data are sent to the cloud for analysis or otherwise analysed locally through an edge structure. IoT devices can also communicate with each other. Human intervention is not necessary, and IoT devices can work independently; human intervention will be required to manage configurations, give instructions and access data.
IoT technologies are spreading rapidly, with growth rates estimated at 12% per year. Moreover, we will have a number of always-connected objects that will already exceed 20 billion in 2021 and result in a turnover of more than several hundred billion dollars in a few years. Therefore, the IoT will increasingly be a set of pervasive technologies, and we will get used to having more and more objects “naturally” connected to the Internet.
Certainly, the search for competitiveness in the sport field has not stopped at Formula 1 and is now pervasive in every sport field, and much now passes in the ability to collect, transmit and analyse data.
Let’s look at these three aspects more deeply.
The acquisition of data:
The first aspect is certainly that of data acquisition. As we have seen, a modern Formula 1 car is equipped with hundreds of sensors (speed, positions, pressures, temperatures, accelerations and much more) whose data are constantly acquired and stored in the internal computer; these data are invaluable in allowing one to understand the very small variations in performance related to the change in multiple parameters and external conditions.
These data are transmitted outside the car thanks to modern telemetry equipment. Today, Formula 1 uses advanced systems to connect the car with the servers, thus anticipating the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) systems that, in a few years, we will see on all our standard cars thanks to transmission technologies such as 5G. Certainly, the same technologies can be used in any sport field.
The data management platform and data analytics:
Data analytics is the ability to interpret the collected data and extract analyses and conclusions thanks to increasingly powerful analysis and artificial intelligence (AI) software. Therefore, there is a need to have dedicated software and platforms to carry out the management and analysis of the collected data. Open systems can make data available through special web-based channels called application programming interfaces (APIs); this is to give third parties the opportunity to use the data themselves for the creation of innovative business models.
As we previously gave the example of how data has been integrated into Formula 1, technology has quickly become fundamental in all aspects of both amateur and professional sport. Now, an athlete’s data can be used to enhance their performance, examine and highlight their weaknesses. Additionally, technologies such as wearable smartwatches enable real-time reading of one’s physical condition, stress and fatigue level for both athletes and everyday individuals.
By comparing the athlete’s data with his previous performances or with the data of other athletes, we are able to generate a cognitive analysis; we can even predict the expected performance of athletes, not to mention predicting the game results. It is therefore possible through the study of physical parameters to optimise training.
In order to enable the acquisition of data from an athlete, there are many different types of wearable technologies, starting from simple smart bands that all of us can now wear on our wrists and going up to advanced tools, such as sensory bands or sensor-equipped vests that can collect in real time many physical parameters, such as Electrocardiogram (ECG), heart and muscle activities and respiratory rates, and correlate these parameters with the movement activity of the athlete in the sport pitch.
In addition, GPS sensors or indoor locating technologies, such as ultra-wide band (UWB), can provide detailed field location and movement information, evaluate the distance travelled, speeds and accelerations and produce a very accurate representation of the athlete’s physical efforts. The video analysis associated with the body data already collected can enhance the understanding of the athlete’s performance and weaknesses. Types of data analysis, such as spaghetti diagrams, can highlight patterns of incorrect movements and train athletes to improve their performance.
The data can provide very important information to improve the safety and health of the single athlete or the sport’s discipline, therefore reducing the chances of injury or improving hospitalisation techniques. Doctors, physiotherapists, athletes’ trainers and coaches, through the accurate study of the data made available to them, can minimise the probability of the athlete’s getting injured or even significantly reduce recovery time after an injury and improve rehabilitation techniques. All this is made possible by the use of sensors that produce real-time tracking of the athlete’s physical activity. Recognising excessive physical stress before the athlete gets injured is certainly an extremely valuable use of data.
AI algorithms can also play a significant role in obtaining data that allow for more informed decisions. For example, during a football game, we can make data-backed decisions on whether certain players should be replaced based on their fatigue level rather than the decision solely being placed by the head coach. Millionaire investments in top players are well worth the support of AI technologies that, in real-time, process all available information and suggest actions aimed at maximising the athlete’s and the team’s performance or minimising the risk of injuries.
Fans, spectators and the stadium of the future:
Another aspect that we certainly cannot overlook but that is fundamental in illustrating the potential of the use of data in the sport field concerns the involvement of fans and spectators.
Traditional stadiums are transformed into smart stadiums. Advanced technologies can increase revenues through the provision of innovative services or enable and create new business models. The stadium of the future is certainly a smart-connected stadium. Modern technologies suitably installed in the stadium will provide the possibility to create advanced services.
Fans equipped with smart wrist bands can enable technologies based on fan location, such as providing access to advanced stadium services or offering personalised services via fidelity and loyalty programs. Digital signage systems can provide timely and personalised information for each user in each area of the stadium, based simply on the viewer’s proximity to the screen. Virtual reality or augmented reality services via the use of smart glasses will enhance the stadium experience, creating a new viewing experience.
Links to social media will collect the voice of the fans to capture and better follow the feeling of the spectators during the game. Sharing the game’s collected data will allow greater involvement of fans in following the strategies of their team and opponents; it will allow profile-based advertising and the sales of services and merchandising, or even online games based on the current real game.
Big data will enable new services based on statistical data analysis and integration with mobile applications to deliver targeted messages. Opening up the data pools to the external realities of the stadium through the use of APIs will enable third-party applications and new business models. Finally, the robust identification of spectator identities (identity certification) will facilitate and improve security, support and admission services and ticket sales, and, by equipping a stadium’s operators with connected devices, will improve and facilitate staff operations.
The video assistant referee (VAR):
We’ve seen how data can be the key to improving performance, from a Formula 1 vehicle to an athlete’s performance, how they can decrease the chances of an accident or speed up physical recovery after an injury and, finally, improve spectator engagement, improve revenues and generate new opportunities and business models, but one last aspect is worth mentioning; the video assistant referee (VAR) is the referee’s assistant via a video link, which supports football games across Europe.
The VAR works in a specially equipped room inside the stadium; his task is to support the referees’ decisions through the analysis of video data of the game in play. The VAR has been in play since the 2016 World Cup to support arbitration decisions or to prove, for important games, incidents that the referees might have missed. In the case of dubious actions, the referee can call the VAR for radio consultation; at this point, the VAR examines the video data and sends the result of his analysis of the video data to the referee in a special area outside the football pitch’s side-lines, called the referee review area. In conclusion, the analysis of video data allows the referee to take arbitration decisions in controversial cases, thus improving the regularity of the game and eliminating possible disputes between opposing teams.
Alessandro Iacoponi Director IoT Council,
EU Tech Chamber