I am form a Country – Portugal – that has in Soccer (in Europe we call it Football) its main National Sport.
All over the whole Country everyone is kind of obsessed with the game, but in a honestly healthy way, because we have got a tradition of having a respectful pool of young talented players – like Cristiano Ronaldo, time and again considered the top player in the World -, and our young normally dream of a career and prospects similar to the incredible athlete that born in Madeira some 30 years ago. This is nothing but a dream, and sometimes as a country we should encourage our most young to pursue other kinds of dreams instead.
Anyway I’m posting on this subject in line with what was the most rewarding read of the day. I also once was one of those young Portuguese who dreamt of being a Ronaldo. But soon enough I shifted to my other love: science and technology, and was lucky and hard working enough to pursue Higher Education studies on those subjects.
This article by Jure Rejec in Data Informed is a precious piece about the growing importance of Big Data technology in precisely Soccer game. Big Data is becoming also important to other Sports, for instance motor racing Formula 1, and others. But this article caught my attention for the level and amount of detailed possible use cases of the technology in the game of Soccer.
Of notice also is the increasing use by Clubs and their Coaches of simulation and Virtual console games to help them with the best decisions, like the sometimes difficult taks of choosing the right player for the various positions: what is called fantasy games. As this excerpt well describes:
Operators of fantasy soccer leagues generally use a limited number of stats, normally from 5 to 20, to sum up a game. However, Oulala Games Ltd has built a mathematical matrix that uses Opta’s data to create an efficient scoring system. This company’s platform uses a sophisticated algorithm to assess the crucial aspects of an athlete’s performance that contribute to an overall result. Their system includes a total of 70 different criteria dependent on a player’s position (keeper, defender, midfielder, and striker) resulting in a total of 275 ways to gain or lose points.
Not only that. In scouting for which players to select for hire and to help in the development of roster decisions, Clubs increasingly rely more on Technology. Not surprisingly the boards of decision in the Clubs and its Corporate partners features a Computer Science and Data Analytics expert in an advisory role:
This type of analytics is useful for clubs when scouting and to help shape roster development decisions. Perhaps the best-known advocate of this approach among top managers is Arsène Wenger. The Arsenal manager once said that the personal touch in player scouting remains decisive, but the computer-generated statistics can certainly help his management to find a player they need. Not surprisingly, back in 2012, the English club even bought U.S.-based data company StatDNA, which provides expert analysis, guiding everything from identifying new players to post-game tactical analysis.
Big Data, Sports and Physiological indicators
The other aspect of the article that I thought was quite relevant had to do with the issue of Big Data used as monotiring tool of physiological indicators and signals of the players. Using advanced statistics, devices developed by companies such as Adidas, and the ability to connect the devices with techniques such as Internet of Things, this is a combination that transforms, enhances and give credit to technological applications in Sports:
The Germans, known for their technological know-how, leveraged the Internet of Things and raised a few eyebrows when they wore Adidas’ miCoach elite team system during training sessions before and during the competition. The wearablemonitoring devices collect and transmit information directly from the athlete’s bodies, including heart rate, distance, speed, acceleration, and power, and display those metrics live on an iPad. All this information is available live to coaches and trainers on the sideline during training, as well as post-session for in-depth analysis. Analysis of the data can help identify players who could use a rest.
In a previous post we already gave the description of Big Data, Data Analytics and related techniques and fields of technology development being implemented in areas such as Healthcare; the application in a Sports setting is actually a complementary step. It won’t be soon enough and we will see other more unexpected use cases in other fields.
Catapult Sports, Big Data and GPS
Such fields could well be Astronomy, Astrophysics or Telecommunications broadly speaking, that already are with an eye close to developments in Big Data and certainly deploying the technology in their demanding Data Management requests and day-to-day business needs. In the article we could read that the Australian company Catapult Sports uses Big Data with global navigation satellite system (GNSS) data to measure and access players’ movement and fatigue levels:
Australian company Catapult Sports uses global navigation satellite system (GNSS) data to measure player movement and fatigue. The company also has a local positioning system, called ClearSky, which can be installed around the indoor area of the stadium when obstacles, like a closed roof, interfere with satellites’ ability to lock on to individual units. ClearSky uses anchor nodes to track players’ movements. The devices are worn at the top of the back, held in place by a compression shirt that looks a bit like a sports bra and can be worn over or under a players’ uniform.
Absolutely awesome read of the Day in the Data and Information Age…