Football. Soccer. The beautiful game. Whatever you call it, the world's most popular sport is being transformed by a Dutch start-up bringing AI to the pitch.
SciSports, founded in 2012 by two self-proclaimed football addicts and data geeks, is innovating on the edge of what is possible. The sports analytics company uses streaming data and applies machine learning, deep learning, and AI to capture and analyze these data, making way for innovations in everything from player recruitment to virtual reality for fans.
Player Selection Goes High Tech
In the era of eight-figure contracts, player recruitment is a high-stakes game. The best teams are not those with the best players but the best combination of players. Scouts and coaches have used observation, rudimentary data, and intuition for decades, but savvy clubs now are using advanced analytics to identify rising stars and undervalued players. "The SciSkill Index evaluates every professional football player in the world in one universal index," says SciSports founder and CEO Giels Brouwer. The company uses machine-learning algorithms to calculate the quality, talent, and value of more than 200,000 players. This helps clubs find talent, look for players who fit a certain profile, and analyze their opponents.
Every week, more than 1,500 matches in 210 leagues are analyzed by the SciSkill technology.
Armed with this insight, SciSports partners with elite football clubs across Europe and other continents to help them sign the right players. This has led to several unexpected-and in some cases lucrative- player acquisitions. For example, a second-division Dutch player did not want to renew his contract, so he went out as a free agent. A new club reviewed the SciSkill index and found his data intriguing. That club was not too sure at first because it thought he looked clumsy in scouting-but the data told the true story. The club signed him as the third striker, and he quickly moved into a starting role and became its top goal scorer. His rights were sold at a large premium within two years, and now he is one of the top goal scorers in Dutch professional football.
Real-Time 3D Game Analysis
Traditional football data companies generate data only on players who have the ball, leaving everything else undocumented. This provides an incomplete picture of player quality. Seeing an opportunity to capture the immense amount of data regarding what happens away from the ball, SciSports developed a camera system called BallJames.
BallJames is a real-time tracking technology that automatically generates 3D data from video.
Fourteen cameras placed around a stadium record every movement on the field. BallJames then generates data such as the precision, direction, and speed of the passing, sprinting strength, and jumping strength. "This forms a complete picture of the game," says Brouwer. "The data can be used in lots of cool ways, from allowing fans to experience the game from any angle using virtual reality, to sports betting and fantasy sports." He added that the data can even help coaches on the bench. "When they want to know if a player is getting tired, they can substitute players based on analytics."

Questions for Case 6.1
1. What does Sci Sports do? Look at its Web site for more information.
2. How can advanced analytics help football teams?
3. What is the role of deep learning in solutions provided by Sci Sports?