Johan Cruyff used to insist that players only have the ball for ~ 3 minutes per game.
So what makes a player great is what they do the other 87 minutes without the ball, walking/jogging/sprinting/zigzagging into space.
While data analytics is not new to sports, it has largely been absent from the world’s most popular sport until the past 5-10 years.
In this episode we had the privilege of chatting with Kostas Pelechrinis, an Associate Professor at the University of Pittsburgh’s School of Computing and Information where he leads the Network Data Science Lab.
Kostas along with co-author Wayne Winston, Professor Emeritus of Decision Sciences at the Kelley School of Business at Indiana University, wrote a fascinating paper to determine which positions contribute more to winning AND are undervalued by the market.
In this effort, they combed through ~ 20,000 games from 11 European leagues over a period of 8 seasons, as well as, player ratings from @easportsfifa!
Tune in as we get into the history of data analytics in soccer dating back to late 70’s, the current state of data analytics and how/if technology can be used to have more and better data.
What do you think of the use of data analytics in modern football?