Using AI to Scout Sports Talent

18

September

2024

4/5 (2)

More than 1 million people in the Netherlands play football under the Royal Dutch Football Association (KNVB), while only 26 men and 23 women make it to the national team. Scouting the right talent in the early stages of their career is an art itself, and professionals are trained to find the few players that grow out to be one of the successful ones. These scouts use data such as speed, goals, completed passes among others, but also review the role a player has in a team outside of these metrics. Is talent quantifiable in every aspect? Or do we need the human skills of a football scout to find the needle in the haystack?

Nnamdi Emefo, CEO of Afriskaut, spoke to the Global Business Report about using Artificial Intelligence to scout for young African sports talent. He talks about the model he built over the course of five years, where he now is able to extract all statistics from a video of a football match within 24 hours, for all 22 players on the field. He created a platform where all this data is available for the whole world to see (against payment). You might think, what is new about that and why can big professional football clubs not generate this theirselves? Nnamdi’s platform is so valuable that even the big clubs like Bayern use his platform. And it is not just football, other sports like tennis or basketball can also be converted into statistics by Nnamdi’s model.

And it appears to be successful in scouting talents. Right now African basketbal players are scouted using this model. These players were successfully matched with clubs in higher divisions. His model is not only able to generate a personal file of performance statistics, but is also able to see if there would be a match with a possible transfer team, taking all data of current players in that team into account.

Another success story besides in basketball can be found in football again, young African boys are also scouted for the youth teams of professional European clubs. His data base is used to find the optimal match that is a fit for both the player, as the team as the club. This way he gives young African boys the opportunity to be taken serious by European clubs, by providing them to prove their worth with data. He believes his model had the ability to mitigate racism in the scouting process, and thrives to be the key player in the scouting proces in the sports industry in Africa in the next couple of years.

See interview here: https://www.youtube.com/watch?v=74pzE6AofG4

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