Farhang Farid, IBM’s associate partner of global business services, told TGG: “In the last 10 to 15 years there has been a lot of focus on an analytical approach to the athlete performance and most of this has been focussed on structured data – measuring movement, resting heart rate and so on.
“But there is a lot of data out there that is unstructured – any text, images, videos – and this is shaping up to be the next horizon of data analytics. A lot of content is being generated by most athletes – pictures they are putting on Instagram, Tweets, Facebook posts, interviews with clubs websites or other publications, psychological tests they have participated in and so on.
“We can feed this data into Watson and he has the ability to decipher the language, the context and create connections and provide insight. We are working on creating overall sentiments for coaches and scouts that can help them decide whether a player will be passionate enough, whether he will gel with the team, or if he will have any issues of character we are going to have to be aware of.
“Teams invest a lot of time and money on understanding performance but one simple character issue can impact the team and whole organisation. We can use Watson to give them that sentiment. We can also look at historical players and try to identify players who are similar from a character perspective.”
Watson - named after IBM’s founder Thomas J Watson - is a Cloud-based tool which can be integrated into a club's or company’s products. It has already been widely adopted (the company believes a billion people will have used it by the end of the year) but its use in the field of sport is relatively new.
Farid explains: “One of our experiments is to go through Instagram photos of potential College draft players and map that against team schedule and try to derive insights. If we see pictures of an athlete partying the night before a game on multiple occasions – which involves teaching Watson what partying looks like – that is a sentiment we can communicate to team managers.
“The ultimate goal is to define any small piece of information that could be useful for consideration of a potential signing. There’s a ton of data out there. In the recent NFL draft, a player [Laremy Tunsil] was being picked at a high round and someone dug out a picture of him on social media smoking a bong.
“That could have multiple levels of impact – it could tell you something about the character but also have a huge impact on the overall perception value or organisational value of a club. Those are things you want to look at and see how you want to manage it."
As they say, knowledge is power. If a club is aware of potentially damaging information like this, they have options - perhaps not to sign a player, or at least carry out damage limitation, by getting them to delete the information for example.