Can AI become the legal dope for sportspersons?

I've always believed that the best of the role models that each of us ordinary people can relate to and derive our personal motivation from – mostly, tend to come from the field of sports.

Be it lawn tennis, football, cricket, badminton, snooker, basketball - you name it - each has produced legends who have gone on to become lifelong role models to people even thousands of miles away and in walks of life which are totally unrelated to the sport in which the legends have managed to achieve greatness.

When heroes tumble

When these role models fall in the eyes of their ardent fans - by trying to excel but by adopting illegal means – then, that renders the biggest blow to their fans which is harder to digest than any major defeat that their role model would have suffered in their entire career.

Unfortunately, we have seen this happen time and again across all kinds of sports such as cricket, cycling, athletics, tennis, football, to name a handful.

Without being sympathetic or supporting the undue means adopted by these fallen heroes, what is, for sure, a fact is that at the start of their journey into the dark side, they all would have had only a good intention at heart before they went astray in choosing the wrong means to achieve their goal.

Constant need to excel, sometimes, pushes one into the wrong way

One may attribute their fall to peer pressure or unrealistic expectations but it is always with the objective of trying to do something to achieve that has not been done before.

This is where I personally believe that technology, especially AI, can play a big role in coming to the aid of potential future role models and prevent them from going astray.

AI could be the new legal dope which can aid professional sportspersons of the future to try and out-perform themselves by pushing physical and imaginary boundaries like never before. And the good news is already here and helping sports rise to newer heights of glory.

AI is already changing sport for the better

Consider this mindboggling difference in winning race statistics 115 years apart (Yes! you read that right - separated by more than a century) from the Tour de France¹

Can AI become the legal dope for sportspersons?

Digest this: In 1903, the 2^nd placed guy finished nearly 3 hours after the winner had crossed the finish line while this year, the gap between the winner and the runner-up was a mere 111 seconds.

This is partly due to the human endurance that constantly strives to push the limit but now, complemented by technology such as AI, it is helping us push those boundaries further.

A wonderful BBC Study³ shows how the technicians from each of the teams collate various data parameters that high-end computers analyze in real-time and give back invaluable insights.

Parameters such as the speed of the cyclist, duration cycled on the given day, the wind speed, gradient of the incline, angle of a sharp turn, distance to the next refreshment zone, distance to the current stage finish line etc. are captured and compared against historical data on a similar weather condition and against past participants - all in a matter of minutes if not seconds - and clear tactics drawn from the analysis that could make the difference between the winner and the rest are relayed back to the rider.

As Mr. Simon Smart⁴ of Smart Aero Technology explains, “The trick here is in developing the tools that can measure the smallest of differences. Once you can measure the small differences, you can spot the small gains and add them up to give your team that edge”.

This is happening not just in cycling but in almost every other competitive sport.

In Tennis for e.g. IBM⁵ is helping generate amazing AI-driven highlights for both the enjoyment of the fans as well as in aiding the players to constantly get better. Similarly, in the DRS (Decision Review System) in cricket, critical decision making is now up to AI influenced systems.

In the highly acclaimed HBR, Thomas Davenport⁶ wrote about competing on analytics and how businesses like banking, retail, hotel management etc., are finding a leading edge of doing business by efficient data analytics. Now with AI getting stronger and reaching more businesses and, in turn, touching those people who use those businesses, AI-driven analytics is giving another paradigm shift in terms of reimagining businesses from a customer point of view and this has started making its presence felt in sports as well.

Every aspect of many sports today is highly competitive, be it an individual or a team discipline.

With each new corner we turn, aided by AI-driven moderations, we are certainly moving towards a future where sports will become more enjoyable, highly balanced and mainly free from opportunities to cheat.

Hence my belief that in the long run AI will be the legal dope that will enable all sportspersons to excel.

References

¹Tour de France

Tour de France consists of 21 day-long segments (stages) over a 23-day period and cover around 3,500 kilometers (2,200 mi).

There are usually between 20 and 22 teams, with eight riders in each. All of the stages are timed to the finish; the riders' times are compounded with their previous stage times. The rider with the lowest cumulative finishing times is the leader of the race and wears the yellow jersey.

²Tour de France winners’ classification

https://en.wikipedia.org/wiki/List_of_Tour_de_France_general_classification_winners

³ BBC Click & Dimension Data at Tour de France

https://www.bbc.co.uk/news/av/technology-44959461/the-tech-helping-drive-the-tour-de-france

⁴ Smart Aero Technology

https://www.bbc.com/news/technology-23312810

⁵ AI transforming Tennis

https://www.bbc.co.uk/news/av/technology-44781898/how-artificial-intelligence-is-transforming-tennis

⁶ Harvard Business Review Competing on Analytics

https://hbr.org/2006/01/competing-on-analytics

About the Author

Nagesh Mallikarjun has over two decades experience in the IT industry and is an Automation Coach with Wipro Ltd.

He has held various positions across the spectrum of the delivery life cycle in multiple business units, donning the roles of a developer, analyst, support engineering, test manager, project manager and delivery manager.

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