AI algorithms are changing the way scouts analyse player performance
Involvement of AI in sports is changing the dynamics of scouting talent not just at the top tier but at the domestic level as well, thus making the process more objective, efficient and inclusive.
The expansion of the sports industry across the world, but more specifically in India, has been nothing short of astonishing. The number of people wanting to pursue a career in sports or even wishing to take the next step in their sports journey has increased significantly. This has led to a rising consciousness regarding digitising the sports ecosystem and adapting to technology to expand the reach of sports. And this is seeping into the grassroots sports ecosystem as well.
The need for video broadcasting and live streaming sports events that are happening below the pro tier level is a testament to the readiness of the sports community to modernise the ecosystem from bottom up.
The sports-tech industry is exploding with newer technologies coming into play. With more and more broadcasting and data capturing and fan engagement tech startups bursting onto the scene, the sports-tech segment has evolved into an industry of its own.
As we understand the functionality of grassroots sports, we are looking at yet another revolution ready to unfold—the AI revolution. Involvement of AI in sports is changing the dynamics completely not just at the top tier but at the domestic level sports industry as well.
Traditional methods of scouting: Challenges and impact
Looking at the sheer scale of the grassroots sports community in India, the biggest AI intervention/adaptation has just started to take shape by bringing in a paradigm shift in the way scouts look at analysing player performances.
This may seem like a sudden AI wave that is taking over the sports ecosystem but, in reality, the need for revolution has been long awaited, with an enormous number of emerging talented athletes yearning for an opportunity to be seen by the scouts and the traditional scouting method being restricted because of various factors.
The traditional methods of scouting always required a combination of art and science. It is a known fact that analysis and further decision-making could be skewed by the subjective judgement of the scouts who would watch the players in action. The situation had gotten to a point, at the local level, where the basic instinct to understand the player performance from an objective, analytical data-based perspective took a backseat. And the unavailability of data catered to this behaviour.
But the bigger impact it had was that the inability of scouts to be present at every single place in a given amount of time resulted in many of the talented players remaining undiscovered. As a result, the sports community, as a whole, lost out on promising future sports stars.
AI revolution drives talent discovery
The involvement of AI in the talent discovery process reduces the probability of misjudgement significantly. AI thrives on data, and today data is everything. Sports associations are realising that having access to that extra piece of information about a player’s game is just the leverage that can help the team go across the finish line.
Today, the demand for the minutest data point from a domestic-level match has increased notably. The fact that sporting associations—such as the Maharashtra Kabaddi Association, Nashik District Cricket Association, and Football Delhi Association—are looking to digitise their events, with the sheer purpose of getting detailed player data, tells us about the direction in which the domestic sports ecosystem in India is headed.
AI tools are the perfect segue for these associations to process enormous data, not just statical but video data as well, and provide critical insight to the scouts.
AI also comes with a huge positive impact in levelling the playing field for all the sports ecosystems that have historically been sidelined for various reasons.
AI can eliminate one of the biggest limitations of the traditional method of scouting—scouts not being present everywhere at the right time, thus missing out on discovering some of the most promising talents.
Broadcasting local games is leading to a simplified process for the generation of player-specific data and player-specific game footage in real time, thus aiding AI technologies to further analyse the information.
What’s promising is that the domestic sports associations, sports clubs, and top-tier sports franchises from the mainland, the rural areas, and the remotest parts of the country—such as the Raigad District Kabaddi Association or the Ladakh Football Association—are understanding the changing dynamics and demanding not just live streaming of the games but also detailed scoring for each match and exclusive access to player data and player-specific game footage.
AI is certainly rewriting the game’s rules, making scouting more objective, efficient, and inclusive. I look forward to what’s in store for the lesser-known sports, regions, and underprivileged talent as the AI evolution goes further ahead, ensuring that true talent—regardless of where it emerges—is recognised and discovered.
The author is Founder and CEO, SportVot, a platform that supports Indian sporting talent.
Edited by Swetha Kannan
(Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the views of YourStory.)