Dhiraj Adya – COO, Tech Mahindra Global Chess League (GCL).
Although I played chess as a child, my recent appointment as the COO of a franchised chess league has helped me experience the pastime through a completely new lens. This experience has helped me draw parallels to other sports and recognize how chess offers unique insights that leaders, especially in the sports-tech space, can learn from.
The main thing is that the rules in chess are simple; all the outcomes are transparent, and every decision is measured. In this way, there is less clutter in the data. I think such high-quality data can provide an ideal foundation for testing hypotheses with modern tools and technologies, including AI, data analytics and fan engagement strategies.
A Test Bed For Decision Making
Most sports generate messy, fragmented data streams that include everything from climate conditions and officiating reports to performance tracking systems, video replays, wearable sensors, injury reports, team formations and even data on human interactions. All of these variables unfold simultaneously, making it a challenge for analysts to interpret and extract meaningful insights.
Chess eliminates this data noise, for every position in chess is discrete, logged and outcomes are simulated across millions of scenarios. The real art lies in taking this clean signal generated by the game and using it so innovative teams can pressure-test AI models.
Some of the use-cases include pre-match prep, game-tree analysis, opponent profiling, real-time decision support and scenario modelling. These are all common needs of coaches and managers across sports.
As can be seen, chess provides a unique place for coaches and executives in other sports to map human intuition with machine-generated probabilities for faster, unbiased decisions.
The main lesson here is to test your hypothesis, pilot your models and perform analytics in an environment where data is complete, clean and the feedback cycle short. Then, after validating your method within this sandbox, replicate the approach and apply it in more complex sports environments/scenarios.
Real-Time Visualization: Turning Insight Into Story
The most powerful technology fails in sport if it can’t be understood in the moment. Chess has pioneered an “explainability layer” that other sports can adopt: live evaluation bars to show advantage shifts, suggested variations to illustrate “what if” scenarios and heat maps that make strategic intent visible to casual fans.
This matters commercially. When audiences can follow the “why,” they are more likely to continue watching. Additionally, sponsors can gain more meaningful inventory (beyond logos), and media teams can produce micro-content in real time. For athletes and coaches, visualization tools can help shorten the path from analysis to action; for fans, they transform complex play into a compelling narrative.
Look for ways to build real-time explanations into your product, not as an afterthought. If viewers understand the decision space, they are more likely to stay and share.
Digital Fan Participation
The future of sports isn’t passive. Chess broadcasts now routinely include prediction games, moderated chats with experts, position “polls” and instant replays of critical moments tuned to different skill levels. These features don’t just entertain, they create participation mechanics that convert viewers into stakeholders.
This participation is the key to unlocking new value. It opens doors for new products, creates richer opportunities for fans and builds a loyal community that sticks around long after the final move.
The main takeaway: Give your audience a chance to co-create with you. When fans can contribute to the narrative, they feel a real sense of ownership.
A Simple Playbook For Sports Leaders
Whether you run a league, club or federation, you can borrow the chess testbed model without changing your sport’s DNA.
• Start where the signal is clean. Identify controlled formats (skills contests, preseason tournaments, academy leagues) to pilot analytics and interactive features with minimal risk.
• Build an explainability layer. Don’t ship “black box” models. Visualize the decision space with simple, shareable cues that work for novices and experts alike.
• Design for participation, not just viewership. Add prediction, creation and community features that reward contributions—leaderboards, badges, highlights built from fan inputs.
• Establish governance. Make every event a data-collection asset: decisions, contexts and outcomes. Create a consistent taxonomy so insights compound across seasons.
Beyond Sports: A Blueprint For Business
I find that lessons from chess also extend naturally to the boardroom. Executives face their own “positions”: pricing decisions, resource allocations, product roadmaps. The same approach—simulate scenarios, visualize trade-offs and blend human judgment with model guidance—reduces decision latency and improves outcomes.
And just as fans engage more deeply when they can participate, employees lean in when they can test assumptions, see the rationale and contribute to the next move.
The Bottom Line
Technology doesn’t automatically make you smarter; it makes your choices more consequential. That’s why a disciplined testbed matters. I think chess offers the rare combination of intellectual precision, complete telemetry and global audience appetite.
Prove innovations there, then scale them to sports with more variables and to businesses with higher stakes. If you can make better decisions under the spotlight of a live clock and perfect information, you can make better decisions anywhere.
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