Silicon Valley technology has officially entered the tactical core of top-tier cricket. A highly advanced artificial intelligence tool called the Sports Forecasting Unit, or SFU, is rewriting how coaches set fields and scout players.
Built by tech entrepreneur Anand Rajaraman and Columbia University Vice Dean of Computing Vishal Mishra, the system moves past basic statistics. It builds literal Digital Twins of players using data from thousands of past matches to simulate live games and track ball-by-ball win probabilities.
The San Francisco Unicorns, co-owned by Rajaraman, recently announced a major technology partnership with Persistent Systems to scale these tools globally.
“The best, simplest way for us to think about it is right now you have two entities: You’ve got the GM, and you’ve got the coach. If you look out five years ahead, you’re going to have the GM, the coach, and the AI.”
Venky Harinarayan, Sports Business Journal interview, May 6, 2026
The tool uses an Average Play Probability scale to measure how a player impacts a team’s chances during high-pressure situations. This predictive power was proven on the field during the 2026 Indian Premier League.
The SFU model generated highly specific fielding placements that led directly to the wickets of Rohit Sharma, Hardik Pandya, Nicholas Pooran, and Shubman Gill. All four marquee players were caught in the exact spots suggested by the AI.
This follows its success during the 2024 T20 World Cup match between India and Pakistan. While mainstream websites gave Pakistan a 95 percent chance of victory at one stage, the SFU model correctly predicted that India remained in a strong position to win.
“We had three or four guys all Ph.Ds from Stanford who were working in all the big tech companies here who literally were volunteering their time just for the opportunity to work on this. What we found very quickly was these guys were not just making us competitive; they were actually pushing the envelope of analytics and cricket.”
Venky Harinarayan, Sports Business Journal interview, May 6, 2026
Beyond match simulations, the system includes a feature called Cricket Lens. This tool functions like ChatGPT for match footage, allowing coaching staffs to type natural language queries and instantly pull up relevant video clips.
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As a player, you quickly learn that data can only take you so far. Walking into a modern dressing room where a Silicon Valley program tells you exactly where to stand can cause real friction. For decades, captains and senior bowlers set fields based on the feel of the match and the batter’s body language.
Cricket is fundamentally unpredictable, and no one can fully know what will happen next. A computer can analyze patterns, look at player weariness, and track historical data, but it cannot map out human psychology on its own.
Ravichandran Ashwin involving himself in this project is highly strategic. By giving his own opinions on body parameters, physical fatigue, and mental strength, he is trying to bridge that gap. He knows the data wave is coming. Instead of fighting it, he is guiding the tool so it remains a helpful assistant rather than trying to replace human intuition.
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