As cricket enters an era increasingly shaped by artificial intelligence and advanced analytics, data has become as important to the game as talent and technique. From influencing team selection and tactical decisions to transforming the way matches are broadcast, analytics now sits at the heart of modern cricket. In this interview, CricViz Head of Analytics Services Sankar Rajgopal explains how the sport’s relationship with data has evolved over the years, the growing role of AI in enhancing fan engagement, and why players and teams that embrace analytics are gaining a crucial edge in an increasingly competitive landscape.
As cricket enters an era increasingly shaped by artificial intelligence and advanced analytics, data has become as important to the game as talent and technique
During the 2015 World Cup semi-final, when India’s chase against Australia started to look hopeless, we put out a graphic (attached) showing that as long as Dhoni was still at the crease, India retained a real chance – based on his record of near-unbeaten chases. Ashwin’s has been fairly direct about players who don’t get on top of AI and analytics risking a shorter career, and how data is consumed and used will be a real differentiator going forward. It’s a view I’d echo from the other side of the fence. When I started, in Tests and ODIs, analytics was largely averages, strike rates, economy rates – the basic vocabulary of the game. T20 broke that. You can’t use one set of numbers to judge every batsman or bowler anymore – an opener and a finisher are solving completely different problems, so the metrics had to fragment and get role-specific. The bigger shift is that it’s moved from being a back-room, post-facto exercise to a live decision-making tool – coaches now want to see the data before making a call, not after. And critically, players themselves have bought in. Ten years ago there was real skepticism from dressing rooms; now most players are aware of matchups and understand why a particular bowler is being targeted at them. Let me walk you through what a typical broadcast day looks like from our side. All of these are fed into the graphics engine via APIs, so the moment a commentator wants to bring up a story, the graphic is already sitting there ready to go, no scrambling required. Broadcast coverage is all about keeping the audience hooked through rich storytelling. AI and pattern recognition help us surface trends that aren’t obvious to the naked eye. For instance, if Virat Kohli brings up a fifty and every boundary has come through the off side, that pattern shows up on our Centurion match page instantly – and that insight gets relayed straight to producers and commentators in real time. On the broadcast side, one moment stands out. We tracked a noticeable spike in viewer retention right after that graphic aired – a good example of how a single well-timed data point can hold an audience through a game that looks all but over.
A day before the game, every producer and commentator on that match gets a preview document from our analysts flagging the main talking points – the storylines worth building the broadcast around.
