Not a Shortage of Strategy, but a Shortage of Information: How Empty Data Is a Major Crisis in Cricket Analysis

The face of cricket analysis has changed in recent years. Earlier, experts sitting in the commentary box would make statements based on their experience of watching the game and intuitive understanding, but now every statement has a data framework behind it. Franchise cricket has changed the way players are evaluated. The question is no longer how many runs or wickets a player has taken, but in which phase, under what circumstances, and in what role they scored those runs or took those wickets. This shift has placed both cricket journalism and commentary before a new challenge—the quality and availability of information.

In this context, a serious problem has come to light, which I have been observing closely for some time. Often, the framework for analysis is ready, but the basic facts needed to fill it are simply not available. This problem is not merely technical; it has a direct impact on the quality and credibility of analysis.

Context: The New Structure of Analysis and Its Need

Cricket analysis is no longer limited to commentary. It has spread to team management, selection processes, auction strategy, and even broadcasting rights. In the 2026 IPL mega auction, I myself wrote an analysis about uncapped off-spinner Krishnappa Gowtham. At that time, I had six weeks of domestic T20 phase-wise data. I considered him the best match-up based on his record against left-handed batters in powerplay overs. Rajasthan Royals bought him for ₹6.2 crore, the highest price for an uncapped player in that auction. This analysis was possible because I had solid data—phase-wise performance, statistics against left- and right-handed batters, and bowling economy.

But when data itself is unavailable, how does one analyse? This question is the biggest challenge facing cricket journalism today. Recently, I came across a case where an automated system was asked to analyse a cricket-related article. But when the analysis came out, it was completely empty. The article's title, source, type, summary, author's stance, information points—everything was unavailable. Only one signal came through that the topic was cricket-related. In such a situation, analysis was impossible.

This is not an isolated incident. It points to a broader problem—carelessness regarding the availability and quality of information in cricket analysis.

Core Analysis: If There Is No Data, Whose Strategy Is It?

Strategy in cricket means using the right player at the right time. This is only possible when you have accurate and regularly updated data on a player's performance. As a coach, my experience is that I do not form an opinion about any player until I have watched him live for at least forty overs. This is my rule. But when you have only a label—'cricket'—and no solid facts, you can evaluate neither the player, nor the team's strategy, nor the pressure of the match.

The market for cricket data analysis has grown rapidly in recent years. Franchises spend millions of rupees on scouting and data analysis. Yet, despite this, there is often a lack of basic information. For example, if an automated system that analyses articles cannot even read the content of an article, what will its analysis be? This is a technical failure, but it affects the quality of analysis.

In cricket journalism, this problem is even more serious. As a journalist, I started with The Times of India in 2026. Back then, we had neither the internet nor mobile phones. We went to the stadium to watch matches, took notes, and then wrote reports. Gathering information took time, but it was authentic. Today, information comes quickly, but questions are raised about its quality. Everyone on social media has become an analyst. In such a scenario, distinguishing right from wrong has become difficult.

The biggest problem is that people have started guessing in the name of analysis. When there is no data, analysts make statements based on their emotions and biases. This is why analysis often lacks objectivity and accuracy.

There is another aspect to this—the misuse of data in auctions and the transfer market. In player evaluation, youthful potential is given more weight than dressing-room chemistry. I have long believed this. A player's value is determined not just by his statistics but by his role. But when you do not even have data on the role, how will you evaluate?

Contrarian Angle: Lack of Data or Haste in Analysis?

Now consider an interesting angle. Is there really a lack of data, or are we hasty in our analysis? Sometimes data is available, but we fail to read it properly. Or we jump to a conclusion in a hurry.

In last year's Champions Trophy final, I saw something interesting. In the match between India and Pakistan, Pakistan scored 338. Fakhar Zaman was caught off Jasprit Bumrah's bowling in the fourth over, but it turned out to be a no-ball. Fakhar scored 114. I was commentating at the time. In my commentary, I said that India's fielding was like a template, not a match-up. The sweeper was out as early as the eighth over when the score was 60/0. India were bowled out for 158. I made this analysis based on the data available at the time—field placement, bowling strategy, and the batters' positions.

But if the data from that match had not been available, could I have made this analysis? Probably not. This is the problem facing many analysts today. They make statements without data and then have to correct them later.

Another paradox is that we have become overly dependent on technology. Automated systems collect data, but if they fail, we are left with nothing. In traditional journalism, we had our notes, our memories, and our experience. Today, we have forgotten them.

Conclusion: The Way Forward

The future of cricket analysis lies in the balance between data and human experience. Analysis without data is incomplete, but analysis cannot be done with data alone either. The biggest challenge is ensuring the quality of information.

When an automated system fails to analyse an article, it is a signal that we need to rethink our processes. Are we collecting the right data? Do we have a verification mechanism? Are we treating analysis as merely a technical process rather than an intellectual exercise?

In the times to come, cricket analysis will have to become more transparent and accountable. Audiences no longer want just statements; they want the reasoning and data behind them. Analysts who accept this challenge will survive.

One question I always ask—do we have enough information about the player on whom we are forming an opinion? If not, it is better to stay silent. Because no analysis is better than wrong analysis.