How to Break Into Sports Analytics
On 'The Last Wicket' podcast, cricket analyst Shubh Aggarwal offered direct advice for aspiring data professionals. He argued the best way to get noticed is to build a portfolio by tracking match stats, producing your own data-driven reports, and sharing those insights publicly with the sports community.
The Indian sports analytics market is valued at USD 225 billion, driven by the increasing use of data to inform player performance, team strategy, and fan engagement. This growth is propelled by investments in sports infrastructure and the adoption of AI and machine learning. Cricket, particularly the Indian Premier League (IPL), accounts for the largest share of this market, with a 34% stake in 2025. Companies like SportsMechanics, which has worked with the Indian Cricket team and various IPL teams since the league's inception, are pioneers in the field. Newer firms such as Stats2Play have helped emerging clubs in the Indian Super League (ISL) by identifying defensive weaknesses in dominant teams. These companies utilize tools for performance analysis, injury prevention, and athlete management. For those aspiring to enter the field, technical skills in Python, R, and SQL are foundational, alongside a strong understanding of statistical analysis and data interpretation. Entry-level roles often involve data collection, performance analysis, and creating reports to assist coaching staff. An entry-level sports analyst in India can expect a salary of around ₹36,194 per month. A strong portfolio for an undergraduate could include projects like analyzing the impact of the home court in the NBA, predicting IPL match winners, or forecasting a FIFA team's likelihood of scoring. Another project idea is to use cricket commentary datasets to analyze team-winning strategies. These projects demonstrate the ability to handle sports data and derive meaningful insights. The use of data extends beyond on-field strategy to include player auctions, where teams use analytics to make informed recruitment decisions. Data is also crucial for preventing player injuries by monitoring workload and physical condition. During broadcasts, analytics enhance the fan experience by providing real-time statistics and predictions. In the IPL, every ball bowled can generate over 100 data points, creating a rich dataset for analysis. Teams are increasingly using wearable technologies to gather real-time data on player health and fatigue. This data-driven approach is transforming training, allowing for more individualized and effective player development programs. The growth of sports analytics in India is not limited to cricket and football; firms like SportsLens are developing analytics solutions for niche sports like kabaddi. This expansion indicates a broader trend of data integration across all levels of Indian sports. The market is projected to reach USD 199.31 Million by 2034, growing at a rate of 15.02% annually.
