July 19, 2023
In esports, data plays a crucial role in understanding player performance, team strategies, and game dynamics. Data scientists are valuable assets, helping teams gain an advantage. If you’re interested in both esports and data analysis, starting a journey as a data scientist in esports can be exciting.
In this article, we’ll share simple tips to help you begin your data-driven adventure in the world of esports.
Build a solid foundation
To become an esports data scientist, having a strong foundation in data analysis and the specific games you want to work with is essential. Start by learning statistical analysis, machine learning, and programming languages like Python or R (I’m personally a huge Python fan). Understanding the basics of data manipulation, data visualization, and how to make predictions will be very helpful.
Immerse yourself in esports
Follow popular esports titles (League of Legends, Valorant, CSGO, …), watch tournaments, live streams, and connect with the esports community. This will enhance your understanding of the games and give you insights into the challenges and opportunities you can find in them for data analysis.
Start with small projects
This could involve analyzing your favorite player’s performance, recognizing and evaluating your favorite team strategies, or finding patterns in game outcomes. Starting small allows you to gain hands-on experience and build a portfolio, which is the bread and butter of finding a job in anything game-related.
Collaborate and network
Esports thrives on collaboration and community. Find and engage with other data scientists, esports analysts, and industry professionals. Participate in online forums, join esports-related communities, and attend conferences and meetups if your localization allows it. Building a solid network will keep you updated on the latest trends and provide mentorship and job opportunities.
Seek practical experience
While theoretical knowledge is important, practical experience is equally crucial. Look for internships, volunteer opportunities, or freelance projects within the esports industry. Real-world experience will let you apply your skills in a professional setting, understand the challenges specific to esports data analysis, and refine your abilities.
Analyze and share insights
Actively analyze esports data and share your findings through blog posts, social media, and forums. Communicating your insights will establish your credibility and attract attention from esports organizations and potential employers. Experiment with different visualization techniques to present your analysis in an engaging and easy-to-understand way.
Stay updated with tools and techniques
Data science, as esports, is constantly evolving, so it’s important to stay updated with the latest tools and techniques. Explore data analysis libraries and frameworks used for esports analytics. Keep an eye on emerging trends like deep learning and AI-driven analytics, as they can greatly help data analysis.
Starting your journey as a data scientist in esports requires a strong foundation in data analysis, domain expertise in the games, and a genuine passion for making the way feel easier. Remember, it’s a continuous learning process, so stay curious, adapt to the new technologies, and embrace the ever-evolving nature of data science. Good luck on your exciting journey!