Project Management
IPMA, SCRUM, Jira, Confluence, MS Project
Improving Player Performance Through Data Analysis
Client: EsportsLabb
Location: Warsaw, PL
Cooperation since: 2020
Project: esportslab.gg
Scope of cooperation: requirements definition, solution design, implementation
Project background
Esports Lab supports e-sports players in better understanding the factors affecting their performance and development potential. The organization’s goal is to increase player self-awareness, enhance coaching methods, and develop organizational knowledge in the e-sports field.
To achieve this goal, the company integrates data from multiple sources, including in-game behaviour, interface usage patterns, and cognitive performance tests. Combining over five years of academic research with the experience of professional players, analysts, and coaches allows Esports Lab to offer advanced solutions that support the development of e-sports talent.
Challenge
Our task was to design a technology concept for a platform capable of collecting, processing, and analyzing data from multiple sources and formats while ensuring high quality and consistency of information.
It was also crucial to prepare a system that would allow players and coaches to quickly draw insights and receive data-driven recommendations. The project had to address specific UX requirements for e-sports athletes and organizations, as well as implement a scalable Azure cloud infrastructure.
Data integration: ensuring smooth flow and consistency of data from various sources.
Analysis and recommendations: processing large volumes of information in a clear and actionable way for players and coaches.
Scalable infrastructure: leveraging cloud technology to guarantee performance and future platform growth.
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ELAB is a platform enabling e-sports teams and individual players to analyse factors affecting their performance. The system collects data from:
- Observations of in-game behaviour (e.g., player positions, executed moves)
- Surveys and declarative data
- Wearable devices (Garmin, Fitbit)
- Cognitive tests
- Mental and physical health measurements
The data is aggregated, standardized, and prepared for analysis in a structured form. Our role included requirements analysis, system concept design, and implementation of a technical solution enabling Esports Lab’s research team to manage and share data efficiently.
Main components of the Azure cloud implementation:
- Authorization portal for access management
- Integration with gaming platforms such as RIOT (League of Legends) and HLTV (Counter-Strike)
- Structured data sharing for AI/ML algorithms
- Integration with wearable devices
- Microservices managed via Azure Kubernetes
- Azure services: Data Lake, Service Bus, Cosmos DB
Project scope
Analysis: requirements and needs analysis, client workshops
Solution design: platform concept, technical architecture, Big Data integration
Development: implementation of microservices on Azure, React SPA, back-end based on Clean Architecture, integration with external systems, QA support, and documentation
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The platform launch brought a range of business and technological benefits. It enables e-sports teams and coaches to quickly analyse data, draw insights, and make decisions based on reliable information, supporting player development and training efficiency. The scalable Azure cloud infrastructure allows easy expansion and handling of increasing data volumes at lower costs.
8x faster data processing
Higher quality data for analysis
90% lower data storage costs
Easy scaling and expansion thanks to Azure
Technologies
Technologies
Microsoft ASP.NET Core, Azure Kubernetes Service, Azure Data Lake Storage, Azure Service Bus, Azure Key Vault, Azure CosmosDB, Azure Cache for Redis, Azure SQL Database, Repository and CI/CD based on Azure DevOps, OAuth 2.0
Integrations
RIOT (LoL), HLTV (CS:GO), GEX (research application), Google, Microsoft, Garmin, Fitbit
Frameworks, libraries, sources
React, WEB API, Microsoft ASP.MVC, Identity Server 4, entity framework core.
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