Field Usage Optimization with a Data Lake on AWS at Let’s Play Soccer
Introduction
Let’s Play Soccer operates a nationwide network of indoor soccer facilities, organizing year-round leagues for players of all skill levels. With hundreds of teams, thousands of games, and complex scheduling demands across multiple cities, optimizing field usage is crucial to operational efficiency and profitability.
Problem/Client Challenges
Let’s Play Soccer faced growing challenges in managing and analyzing operational data:
- Dispersed and inconsistent data across locations and systems.
- Lack of visibility into field usage trends, idle time, and overbooking patterns.
- Manual reporting processes that made it difficult to align staffing, maintenance, and scheduling.
- Missed opportunities for upselling and maximizing facility utilization.
To address these issues, Let’s Play Soccer partnered with us to build a centralized Data Lake on AWS that could integrate data across multiple domains and provide actionable insights.
Solution
- Architecture Overview
We developed a modern, cloud-native Data Lake architecture on AWS, enabling scalable data ingestion, transformation, and analytics:- Amazon S3: Centralized storage for raw and curated data from all facilities.
- AWS Glue: Used for schema discovery, ETL pipelines, and data cataloging.
- Amazon Athena: Enabled fast, serverless querying of structured and semi-structured data.
- AWS Lake Formation: Ensured secure, fine-grained access control to sensitive data.
- Amazon QuickSight: Delivered interactive dashboards for operations, finance, and regional managers.
- Data Domains Integrated
The Data Lake ingested and normalized key data domains:- Player Data: Registration info, attendance, demographics.
- Team Data: Rosters, league affiliations, win/loss records.
- Season Data: Game schedules, field assignments, time slots, league formats.
- Payment Data: Team fees, individual payments, promotions, and revenue patterns.
- Optimization Model
We created analytics pipelines and dashboards to:- Identify underutilized time slots by location and day-of-week.
- Analyze team scheduling preferences to better match demand.
- Correlate payment trends with field usage, identifying which time slots drive the most revenue.
- Track no-shows and cancellations, and their impact on utilization.
- Recommend dynamic scheduling strategies, like flexible formats or discounts during low-demand hours.
Results
| Outcome | Impact |
|---|---|
| Increased Field Utilization | Identified 15% of weekly hours that could be repurposed for training, youth leagues, or rentals. |
| Data-Driven Scheduling | Enabled dynamic schedule optimization, reducing peak-time bottlenecks. |
| Revenue Insights | Correlated payment and attendance data to highlight high-ROI slots and underperforming leagues. |
| Operational Efficiency | Improved staffing and maintenance planning aligned with usage trends. |
| Scalable Analytics Platform | Empowered regional managers with dashboards and self-service reporting tools. |
Conclusion
The AWS-powered Data Lake transformed Let’s Play Soccer’s ability to understand and optimize facility usage. By bringing together player, team, season, and payment data in a unified, queryable format, leadership gained clear visibility into how every hour of field time was used—and how it could be better monetized.
This solution not only enhanced operational efficiency but also laid the foundation for smarter business growth and more responsive community engagement across all locations.