Sports Software That Handles Game Day Traffic
Build analytics platforms, ticketing systems, and streaming apps that can handle 50x traffic spikes without compromising UX or data accuracy.
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Trusted and top rated tech team
Fan engagement fails when platforms lack scale
Mobile apps crash during live events, live stats lag, and ticketing systems freeze during championship sales. Manual data entry delays analytics, and wearables lack infrastructure to process sensor data at scale. We build sports software with streaming data pipelines, mobile-first architecture, and load testing for peak traffic. This ensures platforms handle game-day demand, athletes get immediate feedback, and fans access live content without latency.
Our capabilities include:
- Real-time sports data processing and analytics
- Mobile app development for iOS and Android
- Wearable and IoT sensor integration
- Live streaming platform infrastructure
- Predictive ML models for performance and betting
- Ticketing and venue management systems
Who we support
Sports platforms face unpredictable traffic that standard infrastructure can’t handle. We help sports tech companies build streaming pipelines, mobile applications that perform under load, and integrations that process sensor data at scale without degradation during peak events.
Teams Managing Performance Data
Your coaching staff needs live biometrics from wearables, instant video analysis, and platforms to track player workload over time. However, current tools don't integrate well, data often arrives too late for in-game decisions, and manual tracking makes it impossible to scale across multiple teams.
Platforms Serving Millions of Fans
Your app must deliver live scores, streaming video, and real-time statistics to millions of concurrent users during championship games. Infrastructure breaks under traffic spikes, latency increases when demand peaks, and users abandon platforms when content lags behind broadcast television or experiences frequent crashes.
Organizations Running Live Events
Your venue needs contactless ticketing, mobile ordering systems, and real-time occupancy tracking that work when 50,000 fans arrive simultaneously. Payment systems fail during peak periods, manual processes create bottlenecks at gates, and lack of data prevents optimizing concessions, parking, or security deployment.
Ways to engage
We offer a wide range of engagement models to meet our clients’ needs. From hourly consultation to fully managed solutions, our engagement models are designed to be flexible and customizable.
Staff Augmentation
Get access to on-demand product and engineering team talent that gives your company the flexibility to scale up and down as business needs ebb and flow.
Retainer Services
Retainers are perfect for companies that have a fully built product in maintenance mode. We'll give you peace of mind by keeping your software running, secure, and up to date.
Project Engagement
Project-based contracts that can range from small-scale audit and strategy sessions to more intricate replatforming or build from scratch initiatives.
We'll spec out a custom engagement model for you
Invested in creating success and defining new standards
At Curotec, we do more than deliver cutting-edge solutions — we build lasting partnerships. It’s the trust and collaboration we foster with our clients that make CEOs, CTOs, and CMOs consistently choose Curotec as their go-to partner.
Why choose Curotec for sports software?
Our engineers build apps that perform even during 50x traffic spikes. We implement streaming pipelines that process sensor feeds without lag and architect systems for game-day load patterns. We also integrate wearable platforms, develop predictive analytics at scale, and optimize for live events. The result is sports software that handles peak demand without crashing or slowing down.
1
Extraordinary people, exceptional outcomes
Our outstanding team represents our greatest asset. With business acumen, we translate objectives into solutions. Intellectual agility drives efficient software development problem-solving. Superior communication ensures seamless teamwork integration.
2
Deep technical expertise
We don’t claim to be experts in every framework and language. Instead, we focus on the tech ecosystems in which we excel, selecting engagements that align with our competencies for optimal results. Moreover, we offer pre-developed components and scaffolding to save you time and money.
3
Balancing innovation with practicality
We stay ahead of industry trends and innovations, avoiding the hype of every new technology fad. Focusing on innovations with real commercial potential, we guide you through the ever-changing tech landscape, helping you embrace proven technologies and cutting-edge advancements.
4
Flexibility in our approach
We offer a range of flexible working arrangements to meet your specific needs. Whether you prefer our end-to-end project delivery, embedding our experts within your teams, or consulting and retainer options, we have a solution designed to suit you.
Sports software capabilities for live events
Real-Time Data Pipeline Architecture
Mobile Load Testing & Optimization
Wearable Integration & IoT Processing
Predictive Analytics Implementation
Live Streaming Infrastructure
Venue Operations Automation
Infrastructure that powers sports software
Mobile Development Frameworks
Our developers build native iOS and Android applications using frameworks that optimize performance for real-time data rendering.
- React Native — Cross-platform framework enabling code reuse across iOS and Android while maintaining native performance for sports apps
- Flutter — UI toolkit delivering 60fps animations and smooth scrolling for live score updates and streaming video interfaces
- Swift/SwiftUI — Apple’s native development stack providing direct hardware access for wearable integration and performance optimization
- Kotlin — Modern Android language with coroutines for efficient background processing of real-time sports data and notifications
- Expo — React Native toolchain accelerating development cycles with over-the-air updates and push notification infrastructure
- Xamarin — Microsoft framework sharing C# codebase across platforms while accessing native APIs for sensor and device integration
Real-Time Data Processing Platforms
Curotec implements streaming architectures that ingest sensor data, process events, and deliver updates with sub-second latency.
- Apache Kafka — Distributed streaming platform handling millions of events per second from wearables, scoreboards, and tracking systems
- Apache Flink — Stream processing engine computing real-time analytics on game statistics and player performance metrics as events occur
- Redis Streams — In-memory data structure managing live sports feeds with microsecond latency for betting odds and score updates
- AWS Kinesis — Managed streaming service ingesting video, sensor data, and user interactions at scale during peak traffic events
- Apache Pulsar — Multi-tenant messaging system distributing real-time updates to millions of concurrent fan app connections
- NATS — Lightweight messaging system providing pub/sub communication for IoT devices and microservices with minimal overhead
Wearable & IoT Integration Tools
We connect devices using protocols that normalize biometric feeds, synchronize timestamps, and route sensor data to analytics systems.
- Apple HealthKit — iOS framework accessing heart rate, activity, and workout data from Apple Watch for athlete monitoring applications
- Google Fit API — Android platform aggregating fitness data from wearables, providing unified access to steps, calories, and biometrics
- Fitbit SDK — Developer tools building custom apps and watch faces while accessing sensor data from Fitbit device ecosystem
- MQTT — Lightweight messaging protocol transmitting sensor readings from IoT devices with minimal bandwidth and battery consumption
- Bluetooth Low Energy (BLE) — Wireless protocol connecting smartphones to tracking devices, heart rate monitors, and GPS sensors efficiently
- ANT+ — Sports-specific wireless standard enabling communication between fitness equipment, power meters, and training applications
Machine Learning & Predictive Analytics
Analytics platforms train models on performance history, deploy inference pipelines, and generate predictions for injuries and outcomes.
- TensorFlow — Machine learning framework building models that predict player fatigue, injury risk, and performance trends from training data
- PyTorch — Deep learning library creating computer vision models analyzing game footage for technique assessment and tactical insights
- scikit-learn — Python library implementing classification and regression algorithms for player scouting and outcome prediction
- MLflow — Platform tracking experiments, versioning models, and deploying ML pipelines for sports analytics at scale
- DataRobot — Automated machine learning system accelerating model development for fantasy sports projections and betting odds calculation
- Amazon SageMaker — Managed ML service training models on historical sports data and deploying real-time inference endpoints
Video Streaming & CDN Infrastructure
Streaming systems deliver adaptive bitrate video with edge caching so millions of viewers watch simultaneously without buffering.
- AWS CloudFront — Global CDN distributing live streams and video-on-demand content with low latency to fans worldwide
- Cloudflare Stream — Video platform handling encoding, storage, and delivery with built-in DRM for protected sports content
- Wowza Streaming Engine — Media server supporting HLS, DASH, and WebRTC protocols for live game broadcasts and multi-angle replays
- Mux — Video infrastructure providing adaptive streaming, real-time analytics, and thumbnail generation for sports highlights
- FFmpeg — Multimedia framework transcoding video formats, extracting highlights, and processing streams for multi-platform delivery
- Akamai — Enterprise CDN absorbing traffic spikes during championship events with edge computing for personalized stream delivery
Load Testing & Performance Monitoring
Performance tools simulate game day traffic patterns, identify bottlenecks, and monitor system behavior under peak concurrent load.
- Apache JMeter — Load testing platform simulating thousands of concurrent users accessing ticketing systems and mobile apps
- Gatling — Performance testing framework generating realistic traffic patterns matching championship game demand spikes
- k6 — Developer-centric tool scripting load tests in JavaScript and integrating performance validation into CI/CD pipelines
- New Relic — Application performance monitoring tracking response times, error rates, and infrastructure health during live events
- Datadog — Observability platform monitoring mobile app performance, API latency, and database query times across deployments
- Grafana — Visualization tool displaying real-time metrics for streaming quality, server capacity, and user experience during games
FAQs about our sports software development
How do you handle traffic spikes during live events?
We architect auto-scaling infrastructure with CDN distribution and load balancing that provisions resources automatically when concurrent users increase. Systems pre-warm during scheduled events and maintain performance through 50x traffic spikes without manual intervention.
Can you integrate with existing wearable platforms?
Yes. We connect to Apple HealthKit, Google Fit, Fitbit, and custom IoT devices through standardized APIs and protocols. Our integration layer normalizes data formats, handles device authentication, and routes biometric feeds to your analytics platforms immediately.
What's your approach to mobile app performance?
We implement native development for performance-critical features, optimize rendering for 60fps animations, reduce bundle sizes, and use background processing for data sync. Load testing simulates game day usage patterns before release.
How do you ensure real-time data accuracy?
We implement event sourcing patterns, timestamp synchronization across distributed systems, and conflict resolution for concurrent updates. Data pipelines include validation checks, and monitoring detects latency issues before they affect user experience.
Can you build predictive analytics for injuries?
Yes. We train ML models on historical performance and biometric data, identify fatigue patterns, and deploy inference pipelines that flag risk indicators. Models retrain on new data and provide explainable predictions coaches can act on.
What's typical timeline for a sports platform?
MVP with core features takes 3-4 months, full platform with real-time analytics 6-9 months, and complex systems with ML integration 9-12 months. Timeline depends on third-party integrations and data migration requirements.
Ready to have a conversation?
We’re here to discuss how we can partner, sharing our knowledge and experience for your product development needs. Get started driving your business forward.
