Orreco

Orreco

paid

Orreco combines biomarkers, computer vision motion data, and AI to help elite sports teams reduce injury risk, optimize performance, and extend athlete careers.

About

Orreco is an enterprise-grade sports science intelligence platform designed for professional sports organizations, elite teams, and high-performance athletes. It merges cutting-edge AI inference with decades of peer-reviewed sports science to deliver actionable insights that reduce injury risk, optimize training loads, and prolong athletic careers. The platform operates as a modular stack, allowing staff to adopt individual modules—such as Biomarkers, Motion Signal, Recovery Labs, Medical Notes, and Wellness—or run the full suite in a single unified dashboard. Its standout Motion Signal module uses computer vision to detect non-contact soft-tissue injury risk early by analyzing movement trends. The AI-powered Tr AI n module predicts future training loads from historical GPS data, while the Women's Performance module leverages menstrual cycle tracking for tailored training and nutrition advice. Orreco's athlete-facing app (@thlete) gives individual athletes ownership of their recovery, readiness, and wellness data, and allows staff to push evidence-based content directly to them. Medical Notes provides centralized, audit-ready injury and illness documentation, and the Analytics & Reporting module offers benchmarking and visualization tools for the entire team dataset. Proven results include a Premier League hamstring injury prediction model with 85% accuracy, a 74% reduction in soft-tissue injuries for an MLS team, and 45+ Olympic medals supported across five Olympic Games. Orreco is purpose-built for sports scientists, performance coaches, medical staff, and athletic directors at professional and Olympic-level organizations.

Key Features

  • Motion Signal (Computer Vision): Analyzes athlete movement trends using computer vision to flag non-contact soft-tissue injury risk before it becomes a problem.
  • Blood Biomarker Tracking: Integrates objective blood biomarker data for real-time decision-making on training, recovery, and athlete readiness.
  • AI Training Load Prediction (Tr AI n): Predicts optimal future training loads by learning from historical GPS and workload data to prevent overtraining.
  • Modular Unified Dashboard: Staff can build a custom platform by selecting only the modules they need—Recovery Labs, Medical Notes, Wellness, Travel, and more—all in one dashboard.
  • Women's Performance Module: Tracks menstrual cycles to personalize training schedules, nutrition recommendations, and recovery advice for female athletes.

Use Cases

  • A Premier League club uses Orreco's Motion Signal module to monitor player movement patterns during training, identifying hamstring injury risk weeks before symptoms appear.
  • An NBA performance team integrates Orreco's Biomarkers module to track blood markers after back-to-back games, informing personalized recovery protocols to maintain player availability.
  • An Olympic swimming program leverages the Women's Performance module to adjust training intensities and nutrition plans around athletes' menstrual cycles, improving performance consistency.
  • An MLS sports science staff uses the Tr AI n module to predict weekly training loads based on GPS history, reducing soft-tissue injuries by 74% over a season.
  • A multi-sport elite academy adopts Orreco's modular platform to unify medical notes, wellness questionnaires, and recovery lab data across all squads in a single auditable dashboard.

Pros

  • Elite-validated science: Grounded in 20+ years of peer-reviewed research and Olympic-level application, including support for 45+ Olympic medals and a Premier League injury model with 85% accuracy.
  • Highly modular and scalable: Teams can start with a single module and scale up as needs grow, avoiding unnecessary complexity or cost from the outset.
  • First platform combining computer vision with internal/external load: Uniquely integrates motion data from computer vision alongside physiological and wellness data for a comprehensive athlete picture.
  • Athlete-facing app included: The @thlete companion app gives athletes direct access to their data and receives evidence-based content pushed from staff, improving buy-in.

Cons

  • Enterprise pricing with limited transparency: Pricing is not publicly listed and is tailored for professional sports organizations, making it inaccessible for amateur clubs or individual coaches.
  • Steep onboarding for full stack: Deploying the full suite of modules—biomarkers, GPS, computer vision, wellness—requires significant organizational readiness and staff training.
  • Primarily designed for team sports at elite level: Individual athletes or small fitness businesses may find the platform over-engineered for their needs.

Frequently Asked Questions

What types of sports teams use Orreco?

Orreco is used by professional and elite teams across sports including soccer (Premier League, MLS), basketball (NBA), baseball (MLB), and Olympic sports. It has been deployed in 145+ countries.

How does Orreco predict injuries?

Orreco uses a combination of blood biomarkers, computer vision motion analysis (Motion Signal), GPS training load data, and AI models trained on historical team data to identify early indicators of injury risk—particularly non-contact soft-tissue injuries.

Does Orreco have an app for athletes?

Yes. The @thlete app gives individual athletes personalized insights on recovery, readiness, and wellness. Staff can also push evidence-based content directly to athletes through the app.

Can teams adopt only part of the Orreco platform?

Yes. Orreco is built as a modular stack. Teams can start with one module—such as Biomarkers or Recovery Labs—and add more modules to their dashboard as their needs and scale evolve.

Is Orreco backed by peer-reviewed research?

Yes. Orreco's science is grounded in peer-reviewed publications in journals such as the British Journal of Sports Medicine and the Journal of Science and Medicine in Sport, ensuring its tools are evidence-based.

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