Load Monitoring Intelligence Engine
Training load analytics platform with ACWR monitoring, workload trends, risk alerts and performance management dashboards.
Project Overview
The Problem
Coaches lack a clear view of acute-to-chronic workload ratios and meaningful weekly load trends, increasing injury risk and limiting performance planning.
The Solution
A load monitoring engine that computes ACWR, monotony, strain and rolling trends — surfaced through coach-friendly dashboards and risk alerts.
Intended Users
- S&C Coaches
- Sport Scientists
- Head Coaches
- Medical Staff
Core Features
ACWR Engine
EWMA and rolling-average ACWR per athlete.
Load Trends
Daily, weekly and block-level trend views.
Risk Alerts
Threshold and trend-based injury risk flags.
Session RPE
Internal load capture via sRPE workflows.
External Load
GPS, distance and high-speed metrics.
Squad Heatmaps
At-a-glance squad load distribution.
System Workflow
Capture
Internal + external load every session.
Compute
ACWR, monotony, strain rolling windows.
Detect
Flag athletes outside safe bands.
Plan
Inform next session prescription.
Dashboard Gallery
ACWR Dashboard
Per-athlete and squad ratios.
Weekly Heatmap
Squad-wide load distribution.
Risk Register
Prioritised list of at-risk athletes.
Metrics & Outputs
ACWR, monotony, strain, training stress balance.
Real-time after each session entry.
Configurable per sport and athlete.
Key Benefits & Outcomes
Lower injury risk through earlier flags
Smarter weekly planning
Squad-level workload transparency
Evidence base for coaching decisions
Technology Stack
Compute
- Python
- EWMA models
- SQL
Capture
- sRPE forms
- GPS imports
Visualisation
- Power BI
- Custom dashboards
Future Roadmap
GPS Auto-Ingest
Direct integration with major GPS vendors.
Injury Model
ML-based injury risk modelling.
Auto Periodisation
AI-assisted weekly plan adjustments.
Want a system like Load Monitoring Intelligence… built for your program?
Start a conversation about scoping, customisation and rollout for your organisation.