TrainingLoad
Evidence-based training load monitoring for endurance athletes
ACWR, monotony, strain
40+ exercise presets
5-factor readiness
Zero backend
01The Problem
Overtraining is the silent killer of athletic performance. Most athletes either ignore load management entirely or use gut feel. The Acute:Chronic Workload Ratio (ACWR) is a validated sports science metric for injury risk — but no consumer tool made it accessible.
02The Approach
Built a self-contained client-side app that calculates ACWR, monotony, strain, and a daily readiness score from user-entered training data. All data lives in localStorage — no account needed, no data leaves the browser.
03Architecture Decisions
ACWR calculation engine
Acute load = 7-day training load sum. Chronic load = 28-day rolling average. The ratio determines injury risk zones: <0.8 (undertraining), 0.8–1.3 (sweet spot), >1.5 (danger zone). Color-coded gauge shows where the athlete sits.
Multi-factor readiness score
Daily readiness is computed from 5 subjective markers: sleep quality, muscle soreness, stress level, energy, and mood. Each is weighted and combined into a 0–100 score with trend analysis.
40+ exercise presets
Pre-loaded with exercises across lifting, cardio, team sport, and recovery categories. Each preset includes typical HR zone distribution and load calculation multipliers.
04Key Insight
Monotony (the consistency of training load) matters as much as total load. High monotony + high load = strain, and strain is strongly correlated with illness and injury. Adding the monotony calculation turned a simple ACWR tracker into a genuine training health monitor.
05Why It Matters
Demonstrates the ability to translate academic sports science literature directly into working software. The ACWR model is from peer-reviewed research — this project shows I can read a paper and build the tool.