Efficiency Factor (EF)
Efficiency Factor compares output with average heart rate to track aerobic efficiency trends across similar endurance sessions.
Efficiency Factor (EF)
Efficiency Factor (EF) links your physiological input to your performance output. In simple terms, it asks: how much pace or power did you produce per beat of heart rate?
It is useful for tracking aerobic efficiency during similar endurance sessions, especially across a base period.
Core idea
EF is simple: output per unit heart rate. As you get fitter, you can produce more output at the same HR, or you can maintain the same output at a lower HR.
Formula
EF is computed as output divided by input:
Cycling
Note: some tools use average power instead. Trainingload.ai uses NP by default to stay consistent with how Decoupling is computed.
Running
Note: Trainingload.ai uses the speed derived from NGP (Normalized Graded Pace) (m/min or yd/min) to reduce terrain effects.
Typical values
EF is a relative metric. You generally shouldn’t compare EF across athletes because resting HR, Max HR, body mass, and measurement devices differ.
- Compare to yourself: compare to your own past EF.
- Typical trend: across a solid 12–16 week base period, EF often rises gradually.
Typical applications
1. Track base training progress
During long base periods, low-intensity endurance work can feel repetitive. A steadily rising EF trend across comparable sessions can be a sign that aerobic efficiency is improving.
- Rising: training may be improving aerobic efficiency.
- Plateau: if EF stops rising for several weeks, your base may be stabilizing, or you may be carrying fatigue.
- Decision point: this can support adding more threshold or interval work, but it should be checked against fatigue, goals, and recent load.
2. Cross-check fatigue signals
If EF changes abruptly, it is not always a fitness change. Unusually low heart rate, unusually high RPE, poor sleep, heat, or sensor issues can all distort EF. Cross-check with how the session felt and with recent training load.
EF vs. aerobic decoupling
EF and Aerobic Decoupling complement each other:
| Metric | Time horizon | Question |
|---|---|---|
| EF | Long-term trend | “How much did I improve over the last month?” |
| Decoupling | Single-workout quality | “Did I maintain efficiency during this long session?” |
EF shows the efficiency level of a session or trend. Decoupling shows whether that efficiency stayed stable later in a long steady effort.
How Trainingload.ai uses EF
- Trend only comparable sessions: EF is most useful when comparing similar routes, durations, terrain, and intensity.
- Filter noisy workouts: Trainingload.ai emphasizes aerobic sessions (mostly Zone 1 / Zone 2) when looking at EF trends.
- Pair with decoupling: EF can rise while late-session drift remains high, so both metrics tell a fuller story.
- Keep equipment consistent: use the same HR strap and power meter when possible. Device differences can hide small real improvements.